Lozier praises promising, and ethical, blindness study – OneNewsNow

New research results show promise in treating people who are blind.

The National Eye Institute funded the study, which is research considered to be ethical.

Dr. David Prentice of the Charlotte Lozier Institute says there have been discussions over using adult stem cells to restore sight, which he calls a different tack for advancing science and medicine.

It's still an ethical way to go about this, he observes. There's no embryonic stem cells, no fetal tissue, none of this unethical type of research direction.

What the scientists did was turn a skin cell directly into a photoreceptor for vision then transplanted it.

Prenticeadvises the testing is very preliminary after the experiment on mice.

But what they find was when they transplanted this newly formed type of vision cell into the eyes of these blind mice, he says, they restored their vision.

The researchers applied chemicals that transformed one cell type into another needed for vision, and there is now potential to help people with all forms of vision blindness or vision correction, which would include macular degeneration and other retinal disorders.

Editor's note: Original posting attribute comments to wrong person.

More here:
Lozier praises promising, and ethical, blindness study - OneNewsNow

A potent CBP/p300-Snail interaction inhibitor suppresses tumor growth and metastasis in wild-type p53-expressing cancer – Science Advances

INTRODUCTION

Metastasis is the major cause of cancer motility and accounts for about 90% of cancer-associated death (1). Cancer metastasis is a multistep and inefficient process in which tumor cells disseminate from the primary tumors, survive in the circulation, and settle and grow at the distant vital organs (24). One key event of metastasis is the epithelial-mesenchymal transition (EMT), a highly conserved developmental program that enables cancer cells to acquire malignancy-associated traits and the properties of tumor-initiating cells (TICs) [also known as cancer stem cells (CSCs)] during tumor initiation and progression (59). A hallmark of EMT is the loss of expression of the key epithelial cell-cell adhesion protein E-cadherin, and the expression levels of mesenchymal markers vimentin, fibronectin, and N-cadherin are also up-regulated in cancer cells undergoing EMT (10). While EMT therapeutics that efficiently reverse EMT and impair EMT-associated therapeutic resistance and tumor-initiating ability (i.e., stemness) are recently proven to be an effective therapeutic strategy for cancer treatment, the therapeutic target of these agents remains unclear (11, 12).

Snail is recognized as a major transcriptional factor that induces EMT by repressing E-cadherin protein (13, 14). Emerging evidence suggests that Snail has a substantially broader impact on tumor progression and metastasis. Following its overexpression in mammary epithelial cells, Snail promotes an EMT program and acquisition of tumor-initiating properties while enhancing tumor invasion, metastasis, tumorigenicity, and therapeutic resistance (9, 10, 15, 16). In addition, Snail accelerates tumor metastasis by suppressing host immune surveillance and inducing tumor microenvironment modulation (17, 18). Snail is also known to promote cancer cell survival by enhancing resistance to apoptosis under the genotoxic stress condition (19). We recently found that Snail deletion stabilizes wild-type, but not mutant, p53 and identified Snail as a molecular bypass that suppresses the antiproliferative and proapoptotic effect executed by wild-type p53 in breast cancer (BrCa) (20). However, it remains largely elusive whether p53 signaling pathway actively participates in Snail-mediated EMT, stemness, migration, and metastasis in cancer cells.

Snail is aberrantly activated in many human cancers and strongly associated with poor prognosis (2023). Many oncogenic signaling pathways, such as hypoxia/hypoxia-inducible factor1, transforming growth factor (TGF), epidermal growth factor (EGF), fibroblast growth factor2, and Notch, are implicated in the regulation of Snail gene expression (8, 24). In many cases, the posttranslational modification actively participates in the regulation of Snail protein. For instance, glycogen synthase kinase 3 (GSK3) and protein kinase D1 (PKD1) can phosphorylate Snail and promote its polyubiquitination and degradation by forming a complex with E3 ligases beta-transducin repeats-containing proteins (-TrCP) and F-Box protein 11 (FBXO11), respectively (2529). Another E3 ligase F-box and leucine-rich repeat protein 14 (Fbxl14), the human homolog of the partner of paired gene product in Xenopus, is also known to degrade Snail in a phosphorylation-independent manner (30, 31). On the other hand, histone acetyltransferases (HATs) such as adenosine 3,5-monophosphate response elementbinding proteinbinding protein (CBP) and p300 interact with Snail and acetylate Snail at lysine-146 (K146) and K187, which consequently reduces Snail ubiquitination and thus enhances its protein stability (18). Given the important role of Snail in driving cancer progression, targeting Snail may exert potent therapeutic benefit in patients with cancer. In the present study, we have successfully identified a small-molecule compound CYD19 as a potent CBP/p300-Snail protein-protein interaction inhibitor. We further demonstrate that CYD19 restores Snail-dependent repression of wild-type p53 and thus impairs tumor cell growth and survival in vitro and in vivo. In addition, CYD19 reverses Snail-mediated EMT in aggressive cancer cells and thus diminishes tumor invasion and metastasis. Our findings demonstrate that Snail protein is a druggable target and that pharmacologically targeting Snail by compound CYD19 may exert potent therapeutic effects in patients with locally advanced and metastatic cancer.

To identify small-molecule compounds having high-affinity binding with Snail, we performed a virtual ligand screening assay based on compound docking into the potential binding pocket of Snail (32). Using the FTMap, an online computational solvent mapping software for predicting the binding hotspots of a protein (http://ftmap.bu.edu/login.php), we identified the evolutionarily conserved arginine-174 (R174) pocket (in red) as a key hotspot in the binding site of Snail protein. Meanwhile, the leucine-178 (L178) side pocket (in yellow) and the serine-257 (S257) hydrophobic pocket (in blue) are also important for the potential binding (Fig. 1, A and B, and fig. S1A). We then performed an established fragment-based virtual screening of the DrugBank database to seek the novel scaffolds (fig. S1B). We retrieved the fragment-like small molecules from the in-house chemical library and docked them in the Snail crystal structure [Protein Data Bank (PDB) ID: 3W5K] (32) using Glide docking algorithms. Small molecules that were able to form binding interactions (e.g., hydrogenic, hydrophobic, or noncovalent interactions) with R174 pocket were scored and ranked according to their Glide results. The docking poses of the top 200 ranked molecules were visually inspected. Fifty molecules representing 23 structural clusters with prior Glide scores were found to bind with R174 pocket (fig. S1C). Notably, we found that pyrrole-pyrimidine fragment (drugbank_431) may also occupy L178 side pocket and its amide group forms a hydrogenic binding interaction with the flexible R174 residue (Fig. 1B). However, the fragment is small and only occupies two binding pockets. As each pocket can describe the binding interaction between the pocket and its preferred moieties, we introduced a hydrophobic moiety to the pyrrole-pyrimidine fragment. Using a small library featured with hydrophobic fragments, we identified N-phenylsubstituted benzamide fragment as a suitable moiety that was predicted to occupy S257 hydrophobic pocket and maintain the compounds ability to form a hydrogenic binding interaction with R174 pocket (Fig. 1B). Using pyrrole-pyrimidine and N-phenylsubstituted benzamide fragments as the core scaffold, we designed and synthesized 17 compounds (fig. S1D). These compounds were docked into R174 pocket of Snail for the second round of filtration, and four compounds (i.e., CYD16 to CYD19) were found to form interaction with R174. As shown, the most potent compound CYD19 was predicted to anchor into Snail cavity by forming binding interactions with hotspot R174 pocket, L178 side pocket, and S257 hydrophobic pocket (Fig. 1, B and C). Next, we performed the biolayer interferometry (BLI) and microscale thermophoresis (MST) assays to measure the dissociation kinetics of CYD19. BLI analysis revealed that CYD19 had a submicromolar potency (Kd = 0.18 M), while the inactive analog CYD18 was approximately 80-fold less potent toward Snail (Kd = 14.1 M) (Fig. 1D). Similarly, MST assay showed that CYD19 was 55-fold more potent toward Snail than CYD18 (0.2 M versus 11.1 M in Kd) (fig. S1E). To further test whether R174 of Snail is important for its interaction with CYD19, we generated the Snail R174A174 mutant (Snail-R174A mutant) and performed the BLI assay. We observed that the R174A mutation caused steric conformation alteration due to dissimilarity of the side chain of residue, and thus, the compound CYD19 could not fit well with Snail-R174A mutant (Fig. 1C, compare right panel and left and middle panels). As expected, CYD19 showed a 16-fold lower binding affinity to Snail-R174A mutant (Kd = 3.0 M) than wild-type Snail (Snail-WT), as assessed by a BLI assay (fig. S1F). Together, the results from the in silico and BLI assays suggest that R174 is essential for the high-affinity binding of Snail with CYD19. Because the C2H2-type zinc fingers (ZFs) are highly conserved across Snail family members, we used BLI assay to examine the dissociation kinetics of CYD19 toward Slug (alternatively termed Snail2), another member of the Snail family (6, 21, 33). As shown, CYD19 had a submicromolar potency (Kd = 0.6 M), while the inactive analog CYD18 was approximately 145-fold less potent toward Slug protein (fig. S1G), suggesting that CYD19 also forms a binding interaction with Slug protein.

(A) Diagram showing that R174 is evolutionarily conserved across species. Hu, human; Ms, mouse; Rt, rat; Ch, chimpanzee; Zf, zebra fish; Cf, clawed frog; Rd., rock dove. (B) Close-up view of three predicted binding pockets of Snail protein (left) and presumed interaction surface of pyrrole-pyrimidine fragment (middle) and hit compound (right) with Snail. (C) Molecular docking analysis. (D) BLI analysis to measure dissociation kinetics of compounds toward Snail recombinant proteins. (E and F) Immunoblot analysis of Snail expression in cancer cells treated with vehicle or CYD19 for 48 hours (E) or in MMTV-PyMT cells treated with vehicle or 50 nM CYD19 and then with cycloheximide (CHX; 100 g/ml) for a total of 48 hours (F). MDA231, MDA-MB-231. (G) Densitometry of Snail protein in cells as described in (F). (H and I) Comparison of exogenous Snail-WT and Snail-R174A expressions in human embryonic kidney (HEK) 293T cells treated with vehicle or CYD19 for 48 hours (H) or in cells treated with vehicle or 50 nM CYD19 for different times (I). (J) Comparison of ubiquitinated Snail-WT and Snail-R174A proteins in HEK293T cells treated with vehicle or 50 nM CYD19 for 48 hours. MG132 (10 M) was added 4 hours before harvesting. IgG, immunoglobulin G; IP, immunoprecipitation; HA-ubi, hemagglutinin-ubiquitin. (K) Comparison of acetylated and phosphorylated Snail-WT versus Snail-R174A proteins in HEK293T cells as described in (J). (L and M) Binding interaction of exogenous (L) or endogenous (M) Snail with endogenous CBP/p300 was monitored in cells that were treated with vehicle or 50 nM CYD19 for 48 hours. (N) His pulldown assay to assess CYD19s impact on association of CBP-HAT with Snail-WT or Snail-R174A. Arrows and asterisks mark specific and nonspecific bands, respectively. (O) Immunoblot analysis of exogenous Snail expression in HEK293T cells treated with vehicle or 50 nM CYD19 and then with CHX (100 g/ml) for a total of 48 hours. (P) Densitometry of exogenous Snail protein in cells described in (O). All representative blots as shown are from three independent experiments.

Next, we asked whether compound CYD19 could affect Snail expression in carcinoma cell cultures. Immunoblot analysis revealed that CYD19 dose-dependently decreased Snail protein levels in freshly isolated human BrCa primary cells, mouse and human BrCa cell lines, and colorectal cancer cell lines (Fig. 1E and fig. S2A). In addition, we observed that CYD19 reduced Snail protein levels in a time-dependent manner (fig. S2B). As expected, CYD18 did not affect Snail protein levels in the tested cell lines (fig. S2C). No significant changes in Snail mRNA levels were detected in CYD19-treated cells relative to control cells, suggesting that CYD19 regulated Snail expression at posttranslational level (fig. S2D). To directly test whether CYD19 could affect Snail protein stability, we cultured vehicle- or CYD19-treated mouse mammary tumor virus-polyoma middle tumor-antigen (MMTV-PyMT) cells in the presence of cycloheximide (CHX; 100 g/ml) to block newly protein synthesis and examined Snail degradation. After treatment with CHX, Snail became unstable and degraded rapidly in CYD19-treated cells, while the protein was relatively stable in vehicle-treated cells, suggesting that CYD19 indeed reduces Snail protein stability (Fig. 1, F and G). Because CYD19 showed a significantly lower affinity with Snail-R174A mutant than Snail-WT, we compared the protein stability of Snail-R174A mutant versus Snail-WT following CYD19 treatment. Treatment of transfected human embryonic kidney (HEK) 293T cells with CYD19 diminished FLAG-tagged Snail-WT protein levels in a dose- and time-dependent manner (Fig. 1, H and I, top). However, treatment with CYD19 at up to 150 nM or for up to 48 hours failed to decrease Snail-R174A mutant protein levels (Fig. 1, H and I, bottom), confirming that R174 is a key amino acid for Snails binding with CYD19. To test whether this CYD19 effect is mediated through a ubiquitination of Snail, we cotransfected HEK293T cells with FLAG-tagged Snail-WT (or Snail-R174A mutant) and hemagglutinin (HA)ubiquitin and treated them with vehicle or CYD19 for 48 hours. MG132 (10 M) was added to the cells 4 hours before cell harvesting, and the cell lysates were subjected to immunoprecipitation (IP) assay using an anti-FLAG antibody. Notably, we observed that CYD19 remarkably increased the ubiquitination levels of Snail-WT but failed to affect the ubiquitination of Snail-R174A mutant (Fig. 1J). The acetylation of Snail has been reported to stabilize Snail protein (18). We therefore asked whether CYD19 could affect Snail acetylation. We found that CYD19 remarkably decreased acetylation of Snail-WT but not Snail-R174A mutant proteins (Fig. 1M). GSK3 and PKD1 can phosphorylate Snail and promotes its ubiquitination and degradation (2529). Snail acetylation can reduce its phosphorylation, which consequently results in increased protein stability (18). Here, we showed that treatment with CYD19 markedly increased phosphorylation levels of Snail-WT protein but had negligible effects on phosphorylation levels of Snail-R174A mutant protein (Fig. 1K). CBP/p300 has been reported to function as the primary HATs that may acetylate Snail at K146 and K187 (18). We therefore hypothesized that CYD19 binds to Snail protein, which consequently interrupts the interaction of Snail with CBP/p300 and results in impairment of Snail acetylation. To test this, we treated exogenous Snail-transfected HEK293T and HCT116 cells with vehicle or CYD19 and subjected the cell lysates to IP assays using anti-FLAG or anti-Snail antibodies, followed by immunoblot analysis using anti-CBP and anti-p300 antibodies (Fig. 1, L and M). We observed that the treatment of HEK293T and HCT116 cells with CYD19 did not affect total CBP/p300 expressions but markedly reduced Snail-bound CBP/p300 levels (Fig. 1, L and M). In notable contrast, CYD19 did not affect the binding of Snail-R174A mutant with CBP/p300 (Fig. 1L, right). To directly evaluate the ability of CYD19 to interfere the interaction between Snail and CBP, we expressed and purified glutathione S-transferase (GST)CBP-HAT (containing HAT domain of CBP protein) and His-tagged Snail-WT and Snail-R174A (His-Snail-WT and His-Snail-R174A, respectively) mutant recombinant proteins in Escherichia coli bacteria and performed in vitro His pulldown experiments. We observed that CYD19 dose-dependently diminished the interaction of CBP-HAT with His-Snail-WT but not His-Snail-R174A mutant recombinant proteins, suggesting that CYD19 directly interferes the binding between CBP and Snail in a dose-dependent manner (Fig. 1N). To examine whether CBP/p300-mediated acetylation of Snail is actively involved in the regulation of Snail protein stability by CYD19, we generated the Snail-K146R/K187R (Snail-2KR) mutant and performed the CHX chase assay. We observed that the half-life of Snail-2KR mutant protein and Snail-WT protein was comparable in vehicle-treated cells (Fig. 1, O and P). However, Snail-2KR mutant protein degraded more rapidly than Snail-WT protein in CYD19-treated cells, suggesting that CBP/p300-mediated acetylation stabilizes Snail protein in the presence of CYD19 (Fig. 1, O and P). Because CYD19 can also form a binding interaction with Slug, we asked whether CYD19 has an impact on Slug protein expression. Unexpectedly, CYD19 did not affect Slug protein expression in a variety of cancer cell lines (fig. S2E). We demonstrated that Slug, unlike Snail, did not form a binding interaction with CBP/p300 (fig. S2F), suggesting that there should exist other potential regulator proteins (not CBP/p300) responsible for modulating Slug protein expression. These findings suggest that compound CYD19 does not interrupt Slugs interaction with its potential regulator proteins and thus loses the ability to affect Slug protein expression.

Importins (e.g., importin ) are reported to transport Snail protein into the nucleus by tightly interacting with several key amino acid residues within Snails ZF domains, including K161, K170, K187, R191, W193 (tryptophan-193), Q196 (glutamine-196), R220, R224, and Q228 (32, 34, 35). Single mutation, double mutations, or multiple mutations in these residues efficiently (or completely) reduce the binding of Snail with importin , thus severely impairing importin mediated nuclear import of Snail protein (32, 34). To assess whether R174 is required for Snail binding to importin and whether CYD19 that specifically binds to R174 could affect Snailimportin binding interaction, we performed serial His pulldown assays, followed by immunoblots using antiimportin and anti-Snail antibodies (34). To this end, His-Snail-WT or His-Snail-R174A mutant recombinant proteins were purified, immobilized on Ninitrilotriacetic acid (NTA) agarose, and incubated, either in the absence or presence of various concentrations of CYD19, with a complete HEK293T cell lysates used as a source of importin . As shown, both Snail-WT and Snail-R174A mutant proteins physically bound with importin indistinguishably (fig. S2G), suggesting that R174 is not required for Snail binding to importin . Furthermore, compound CYD19 at various concentrations failed to affect binding of Snail-WT with importin (fig. S2H). In addition, we performed in-cell experiments to test whether mutation in R174 could affect Snail subcellular localization. To completely exclude the possibility that small molecules (smaller than 50 kDa) such as Snail protein can diffuse into the nucleus through nuclear pore complexes, we increased the sizes of green fluorescent protein (GFP)Snail-WT and GFP-Snail-R174A proteins by fusing them to GST and transfected them into MCF7 BrCa cells (32, 34). Although GFP-GST was detected in the nucleus and cytoplasm, both GFP-Snail-WT and GFP-Snail-R174A mutant proteins were exclusively localized in the nucleus (fig. S2I), suggesting that R174 is not required for Snail binding to importin and plays no role in importin mediated Snail nuclear import. Intracellular localization of Snail protein was also examined by cell fractionation. As shown, FLAG-tagged Snail-WT and Snail-R174A mutant proteins were both exclusively localized in the nucleus of vehicle- and CYD19-treated cells (fig. S2J). These findings suggest that compound CYD19 that forms binding interaction with R174 pocket of Snail protein does not affect Snailimportin interaction and subsequent Snail subcellular localization. Together, our data support the mode of action by on-target effect of compound CYD19; that is, CYD19 specifically binding to hotspot R174 pocket of Snail protein disrupts the interaction of Snail with CBP/p300 and eventually triggers Snail protein degradation without affecting Snailimportin interaction and subsequent Snail subcellular localization.

Snail has been shown to induce EMT and promote migration and metastasis in various cancer types (5, 8). TGF signaling is known to activate EMT in epithelial-like cancer cells through transcriptionally inducing Snail (8). We therefore tested whether CYD19 could block TGF1/Snail-driven EMT phenotypes in cancer cells. To do this, we pretreated cells with vehicle or TGF1 (2 ng/ml) for 24 hours and further treated them with vehicle or various concentrations of CYD19 in combination with TGF1 (2 ng/ml) for another 48 hours. Notably, we found that CYD19 efficiently blocked TGF1/Snail-driven EMT phenotypes in freshly isolated human BrCa primary cells and various cancer cell lines, as evidenced by increased expression of epithelial marker (E-cadherin) and decreased expressions of mesenchymal markers such as vimentin, N-cadherin, and fibronectin (Fig. 2, A and B, and fig. S3A). Snail is also known to transcriptionally activate inflammatory cytokine genes such as tumor necrosis factor (TNF), extension repair cross-complementation group 1 (ERCC1), C-C motif chemokine ligand 2 (CCL2), CCL5, and interleukin-8 (IL8) (18, 36, 37). We next examined the impact of CYD19 on TGF1/Snail-modulated cytokinome in cancer cells. We observed that CYD19 treatment completely abolished TGF1/Snail-mediated activation of the indicated inflammatory cytokine genes in human BrCa primary cells and various cancer cell lines (fig. S3B), indicating the impact of CYD19 on tumor microenvironment remodeling during cancer progression. TNF has been demonstrated to stabilize Snail protein by modulating nuclear factor B signaling pathway (27). Thus, we evaluated the impact of CYD19 on TNF-stimulated Snail expression. To do this, we treated cells with vehicle or CYD19 for 48 hours and added TNF (10 ng/ml) to stimulate the cells 8 hours before cell harvesting. We found that CYD19 efficiently blocked TNF-stimulated Snail protein expression (Fig. 2C). Together, these findings suggest the important role of CYD19 in suppressing the external stimulusinduced Snail expression. Given that Snail-induced EMT is closely related to migration and invasion of cancer cells, we examined the impact of CYD19 on cancer cell migration. To do this, equal numbers of vehicle- or CYD19-pretreated cells were cultured in serum-free medium supplemented with vehicle or CYD19 in the upper chambers of transwell inserts, while the lower chambers were filled with medium containing 10% serum. We found that CYD19 dose-dependently reduced migration of a variety of cancer cell lines (fig. S3C). To test whether CYD19 inhibited cell migration by specifically targeting Snail protein, we infected Snailfl/fl MMTV-PyMT cancer cells, a cell line that was previously established in our laboratory (20), with adeno-galactosidase (Gal) or adeno-Cre to generate control or Snail-deleted cells, treated them with CYD19 (or vehicle), and subjected them to cell migration assay (Fig. 2, D to F). As expected, migration of Snail-deleted cells was markedly reduced compared to control cells, and CYD19 remarkably suppressed migration of control cells but largely failed to inhibit migration of Snail-deleted cells (Fig. 2, E and F). Moreover, we silenced Snail expression in HCT116 and SUM159 cells and then subjected the cells to migration analysis. As shown, cell migration was slightly reduced in HCT116 cells where Snail was moderately silenced but significantly reduced in cells where Snail was almost completely depleted; CYD19 efficiently reduced migration of control and Snailmoderately silenced HCT116 cells but did not affect migration of Snailcompletely silenced cells (Fig. 2, G and H). A similar phenotype was also observed in SUM159 cells (Fig. 2, I and J). These results suggest that CYD19 inhibits cell migration by specifically targeting Snail protein. Recently, Snail has been reported to play a critical role in regulating aldehyde dehydrogenasepositive (ALDH+) CSC expansion in established MMTV-PyMT breast tumors (20, 38). Here, we observed substantially reduced numbers of ALDH+ CSCs in CYD19-treated cells compared to vehicle-treated cells, suggesting that CYD19 blocked Snail-driven CSC expansion in MMTV-PyMT cells (Fig. 2, K and L).

(A) Immunoblot analysis of Snail, E-cadherin, and vimentin expressions in primary cancer cells and cancer cell lines that were treated with vehicle (Veh.) or TGF1 (2 ng/ml) for 24 hours and then with vehicle or CYD19 in the presence of TGF1 for another 48 hours. (B) Immunofluorescence staining of E-cadherin and vimentin in MMTV-PyMT (left) and 4T1 (right) cells as described in (A). Nuclei were counterstained with 4,6-diamidino-2-phenylindole (DAPI) (blue). (C) Immunoblotting of Snail expression in MMTV-PyMT and HCT116 cells. Cells were treated with vehicle or CYD19 for 48 hours, and TNF (10 ng/ml) was added 8 hours before cell harvesting. (D) Immunoblotting of Snail expression in Snailfl/fl MMTV-PyMT cells that were infected with adeno-Gal or adeno-Cre vectors. (E and F) Equal numbers (2 105 cells per well) of control and Snail-deleted MMTV-PyMT cells pretreated with vehicle or CYD19 for 48 hours were subjected to cell migration assays, and invaded cells were quantified (F). (G and I) Immunoblot analysis of Snail expression in HCT116 (G) and SUM159 (I) cells that were infected with lentiviral vectors expressing controlshort hairpinmediated RNA (shRNA) or two independent Snail-shRNAs. (H and J) Equal numbers (2 105 cells per well) of HCT116 (H) and SUM159 (J) cells were subjected to cell migration assays, and invaded cells were quantified. (K and L) Representative histogram (K) and quantification (L) of ALDH+ subpopulation in control and Snail-deleted MMTV-PyMT cells. All representative blots, images, and histograms as shown are from three independent experiments. All data are presented as means SD (n = 3 independent experiments). *P < 0.05 and **P < 0.01. N.S., not significant. Differences are tested using one-way analysis of variance (ANOVA) with Tukeys post hoc test (H and J) and unpaired two-tailed Students t test (L).

We previously showed that Snail interacts directly with wild-type, but not mutant, p53, thereby triggering its proteasome degradation in BrCa cells (20). Therefore, we asked whether CYD19 has an impact on expression of wild-type and mutant p53. Immunoblot analysis revealed that CYD19 dose-dependently increased wild-type p53 protein levels in various cell lines (Fig. 3A, left). In notable contrast, CYD19 did not affect mutant p53 protein expression in MDA-MB-231, SW620, and DLD1 cells (Fig. 3A, right). Immunofluorescence analysis revealed markedly decreased Snail expression in tandem with increased p53 expression in CYD19-treated MMTV-PyMT and HCT116 cells relative to control cells (Fig. 3B). Although CYD19 did not affect TP53 expression, the compound did increase the mRNA and protein levels of p53 targets p21 and MDM2 in MMTV-PyMT and HCT116 cells in a dose- and time-dependent manner (Fig. 3, C and D, and fig. S4, A and B). To test whether CYD19 could affect wild-type p53 protein stability, vehicle- or CYD19-treated MMTV-PyMT cells were cultured in the presence of CHX (100 g/ml) to block newly protein synthesis, and p53 degradation was examined. After treatment with CHX, p53 protein in vehicle-treated cells was unstable and degraded rapidly starting from 1/2 hours after CHX treatment, while p53 protein in CYD19-treated cells was more stable and started to degrade 2 hours after CHX treatment (Fig. 3, E and F), suggesting that CYD19 increases wild-type p53 protein stability. Consistently, we observed that CYD19 robustly decreased the ubiquitination of endogenous p53 in MMTV-PyMT cells (Fig. 3G). Notably, increase in p53 protein levels and activity are associated with increased levels of p53 acetylation (20, 39), and following Snail deletion, p53 acetylation levels increase (20). We found that CYD19 treatment of MMTV-PyMT cells exhibited increased levels of acetylated p53 (Fig. 3H), suggesting that CYD19 promotes p53 acetylation and thus stabilizes p53 protein by inhibiting Snail protein expression. We previously demonstrated that Snail binds to wild-type p53 and triggers p53 deacetylation by recruiting histone deacetylases (HDACs) to the complex (20). Here, we observed that CYD19 robustly diminished Snail-mediated binding interaction of wild-type p53 with HDAC1 (Fig. 3I), indicating that CYD19 disrupts the HDAC1 recruitment to wild-type p53 and thus increases p53 acetylation and protein levels. To directly test whether Snail is required for CYD19-mediated up-regulation on wild-type p53 expression, we compared expressions of p53 and its target protein p21 in control and Snail-deleted MMTV-PyMT cells in the presence of increasing concentrations of CYD19. Notably, we found that CYD19 robustly increased p53 and p21 expressions in control cells but largely failed to increase their expressions in Snail-deleted cells (Fig. 3J), suggesting that CYD19-mediated up-regulation on p53 pathway heavily depends on Snail expression. Snail silencing robustly increased expression of wild-type p53 protein in HCT116 cells but did not affect mutant p53 expression in DLD1 and SUM159 cells (fig. S4, C to E), confirming our previous observations (20).

(A) Immunoblot analysis of p53 expression in wild-type (left) and mutant (right) p53-expressing cells that were treated with vehicle or CYD19 for 48 hours. (B) Immunofluorescence staining of Snail and p53 in MMTV-PyMT (left) and HCT116 (right) cells treated with vehicle or 50 nM CYD19 for 48 hours. (C) Reverse transcription quantitative polymerase chain reaction (qPCR) analysis of p53, p21, and MDM2 expressions in MMTV-PyMT (top) and HCT116 (bottom) cells as described in (B). (D) Immunoblot analysis of p53, p21, and MDM2 expressions in MMTV-PyMT and HCT116 cells treated with vehicle or CYD19 for 48 hours. (E) Immunoblot analysis of p53 expression in MMTV-PyMT cells treated with vehicle or 50 nM CYD19 and then with CHX (100 g/ml) for a total of 48 hours. (F) Densitometry of p53 protein in cells as described in (E). (G) Comparison of ubiquitinated p53 protein in vehicle- and CYD19-treated MMTV-PyMT cells. MG132 (10 M) was added 4 hours before harvesting. Lysates from vehicle- and CYD19-treated cells loaded at ratios of 2:1 and 1:1 were subjected to IP assay using an anti-p53 antibody. (H) Comparison of acetylated p53 protein in vehicle- and CYD19-treated MMTV-PyMT cells as described in (G). (I) Comparison of binding interaction of p53 with HDAC1 in vehicle- and CYD19-treated MMTV-PyMT cells as described in (G). (J) Comparison of Snail, p53, and p21 expressions in control (left) and Snail-deleted (right) MMTV-PyMT cells that were treated with vehicle or CYD19 for 48 hours. All representative blots and images as shown are from three independent experiments. All data are presented as means SD (n = 3 independent experiments). **P < 0.01. Differences are tested using unpaired two-tailed Students t test (C).

We previously identified Snail as a molecular bypass that suppresses the antiproliferative and proapoptotic effects exerted by wild-type p53 in BrCa (20). Because compound CYD19 increases protein expression of wild-type, but not mutant, p53, we asked whether the compound could affect proliferation and survival of cancer cells harboring wild-type or mutant p53. Notably, we observed that cells harboring wild-type p53 were significantly more sensitive to CYD19 treatment than cells expressing mutant p53, as assessed by the CCK-8 (cell counting kit-8) proliferation assay (Fig. 4A). Furthermore, CYD19 induced apoptosis in a dose-dependent manner in cells expressing wild-type p53 but essentially failed to induce apoptosis in cells with mutant p53 (Fig. 4B and fig. S5A). Consistently, treatment of wild-type p53-expressing MMTV-PyMT and HCT116 cells with compound CYD19 dose-dependently increased expressions of p53-inducible proapoptotic proteins Puma and Bax and triggered the release of cytochrome c (Cyt-c) from mitochondria, thus inducing the activation (cleavage) of caspase 9 and caspase 3, a dominant executor of cell apoptosis (Fig. 4C). CYD19 also increased Bax expression and induced caspase 3 activation in a time-dependent manner (fig. S5B). To determine whether Snail is required for CYD19-mediated up-regulation on proapoptotic protein expressions, we compared their expressions in control and Snail-deleted MMTV-PyMT cells in the presence of increasing concentrations of CYD19. As shown, we observed that CYD19 dose-dependently increased Bax and activated caspase 3 expressions in control MMTV-PyMT cells, while the compound essentially failed to increase proapoptotic protein expressions in Snail-deleted cells (Fig. 4D). The CCK-8 cell proliferation assay further revealed that Snail-deleted MMTV-PyMT cells were substantially less sensitive to CYD19 treatment than control cells (Fig. 4E). To directly test whether Snail is required for CYD19-mediated inhibition on cell proliferation and survival, Snail expression was silenced in HCT116 cells, and cell proliferation and survival were assessed in control and Snail-silenced cells in the presence of vehicle or increasing concentrations of CYD19. As shown, we found that CYD19 dose-dependently induced apoptosis in control HCT116 cells but essentially failed to induce apoptosis in Snail-silenced cells (Fig. 4F and fig. S5C). Consistently, the CCK-8 cell proliferation assay revealed that Snail-silenced HCT116 cells were significantly less sensitive to CYD19 treatment than control cells (Fig. 4G). To further test whether p53 is required for CYD19-mediated inhibition on cell survival and proliferation, p53 expression were silenced in HCT116, and cell survival and proliferation were assessed in control and p53-silenced cells in the presence of vehicle or increasing concentrations of CYD19. As compared with control cells, p53-silenced HCT116 cells had significantly diminished responsiveness to CYD19 to inhibit cell survival and proliferation (Fig. 4, H and I, and fig. S5D). Notably, Snail silencing efficiently reduced proliferation of wild-type p53-expressing tumor cells but did not affect growth of mutant p53-expressing cells (fig. S5E), which confirms and extends our previous observations (20). Given that Snail-driven EMT confers tumor resistance toward many chemotherapeutics (10, 15, 16), the impact of CYD19 on EMT-driven chemoresistance was therefore examined. We found that low-dose taxol (doses ranging from 0.5 to 4.0 nM in MMTV-PyMT cells and from 1.0 to 8.0 nM in HCT116 cells) or CYD19 (20 nM in both cell lines) had no impact on cell proliferation, while low-dose taxol in combination with CYD19 (25 nM) yielded a strong and superior antiproliferation activity in both cell lines (Fig. 4J), suggesting that CYD19 reverses EMT-driven chemoresistance and thus sensitizes cancer cells to low-dose chemotherapy. Together, our findings suggest that CYD19 reduces proliferation and survival of tumor cells in a TP53 wild typedependent fashion.

(A) CCK-8 cell proliferation assay for wild-type and mutant p53-expressing cells treated with vehicle or CYD19 for 48 hours. (B) Quantification of apoptotic subpopulation in various cell lines treated with vehicle or CYD19 for 48 hours. (C) Immunoblot analysis of the indicated protein expressions in MMTV-PyMT (left) and HCT116 (right) cells as described in (B). C-casp9, cleaved caspase 9. (D) Immunoblot analysis of the indicated protein expressions in control and Snail-deleted MMTV-PyMT cells treated with vehicle or CYD19 for 48 hours. (E) CCK-8 analysis for control and Snail-deleted MMTV-PyMT cells treated with vehicle or CYD19 for 48 hours. (F) Quantification of apoptotic subpopulation in control and Snail-silenced HCT116 cells treated with vehicle or CYD19 for 48 hours. (G) CCK-8 analysis for control and Snail-silenced HCT116 cells treated with vehicle or CYD19 for 48 hours. (H) Quantification of apoptotic subpopulation in control and p53-silenced HCT116 cells treated with vehicle or CYD19 for 48 hours. (I) CCK-8 analysis for control and p53-silenced HCT116 cells treated with vehicle or CYD19 for 48 hours. (J) CCK-8 analysis for MMTV-PyMT and HCT116 cells that were treated with vehicle or taxol in combination with vehicle or 25 nM CYD19 for 48 hours. All representative blots as shown are from three independent experiments. All data are presented as means SD (n = 3 independent experiments). **P < 0.01. Differences are tested using one-way ANOVA with Tukeys post hoc test (B, F, and H).

Snail has been known to play an essential role in controlling tumor progression and metastasis as well as the expansion of TICs in MMTV-PyMT transgenic mice (20), a mouse model of BrCa that mirrors the multistep progression of human BrCa (40). Here, we asked whether CYD19 could affect Snail-driven progression and metastasis of spontaneous breast tumors in MMTV-PyMT transgenic mice. To do this, we treated 2-month-old female littermates that developed palpable breast tumors in a total volume of ~0.4 cm3 with vehicle or CYD19 (30 mg/kg) for consecutive 25 days and examined the formation of primary and metastasized tumors. As shown, tumor volumes and weights were robustly reduced in CYD19-treated mice compared to vehicle-treated mice (Fig. 5, A and B). Notably, CYD19 did not affect body weights of tumor-bearing mice or induce detectable histological alterations in their vital organs such as the heart, liver, spleen, or kidneys, supporting the absence of toxicity in CYD19-treated mice (fig. S6, A and B). Furthermore, we observed that CYD19 substantially decreased the percentages of proliferative (Ki67-positive) and mitotic (phospho-histone H3positive) cells but increased the percentages of apoptotic (cleaved caspase 3positive) cells (Fig. 5, C and D, and fig. S6, C and D). As expected, tumors of CYD19-treated mice exhibited remarkably reduced Snail expression in tandem with increased wild-type p53 protein levels, as assessed by immunoblot and immunofluorescence analyses (Fig. 5E and fig. S6, E and F). Histological analysis revealed that vehicle-treated tumors progressed to poorly differentiated adenocarcinomas at the end of the treatment, while CYD19-treated tumors exhibited a more differentiated phenotype (Fig. 5F). Consistently, tumors of CYD19-treated mice showed an increase in E-cadherin expression in tandem with reduced vimentin expression, suggesting that CYD19 suppresses Snail-driven EMT in the in vivo setting (Fig. 5, G and H). We observed that CYD19 remarkably impaired ALDH+ CSC expansion in primary tumors (Fig. 5, I and J), which is consistent with the in vitro observations (Fig. 2, M and N). Snail is known to promote recruitment of tumor-associated macrophages (TAMs), thus facilitating tumor progression (18). We observed that CYD19 reduced intratumoral infiltration of F4/80+ TAMs and CD31+ endothelial cells (Fig. 5, K and L). CYD19 also reduced metastatic potential of primary tumors, as evidenced by remarkably fewer and smaller metastatic nodules in the lungs of CYD19-treated mice relative to vehicle-treated mice (Fig. 5, M to O). Collectively, the findings suggest that CYD19 suppressed Snail-driven tumor progression, pulmonary metastasis, and CSC expansion in MMTV-PyMT transgenic mice that express wild-type p53.

(A and B) Primary tumor volumes (A) and weights (B) were measured in MMTV-PyMT mice that were intraperitoneally treated with vehicle or CYD19 (30 mg/kg) for 25 consecutive days (n = 6 mice, each). (C) Immunohistochemical staining of Ki67 (top) and cleaved caspase 3 (bottom) in primary tumors of vehicle- and CYD19-treated mice (n = 6 mice, each). (D) Quantification of Ki67-positive (Ki67+; top) and cleaved caspase 3positive (C-casp3+; bottom) cells in tumors as described in (C). (E) Immunoblot analysis of Snail and p53 expressions in tumor lysates of vehicle- and CYD19-treated mice (n = 3 pools from six mice, each). (F) Hematoxylin and eosin (H&E) staining for primary tumors as described in (C) (n = 6 mice, each). Magnified areas of boxed sections are shown in the bottom panels. (G) Immunofluorescence staining of E-cadherin and vimentin in primary tumors as described in (C) (n = 6 mice, each). (H) Quantification of staining intensity in primary tumors as described in (G). (I and J) Representative histogram (I) and quantification (J) of ALDH+ subpopulation in primary tumors as described in (C) (n = 6 mice, each). DEAB, diethylaminobenzaldehyde. (K) Immunofluorescence staining of F4/80 and CD31 in primary tumors as described in (C) (n = 6 mice, each). (L) Quantification of staining intensity in primary tumors as described in (K). (M) H&E staining for vehicle- and CYD19-treated lungs (n = 6 mice, each). (N) Magnified areas of boxed sections in (M) are shown. (O) Quantification of nodules in vehicle- and CYD19-treated lungs as described in (M). All data are presented as means SD (n = 6 independent experiments). *P < 0.05 and **P < 0.01. Differences are tested using Mann-Whitney U test.

Next, we asked whether CYD19 had a similar impact on colon cancer growth and hepatic metastasis using a HCT116 xenograft model in which 1 106 HCT116 cells in 50 l of diluted Matrigel were injected subcutaneously into the dorsal flank of athymic BALB/c nude mice. We observed that CYD19 dose-dependently reduced the growth of HCT116 xenograft tumors (Fig. 6, A and B), without eliciting body weight loss or histological alterations in the vital organs such as the heart, liver, spleen, lung, and kidney (fig. S7, A and B). Furthermore, we found that CYD19 reduced the percentages of proliferative and mitotic cells while increasing the percentages of apoptotic cells in xenograft tumors (Fig. 6, C and D, and fig. S7, C and D). Notably, CYD19 suppressed Snail expression while increasing p53 expression in xenograft tumors, as assessed by immunoblot and immunohistochemical analyses (Fig. 6E and fig. S7, E to H). In addition, impaired EMT was detected in CYD19-treated xenograft tumors, as illustrated by increased E-cadherin expression in tandem with a reduction in vimentin expression (Fig. 6, F and G). We next examined the impact of CYD19 on ALDH+ CSC expansion in HCT116 xenograft tumors. To do this, we sorted ALDH+ and ALDH cells from HCT116 xenograft tumors and performed in vitro tumorsphere assay. The results demonstrated that ALDH+ but not ALDH cells had the potential to form tumorspheres, confirming that ALDH can be used for identification of CSCs in HCT116 xenograft tumors (fig. S7I). Notably, we observed that CYD19 severely impaired ALDH+ CSC expansion in HCT116 xenograft tumors (Fig. 6, H and I). To further examine whether the in vivo anticancer effect of CYD19 is Snail-dependent, we subcutaneously implanted 1 106 control or 2 106 Snail-silenced HCT116 cells into nude mice, treated mice with vehicle or CYD19 (30 mg/kg) for two consecutive weeks starting at 7 days after implantation, and monitored tumor growth. The volumes of xenograft tumors formed by 1 106 control or 2 106 Snail-silenced cells were comparable (Fig. 6J). Notably, CYD19 suppressed tumor growth of control cells but largely failed to affect tumor growth of Snail-silenced cells (Fig. 6J), suggesting that CYD19 suppresses tumor growth by specifically targeting Snail protein. Furthermore, immunoblot analysis of xenograft tumor lysates revealed that Snail expression was efficiently silenced in Snailshort hairpinmediated RNA 2 (shRNA2)expressing cells where p53 protein was robustly increased (Fig. 6K, compare lane 3 versus lane 1). As expected, CYD19 decreased Snail expression while increasing p53 protein in control cells (Fig. 6K, compare lane 2 versus lane 1), and the compound lost its ability to increase p53 expression in Snail-silenced cells (Fig. 6K, compare lane 4 versus lane 3). In addition, equal numbers (1 106) of control or Snail-silenced HCT116 cells were implanted into nude mice; the mice were treated with vehicle or CYD19, and tumor growth was monitored. As shown in fig. S7J, CYD19 suppressed tumor growth of control cells by 60.3% at the end point of treatment (compare curve 2 versus curve 1), and Snail silencing itself reduced tumor growth by 64.8% (compare curve 3 versus curve 1). While CYD19 remarkably reduced control tumor growth by 60.3%, the compound inhibited tumor growth of Snail-silenced cells by 4% (compare curve 4 versus curve 3), further confirming that CYD19 suppresses tumor growth by specifically targeting Snail protein. Next, we assessed the impact of CYD19 on tumor metastasis using a hepatic metastasis model in which 1 106 GFP-labeled HCT116 cells were intrasplenically injected to nude mice. The results demonstrated that CYD19 treatment for three consecutive weeks robustly reduced tumor metastasis and nodule formation in the livers (Fig. 6, L and M). Together, these findings suggest that CYD19 reduces Snail-driven tumor growth, hepatic metastasis, and CSC expansion in colon cancer xenografts expressing wild-type p53.

(A and B) HCT116 xenograft tumor volumes (A) and weights (B) were measured in athymic nude mice that were intraperitoneally treated with vehicle or CYD19 for two consecutive weeks (n = 6 mice, each). (C) Immunohistochemical staining of Ki67 (top) and cleaved caspase 3 (bottom) in xenograft tumors of vehicle- and CYD19-treated mice (n = 6 mice, each). (D) Quantification of Ki67+ (top) and C-casp3+ (bottom) cells in tumors as described in (C). (E) Immunoblot analysis of Snail and p53 expressions in tumor lysates of vehicle- and CYD19-treated mice (n = 3 pools from six mice, each). (F) Immunofluorescence staining of E-cadherin and vimentin in xenograft tumors of vehicle- and CYD19-treated mice (n = 6 mice, each). (G) Quantification of staining intensity in xenograft tumors as described in (F). (H and I) Representative histogram (H) and quantification (I) of ALDH+ subpopulation in xenograft tumors as described in (C) (n = 6 mice, each). (J) Growth of HCT116 xenograft tumors derived from 1 106 control cells or 2 106 Snail-silenced cells was monitored in nude mice treated with vehicle or CYD19 for two consecutive weeks (n = 6 mice, each). (K) Immunoblot analysis of Snail and p53 expressions in lysates of xenograft tumors as described in (J). (L) Representative phase contrast (top), GFP fluorescence (middle), and H&E (bottom) images of vehicle- and CYD19-treated livers (n = 6 mice, each). Mice were treated with vehicle or CYD19 for three consecutive weeks starting from the third day after surgery. (M) Quantification of fluorescence intensity in livers as described in (L). All data are presented as means SD (n = 6 independent experiments). **P < 0.01. Differences are tested using Mann-Whitney U test.

The ZF transcription factor Snail is aberrantly activated in a variety of malignant tumor types (2023) and plays an essential role in EMT, metastasis, stem celllike properties, cancer metabolism, microenvironment modulation, immune evasion, cancer recurrence, and therapeutic resistance (9, 10, 1318, 41, 42). Snail is also known to promote cancer cell survival by enhancing resistance to apoptosis under the genotoxic stress condition (19). We recently identified Snail as a molecular bypass that suppresses the antiproliferative and proapoptotic effect in BrCa (20). Given the important role of Snail in driving cancer progression, we propose that targeting Snail would be an attractive anticancer therapeutic approach. However, to our knowledge, the development of small molecules to inhibit Snails functions is unsuccessful, as there is no clear ligand-binding domain for targeting Snail (43). In the current study, we have identified the evolutionarily conserved R174 pocket as a key hotspot in the binding site of Snail. Using fragment-based virtual screening analysis in combination with Glide docking algorithms, we have screened 50 small molecules that represent 23 structural clusters. Using the pyrrole-pyrimidine fragment and N-phenylsubstituted benzamide fragment as the core scaffold, we then designed 17 small-molecule compounds. Using BLI and MST analyses, the compound CYD19 that is predicted to form both hydrogenic and hydrophobic binding interactions with R174 pocket has been eventually identified as a lead compound showing the highest binding affinity with recombinant Snail protein among these compounds. BLI analysis reveals that Snail-R174A mutant protein is 16-fold less potent toward CYD19 than Snail-WT protein. Serial biochemical analyses further show that Snail-WT protein can be efficiently captured by CYD19 and is consequently degraded through the ubiquitin-proteasome pathway, while Snail-R174A mutant protein is essentially resistant to degradation following CYD19 treatment because of its inefficient interaction with CYD19. On the basis of these observations, we conclude that the evolutionarily conserved R174 pocket instead of the ligand-binding domain within Snail protein is critical for its interaction with the compound CYD19.

CBP/p300 HATs have been shown to bind to acetylate and stabilize Snail by repressing its polyubiquitination and subsequent proteasome degradation (18). Note that CYD19 binding to Snail has no impact on the interaction of Snail with importin 1, thus failing to affect importin 1mediated nuclear import of Snail protein. On the basis of Snailimportin 1 cocrystal structure (32), we propose that CYD19 binds to the outer surface of Snailimportin 1 complex and thus impairs the surface contactmediated Snail-CBP/p300 interaction. Following treatment of cancer cells with CYD19, Snail acetylation level is reduced while its levels of phosphorylation and ubiquitination are increased, thereby promoting proteasome degradation of Snail. Two phosphorylation-dependent E3 ligases -TRCP and FBXO11 and one phosphorylation-independent E3 ligase FBXL14 have been identified that mediate Snail degradation (2531). Although we observed that CYD19-treated cells increased the phosphorylation levels of Snail, we could not exclude the possibility that FBXL14 is also responsible for Snail degradation. Snail is abundantly expressed in specific cell lineages during embryonic development, becomes essentially undetectable in normal adult tissues, and is reactivated in cancerous tissues, revealing the spatial and temporal expression pattern of Snail in normal and neoplastic states (7, 2023, 44, 45). Notably, we have observed that CYD19 potently suppresses Snail-driven cancer growth and metastasis without eliciting obvious side toxicity in tumor-bearing mice. This can be attributed to the high selectivity of the compound for targeting Snail protein and the spatial expression pattern of Snail in cancerous tissues versus normal tissues (7, 2023, 44, 45). Since CYD19 specifically interrupts the binding interaction of CBP/p300 with Snail without affecting its enzymic activity, we expect that CYD19 may have a significantly lower toxicity than the enzyme inhibitors of CBP/p300 or deubiquitinases 3, two enzymes that may affect expression of many downstream proteins including Snail protein (18, 43). Notably, Slug, unlike Snail, cannot form a binding interaction with CBP/p300, and there should exist other potential regulator proteins responsible for modulating Slug protein expression. We therefore propose that compound CYD19 does not interrupt Slugs interaction with its regulator proteins and thus loses the ability to affect Slug protein expression. Future work is needed to identify the regulator proteins that are responsible for modulating Slug protein expression.

The tumor suppressor p53 protein is stabilized and activated in response to cellular stress, thereby triggering growth arrest and apoptosis in cancer cells. TP53 is a frequent mutational target in human cancers (~50%), and mutant p53 loses the function of wild-type p53 but functions as an oncoprotein instead (46). The EMT-associated transcription factors, including Slug, Zinc Finger E-Box Binding Homeobox 1 (ZEB1), and Twist, have been reported to indirectly or directly affect p53 function, but the outcome of these interactions has varied (19, 47, 48). Using a MMTV-PyMT BrCa mouse model, we recently find that Snail deletion stabilizes wild-type, but not mutant, p53 and identify Snail as a molecular bypass that suppresses the antiproliferative and proapoptotic effects executed by wild-type p53 (20). Here, we further present in vitro data demonstrating that silencing Snail robustly reduces growth of wild-type p53expressing tumor cells but does not affect growth of tumor cells expressing mutant p53. Snail deficiency in embryonic endothelial cells epigenetically enhances Delta Like Canonical Notch Ligand 4 (DLL4)/Notch signaling but does not affect wild-type p53 protein expression, which consequently represses embryonic vascular remodeling without affecting proliferation or survival of endothelial cells (44). On the basis of these observations, we propose that Snail functions as a key regulator in tumor progression and embryonic vascular development through two distinct mechanisms.

In the present study, we found that compound CYD19 specifically binds to hotspot R174 pocket of Snail protein and thus disrupts the binding interaction of Snail with CBP/p300, which eventually triggers Snail protein degradation through the ubiquitin-proteasome pathway. CYD19 restores Snail-dependent repression of wild-type p53 and thus reduces tumor cell growth and survival. CYD19 also reverses Snail-driven EMT and impairs EMT-associated tumor invasion and metastasis. Given that aberrantly activated Snail is associated with poor prognosis and that more than 50% of patients with cancer express wild-type p53, pharmacologically targeting Snail by CYD19 may exert good therapeutic benefits in patients with cancer especially harboring wild-type p53. Moreover, pharmacologically targeting Snail by CYD19 may also diminish EMT-associated therapeutic resistance and thus sensitizes tumors to low-dose chemotherapy, supporting the rationale for the combination of CYD19 with nontoxic low-dose chemotherapeutics for cancer treatment in the clinic.

Mice were housed under standard specific pathogenfree conditions, and all animal experiments were performed in accordance with protocols approved by the Animal Ethics Committee of China Pharmaceutical University. MMTV-PyMT transgenic mice on FVB background were purchased from the Jackson laboratory (#002374), and the colony was maintained in our laboratory. Male athymic BALB/c nu/nu nude mice were obtained from Qinglongshan Animal Facility (Nanjing, China). The maximal tumor sizes permitted under the approved protocols are 3 cm (length) by 3 cm (width). The clinical study was approved by the Ethics Committee of the First Affiliated Hospital of Nanjing Medical University, and written informed consents were obtained from each participant before procedure.

The crystal structure of Snail has been reported (32), thus offering an opportunity for structure-based drug design. FTMap, an online computational solvent mapping software (http://ftmap.bu.edu/login.php), was applied to predict the binding hotspots of a protein by using a set of 16 small organic molecules (that is, probes) that vary in size, shape, and polarity. The probes were applied to find favorable positions using an empirical energy function and the CHARMM potential with a continuum electrostatics term. The regions that bind several small organic probe clusters are defined as the predicted hotspots. The residues with the highest number of interactions are defined as the main hotspots. The druggable binding cleft of Snail (PDB ID: 3W5K) (32) mainly consists of three main subpockets: R174 pocket, L178 side pocket, and S257 hydrophobic pocket. For each pocket, a set of chemically related fragments were identified. On the basis of the DrugBank database for virtual screening, an in-house chemical library containing fragment-like molecules was prepared to explore the potential small molecules that form a high-affinity binding interaction with Snail protein. The DrugBank database (http://www.drugbank.ca), which consists of 7736 drug items (including 1584 Food and Drug Administrationapproved small-molecule drugs), was applied for drug screening. For virtual screening, the simulations were applied through the software Schrdinger 2016. Preparation of the crystal structures of Snail (32) was carried out using the Protein Preparation Wizard module. Proper preparation of the ligands was accomplished by the LigPrep module. All other parameters were set to the default values. The cavity that surrounds within 15 of the R174 pocket was defined as the binding site. Top-ranking 200 molecules were picked up for visual observation based on docking scores of Glide_SP module. These molecules were then filtered on the basis of the predefined interaction to the Snail crystal structure. The pyrrole-pyrimidine (DrugBank_431) fragment could form close atomic contacts with residues in both R174 binding pocket and L178 binding pocket. The molecules were further optimized to improve the compounds shape complementarity to the third S257 hydrophobic binding pocket. A small-molecule library featured by hydrophobic fragments was applied to screen the appropriate hit compounds. Both pyrrole-pyrimidine and N-phenylsubstituted benzamide fragments were predicted to match Snail protein: (i) engaging in H bondacceptor interactions with the backbone residue of R174 (hinge binding region), (ii) occupying S257 hydrophobic pocket, and (iii) positioning an aromatic group to make edge-to-face interaction with L178 side pocket. Last, 17 candidate compounds were selected and synthesized for further docking and experimental validation.

Details of the organic synthesis and chemical characterization of the compounds are available upon reasonable request. Compounds used in assays were dissolved in 100% dimethyl sulfoxide and kept as 50 mM stock solutions for in vitro studies.

All cell lines used in the study were purchased from the American Type Culture Collection. Cells were tested for mycoplasma contamination every 1 month, and only mycoplasma-negative cells were used. Wild-type and Snailfl/fl MMTV-PyMT cancer cells were generated and maintained in our laboratory as described previously (20). MMTV-PyMT cancer cells were cultured in Dulbeccos modified Eagles medium (DMEM)/F12 medium supplemented with 5% heat-inactivated fetal bovine serum (FBS) (Thermo Fisher Scientific, #10099-147), EGF (10 ng/ml; PeproTech, #315-09), hydrocortisone (500 ng/ml; Sigma-Aldrich, #H0888), insulin (5 mg/ml; #I9278), cholera toxin (20 ng/ml; #C8052), and 1% penicillin-streptomycin (Thermo Fisher Scientific, #15140122). HEK293T, HCT116, RKO, 4T1, DLD1, SW620, SUM159, and MDA-MB-231 cells were grown in DMEM supplemented with 10% FBS and 1% penicillin-streptomycin. For isolation of human BrCa primary cells, freshly isolated breast tumors were rinsed extensively three times in cold phosphate-buffered saline (PBS) supplemented with 1% penicillin-streptomycin and chopped into small fragments (~1 mm3). Tissue fragments were digested into single-cell suspension by incubation in DMEM containing 10% FBS, 1% penicillin-streptomycin, collagenase type 1 (1 mg/ml; Sigma-Aldrich, #C0130), and hyaluronidase (125 U/ml; STEMCELL Technologies, #07919) for 12 to 18 hours at 37C with slow agitation. After incubating for 5 min at room temperature without agitation, the stromal cellenriched supernatant was discarded, and the epithelial cellrich pellets were filtered with a 40-m nylon mesh to remove cell clumps. Tumor epithelial cells were washed three times, resuspended, and cultured in DMEM/F12 medium containing 5% heat-inactivated FBS, EGF (10 ng/ml), hydrocortisone (500 ng/ml), insulin (5 mg/ml), cholera toxin (20 ng/ml), and 1% penicillin-streptomycin.

The binding of various concentrations of CYD19 to Snail-R174A mutant proteins was determined using BLI assays with an Octet RED96 instrument (ForteBio). Briefly, recombinant Snail-R174A mutant proteins were dissolved in PBS. For biotin labeling, EZ-Link NHS-Biotin was incubated for 60 min with proteins at room temperature (1:3 molar ratio of protein to biotin). Desalination was used to remove the excess of biotin. The biotinylated protein was immobilized onto Super Streptavidin (SSA) biosensors for further measurement. A duplicate set of SSA sensors incubated in the buffer without protein were used as negative binding control. The assay was determined in black 96-well plates at different concentrations of CYD19 and PBS as a nonspecific interaction control. The binding event was recorded according to the shift in the interference pattern of the light. Data were then analyzed in ForteBio Data Analysis to calculate the association and dissociation rates using 1:1 binding model, and Kd was represented by the ratio Koff/Kon.

A Monolith NT.115 purchased from NanoTemper Technologies was used for MST assays. The concentration of GFP-tagged Snail recombinant protein was diluted according to the manufacturers instructions. The selected compounds at different concentrations were incubated with GFP-tagged Snail protein for 5 min at room temperature in assay buffer containing 0.05% Tween 20. Thermophoresis was then determined at 25C with 20 to 50% excitation power and 40 to 60% MST power.

Recombinant His-tagged Snail protein was purified from E. coli (BL21) by Ni-NTA affinity chromatography. Cells were lysed in lysis buffer [containing 10 mM MgCl2, 150 mM NaCl, 20 mM tris-HCl (pH 8.0), and 10 mM imidazole] and eluted stepwise using 50, 300, and 500 mM imidazole in wash buffer. The eluted protein was further purified by size exclusion chromatography using a Superdex 75 (Millipore) equilibrated with 20 mM Hepes (pH 7.0), 50 mM NaCl, and 2 mM tris(2-carboxyethyl)phosphine (TCEP). Recombinant GST-tagged CBP-HAT protein was purified from E. coli (BL21) by affinity glutathione-agarose chromatography. Cells were lysed in STE buffer [containing 10 mM tris-HCl buffer, 100 mM NaCl, 1 mM EDTA, 0.01% Triton X-100, and 1 mM dithiothreitol (pH 7.5)] and eluted stepwise using elute buffer [200 mM tris-HCl and 30 mM l-glutathione reduced (pH 8.0)].

For apoptosis analysis, cancer cells were treated with vehicle or various concentrations of CYD19 for 48 hours, and the percentage of apoptotic cells was determined by the fluorescein isothiocyanate annexin V apoptosis detection kit I (BD Biosciences, #556547) according to the manufacturers instructions. The cell apoptosis was analyzed with FlowJo software. For ALDH activity analysis, tumors were chopped into small fragments (around 1 mm3), digested into single-cell suspension by incubation in digestion buffer [0.1% collagenase type 2 (Sigma-Aldrich, #C6885) and deoxyribonuclease I (3 U/ml; Sigma-Aldrich, #D5025)] for 30 min at 37C, and then filtered with a 40-m nylon mesh to remove cell clumps. The single-cell suspensions or cancer cell lines were subjected to serial incubations with an antibody cocktail containing CD31, CD45, and Ter119 (STEMCELL Technologies, #19757C.1); a secondary biotin-labeled antibody cocktail (STEMCELL Technologies, #19153); and magnetic beads (15 min each) on ice (STEMCELL Technologies, #19150). The unbound cells were collected, and the bound cells were discarded. Cells were washed extensively and subjected to ALDH activity assay using a kit from STEMCELL Technologies according to the manufacturers instructions. For each sample, half of the cells were treated with diethylaminobenzaldehyde (DEAB), and the other half were incubated with an activated ALDEFLUOR reagent. Gating was established using fixable viability dye exclusion for viability, and DEAB-treated cells were used to define negative gates. Flow cytometry data were collected with a MACSQuant flow cytometer (BD Biosciences), and analysis was conducted using FlowJo software.

Cells were treated with vehicle or various concentrations of CYD19 for 48 hours, and equal numbers (2 105 cells per well) of the cells were seeded in FBS-free DMEM culture medium in the presence of vehicle or various concentrations of CYD19 in the upper chambers of transwell inserts with an 8-m pore size (BD Biosciences, #354480). The lower chambers were filled with 1 ml of complete medium supplemented with 10% FBS. Cells were allowed to invade the bottom chamber for 12 or 18 hours. Noninvading cells in the upper surface were removed, and invaded cells on the lower surface were fixed with 90% methanol and stained with 0.1% crystal violet for 5 min. The stained cells were photographed and quantified.

Cell proliferation was measured by a CCK-8 kit (Yeasen, #40203ES60) according to the manufacturers instructions. Briefly, cells were seeded in 96-well plates at 4 103 cells per well in culture medium supplemented with 10% FBS. Cells were allowed to adhere for 12 hours and then treated with vehicle or various concentrations of CYD19 for another 48 hours. Cell proliferation was measured, and absorbance intensity was determined with a Molecular Devices microplate reader at 450 nm.

Single-cell suspensions of 1 106 HCT116 cells in 50 l of diluted Matrigel (1:1; BD Biosciences, #356234) were injected subcutaneously into the dorsal flank of male nude mice at 6 to 8 weeks of age. Mice were randomized into three groups until their tumors reached a size of approximately 100 mm3. Mice were then treated with vehicle [formulated in ethanol/cremophor/water at 10:10:80 (v/v/v)], CYD19 (30 mg/kg), or CYD19 (50 mg/kg) via intraperitoneal injection for two consecutive weeks. Tumor volumes were measured every 1 day using the formula length width2/6. At the end point of treatment, mice were euthanized, and tumors and key organs were dissected, photographed, and weighed. Tissues were either fixed in 4% paraformaldehyde (PFA) for immunohistochemical and histological analyses or snap-frozen in liquid N2 and stored at 80C for immunoblot analysis. In some experiments, 1 106 control-shRNAexpressing cells and 2 106 (or 1 106) Snail-shRNA2expressing cells were used to form tumor xenografts in comparable sizes. For liver metastasis assay, a left subcostal surgical incision was created, and 1 106 GFP-labeled HCT116 cells were intrasplenically injected into the spleen of male nude mice (6 to 8 weeks of age). Mice were then treated intraperitoneally with vehicle or CYD19 (30 mg/kg) for three consecutive weeks starting from the third day after surgery, and livers were then harvested for analysis.

MMTV-PyMT female mice bearing primary tumors with an average volume of 400 mm3 were divided into two groups and intraperitoneally injected with vehicle or CYD19 (30 mg/kg) for 25 consecutive days. Tumors were measured every 1 day using a caliper, and the volumes were calculated using the formula length width2/6. At the end of treatment point, mice were euthanized, and tumors, lungs, and key organs were dissected for further use.

p3XFLAG-Snail-WT, p3XFLAG-Slug-WT, and pLKO.1-ms.p53-shRNA vectors were generated and used as described previously (20, 21). pET23a(+)-His-Snail-WT, His-Snail-R174A, p3XFLAG-Snail-R174A, FLAG-Snail-K147R/K186R, pLKO.1-hu.p53-shRNA (targeting mRNA sequence from ATG, 176 to 196), pLKO.1-Snail-shRNA1 (468 to 486), pLKO.1-Snail-shRNA2 (1515 to 1533), pCDN3.1-GST-Snail-WT-GFP, and pCDN3.1-GST-Snail-R174A-GFP vectors were generated by GenScript Biotech Inc. (Nanjing, China). HA-ubiquitin (#18712), GST-CBP-HAT (#21093), pLKO.1-TRC (#10879), psPAX2 (#12260), and pMD2.G (#12259) were purchased from Addgene. To produce pLKO.1 lentiviral particles, HEK293T cells were cotransfected with pLKO.1-shRNA, psPAX2, and pMD2.G at a ratio of 4:3:1 using Lipofectamine 2000 Reagent (Invitrogen, #11668027). Cells were fed with fresh medium 24 hours after transfection, and conditioned medium containing viral particles was harvested 48 and 72 hours after transfection. Viral particles were stored at 80C for further use or immediately used. For lentiviral infection, target cells were incubated with a mixture of conditioned medium (containing viral particles) and culture medium at a ratio of 1:1 for 24 hours in the presence of polybrene (8 g/ml; Sigma-Aldrich, #H9268). Cells were reinfected with viral particles for another 24 hours and harvested for further use. For adenoviral infection, cells were infected with complete medium supplemented with adeno-Gal or adeno-Cre viral particles for 24 hours, refed with fresh medium containing viral particles, and further cultured for another 24 hours. Cells were collected for further use.

For immunoblot analysis, cells were lysed in RIPA lysis buffer (Thermo Fisher Scientific, #89901) supplemented with protease inhibitor cocktail (#87786), and total cell lysates were collected for further uses. In some experiments, nuclear and (or) cytoplasmic proteins were extracted using the NE-PER Nuclear and Cytoplasmic Extraction Reagents (Thermo Fisher Scientific, #78833) according to the manufacturers instructions. The cell lysates were subjected to immunoblot assay using primary antibodies against Snail (#3895; 1:1000), Slug (#9585; 1:1000), Cyt-c (#4280; 1:1000), caspase 3 (#9665; 1:1000), caspase 9 (#9508; 1:1000), cleaved caspase 3 (#9661; 1:500), cleaved caspase 9 (#52873; 1:500), p53 (#2524; 1:1,000), Bax (#2772; 1:1000), Puma (#24633; 1:1000), pan-acetyl-Lys (pan-AcK; #9441; 1:500), CBP (#7389; 1:1000), p300 (#70088; 1:1000), ubiquitin (#3936; 1:1000), HDAC1 (#5356; 1:1000), vimentin (#5741; 1:1000), histone H3 (#4499; 1:2000), HA-tag (#3724S; 1:2000), -tubulin (#2128; 1:2000) (all from Cell Signaling Technology), E-cadherin (BD Biosciences, #610181; 1:5000), p21 (#ab7903; 1: 200), MDM2 (#ab16895; 1:500), phospho-Ser/Thr (#ab17464; 1:1000) (all from Abcam), FLAG (#F3165; 1:1000), importin (Thermo Fisher Scientific, #MA3-070), and -actin (#A5316; 1:10,000) (both from Sigma-Aldrich), followed by incubation with appropriate horseradish peroxidase (HRP)conjugated secondary antibodies. Blots were detected by enhanced chemiluminescence (Thermo Fisher Scientific, #32106). For IP assay, cells were lysed in IP lysis buffer [50 mM tris-HCl, 150 mM NaCl, 1 mM EDTA, and 1% NP-40 (pH 7.4)] containing protease inhibitor cocktail for 20 min on ice. The cell lysates were sonicated, clarified, and incubated with antibodies against control immunoglobulin G, FLAG (1:100), Snail (1:100), HDAC1 (1:100), or p53 (1:100), followed by incubation with precleared Protein A/G agarose beads (Santa Cruz Biotechnology, #sc-2003). The immunocomplexes were subjected to immunoblot analysis using antibodies against ubiquitin, HA, pan-AcK, phospho-Ser/Thr, CBP, p300, FLAG, or p53. For His pulldown assay, GST-CBP-HAT, His-Snail-WT, and His-Snail-R174A mutant recombinant proteins were expressed and purified from E. coli (BL21). The bead-bound His-tagged proteins were preincubated with various concentrations of CYD19 for 15 min at 4C on a rotator, and eluted GST-CBP-HAT protein was added to the reaction mixtures and incubated for another 2 hours. The beads were collected, extensively washed, eluted, electrophoresed, and subjected to Coomassie staining. In some experiments, His-Snail-WT and His-Snail-R174A mutant recombinant proteins were immobilized to Ni-NTA agarose and incubated with whole lysates of HEK293T cells for 3 hours (34). After extensive washes, the bound proteins were eluted with SDS sample buffer, resolved by SDSpolyacrylamide gel electrophoresis, and analyzed by immunoblotting.

Total RNAs were extracted and reversely transcribed using TRIzol reagent (Invitrogen, #15596018) and the PrimeScript RT reagent kit (Takara, #RR037A), respectively, according to the manufacturers instructions. Quantitative polymerase chain reaction (qPCR) was performed on an Applied Biosystems QuantStudio 3 qPCR (Thermo Fisher Scientific) using the SYBR Green PCR Master Mix (Takara, #RR820A), and relative mRNA expressions were normalized to glyceraldehyde-3-phosphate dehydrogenase (GAPDH). qPCR primers for amplifying the indicated genes are used as follows: GAPDH, 5-CACCGTCAAGGCTGAGAACGG-3/5-GACTCCACGACGTACTCAGCC-3; Gapdh, 5-CCCTGGCCAAGGTCATCCATG-3/5-TGATGTTCTGGGCAGCCCCAC-3; SNAI1, 5-TCGGAAGCCTAACTACAGCGA-3/5-AGATGAGCATTGGCAG CGAG-3; Snai1, 5-AAGATGCACATCCGAAGC-3/5-ATCTCTTCACATCCGAGTGG-3; TP53, 5-GTTCCGAGAGCTGAATGAGG-3/5-TCTGAGTCAGGCCCTTCTGT-3; Trp53, 5-AGCTCCCTCTGAGCCAGGAGA-3/5-TCCTCAACATCCTGGGGCAGC-3; CDKN1A, 5-TCTTGTACCCTTGTGCCTCG-3/5-GTTCCTGTGGGCGGATTAGG-3; Cdkn1a, 5-TGCCGTTGTCTCTTCGGTCCC-3/5-TAGACCTTGGGCAGCCCTAGG-3; MDM2, 5-GTGAATCTACAGGGACGCCATC-3/5-CTGATCCAACCAATCACCTGA A-3; Mdm2, 5-CGCTGAGTGAGAGCAGACGTC-3/5-GCTCCCCAGGTAGCTCATCTG-3; CDH1, 5-GTCAGTTCAGACTCCAGCCCG-3/5-CGTGTAGCTCTCGGCGTCAA-3; Cdh1, 5-GAAGTCCATGGGGCACCACCA-3/5-CTGAGACCTGGGTACACGCTG-3; CDH2, 5-CGACCCAAACAGCAACGACGC-3/5-CGGGTGCTGAATTCCCTTGGC-3; Cdh2, 5-TGTGCACGAAGGACAGCCCCT-3/5-CCTGCTCTGCAGTGAGAGGGA-3; VIM, 5-GCCCTAGACGAACTGGGTC-3/5-GGCTGCAACTGCCTAATGAG-3; Vim, 5-AGCGTGGCTGCCAAGAACCTC-3/5-GCAGGGCATCGTGTTCCGGT-3; FN1, 5-CATCCCTGACCTGCTTCCTGG-3/5-CTGTACCCTGTGATGGGAGCC-3; Fn1, 5-GGGTGACACTTATGAGCGCCC-3/5-GACTGACCCCCTTCATGGCAG-3; ERCC1, 5-GCATCATTGTGAGCCCTCGGC-3/5-GTGCAGGTTGTGGTAGCGGAG-3; Ercc1, 5-CCACAACCTCCATCCAGACTA-3/5-GCTTCTGCT CATACGCCTTGTA-3; CCL2, 5-AGTCTCTGCCGCCCTTCTGTG-3/5-CGCGAGCCTCTGCACTGAGAT-3; Ccl2, 5-CTGTCATGCTTCTGGGCCTGC-3/5-CAGC AGGTGAGTGGGGCGTTA-3; CCL5, 5-CAGCCCTCGCTGTCATCCTCA-3/5-GTGGGCGGGCAATGTAGGCAA-3; Ccl5, 5-AGCAATGACAGGGAAGCTATAC-3/5-AGGACTCTGAGACAGCACAT-3; TNFA, 5-GATTCTGAGCAAAATAGCCAGCA-3/5-GGCTTCCTTCTTGTTGTGTGT-3; Tnfa, 5-CCCTCACACTCAGATCATCTTCT-3/5-GCTACGACGACGTGGGCTACA-3; IL8, 5-ACTGAGAGTGATTGAGAGTGGAC-3/5-AACCCTCTGCACCCAGTTTTC-3; and Il8, 5-TGTGAGGCTGCAGTTCTGGCAAG-3/5-GGGTGGAAAGGTGTGGAATGCGT-3. The specificity of the PCR amplification was validated by the presence of a single peak in the melting curve analyses.

For histological assays, tumor and normal tissues were fixed in 4% PFA and embedded in paraffin. The embedded tissues were sectioned at 5 m, deparaffinized, and subjected to hematoxylin and eosin (H&E) staining according to the manufacturers instructions. For immunocytochemical analysis, cells were grown on chamber slides, fixed with 4% PFA, and incubated with primary antibodies against E-cadherin (1:1000), vimentin (1:200), Snail (1:200), or p53 (1:200), followed by incubation with goat anti-mouse and anti-rabbit Alexa secondary antibodies (all from Thermo Fisher Scientific, 1:300). Cells were then counter stained with 4it6-diamidino-2-phenylindole (DAPI), and images were acquired on a Zeiss LSM 800 microscope. For immunohistochemical analysis, deparaffinized sections were rehydrated and subjected to antigen heat retrieval with citric acidbased Antigen Unmasking Solution (pH 6.0; Vector Laboratories, #H-3300). The sections were incubated in 0.3% H2O2 (in PBS) and then in blocking buffer (5% goat serum in PBS). The sections were then incubated in blocking buffer containing primary antibodies against Ki67 (Abcam, #ab15580; 1:1000), cleaved caspase 3 (1:100), phosphohistone H3 (Cell Signaling Technology, #9849; 1:200), and Snail (1:100), followed by incubation with biotinylated goat anti-mouse (Vector Laboratories, #BA-9200; 1:200) and goat anti-rabbit (Vector Laboratories, #BA-1000; 1:200) secondary antibodies. Standard avidin-biotin complex (ABC) kit (Vector Laboratories, #PK-6101) and 3,3-diaminobenzidine (DAB) HRP Substrate Kit (Vector Laboratories, #SK-4105) were used for the detection of HRP activity. Slides were counterstained with hematoxylin, dehydrated, and mounted. For immunofluorescence analysis, rehydrated tissues were incubated in blocking buffer containing primary antibodies against E-cadherin (1:400), vimentin (1:200), F4/80 (Thermo Fisher Scientific, #14-4801-81; 1:100), CD31 (Dianova, #DIA310; 1:100), or p53 (1:800), followed by incubation with goat anti-mouse, anti-rabbit, and anti-rat Alexa Fluor secondary antibodies (all from Thermo Fisher Scientific; 1:300). The sections were then counter stained with DAPI, and images were acquired on a Zeiss LSM 800 microscope.

Data were presented as means SD. Statistical analysis was carried out as described in each corresponding figure legend, and sample size were shown in each figure legend.

Differences were evaluated by Mann-Whitney U test, unpaired two-sided Students t test, or one-way analysis of variance (ANOVA) with Tukeys post hoc test. P < 0.05 was considered statistically significant.

Acknowledgments: Funding: This research was supported by grants from the National Natural Science Foundation of China (81973363, 81973188, 81803033, 81572745, and 81603134), the Jiangsu Province Natural Science Funds for Distinguished Young Scholar (BK20170029), the Jiangsu Province Natural Science Funds for Young Scholar (BK20180573 and BK20160758), the Jiangsu Province Innovative Research Program, the State Key Laboratory of Natural Medicines of China Pharmaceutical University (SKLNMZZCX201808), and the Double First-Class University project (CPU2018GF02). Author contributions: Z.-Q.W. and T.L. conceived the project, designed experiments, interpreted data, and wrote the manuscript. H.-M.L., Y.-R.B., Y.L., and R.F. performed experiments and interpreted data with the help from W.-C.L., N.J., Y.X., and B.-X.R. Y.-D.C. designed and synthesized the compounds. S.W. and H.X. provided fresh human breast tumor samples. Competing interests: T.L., Y.-D.C., Z.-Q.W., and H.-M.L. are inventors on three pending patents (no. PCT/CN2019/102696, 27 August 2019; no. 201811623605.0, 28 December 2018; and no. 201811212157.5, 23 October 2018) related to this work. Z.-Q.W., T.L., Y.-D.C., R.F., H.-M.L., and Y.L. are inventors on a pending patent (no. 202010050205.6, 16 January 2020) related to this work. The authors declare that they have no other competing interests. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. Additional data related to this paper may be requested from the authors.

See the original post:
A potent CBP/p300-Snail interaction inhibitor suppresses tumor growth and metastasis in wild-type p53-expressing cancer - Science Advances

PHF20L1 as a H3K27me2 reader coordinates with transcriptional repressors to promote breast tumorigenesis – Science Advances

INTRODUCTION

A diverse array of posttranslational modifications that often occur on histone tails represents an essential means to regulate DNA-templated processes such as gene transcription (1). The methylation of histone lysine residue regulates multiple biological processes, including genome stability, gene expression, cell proliferation, and nuclear architecture (2). Histone methylation homeostasis is mediated by a series of methylase and demethylase complexes, and the recognition of methylated histones is accomplished by readers that usually contain plant homeodomain (PHD) finger domains, WD40 repeats, CW domains, PWWP domains, and the royal superfamily, including proteins with chromodomains, TUDOR domains, and malignant brain tumor (MBT) repeats (3). TUDOR domaincontaining proteins (TDRDs) have the potential to recognize histone methylation, and the abnormal overexpression of several TDRDs has been observed in breast cancer (4). PHD finger protein 20 (PHF20) and PHF20L1 share similar domains and are homolog TDRDs. PHF20 is a component of the MOF (male absent on the first)nonspecific lethal lysine acetyltransferase complex, which is involved in transcriptional activation (57). As a histone reader, PHF20 recognizes histone H3K4me2 via its PHD finger, and the H3K4me2-binding function of the PHD finger is essential for PHF20-dependent histone acetylation, target gene activation, and cancer cell growth (8). PHF20L1 was reported to recognize nonhistone methylation (9, 10). However, its roles in the recognition of histone modifications and in tumor progression remain largely unknown.

The polycomb repressive complex 2 (PRC2) is involved in repressing gene transcription through the methyltransferase activity of EZH2 for H3K27me2 and H3K27me3 writing, thus playing an important role in a number of biological processes, including embryonic development, cell fate decisions, and cancer progression (11). In mouse embryonic stem cells, H3K27me2 is the dominant modification form, reaching 70%, while H3K27me1 and H3K27me3 only occupy 7 and 4% of the total H3, respectively (12). H3K27me3 is mainly enriched within the promoters of silenced genes (13); conversely, H3K27me1 and H3K27ac accumulate on transcriptionally active genes (12, 14). Although H3K27me2 is distributed in large chromatin regions, its function remains enigmatic, and the readers that recognize H3K27 methylation modifications need to be further elucidated.

As one of the four major types of adenosine 5-triphosphate (ATP)dependent chromatin remodeling complexes, the nucleosome remodeling and deacetylase (NuRD) complex participates in a variety of biological processes, such as chromatin assembly, tumor progression, genomic stability, mitochondrial homeostasis, and pluripotency, through diverse assembly methods (15, 16). It has been reported that the NuRD complex promotes tumor progression via its deacetylation activity, which results in the silencing of various tumor suppressor genes (TSGs) (17). Metastasis associated 1 (MTA1) is a core factor of the NuRD complex, whose methylation is essential for the formation of the NuRD complex (18). Increasingly, key nuclear proteins such as lysine specific demethylase 1 (LSD1) have been reported to be incorporated into the NuRD complex superfamily, adding new features to this complex (19). It has been demonstrated that PRC2 and the NuRD complex can synergistically mediate H3K27 methylation and acetylation homeostasis to modulate the expression of transcriptionally poised genes in embryonic stem cells (20). However, the regulation of H3K27 modifications by PRC2 and the NuRD complex remains to be further explored in breast cancer.

The Warburg effect refers to cancer cells that exhibit aberrant metabolism characterized by high glycolysis even in the presence of abundant oxygen. This mechanism has now been widely accepted as a hallmark of cancer, which facilitates tumor growth with elevated glucose uptake and lactate production (21). Here, we report that PHF20L1 is a histone methylation reader protein, which recognizes H3K27me2 and collaborates with PRC2 and the NuRD complex in regulating H3K27 modifications to suppress a series of tumor suppressors, ultimately promoting the Warburg effect and breast tumorigenesis.

TDRDs are often dysregulated in breast cancer (The Cancer Genome Atlas and Molecular Taxonomy of Breast Cancer International Consortium datasets) (4), and the vast majority of TUDOR domainrecognizing ligands have been reported (fig. S1A). To explore the characteristics of these TDRDs that govern breast cancer proliferation, small interfering RNA (siRNAs) targeting indicated that TDRDs were transfected into human mammary carcinoma MDA-MB-231 or Hs 578T cells to assess the state of cell growth. In these experiments, at least two independent siRNA sequences were tested for each gene (fig. S1B) and then mixed for subsequent growth curve experiments and 5-ethynyl-2-deoxyuridine (EdU) assays. As reported (22), the knockdown (KD) of some TDRDs such as lysine demethylase 4A (KDM4A) substantially inhibited the growth of MDA-MB-231 cells. However, unexpectedly, our results showed that the depletion of PHF20L1 had a stronger inhibitory effect on the proliferation of MDA-MB-231 cells than the suppression of other TUDOR domain proteins (fig. S1C). To further consolidate our results, we transfected MDA-MB-231 and Hs 578T cells with siRNAs for 48 hours and then performed the EdU assays using a Click-iT EdU Alexa Fluor 488 imaging kit (Life Technologies). Immunofluorescence staining followed by microscopic analysis indicated that the deficiency of TDRDs, including PHF20L1, KDM4A, or ubiquitin like with PHD and ring finger domains 1 (UHRF1), could notably inhibit the proliferative activity of breast cancer cells (fig. S1, D to F). Together, these results suggest that PHF20L1 is necessary to maintain the proliferative state of breast cancer cells.

To determine how PHF20L1 regulates breast cancer cell growth, we performed RNA sequencing (RNA-seq) experiments in MDA-MB-231 cells using siRNA against PHF20L1 and control oligonucleotides. Compared to levels in the control, we identified a total of 1793 up-regulated genes and 1436 down-regulated genes (fold change, >1.5; P < 0.001) in PHF20L1-deficienct cells (Fig. 1A, left). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the differentially expressed genes revealed that the dysregulated genes were involved in vital biological processes. Further, down-regulated genes were enriched in pathways that regulate metabolic pathways, cell cycle, and glycolysis/gluconeogenesis, whereas up-regulated genes were enriched in pathways related to cell adhesion, insulin resistance, and lysosome (Fig. 1A, right). The epigenetic silencing of TSGs is one of the crucial reasons that promote tumorigenesis (23). Considering that PHF20L1 is essential for the proliferation of breast cancer cells, by analysis of the RNA-seq results, we found that the depletion of PHF20L1 could indeed up-regulate the expression of several well-known TSGs, including HIC1, KISS1, RASSF1, FBXW7, BRCA1, PTPRG, IGFBPL1, MTUS1, FHIT, CHFR, CASP7, FOXO3, and GLI3 (Fig. 1B, top). Meanwhile, the enrichment of differentially expressed genes in the metabolic pathways and glycolysis pathways indicated that PHF20L1 may play important roles in promoting the Warburg effect. In the RNA-seq data, we also found many glycolysis-related genes (GRGs) including SIRT1, GLUT1, HK2, GPI, ALDOA, GAPDH, PGK1, PGAM1, ENO1, ENO2, PKM, and LDHA were decreased in PHF20L1-depleted cells (Fig. 1B, bottom). Five representative differentially expressed genes of both up-regulated TSGs and down-regulated GRGs were further validated by quantitative reverse transcription polymerase chain reaction (qRT-PCR) analysis using PHF20L1 KD MDA-MB-231 cells (Fig. 1, C and D). Further, the reexpressing siRNA-resistant FLAG-PHF20L1 (WTres) was found to rescue the up-regulation of TSGs and the down-regulation of GRGs in PHF20L1-deficient cells (Fig. 1E).

(A) Heatmap representation of differentially expressed genes (fold change, >1.5; P < 0.001) in control (siControl) and PHF20L1 KD (siPHF20L1-1, siPHF20L1-2, and siPHF20L1-3) MDA-MB-231 cells. Red, up-regulated genes; blue, down-regulated genes. The right panel shows the results of the KEGG pathway analysis of differentially expressed genes. Data were analyzed using KOBAS 3.0 software (B) Heatmap of known TSGs and GRGs identified by RNA-seq. (C and D) qRT-PCR analysis of selected TSGs and GRGs in PHF20L1 KD (siPHF20L1) MDA-MB-231 cells. TUBB (-tublin) served as an irrelevant control gene. The mRNA levels were normalized to those of ATCB (-actin). (E) Western blotting analysis of selected TSGs and GRGs in control, PHF20L1 KD, and PHF20L1 KD MDA-MB-231 or Hs 578T cells stably expressing short hairpin RNA (shRNA)resistant PHF20L1 (WTres). -Actin served as loading control. (F) Gene set enrichment analysis (GSEA) plot of MYC signal pathway (left) and hypoxia signal pathway (right). FDR, false discovery rate; NES, normalized enrichment score. (G) MYC KD significantly down-regulates the expression of PHF20L1. The expression of MYC or PHF20L1 was measured by qRT-PCR and Western blotting in MDA-MB-231 cells transfected with siRNAs as indicated. (H) Western blotting analysis of the expression of PHF20L1 and hypoxia-inducible factor 1 (HIF1) in MDA-MB-231 cells treated with CoCl2. (I) Primer pairs including #1 to #6 were synthesized to cover the promoter region of PHF20L1 and quantitative chromatin immunoprecipitation (qChIP)based promoter walk was performed using normal or CoCl2-treated MDA-MB-231 cells. (J) Luciferase activity of PHF20L1 promoter reporters in human embryonic kidney (HEK) 293T cells transfected with vector, MYC, or HIF1. (K) MDA-MB-231 cells were transfected with indicated siRNAs or infected with lentiviruses as indicated. ECAR (extracellular acidification rate) was then determined separately. (L) A proposed model underlying the role of the MYC/HIF1a-PHF20L1 axis in regulating the expression of TSGs and GRGs. All error bars represent means SD. Two-tailed unpaired t test, *P < 0.05 and **P < 0.01 (C, D, G, I, J, and K).

To further investigate the biological significance of PHF20L1, we performed gene set enrichment analysis (GSEA) using GSEA v2.2.2 software on differentially expressed PHF20L1 target genes and found strong enrichment on the targets of MYC and hypoxia signature genes (Fig. 1F). It has been reported that MYC and hypoxia-inducible factor 1 (HIF1) are key factors in the regulation of glycolysis in cancer cells and that their abnormal expression could promote the glycolysis process (24, 25). GSEA results suggested that PHF20L1 might participate in the MYC and hypoxia signaling pathways. To explore the crucial role of PHF20L1 in the MYC signaling pathway, we transfected PHF20L1 siRNAs into MDA-MB-231 cells and found that the KD of PHF20L1 did not influence mRNA and protein levels of MYC (Fig. 1G, top) but that mRNA and protein levels of PHF20L1 were notably decreased in MYC KD MDA-MB-231 cells (Fig. 1G, bottom), which indicated that PHF20L1 is downstream of the MYC signaling pathway. It has been reported that HIF1 expression in mammalian cells can be induced in response to hypoxic conditions (1% O2) or hypoxia activators, such as deferoxamine and cobalt chloride (CoCl2) (26). To further determine whether hypoxic conditions induce PHF20L1 expression, we examined protein levels of PHF20L1 in MDA-MB-231 cells exposed to CoCl2 treatment. We found that PHF20L1 was indeed induced by hypoxic conditions (Fig. 1H). Moreover, further quantitative chromatin immunoprecipitation (qChIP) assays using specific antibodies against MYC and HIF1 showed strong binding to PHF20L1 #5 and #6 promoter regions of MYC and HIF1, respectively (Fig. 1I). To further test whether MYC and HIF1 could directly regulate PHF20L1 transcription, we searched up to ~2 kb of the PHF20L1 promoter regions for possible MYC- and HIF1-binding sites. The luciferase reporter assays were performed using constructs containing the deletion mutants of each putative binding region. The results showed that overexpression of MYC and HIF1 significantly increased the reporter activity of the PHF20L1 promoter. Moreover, deletion of the 650 to 308 fragment abrogated the MYC-mediated promoter reporter activity, whereas deletion of the 308 to 0 fragment eliminated HIF1-mediated promoter reporter activity. Meanwhile, deletion of the 650 to 0 promoter fragment almost completely abolished reporter activity (Fig. 1J). Together, these data indicate that PHF20L1 is a direct target gene of MYC/ HIF1. To further explore the key role of PHF20L1 in altering glycolysis levels in breast cancer cells, MDA-MB-231 cells were transfected with siRNAs or infected with lentiviruses as indicated, and glycolysis levels were measured using a Seahorse XFe24 system (Seahorse Bioscience). Our experiments revealed that PHF20L1 loss of function could significantly reduce the extracellular acidification rate (ECAR), which reflects overall glycolysis levels. Meanwhile, these effects could be reversed by the reexpression of siRNA-resistant PHF20L1 (Fig. 1K, left). In addition, the reduction in glycolysis flux due to MYC depletion was also partially reversed by the reexpression of PHF20L1 (Fig. 1K, right). Together, these experiments revealed that PHF20L1, as a MYC- and HIF1-driven gene, could repress the expression of several tumor suppressors such as HIC1, KISS1, and BRCA1 and then promotes the expression of GRGs. (Fig. 1L).

PHF20L1 has MBT, TUDOR, and PHD domains; to further explore the molecular mechanisms through which PHF20L1 exerts its biological functions, we first used a modified histone peptide array containing peptide-cellulose conjugates spotted onto the planar surface of a standard microscope slide in a three-dimensional layer, carrying various histone modifications in duplicate (available on the Active Motif official website), to screen potential histone-binding sites. We found that the glutathione S-transferase (GST)fused TUDOR domain of PHF20L1 binds strongly to the H3K27me2 peptide, whereas the MBT and PHD domains had no specific binding sites (Fig. 2, A and B). The TUDOR domain of PHF20L1 could only recognize the peptide with H3K27me2 but not the peptide with H3K27me2S28p, H3R26me2sK27me2S28p, or H3R26me2aK27me2S28p. The finding that the GST-TUDOR could not bind the peptides that contain H3S28p in addition to H3K27me2 suggested that the binding is inhibited by S28p. Biotinylated histone peptide pull-down assays with GST- or FLAG-fused PHF20L1 full-length or truncated mutants, as indicated, further confirmed the screening results of peptide array (Fig. 2C). A schematic illustration of the four different domains of PHF20L1 and GST-fused domains purified from BL21 Escherichia coli are shown in Fig. 2 (D and E). To further explore binding between the TUDOR domain and H3K27me2, we performed quantitative isothermal titration calorimetry (ITC) assays, and the results revealed an affinity dissociation constant (KD) of 73.6 M for the PHF20L1 TUDOR domain to the H3K27me2 peptide, which was much lower than that with other modifications (Fig. 2F). Meanwhile, the results from surface plasmon resonance (SPR) assays further confirmed the specific binding between the PHF20L1 TUDOR domain and the H3K27me2 peptide (Fig. 2G). Previous studies have shown that the TUDOR domain of PHF1 recognizes the H3K36me3 peptide (27), and the results of ITC and SPR assays further revealed that the PHF20L1 TUDOR domain did not bind H3K36me3, which also indicated the specificity of PHF20L1 for H3K27me2 recognition. Moreover, we found that the PHF20L1 TUDOR domain is highly conserved among different species (Fig. 2H). To further explore the key amino acids of PHF20L1 that play important roles in recognizing H3K27me2, peptide pull-down experiments with GST-fused several TUDOR mutants were performed. The results showed that except for mutations in the glutamate-92 and threonine-98, other mutations could not abolish the interaction between H3K27me2 and the PHF20L1 TUDOR domain (Fig. 2I). Similar results were observed in peptide pull-down assays using FLAG-fusion PHF20L1 WT (wild type) and mutants (Fig. 2J). These results revealed the importance of the E92 and T98 residues of PHF20L1 TUDOR in H3K27me2 binding, probably because E92 and T98 residues are essential for the formation of hydrogen bonds between TUDOR and H3K27me2 or they are crucial for the maintenance of the structure of the TUDOR protein. Together, these experiments identified PHF20L1 as an important histone reader exhibiting high affinity and selectivity for H3K27me2 based on the TUDOR domain, which might be involved in transcriptional regulation.

(A) Anti-GST immunoblot of the GST, GST-fused MBT, TUDOR, and PHD domains were measured on a histone peptide array. Peptides were spotted in duplicate as shown in two boxes on the same array. The positions of H3K27me1-, H3K27me2-, and H3K27me3-containing peptides are highlighted with yellow, blue, and red circles. (B) Graphical analysis of the highest binding events detected showing the binding specificity of the GST-TUDOR domain measured on a histone peptide array. (C) Western blotting analysis of histone peptide pull-down assays with GST- or FLAG-fused proteins as indicated. (D and E) Schematic illustrating the four different domains of PHF20L1 and the GST-fused domains purified from BL21 E. coli. (F) Experimental ITC titration curves of the PHF20L1 TUDOR domain to the indicated peptides. (G) SPR analysis of the interaction of PHF20L1 TUDOR with peptides as indicated. (H) Conservation of the PHF20L1 TUDOR domain among 10 species and the designated mutation amino acid sites were shown. (I and J) Western blot analysis of the peptide pull-down analysis using the GST- or FLAG-fused point mutants as indicated.

H3S28p was reported to lead to gene promoter remodeling and transcriptional activation (28). Since the interaction between H3K27me2 and PHF20L1 was repelled by H3S28p, we next investigated whether PHF20L1 is involved in transcriptional repression. First, to identify PHF20L1 interacting proteins, cellular extracts from human embryonic kidney (HEK) 293T and MDA-MB-231 cells stably expressing FLAG-PHF20L1 were subjected to affinity purification using anti-FLAG beads, and the eluates were resolved using an SDSpolyacrylamide gel electrophoresis (SDS-PAGE) gel followed by silver staining to identify interacting proteins. Mass spectrometry analysis showed that PHF20L1 was indeed copurified with subunits of transcription repressionrelated complexes such as PRC2 and the NuRD complex, including EZH2, SUZ12, EED, Mi-2/, histone deacetylase 1/2 (HDAC1/2), MTA1/2, and MBD3 in both cell lines with a high abundance (Fig. 3A). The mass spectrometry details are shown in tables S1 and S2. The presence of PRC2 and NuRD subunits in the PHF20L1 interactome was confirmed by Western blotting with antibodies against the indicated components in the corresponding two cell lines (fig. S2A). Since PHF20 and PHF20L1 are homolog TDRDs with similar domains, we further performed coimmunoprecipitation (Co-IP) experiments using the FLAG antibody in MDA-MB-231 cells that stably expressed FLAG-PHF20L1 or PHF20. The results showed obvious interactions between PHF20L1 and the PRC2/NuRD complex, as well as interaction between PHF20 and MOF (Fig. 3B), as previously reported (5, 6). Unexpectedly, we also found that the PHF20 and PRC2 had some interactions. To further confirm whether their interaction was caused by the DNA fragments that might link some epigenetic regulators together, the Co-IP experiments stated before were performed in the presence or absence of deoxyribonuclease (DNase). The results showed that the interaction between PHF20 and PRC2 disappeared in the presence of DNase, indicating that this binding was indirect (Fig. 3B). Collectively, these results support the notion that PHF20L1 selectively interacts with the PRC2/NuRD complex, whereas PHF20 specifically interacts with MOF. To further confirm the interaction between PHF20L1 and the two transcriptional repressor complexes, we performed Co-IP experiments with HEK293T, MDA-MB-231, and Hs 578T cells. The results showed robust interactions between PHF20L1 and PRC2 or the NuRD complex in vivo (Fig. 3C). We next performed protein fractionation experiments with nuclear proteins by fast protein liquid chromatography (FPLC) with Superose 6 gel filtration chromatography. Western blotting analysis showed that the elution pattern of PHF20L1 largely overlapped with that of PRC2 components, including EZH2 and SUZ12, and NuRD complex proteins, including Mi-2, MTA1/2, HDAC1/2, RbAp46/48, and MBD3 (fig. S2B). These results also indicated a major peak at approximately 667 to 2000 kDa for PHF20L1, PRC2, and NuRD subunits. Furthermore, analysis of the FLAG-PHF20L1 affinity eluate by FPLC with Superose 6 gel filtration chromatography showed that FLAG-PHF20L1 exists in a multiprotein complex, containing PRC2 and NuRD subunits (fig. S2C). To define the key domains of PHF20L1 responsible for directly interacting with PRC2 and the NuRD complex in vivo, a series of PHF20L1 FLAG-tagged domain or deletion mutants were expressed in HEK293T cells. Co-IP with an anti-FLAG antibody followed by Western blotting with indicated antibodies showed that the middle part of PHF20L1, termed the PRC2-NuRDinteracting domain (PNID), was responsible for interactions with PRC2 and the NuRD complex (fig. S2D).

(A) Immunopurification and mass spectrometry analysis of PHF20L1-associated proteins in HEK293T and MDA-MB-231 cells. The eluates were resolved by SDS-PAGE and silver-stained, and the bands were retrieved and analyzed by mass spectrometry. (B) Cellular lysates from MDA-MB-231 cells were immunoprecipitated with antibodies against FLAG in the presence or absence of DNase. (C) Association of PHF20L1 with PRC2 and NuRD in HEK293T, MDA-MB-231, and Hs 578T cells. Whole-cell lysates were prepared, and Co-IP was performed. (D) Molecular interaction between PHF20L1 and PRC2 or NuRD subunits. GST/His pull-down assays using bacterially expressed GST/His-fused proteins and in vitro transcribed/translated proteins are shown as indicated. (E and F) GST pull-down assays with GST-fused truncated EZH2 or MTA proteins and in vitrotranscribed/translated PHF20L1. (G) Mapping the interface in PHF20L1 for the interaction between PHF20L1 and PRC2 or NuRD by GST pull-down assays with GST-fused PHF20L1 domain constructs and in vitrotranscribed/translated PRC2 and NuRD subunits. (H) Mapping the interface in PNID for the interaction between PHF20L1 and PRC2 or NuRD by GST pull-down assays with GST-fused PNID domain constructs and in vitrotranscribed/translated EZH2 and MTA1/2. (I) PHF20L1 has intrinsic transcription repressive activity. HEK293T cells were transfected with the indicated plasmids, and Gal4 luciferase reporter activity was measured. (J) Identification of the essential domains required for the transcriptional repressive activity of PHF20L1. The PHF20L1 deletions fused to the C terminus of Gal4 DNA binding domain were transfected into HEK293T cells, and Gal4 luciferase reporter activity was measured. (K) Effect of depletion of EZH2 or MTA1 on PHF20L1 repressive activity. HEK293T cells were transfected as indicated constructs along with siRNAs against EZH2 or MTA1 for 48 hours, and Gal4 luciferase reporter activity was measured. All error bars represent means SD of triplicate measurements that have been repeated three times with similar results. Two-tailed unpaired t test, *P < 0.05 (I to K).

To further address the role of PHF20L1 in the context of a multiprotein complex, we then performed pull-down experiments by incubating of His-fused PHF20L1 with in vitrotranscribed/translated individual components of PRC2 and the NuRD complex as indicated. These experiments indicate that PHF20L1 interacts with EZH2, MTA1, MTA2, and potentially HDAC1, but not MTA3 (Fig. 3D, left). Similarly, GST pull-down experiments with GST-fused components of PRC2/NuRD complex and in vitrotranscribed/translated PHF20L1 obtained similar results (Fig. 3D, right). Meanwhile, GST pull-down assays with GST-fused D1, D2, CXC, or the SET domain of EZH2 and in vitrotranscribed/translated PHF20L1 suggested that the D1 domain of EZH2 is responsible for the interaction between EZH2 and PHF20L1 (Fig. 3E). Similar experiments also showed that the Swi3-Ada2-N-CoR-TFIIIB (SANT) domains of MTA1/2 are responsible for the interaction between MTA1/2 and PHF20L1 (Fig. 3F). Moreover, GST pull-down assays showed that the GST-fused PHF20L1 PNID domain directly interacts with EZH2 and MTA1/2 in vitro (Fig. 3G), which is consistent with the aforementioned in vivo results. The PNID domain is a large domain with 500 amino acids. To elucidate the PRC2 and NuRD interacting region more precisely, we subdivided the PNID domain into five parts (named P1 to P5 for short). GST pull-down assays were performed with GST-fused segments, and in vitrotranscribed/translated EZH2, MTA1, and MTA2 showed that P2 and P5 are responsible for the interactions between PHF20L1 and MTA1/2 or EZH2, respectively (Fig. 3H). Therefore, P2 and P5 were named the NuRD-interacting domain (NID) and PRC2-interacting domain (PID). The results of Co-IP assays further substantiated that the NID and PID was corresponded for NuRD and PRC2 binding, respectively (fig. S2E). Collectively, these results indicate that PHF20L1 interacts with PRC2 and the NuRD complex through the PID and NID regions. The GST/His-fused proteins purified from BL21 E. coli are shown in fig. S2 (F to K).

The physical association between PHF20L1 and the PRC2-NuRD complex led us to hypothesize that PHF20L1 might be functionally involved in transcriptional repression. To verify our hypothesis, full-length PHF20L1 was fused to the C terminus of the Gal4 DNA binding domain (Gal4-PHF20L1), and the fused construct was expressed in HEK293T cells. A Gal4-driven luciferase reporter system containing five copies of the Gal4-binding sequence was used to test the transcriptional activity. The results revealed that the expression of Gal4-PHF20L1, but not FLAG-PHF20L1, leads to a significant reduction in expression of the reporter gene, in a dose-dependent manner (Fig. 3I), indicating that PHF20L1 exerts robust repressive activity. Since the PID and NID domain of PHF20L1 is responsible for interacting with PRC2 and the NuRD complex, we further investigated whether the PID or NID domain is essential for the transcriptional repression activity of PHF20L1. For this, we investigated the contribution of each PHF20L1 domain to its repressive transcriptional function. A series of Gal4 DNA-binding domain (Gal4-DBD) fused deletion constructs were generated, and the repressive activities of those constructs were monitored using Gal4 upstream activating sequence (UAS) luciferase reporter assays. Notably, deletion of the MBT, TUDOR, C-terminal, or PHD domain did not affect the repressive activity of PHF20L1, whereas the deletion of PNID resulted in a substantial reduction in the repressive transcriptional activity of PHF20L1 (fig. S2L). The results also showed that deletion of the P1, P3, or P4 region did not affect the transcriptional repressor activity of PHF20L1, whereas deletion of PID or NID resulted in a significant reduction in PHF20L1 transcriptional repressor activity (Fig. 3J). To determine whether PRC2 and NuRD activity are required for PHF20L1-mediated repression, we performed loss-of-function experiments with the Gal4 UAS luciferase reporter system. As shown, the KD of EZH2 and MTA1 led to a substantial reduction in the repressive transcriptional activity of PHF20L1 (Fig. 3K). Meanwhile, we measured reporter activity in HEK293T cells upon treatment with GSK126, a specific EZH2 inhibitor (29), and trichostatin A (TSA), a specific HDAC inhibitor (30). The results indicated that GSK126 or TSA treatment could almost completely alleviate the PHF20L1-mediated repression of reporter activity (fig. S2M), suggesting that PHF20L1-mediated repression requires the assistance of PRC2 and the NuRD complex. Together, these results suggest that PHF20L1 has intrinsic transcriptional repressor activity through coordinating with PRC2 and the NuRD complex.

The NuRD complex removes H3K27ac from certain target gene regions, facilitating PRC2 binding, and, subsequently, the catalysis of histone methylation on H3K27 (31). The findings that PHF20L1 is an H3K27me2 reader that interacts with PRC2 and the NuRD complex, prompted us to explore its function in chromosomal events and the underlying mechanism of transcriptional repression. First, we performed a series of ChIP sequencing (ChIP-seq) experiments, with specific antibodies against PHF20L1, EZH2, MTA1, H3K27me2, H3K27me3, and H3K27ac in normal or PHF20L1 KD MDA-MB-231 cells. We found that the enrichment of PHF20L1, EZH2, MTA1, H3K27me2, and H3K27me3 at the promoter region was substantially less than that of H3K27ac (Fig. 4A), suggesting that PHF20L1 might not share a large-scale chromatin region with H3K27ac. To further explore the relationship between PHF20L1 and two transcriptional repressor complexes in chromatin, we further analyzed ChIP-seq data. The characteristic genomic landscapes of EZH2, MTA1, H3K27me2, H3K27me3, and H3K27ac at PHF20L1-binding sites showed that these proteins were notably enriched in regions surrounding the PHF20L1 binding peaks except H3K27ac (Fig. 4, B and C), which was reported to be associated with enhanced activation of transcription (32).

(A) Genomic distribution of PHF20L1, EZH2, MTA1, H3K27me2, H3K27me3, and H3K27ac ChIP-seq peaks. (B and C) ChIP-seq density heatmaps and profiles of EZH2, MTA1, H3K27me2, H3K27me3, and H3K27ac on PHF20L1 binding regions. TSS, transcription start site. (D) The average occupancy of EZH2, MTA1, H3K27me2, H3K27me3, and H3K27ac along the transcription unit in normal and PHF20L1 KD MDA-MB-231 cells. TTS, transcription termination site. (E) Visualized peaks at representative loci using an integrative genomics viewer. (F and G) qChIP analysis using specific antibodies against PHF20L1, EZH2, MTA1, H3K27me2, H3K27me3, H3K27ac, and H3 were performed in control, PHF20L1 KD, and PHF20L1 KD MDA-MB-231 cells stably expressing shRNA-resistant PHF20L1 (represented as WTres), PHF20L1E98K, PHF20L1NID, or PHF20L1PID. ACTB served as control. (H) Western blotting analysis of EZH2 and MTA1 in cells as in (F and G). Data shown are means SD of triplicate measurements that have been repeated three times with similar results. Two-tailed unpaired t test, *P < 0.05 and **P < 0.01 (F and G).

We next sought to confirm that PHF20L1 is required for the chromatin recruitment of PRC2 and the NuRD complex. Consistent with our expectations, the analysis of ChIP-seq data showed that PHF20L1 loss of function led to a moderate reduction in EZH2, MTA1, H3K27me2, and H3K27me3 on chromatin, whereas the average genome-wide occupancy of H3K27ac was slightly increased (Fig. 4D). Genomic distributions and peak locations in PHF20L1 KD MDA-MB-231 cells also demonstrated that decreases in H3K27me2 and H3K27me3 levels were linked to increased H3K27ac levels in PHF20L1-occupied genes (Fig. 4E).

qChIP analyses were also performed using specific antibodies against PHF20L1, EZH2, MTA1, H3K27me2, H3K27me3, and H3K27ac at selected gene regions, including BRCA1, GATA binding protein 2 (GATA2), glutathione S-transferase mu 2 (GSTM2), hypermethylated in cancer 1 (HIC1), KiSS-1 metastasis suppressor (KiSS1), stathmin 3 (STMN3), villin like (VILL), and zinc finger protein 512B (ZNF512B). Consistent with ChIP-seq results, PHF20L1 KD significantly reduced the enrichment of PHF20L1, EZH2, MTA1, H3K27me2, and H3K27me3 on PHF20L1 target genes, whereas the enrichment of H3K27ac resulted in a noteworthy increase. Moreover, the KD of EZH2 or MTA1 also resulted in a similar trend (fig. S3, A and B). qRT-PCR and Western blotting analysis confirmed that KD of PHF20L1 does not result in the down-regulation of EZH2 or MTA1 expression (fig. S3C), suggesting that the decreased recruitment was not caused by changes in overall expression levels. To further explore whether TUDOR, NID, and PID domains are essential for the recruitment of PRC2 and NuRD to the targets promoters, rescue experiments were performed by ectopically expressing short hairpin RNA (shRNA)resistant WT PHF20L1 (WTres) or other mutants including E92K, PHF20L1 lacking the NID domain (NID), and PHF20L1 lacking PID domain (PID) in PHF20L1-depleted MDA-MB-231 cells. Then, qChIP assays were used to assess the occupancy of PHF20L1, EZH2 (representing PRC2), and MTA1 (representing the NuRD complex) at the indicated TSGs in Fig. 4F. Because of the loss of antibody recognition epitope, we could not conduct qChIP experiment stated above in MDA-MB-231 cells stably expressing shRNA-resistant PHF20L1NID. The results showed that the wild-type PHF20L1 could bind stably with the target promoters, and only the wild-type PHF20L1, but not the E92K, PHF20L1NID, or PHF20L1PID mutant, restored the recruitments of PRC2 and the NuRD complex caused by the depletion of PHF20L1 (Fig. 4F). At the same time, the related histone modifications H3K27me2, H3K27me3, and H3K27ac are also tested with the rescue experiments with the same design using qChIP assays. The results revealed that wild-type PHF20L1, but not the E92K, PHF20L1NID, or PHF20L1PID mutant, could reinstate the epigenetic changes caused by the depletion of PHF20L1 (Fig. 4G). These results showed that none of the mutants fully rescues PRC2 or NuRD binding and the modification status of the genes, indicating that the whole complex could only function if all parts are present. The Western blotting assays confirmed the KD or overexpression efficiency of PHF20L1 along with the mutations or deletions; moreover, the results also demonstrated that those experimental designs did not result in the change of EZH2 or MTA1s expression level (Fig. 4H). Together, these results suggest that the TUDOR domain, PID, and NID are critical for the transcriptional repressor activity of PHF20L1 through recognition of H3K27me2 to coordinate with PRC2 and the NuRD complex.

On the basis of the transcriptome sequencing analysis results and the role of PHF20L1 in tumor glycolytic processes, it was reasonable to postulate that PHF20L1 in association with PRC2 and NuRD plays a role in breast tumorigenesis. To this end, we first detected the protein expression profiles at different cell cycle stages synchronized using thymidine and found that PHF20L1, EZH2, and MTA1 were coexpressed in a cell cycledependent manner and are relatively abundant during the stages of DNA synthesis (fig. S4A, left). We further found that, compared with that in the control, the KD of PHF20L1 could notably block the cell cycle at the G1-S checkpoint (fig. S4A, right). To further explore the functional significance of PHF20L1 in breast cancer progression and metastasis, colony formation and transwell invasion assays were performed in PHF20L1-depleted MDA-MB-231 and Hs 578T cells, which were stably expressed shRNA-resistant PHF20L1 (WTres). We found that the KD of PHF20L1 notably decreased the colony number and invasive potential of MDA-MB-231 and Hs 578T cells but that the reexpression of shRNA-resistant PHF20L1 could reverse these effects (fig. S4, B to D). Together, these results indicate that PHF20L1 plays an important role in the development of breast cancer.

We demonstrated that the TUDOR, PID, and NID domains are critical for PHF20L1 to recognize H3K27me2 and recruit transcriptional repressor complexes. To explore the intrinsic function of each PHF20L1 domain, full-length PHF20L1 or MBT, TUDOR, PNID, PHD, and C-terminal deletion mutations were stably expressed in MDA-MB-231 cells, and growth curve experiments and transwell assays were performed. The results showed that deletion of the PNID or TUDOR domain could significantly reduce the ability of PHF20L1 to promote cell proliferation and invasion but that the PHD domain and C terminus of PHF20L1 were not required (fig. S4, E and F). Moreover, the rescue experiments were conducted as stated previously in Fig. 3 (F to H) for cell proliferation assays and transwell assays to further determine whether the H3K27me2 recognition function and the recruitment of PRC2 and the NuRD complex by PHF20L1 are essential for its carcinogenetic and metastatic promoting effects. We found that the expression of PHF20L1 WTres but not E92K, PHF20L1NID, or PHF20L1PID fully rescued the colony formation ability and invasive potential of PHF20L1 KD MDA-MB-231 and Hs 578T cells (Fig. 5, A to D), suggesting that both the recognition of H3K27me2 by the TUDOR domain and the recruitment of PRC2 and the NuRD complex by the PID and NID are important for the function of PHF20L1 in breast cancer cells. To further explore whether TUDOR, NID, and PID domains are necessary for transcriptional inhibitory activity of PHF20L1, rescue experiments were performed and confirmed that the up-regulation of TSGs and the down-regulation of GRGs caused by the depletion of PHF20L1 could be completely rescued by the ectopic expression of PHF20L1 WTres but not the E92K, PHF20L1NID, or PHF20L1PID mutants (Fig. 5E). These results suggested that the TUDOR, NID, and PID domains are required for PHF20L1 to function as a transcriptional repressor in breast cancer cells. To investigate the functional synergy between PRC2, NuRD, and PHF20L1, the KD of PHF20L1, together with EZH2 or MTA1 gain-of-function experiments, was performed in MDA-MB-231 cells. Colony formation assays and transwell assays results revealed that the KD of PHF20L1 notably decreased the proliferation and invasion of MDA-MB-231 cells, and this effect could hardly be rescued by the reexpression of EZH2 or MTA1 (fig. S4, G to I). These results indicate that the functions of EZH2 and MTA1 are dependent on the existence of PHF20L1. Since PHF20L1, PRC2, and the NuRD complex could act as a whole complex to exert transcriptional repression activity, we thus further investigated whether PRC2 and the NuRD complex also regulate the expression of PHF20L1 target genes. qRT-PCR and Western blotting analysis demonstrated that the KD of EZH2 or MTA1, respectively, in MDA-MB-231 cells could lead to increased expression of PHF20L1 target TSGs and the decreased expression of PHF20L1 target GRGs at the mRNA and protein level (fig. S4, J and K). These results support our arguments that PHF20L1 may play important roles in breast cancer by recruiting PRC2 and the NuRD complex to transcriptionally repress a range of TSGs including HIC1, KISS1, and BRCA1, thus synergizing the functions of PRC2 and NuRD.

(A) Colony formation assays were performed in control, PHF20L1 KD, and PHF20L1 KD MDA-MB-231 cells stably expressing shRNA-resistant PHF20L1 (represented as WTres), PHF20L1E98K, PHF20L1NID, or PHF20L1PID. (B) Colony formation assays were performed in control, PHF20L1 KD, and PHF20L1 KD Hs 578T cells stably expressing shRNA-resistant PHF20L1, PHF20L1E98K, PHF20L1NID, or PHF20L1PID. (C) Transwell invasion assays were performed in cells as in (A). IgG, immunoglobulin G. (D) Transwell invasion assays were performed in cells as in (B). Data shown are means SD. Two-tailed unpaired t test, *P < 0.05 and **P < 0.01 (A to D). (E) Western blotting analysis of the TSGs and GRGs in MDA-MB-231 cells as in (A). (F) MDA-MB-231 cells infected with lentiviruses carrying shControl, shPHF20L1, or stably expressing vector PHF20L1 were inoculated orthotopically into the abdominal mammary fat pads of 6-week-old female BALB/c nude mice (n = 5), and tumor volumes were measured weekly. Data shown are means SD. **P < 0.01 at the final day. (G) MDA-MB-231 cells stably expressing firefly luciferase were infected as in (F) then injected intravenously through the tail veins of 6-week-old female severe combined immunodeficient (SCID) mice (n = 6). Lung metastasis was monitored using bioluminescent imaging up to 7 weeks after injection. Representative in vivo bioluminescent images are shown. Data shown are means SD. Two-tailed unpaired t test, *P < 0.05. (H) Immunohistochemical (IHC) staining of PHF20L1, EZH2, MTA1, and HIC1 in breast carcinoma samples (histological grades I, II, and III) paired with adjacent normal mammary tissues. Representative images (original magnification, 200) are shown. (I) Scores of the stained sections from (H) were determined by Image-Pro Plus software and are presented with box plots. Boxes represent the 25th and 75th percentiles; lines represent the median, and whiskers show the minimum and maximum points. *P < 0.05, **P < 0.01, and ***P < 0.001 by one-way analysis of variance (ANOVA). (J) Immunohistochemistry results from (H) were used to analyze the correlation coefficient and P values as indicated. (K) Analysis of public datasets (GSE21653 and GSE27562) from breast cancer for the correlation of MYC, HIF1A, HIC1, KISS1, and PHF20L1. (L) The proposed model for the MYC/HIF1-(PHF20L1-PRC2-NuRD)-HIC1/KISS1 axis in breast carcinogenesis. Photo credit: Yongqiang Hou, Tianjin Medical University.

To further establish the role of PHF20L1 in breast carcinogenesis in vivo, we first examined how PHF20L1 loss of function affects the growth of tumors developed from MDA-MB-231 cells in a mouse model. MDA-MB-231 cells infected with lentiviruses carrying shPHF20L1 or corresponding shControl were transplanted into the abdominal mammary fat pad of athymic BALB/c female mice (n = 5). The tumors were measured weekly to assess proliferation. As shown, PHF20L1 KD was associated with a notable decrease in the growth of primary MDA-MB-231 tumors (Fig. 5F, top). Furthermore, MDA-MB-231 cells stably expressing PHF20L1 were transplanted into the abdominal mammary fat pad of athymic BALB/c female mice (n = 5). Results showed that PHF20L1 overexpression could substantially promote breast cancer tumor growth (Fig. 5F, bottom). To assess the function of PHF20L1 in tumor metastasis, MDA-MB-231 cells stably expressing firefly luciferase were infected with lentiviruses carrying shPHF20L1, FLAG-PHF20L1, and the corresponding control; then, the cells were intravenously injected into immunocompromised severe combined immunodeficient (SCID) female mice (n = 6). Metastatic tumors were measured by quantitative bioluminescence imaging after 7 weeks using an IVIS imaging system (Xenogen). We found that PHF20L1 deficiency significantly reduced breast cancer cells lung metastasis in vivo, whereas the overexpression of PHF20L1 could promote lung metastasis (Fig. 5G). Together, these results support the notion that PHF20L1 cooperates with PRC2 and the NuRD complex to promote breast carcinogenesis.

To confirm the clinicopathological relevance of the MYC/HIF1(PHF20L1-EZH2-MTA1)HIC1/KISS1 axis in breast cancer, we collected 176 breast carcinoma samples and analyzed the expression profiles of PHF20L1, EZH2, MTA1, and HIC1 by immunohistochemical (IHC) staining. Notably, IHC analysis using Image-Pro Plus software showed that the expression of PHF20L1, EZH2, and MTA1 was concurrently up-regulated and appeared to be positively correlated with histological grades, whereas the expression of HIC1 was down-regulated and negatively correlated with histological grades or the expression of PHF20L1, EZH2, and MTA1 (Fig. 5, H to J). In addition, to gain a deeper understanding of the role of PHF20L1 in breast cancer progression, analysis of two published clinical datasets (GSE21653 and GSE27562) showed that the expression level of PHF20L1 is positively correlated with the expression of MYC, HIF1A, EZH2, MTA1, SIRT1, and LDHA while negatively correlated with the expression of HIC1 and KISS1 (Fig. 5K and fig. S5A). To further extend our observations on clinical relevance, we analyzed Kaplan-Meier plots based on PHF20L1, EZH2, MTA1, and HIC1 in breast cancer. As shown in fig. S5B, higher PHF20L1 expression is associated with worse overall survival for patients with breast cancer. Consistently, high expression levels of EZH2 and MTA1 were also associated with poor prognosis, whereas patients with high HIC1 expression had longer survival times. To explore whether the oncogenic effect of PHF20L1 also exists in other kind of cancers, we collected several carcinoma samples and performed tissue microarrays, followed by IHC staining to examine the expression of PHF20L1. At least six samples paired with adjacent normal tissues were used. The results showed that in addition to that in breast cancer, PHF20L1 is also progressively increased in lymphoma, cerebral cancer, esophageal cancer, prostate cancer, and pancreatic cancer (fig. S5C). In addition, the analysis of published lymphoma clinical datasets (GSE132929) and glioma datasets (GSE51062) also showed that the expression level of PHF20L1 is positively correlated with the expression of MYC, HIF1A, EZH2, MTA1, SIRT1, and LDHA while negatively correlated with the expression of HIC1 or KISS1 (fig. S5D). Together, these data support our overall hypothesis that PHF20L1 as an H3K27me2 reader could cooperate with the PRC2/NuRD complex to inhibit the expression of TSGs such as HIC1 and KISS1, participating in MYC and hypoxia signaling and leading to tumor progression (Fig. 5L).

Although our previous work herein confirmed the important role of PHF20L1 in breast cancer cells, its intrinsic role in vivo remained unknown. To further investigate the core function of PHF20L1 in vivo, we first established Phf20l1 knockout (KO) mice using CRISPR/Cas9-mediated genome editing (fig. S6A). Genotyping of offspring revealed that Phf20l1-null mice were viable; although embryonic death were observed in a small number of mice, the proportions of genotypes in newborn mice were not notably different in accordance with Mendels law of inheritance. However, unexpectedly, some Phf20l1 KO homozygous embryos and individuals exhibited growth retardation (Fig. 6A). We further tracked the growth and development of these mice after birth. Statistical analysis showed that Phf20l1-null mice exhibited marked growth retardation. Moreover, body weight statistics revealed that Phf20l1 KO mice of the same age weighed significantly less than wild type. With age, the weight differences gradually diminished (fig. S6B). In addition, further analysis results showed that, compared to that in wild-type mice, the reproductive age of Phf20l1-null mice was significantly delayed, and these animals exhibited lower fertility (Fig. 6B).

(A) Uterine tissue excised from a pregnant female at 17.5 days post coitum (left). Phf20l1 KO adults are smaller than normal at about 4 weeks old (right). E17.5, embryonic day 17.5. (B) Phf20l1-null mice has delayed reproductive age and exhibited lower fertility. (C) The expression profiles of indicated GRGs were measured using IHC staining in littermate embryos. (D) Mammary ductal developmental defects in Phf20l1 CKO mice (represented as Phf20l1f/f; MMTV-Cre) at about 6 weeks old. (E) IHC staining of cyclin D1 and Ki67 in mammary glands of 6-week-old control and Phf20l1-null mice. (F) Representative bright-field imaging of mammary adenocarcinoma from MMTV-PyVT; Phf20l1f/f; MMTV-Cre (represented as MMTV-PyVT; Phf20l1 CKO) and MMTV-PyVT; Phf20l1+/+; MMTV-Cre (represented as MMTV-PyVT; Phf20l1 WT) mice. The circles indicate surface tumors. The biggest tumors of 110-day-old mice were obtained and calculated (n = 6). (G) IHC staining of Ki67 and cyclin D1 in mammary tumors isolated from MMTV-PyVT; Phf20l1 CKO and MMTV-PyVT; Phf20l1 WT mice. Data shown are means SD. Two-tailed unpaired t test, *P < 0.05 and **P < 0.01 (D to G). (H) Mammary adenocarcinoma incidence in MMTV-PyVT; Phf20l1 WT (n = 10) and MMTV-PyVT; Phf20l1 CKO (n = 16) mice depicted as the percentage of tumor-free mice. Mice were considered to be tumor free until a palpable mass (>4.0 mm) persisted for longer than 4 days. Log-rank test was used. (I) Overall survival analysis of the MMTV-PyVT; Phf20l1 WT (n = 9), MMTV-PyVT; Phf20l1 CKO (n = 8) mice, log-rank test. Photo credit: Yongqiang Hou, Tianjin Medical University.

Since we have shown that PHF20L1, as a MYC/HIF1-driven oncogene, could regulate the expression of GRGs and glycolysis process in breast cancer cells, we tested whether the expression levels of these genes were also changed in Phf20l1-null mice. First, the results of IHC staining with the littermate embryos at day 17.5 of gestation showed that the expression levels of GRGs such as Sirt1, Ldha, and Pgk1 were indeed down-regulated in Phf20l1-null mice (Fig. 6C). By detecting the mRNA levels of target genes in major organs of 4-week-old Phf20l1-null mice compared to those in wild-type mice, we found that the expression levels of GRGs such as Sirt1, Ldha, Pgk1, and Gapdh were down-regulated in the liver, spleen, and kidney (fig. S6C). Together, these results further indicate that a series of GRGs is indeed down-regulated in Phf20l1-null mice, which might contribute to growth retardation.

Next, we investigated the physiological role of PHF20L1 in mammary gland development with the Phf20l1 KO mice. The results showed that Phf20l1 deletion induced notable mammary ductal outgrowth delay. However, the KO mice were smaller than the wild-type mice (fig. S6D). To exclude the effects of differences in body weights and sizes, we generated Phf20l1 conditional knockout (CKO) mice, by crossed mice bearing floxed Phf20l1 with MMTV-Cre mice in which Cre expression was driven by the mouse mammary tumor virus promoter (MMTV-Cre) (fig. S6E). Compared to Phf20+/+; MMTV-Cre mice, virgin Phf20l1flox/flox; MMTV-Cre (Phf20l1f/f; MMTV-Cre) mice also showed a phenotype with mammary ductal outgrowth delay, whereas these animals appeared normal and did not differ from wild-type mice with respect to bodyweight. Furthermore, the results of qRT-PCR assays validated that the Phf20l1s deletion occurs in the mammary epithelium (Fig. 6D). The observation of these small but otherwise normal mammary glands revealed that Phf20l1 deficiency suppressed mammary ductal growth during puberty. Furthermore, we confirmed that the deletion of Phf20l1 could significantly reduce the number of proliferative cells in virgin mice based on IHC staining for cyclin D1 and Ki67 (Fig. 6E). Together, our findings indicate that Phf20l1 deletion contributes to the down-regulation of GRGs and growth retardation, especially delaying mammary ductal outgrowth.

To unravel the pathological roles of PHF20L1 in breast cancer in vivo, we crossed Phf20l1f/f; MMTV-Cre (Phf20l1 CKO) or WT mice with MMTVpolyoma virus middle T (PyVT) transgenic mice, respectively. The results showed that the volumes of the tumors from MMTV-PyVT; Phf20l1f/f; MMTV-Cre (represented as MMTV-PyVT; Phf20l1 CKO) mice were notably smaller than those of MMTV-PyVT; Phf20l1+/+; MMTV-Cre (represented as MMTV-PyVT; Phf20l1 WT) control mice (Fig. 6F). Compared to those in breast cancer tissues of control mice, decreased cyclin D1 and Ki67 protein levels were observed in tumors of MMTV-PyVT; Phf20l1 CKO mice (Fig. 6G). In addition, all MMTV-PyVT; Phf20l1 WT mice spontaneously developed breast tumors at 77 to 138 days after birth. Notably, the earliest tumor lumps in MMTV-PyVT; Phf20l1 CKO mice appeared at 100 days (Fig. 6H). The survival analysis revealed that genetic ablation of Phf20l1 resulted in a markedly prolonged survival (Fig. 6I). Together, these results demonstrated that PHF20L1 inhibits tumorigenesis in vivo and is a potential oncogene for breast cancer.

Our results identify that PHF20L1 is a reader for H3K27me2, which is predominantly recognized by the TUDOR domain, and links PRC2-mediated methylation and NuRD-mediated deacetylation to repress gene expression. PHF20L1 has three classical domains, namely MBT, TUDOR, and PHD. On the basis of in vitro studies, the isolated MBT domain preferentially binds mono- or dimethylated histones but not trimethylated or unmethylated histone peptides (33). Most TDRDs recognize a variety of histone methylations. For example, the tandem-TUDOR domain of JMJD2 family proteins (JMJD2A, JMJD2B, and JMJD2C) is able to read H3K4me3 or H4K20me3 (34). Most of the PHD fingers recognize the methylation of H3K4 and the partial methylation state of H3R2 and H4R3 (35). Several studies have shown that the MBT domain of PHF20L1 binds nonhistone methylation sites instead of binding to methylated histones (9). However, we found that isolated MBT and PHD domain of PHF20L1 demonstrates no specific binding to a modified histone peptide array, while the TUDOR domain exhibited strong specificity for binding to H3K27me2 but not to other histone modifications. It is reported that the second TUDOR domain of PHF20 binds dimethylated peptides derived from the H3 and H4 histone tails, including H3K27me2; although PHF20 could bind dimethylated peptides, it exhibited a preference for peptides containing H3K36me2 than H3K27me2, H3K9me2, H4K20me2, and H3K79me2 (36). Moreover, PHF20L1 and PHF20 share analogous domains, but PHF20L1 preferentially mediates transcriptional repression, while PHF20 mediates transcriptional activation. Their functional similarity and differences as well as the potential molecular mechanisms need to be further studied. Collectively, combined with other studies, our view is that the MBT domain of PHF20L1 might be more likely to bind nonhistone binding sites, whereas the TUDOR domain allows PHF20L1 to participate in chromatin events. However, the ligands of the PHF20L1 PHD domain are still unknown, and this requires further investigation.

Our results confirmed that the TUDOR domain of PHF20L1 recognizes H3K27me2, while the H3S28p impairs the binding of PHF20L1 TUDOR to H3K27me2. It was reported that H3S28 phosphorylation blocks the deposition of PRC2 and exerts a strong transcriptional activation signal (28, 37), further supporting our notion that PHF20L1 has transcriptional inhibitory activity. In addition, ITC and SPR experiments showed that the PHF20L1 TUDOR domains also have the slight ability to bind H3K27me3 (Fig. 2, F and G), considering that the depletion of PHF20L1 reduced not only H3K27me2 but also H3K27me3 at PHF20L1-occupied genes, we conclude that PHF20L1 is essential to maintain a microenvironment of transcriptional repression at the H3K27 site.

PRC2 and the NuRD complex could coexist in specific gene regions to govern the transcription of related genes during embryonic development, and the NuRD complex is mainly responsible for removing histone acetylation, whereas PRC2 can catalyze di- or trimethylation on H3K27 (20). We showed that in breast cancer, PHF20L1 inhibits the transcription of target genes by coordinating with the PRC2/NuRD complex on H3K27me2 enrichment gene regions, bridging histone cross-talk between methylation and deacetylation at H3K27. Our series of ChIP-seq results showed that KD of PHF20L1 could cause a relatively mild but sufficiently clear change in the modifications of H3K27 site. We further validated the changes using qChIP experiments on the promoters of the target genes. The results suggested that PHF20L1 KD could notably reduce the occupancy of PRC2 and the NuRD complex at target gene promoters and lead to decreased H3K27me2/3 and increased H3K27ac levels at the corresponding regions. We suspect that, as a reader protein, PHF20L1 is not able to write or erase epigenetic modifications directly, thus regulating epigenetic markers in a quite modest manner. Moreover, our further work will focus on the intrinsic links among PHF20L1, PRC2, and NuRD during the regulation of H3K27 modifications.

TSGs refer to those for which loss of function contributes to the malignant phenotype, whereas oncogene expression promotes cancerous phenotypes (23). HIC1 is an epigenetically regulated tumor suppressor that forms a transcriptional repressive complex with SIRT1 deacetylase binding the SIRT1 promoter and repressing its transcription (38). HIC1 could participate in tumor metabolism, especially the glycolytic process, through the HIC-SIRT1-TP53 axis (39). There are also other tumor suppressors such as tumor protein p53 (TP53), phosphatase and tensin homolog (PTEN), BRCA1, KISS1 that could cause metabolic reprogramming, especially lowering glycolysis levels to inhibit tumorigenesis (4042). Combined with ChIP-seq and RNA-seq analysis, we identified many TSGs that were inhibited by the PHF20L1/PRC2/NuRD complex, from which we selected HIC1, KISS1, and BRCA1 for further validation at the mRNA and protein level. RNA-seq analysis also showed that PHF20L1 KD causes the significant down-regulation of SIRT1, which further supports a mechanism whereby PHF20L1 directly inhibits HIC1 expression. Although the mechanism through which HIC1, KISS1, and BRCA1 inhibit the Warburg effect is relatively clear, the effect of other PHF20L1 target TSGs on glycolysis requires further clarification.

HIF1 is a key regulator of the Warburg effect and transcriptionally activates the expression of the majority of GRGs by binding hypoxia-responsive elements of glycolytic gene promoters (25). The overexpression or hyperactivation of MYC, a helix-loop-helix leucine zipper transcription factor, is one of the most common drivers of human cancer, and MYC also directly transactivates GRGs and stimulates aerobic glycolysis (24). Although the role of HIF1 and MYC in various cancers has become increasingly apparent, there are still many challenges regarding their application as drug targets in clinical practice. RNA-seq followed by GSEA analysis and subsequent experiments revealed that PHF20L1 is a downstream component of the MYC, and hypoxia signaling pathway and overexpression of PHF20L1, to a certain extent, could obviously promote glycolysis in breast cancer cells. Given the central roles of PHF20L1 in coordinating the function of the PRC2/NuRD complex and participating in the MYC/hypoxia signaling pathway, it could be a potential drug target for breast cancer.

Our results revealed that PHF20L1 is significantly up-regulated in breast cancer and that its expression appears to be positively associated with histological grades. However, the correlation between PHF20L1 and the molecular pathological subtypes including the luminal, HER2-positive, and basal-like breast cancer requires further investigation. Moreover, compared to levels in adjacent normal tissues, PHF20L1 was also found to be notably overexpressed in lymphoma, cerebrum cancer, esophageal cancer, prostate cancer, and pancreatic cancer, but significant up-regulation was not observed in some cancers such as lung cancer and cervical cancer. Therefore, we speculated that PHF20L1 might have tissue-specific expression patterns in different tumors. At present, we know little about PHF20L1, and the physiological and pathological functions of PHF20L1 in other tissues need to be further studied.

Suz12-, Eed-, or Ezh2-deficient mice are not viable and die during early implantation stages (43); meanwhile, PRC2 was reported to be essential for the development of the mammary gland (44). Further, Mta1 CKOs cause inappropriate mammary gland development (45). We showed that Phf20l1-deficient mice are viable but exhibit mammary ductal outgrowth delay. Badeaux et al. (46) reported that without Phf20, some mice died after birth, while surviving mice were notably smaller than wild-type mice, which is similar to the phenotype of Phf20l1 KO mice. PHF20 was reported to recognize histone H3K4me2 via its PHD finger and participates in transcriptional activation through interaction with MOF, while we found that PHF20L1 as a H3K27me2 reader coordinates with the PRC2/NuRD complex to mediate transcriptional inhibition. The epigenetic mechanistic difference between PHF20 and PHF20L1 has yet to be determined and needs to be studied in the future.

In summary, our findings indicate that PHF20L1, a H3K27me2 recognition protein that is characterized by its TUDOR domain, serves as a potential MYC and hypoxia-driven oncogene and plays a vital role in transcriptional repression by coordinating with PRC2 and the NuRD complex to repress several tumor suppressors such as HIC1, KISS1, and BRCA1, thus up-regulating the GRGs, leading to Warburg effect and tumor progression. Moreover, Phf20l1 deletion induces growth retardation and mammary ductal outgrowth delay and inhibits tumorigenesis in vivo. These findings support the pursuit of PHF20L1 as a potential therapeutic target of breast cancer.

The sources of antibodies against the following proteins were as follows: FLAG (F1408, IP; 1:10,000 for WB), PHF20L1 (HPA028417; IP; ChIP; 1:500 for WB and 1:100 for IHC), HDAC1 (H3284; 1:10,000 for WB), HDAC2 (H3159; 1:10,000 for WB), EZH2 (AV38470; 1:1,000 for WB), RbAp46/48 (R3779; 1:1000 for WB), and actin (A1978; 1:10,000 for WB) from Sigma-Aldrich; Mi-2 (sc-11378x; 1:500 for WB), SIN3A (sc-994; 1:1000 for WB), MBD3 (sc-271521; 1:1000 for WB), KISS1 (sc-101246; 1:500 for WB), HIC1 (sc-271499; 1:500 for WB), cyclin E (sc-247; 1:1000 for WB), cyclin D1 (sc-450; 1:1000 for WB), and m-IgGk BP-HRP (horse radish peroxidase) (sc-516102; 1:5,000 for WB) from Santa Cruz Biotechnology; H3 (ab1791; ChIP; 1:10,000 for WB); MTA2 (ab50209; 1:1000 for WB), LDHA (ab101562; 1:1000 for WB), BRCA1 (9010; 1:500 for WB), PGK2 (ab38007; 1:1000 for WB), MYC (ab32072; ChIP; 1:1000 for WB), and HIF1 (ab1; ChIP; 1:500 for WB) from Abcam; SUZ12 (3737s; 1:1000 for WB); MTA1 (5647/5647s; IP; ChIP; 1:1000 for WB), and cyclin D1 (55506; 1:200 for IHC) from Cell Signaling Technology; EED (GTX628007; 1:500 for WB) from GeneTeX; H3K27me1 (07-448; ChIP), H3K27me2 (07-452; ChIP), H3K27me3 (07-449; ChIP), and H3K27ac (07-360; ChIP) were purchased from Millipore; and GST (27457701v; 1:5000 for WB) from GE Healthcare Life Sciences. The histone tail peptides were purchased from Scilight-Peptide (Beijing, China). Protein A/G, Sepharose CL-4B beads were purchased from Amersham Biosciences, and the protease inhibitor mixture cocktail was purchased from Roche Applied Science. The siRNAs and shRNAs of PHF20L1 were purchased from Sigma-Aldrich. siRNAs and shRNAs of the other genes were obtained from GenePharma (Shanghai, China).

We thank S. Pradhan (New England Biolabs) for providing the FLAG-tagged PHF20L1 plasmid, and plasmids containing complementary DNA (cDNA) of MTA1, EZH2, and PHF20 were purchased from Open Biosystems. cDNAs were cloned into pLVX-Tight-Puro (Addgene), p3 FLAG-CMV-10 (Addgene), pCMV-Tag 2B (Addgene), pcDNA3.1-A (Addgene), pET-30a (+) (Addgene), and pGEX GST-fusion plasmids (GE Life Science). Deletion and mutation were introduced by PCR and site-directed mutagenesis using Mut Express MultiS Fast Mutagenesis Kit V2 (Vazyme). All plasmids used were confirmed by sequencing.

All cell lines were obtained from the American Type Culture Collection. HEK293T and Hs 578T cells were maintained in Dulbeccos modified Eagles medium (DMEM) supplemented with 10% fetal bovine serum (FBS). Cells were maintained in a humidified incubator equilibrated with 5% CO2 at 37C. MDA-MB-231 cells were cultured in L-15 medium supplemented with 10% FBS and without CO2. Transfections were performed using Lipofectamine 2000 or Lipofectamine RNAiMAX Reagent (Invitrogen, Carlsbad, CA) according to the manufacturers instructions. Each experiment was performed in triplicate and repeated at least three times. For RNA interference experiments, at least two independent siRNA sequences were tested for each gene, and the details of siRNA sequences covered in this article are available in table S3.

Total RNA was isolated from samples using TRIzol reagent following the manufacturers instructions (Invitrogen). Potential DNA contamination was removed using a ribonuclease-free DNase treatment (Promega). cDNA was prepared using the MMLV Reverse Transcriptase (Fermentas). Relative quantitation was performed using the ABI PRISM 7500 System (Applied Biosystems), which measures real-time SYBR Green fluorescence. Quantitation was then performed using the comparative Ct method (2Ct) with the expression of ACTB (-actin) as an internal control. The primers used are listed as the following in table S4. For RNA-seq analysis, total RNA was extracted, and three biological replicates were prepared. RNA-seq samples were sequenced using Illumina NextSeq 500. Raw reads were mapped to the human reference genome (hg19). The TopHat2 package was used to analyze the transcriptome, and htseq-count v0.6.0 was used to quantize transcript abundances. Differentially expressed genes were determined using DESeq2. Genes with a fold change of 1.5 and P value of <0.001 were selected as differential genes, and raw data are available on http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE128232.

A modified histone peptide array (Active Motif) was used for MBT, TUDOR, or PHD domain binding detection. A modified protein domain kit and an analysis software (Active Motif) were used in accordance with the manufacturers instructions. Peptide pull-down assays were performed. Briefly, biotinylated peptides (20 mg) were immobilized on 10 ml of streptavidin beads (Sigma, St. Louis, MO, USA) in 200 ml of binding buffer [50 mM tris-HCl (pH 7.5), 15 mM NaCl, 1 mM EDTA, 2 mM dithiothreitol, and 0.5% NP-40] at 4C. The next day, the beads were washed three times with binding buffer and then incubated with 25 mg of GST fusion protein or FLAG-tagged protein for 2.5 hours with rotation at 4C. After five washes with the binding buffer, the beads were boiled in protein loading buffer, and the resulting proteins were fractionated using 10% SDS-PAGE and subjected to Western blotting analysis using an anti-GST or FLAG antibody. The modified histone peptide arrays were analyzed using Active Motifs Array Analyze software. The software can analyze the spot intensity of the interactions.

ITC experiments were performed using an Affinity ITC system (TA Instruments). Briefly, the synthesized peptides (>98% purity) and purified proteins were all subjected to extensive dialysis against 100 mM NaCl and 25 mM tris (pH 7.5). Protein concentration was measured using a BCA Pierce protein assay kit (Thermo Fisher Scientific). Peptides at concentrations of 1.0 mM were loaded into the ITC syringe, and PHF20L1 TUDOR at a concentration of 0.1 mM was loaded into the ITC cell. Each titration consisted of 20 successive injections at 25C. The binding isotherm results were analyzed using NanoAnalyze Software (TA Instruments).

SPR experiments were performed using a Biacore T200 (GE Healthcare). All SPR-based materials were purchased from GE Healthcare. Biotin peptides and Scilight-Peptide (Beijing, China) were diluted in HEPES buffered saline-EP (HBS-EP; GE Healthcare) and immobilized on an SA chip. Approximately 600 resonance units (RU) of the immobilized peptides were obtained. Interaction analyses were tested using HBS-EP as a running buffer. Increasing concentrations of PHF20L1 TUDOR (0.2, 0.4, 0.8, 1.6, 3.2, and 6.4 ) were injected using the Kinetics/Affinity program. A flow cell without immobilized peptide served as a nonspecific binding control. The SA chip surface was regenerated after each cycle by injecting 10 mM NaOH for 30 s. Ka, Kd, and KD were determined using the Kinetics model in the Biacore T200 evaluation software version 2.0.

Immunopurification assays were performed as described previously (47). Briefly, a FLAG-tagged PHF20L1 plasmid was transfected into HEK293T cells, which were harvested 48 hours later. Anti-FLAG immune affinity columns were prepared using anti-FLAG M2 affinity gel (Sigma) following the manufacturers suggestions. Cell lysates were obtained from about 5 108 cells and applied to an equilibrated FLAG column of 1-ml bed volume to allow for the adsorption of the protein complex to the column resin. After binding, the column was washed with cold BC500 buffer containing 50 mM tris, 2 mM EDTA, 500 mM KCl, 10% glycerol, and protease inhibitors. FLAG peptide (0.2 mg/ml; Sigma-Aldrich) was applied to the column to elute the FLAG protein complex, as described by the vendor. Fractions of the bed volume were collected and resolved on SDSpolyacrylamide gel, silver-stained, and subjected to liquid chromatographytandem mass spectrometry sequencing and data analysis.

For immunoprecipitation assays, cells were washed with cold phosphate-buffered saline (PBS) and lysed with cold lysis buffer at 4C for 30 min. A total of 500 g of cellular extracts was incubated with appropriate primary antibodies or normal rabbit/mouse immunoglobin G (IgG) on a rotator at 4C overnight, followed by the addition of protein A/G Sepharose CL-4B beads for 2 hours at 4C. Beads were then washed five times with lysis buffer [50 mM tris-Cl (pH 7.4), 150 mM NaCl, 1 mM EDTA, 1% NP-40, 0.25% sodium deoxycholate, and a protease inhibitor mixture]. The immune complexes were subjected to SDS-PAGE followed by immunoblotting with secondary antibodies. Immunodetection was performed using enhanced chemiluminescence (ECL System, Thermo Scientific) according to the manufacturers instructions.

GST/His-fused constructs were expressed in BL21 E. coli. In vitro transcription and translation experiments were performed using rabbit reticulocyte lysate (TNT systems, Promega) according to the manufacturers recommendation. In GST/His pull-down assays, about 5 g of the appropriate GST/His fusion proteins with 30 l of glutathione-Sepharose or Ni beads was incubated with 5 to 8 l of the in vitrotranscribed/translated products in binding buffer [75 mM NaCl and 50 mM Hepes (pH 7.9)] at 4C for 2 hours in the presence of the protease inhibitor mixture. The beads were washed five times with binding buffer, resuspended in 30 l of 2 SDS-PAGE loading buffer, and detected by Western blotting.

Luciferase activity was measured using a dual luciferase kit (Promega, Madison, WI) according to the manufacturers protocol. Each experiment was performed in triplicate and repeated at least three times.

Normal cells or PHF20L1-depleted MDA-MB-231 cells were maintained in DMEM supplemented with 10% FBS. Approximately 5 107 cells were used for each ChIP-seq assay. The chromatin DNA precipitated by polyclonal antibodies against PHF20L1, EZH2, MTA1, H3K27me2, H3K27me3, or H3K27ac. The DNA was purified with a Qiagen PCR purification kit, and a Vazyme TruePrep DNA Library Prep Kit V2 for Illumina (Vazyme Biotech) was used for DNA library construction. In-depth whole genome DNA sequencing was performed by the Annoroad, Beijing. The raw sequencing image data were examined using the Illumina analysis pipeline, aligned to the unmasked human reference genome (hg19) using ELAND (Illumina), and further analyzed by MACS. Enriched binding peaks were generated after filtering through the input data. The ChIP-seq peak distribution statistics were performed using the Cis-regulatory element annotation system. All ChIP-seq data are available on http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE128231. Eluted DNA was purified using a PCR purification kit (QIAGEN), and qChIPs were performed using the TransStart Top Green qPCR Supermix (TransGen Biotech) by quantitative real-time PCR on the ABI 7500-FAST System. The qChIP PCR primers are available in table S4.

The ECAR was measured using the Seahorse XF24 Extracellular Flux Analyzer (Seahorse Bioscience). Experiments were performed according to the manufacturers instructions. ECAR was measured using a Seahorse XF Glycolysis Stress Test Kit (Agilent Technologies).

MDA-MB-231 cells were treated as indicated, and the cells were maintained in culture media for about 14 days and then stained with crystal violet.

Transwell chamber filters (Chemicon Incorporation) were coated with Matrigel. Cells were suspended in serum-free DMEM at a concentration of 5.0 105 cells/ml, and 300 l of the cell suspension was placed in the upper chamber of the transwell. The chamber was transferred to a well containing 500 l of media that included 10% FBS. Cells were incubated for 36 hours at 37C. Cells in the top well were removed by wiping the top of the membrane using a cotton swab. The membranes were then stained, and the remaining cells were counted. Four high-powered fields were counted for each membrane.

MDA-MB-231 cells were infected with indicated lentiviruses, and 5 106 viable cells in 100 ml PBS were injected subcutaneously into 6-week-old BALB/c nude mice (Vital River Laboratories, Beijing, China). Female nude mice (n = 5) were used in each experiment. Tumors were measured every 7 days using a vernier caliper, and the volume was calculated according to the formula: 1/2 length square width.

MDA-MB-231 cells stably expressing firefly luciferase (Xenogen) were infected with indicated lentiviruses, and 2 106 cells were injected into the lateral tail vein of 6-week-old female SCID mice. For bioluminescence imaging, mice were injected abdominally with 200 mg/g of d-luciferin in PBS. Fifteen minutes after injection, mice were anesthetized, and bioluminescence was imaged with a charge-coupled device camera (IVIS, Xenogen). Bioluminescence images were obtained with a 15-cm field of view, a binning (resolution) factor of 8, 1/f stop, open filter, and imaging time of 30 s to 2 min. Bioluminescence from the relative optical intensity was defined manually. Photon flux was normalized to background, which was defined from a relative optical intensity drawn over a mouse not administered an injection of luciferin.

The Phf20l1 KO and CKO mouse models were generated by Shanghai Model Orgnaisms Center Inc. Strategies of Phf20l1 KO and CKO mouse model were illustrated in fig. S6 (A and D). To obtain MMTV-PyVT; Phf20l1flox/flox; MMTV-Cre female mice, MMTV-PyVT (mouse mammary tumor viruspolyoma virus middle T antigen) transgenic male mice were crossed with Phf20l1flox/flox; MMTV-Cre female mice, and the tail DNA was analyzed by PCR to determine the mouse genotype. All mice studies were approved by the Ethical Committee of Tianjin Medical University (permit number: SYXK 2009-0001).

Embryonic day 17.5 (E17.5) embryos, mouse mammary glands, or samples from adjacent normal tissues of pathological grade I, II, and III were fixed in 10% neutral-buffered formalin overnight, then processed, paraffin-embedded, sectioned, and stained with hematoxylin and eosin according to a standard protocol. For IHC staining, 6-m sample sections were incubated with primary antibodies overnight at 4C in a humidified chamber, followed by incubation with the HRP-conjugated secondary antibodies for 2 hours. Staining was completed by 5- to 10-min incubation with diaminobenzidine substrate, which results in a brown-colored precipitate at the antigen site.

Mammary glands were harvested and fixed in Carnoys solution (6:3:1 of 100% ethanol, chloroform, and glacial acetic acid) and stained with carmine alum. The extent of ductal outgrowth was measured on whole inguinal mounts as the distance from the center of the lymph node to the leading edge of the ductal mass.

Results were reported as means SD for triplicate experiments unless otherwise noted. SPSS version 17.0 and two-tailed unpaired t tests were used for statistical analysis. The correlation coefficients were calculated using Cor function of the R programming software. Datasets were downloaded from http://www.ncbi.nlm.nih.gov/geo (Ivhsina; Gene Expression Omnibus: GSE21653, GES27562, GSE132929, and GSE51062). Data for the Kaplan-Meier survival analysis were from http://kmplot.com/analysis/index.php?p=service&cancer=breast.

Acknowledgments: Funding: This work was supported by grants from the Major State Basic Research Development Program of China (grant number 2016YFA0102400 to Y.W.) and National Natural Science Foundation of China (grant numbers 81773017 and 41931291 to Y. W.); Author contributions: Y.H. and Y.W. conceived this project. Y.H., W.L., D.S., X.Y., W.H., Yang Yang, Ying Yang, W.F., T.Z., and K.Z. mainly conducted experiments. Y.H., D.S., W.H., J.G., H.Y., X.T., R.Q., and K.Z. acquired data. Y.H., D.S., and Y.W. analyzed data. Y.H., D.S., W.H., and Y.W. wrote the manuscript. Competing interests: The authors declare that they have no competing interests. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. For the RNA-seq and ChIP-seq data, they can be found at the Gene Expression Omnibus database under accession numbers GSE128231 and GSE128232. Additional data related to this paper may be requested from the authors.

Read more:
PHF20L1 as a H3K27me2 reader coordinates with transcriptional repressors to promote breast tumorigenesis - Science Advances

Stem Cells Market Expected to Boost the Global Industry Growth in the Near Future – Germany English News

Advance Market Analyticsreleased the research report ofGlobal Stem CellsMarket, offers a detailed overview of the factors influencing the global business scope.Global Stem Cells Market research report shows the latest market insights with upcoming trends and breakdown of the products and services.The report provides key statistics on the market status, size, share, growth factors of the Global Stem Cells.This Report covers the emerging players data, including: competitive situation, sales, revenue and global market.

Free Sample Report + All Related Graphs & Charts @ https://www.advancemarketanalytics.com/sample-report/72815-global-stem-cells-market-1

The stem cell is used for treating chronic diseases such as cardiovascular disorders, cancer, diabetes, and others. Growing research and development in stem cell isolation techniques propelling market growth. For instance, a surgeon from Turkey developed a method for obtaining stem cells from the human body without enzymes which are generally used for the isolation of stem cells. Further, growing healthcare infrastructure in the developing economies and government spending on the life science research and development expected to drive the demand for stem cell market over the forecasted period.

The Global Stem Cellsis segmented by following Product Types:

Type (Adult Stem Cells (Neuronal, Hematopoietic, Mesenchymal, Umbilical Cord, Others), Human Embryonic Stem Cells (hESC), Induced Pluripotent Stem Cells, Very Small Embryonic-Like Stem Cells), Application (Regenerative Medicine (Neurology, Orthopedics, Oncology, Hematology, Cardiovascular and Myocardial Infraction, Injuries, Diabetes, Liver Disorder, Incontinence, Others), Drug Discovery and Development), Technology (Cell Acquisition (Bone Marrow Harvest, Umbilical Blood Cord, Apheresis), Cell Production (Therapeutic Cloning, In-vitro Fertilization, Cell Culture, Isolation), Cryopreservation, Expansion and Sub-Culture), Therapy (Autologous, Allogeneic)

Region Included are: North America, Europe, Asia Pacific, Oceania, South America, Middle East & Africa

Country Level Break-Up: United States, Canada, Mexico, Brazil, Argentina, Colombia, Chile, South Africa, Nigeria, Tunisia, Morocco, Germany, United Kingdom (UK), the Netherlands, Spain, Italy, Belgium, Austria, Turkey, Russia, France, Poland, Israel, United Arab Emirates, Qatar, Saudi Arabia, China, Japan, Taiwan, South Korea, Singapore, India, Australia and New Zealand etc.Enquire for customization in Report @:https://www.advancemarketanalytics.com/enquiry-before-buy/72815-global-stem-cells-market-1

Strategic Points Covered in Table of Content of Global Stem Cells Market:

Chapter 1: Introduction, market driving force product Objective of Study and Research Scope the Global Stem Cells market

Chapter 2: Exclusive Summary the basic information of the Global Stem Cells Market.

Chapter 3: Displayingthe Market Dynamics- Drivers, Trends and Challenges of the Global Stem Cells

Chapter 4: Presenting the Global Stem Cells Market Factor Analysis Porters Five Forces, Supply/Value Chain, PESTEL analysis, Market Entropy, Patent/Trademark Analysis.

Chapter 5: Displaying the by Type, End User and Region 2013-2018

Chapter 6: Evaluating the leading manufacturers of the Global Stem Cells market which consists of its Competitive Landscape, Peer Group Analysis, BCG Matrix & Company Profile

Chapter 7: To evaluate the market by segments, by countries and by manufacturers with revenue share and sales by key countries in these various regions.

Chapter 8 & 9: Displaying the Appendix, Methodology and Data Source

Finally, Global Stem Cells Market is a valuable source of guidance for individuals and companies.

Data Sources & Methodology

The primary sources involves the industry experts from the Global Stem Cells Market including the management organizations, processing organizations, analytics service providers of the industrys value chain. All primary sources were interviewed to gather and authenticate qualitative & quantitative information and determine the future prospects.

In the extensive primary research process undertaken for this study, the primary sources Postal Surveys, telephone, Online & Face-to-Face Survey were considered to obtain and verify both qualitative and quantitative aspects of this research study. When it comes to secondary sources Companys Annual reports, press Releases, Websites, Investor Presentation, Conference Call transcripts, Webinar, Journals, Regulators, National Customs and Industry Associations were given primary weight-age.

Get More Information: https://www.advancemarketanalytics.com/reports/72815-global-stem-cells-market-1

Thanks for reading this article; you can also get individual chapter wise section or region wise report version like North America, Europe or Asia.

About Author:

Advance Market Analytics is Global leaders of Market Research Industry provides the quantified B2B research to Fortune 500 companies on high growth emerging opportunities which will impact more than 80% of worldwide companies revenues.

Our Analyst is tracking high growth study with detailed statistical and in-depth analysis of market trends & dynamics that provide a complete overview of the industry. We follow an extensive research methodology coupled with critical insights related industry factors and market forces to generate the best value for our clients. We Provides reliable primary and secondary data sources, our analysts and consultants derive informative and usable data suited for our clients business needs. The research study enable clients to meet varied market objectives a from global footprint expansion to supply chain optimization and from competitor profiling to M&As.

Contact Us:

Craig Francis (PR & Marketing Manager)AMA Research & Media LLPUnit No. 429, Parsonage Road Edison, NJNew Jersey USA 08837Phone: +1 (206) 317 1218[emailprotected]

Connect with us athttps://www.linkedin.com/company/advance-market-analyticshttps://www.facebook.com/AMA-Research-Media-LLP-344722399585916https://twitter.com/amareport

Follow this link:
Stem Cells Market Expected to Boost the Global Industry Growth in the Near Future - Germany English News

Cyborg computer chips will get their brain from human neurons – SYFY WIRE

A.I.has already gotten to almost sci-fi levels of emulating brain activity, so much so that amputees can experience mind-controlled robotic arms, and neural networks might soon be a thing. That still wasnt enough for the brains behind one ambitious startup, though.

Cortical Labs sounds like it could have been pulled from the future. Co-founder and CEO Hong Wen Chong and his team are merging biology and technology by embedding real neurons onto a specialized computer chip. Instead of being programmed to act like a human brain, it will use those neurons to think and learn and function on its own. The hybrid chips will save tremendous amounts of energy with an actual neuron doing the processing for them.

Biological neural networks can solve problems in unfamiliar situations independent of acquired knowledge due to their self-organizing properties, says the companys website. Fluid intelligence is an essential requirement for autonomous robots.

Bio-computing was first switched on with neurons from mouse embryos, but can now use human neurons. Cortical Labs can morph human skin cells back into stem cells and then induce them to grow into actual human neurons. This was a process originally developed by Japanese scientists who were looking to eliminate the controversy that comes with using human embryonic stem cells. These cells are so useful because they havent yet decided what their function will be. That means they can be manipulated into just about anything.

After the skin cells undergo their transformation into neurons, a nourishing liquid medium is used to embed them onto a tiny metal oxide chip that has an even tinier grid of 22,00 electrodes. It is these electrodes that speak to programmers about when to zap electrical inputs to the neurons, letting them know what kind of outputs they are getting.

Artificially created neurons turn out the same as neurons that would (hypothetically) be taken from your gray matter, except there is no brain invasion required. Something like that would cross over from science fiction to science horror.

Right now, these chips are close to processing things like a dragonfly brain, so there are still upgrades to be made. Remember spending hours at the arcade playing Pong? Chong is determined to teach the chips to play that retro Atari game, and being powered by neurons uses just a fraction of what they would if they were only functioning on computerized intelligence. Think about it. The human brain has over a billion neurons, and our level of intelligence runs on only about 20 watts of power. Thats more than enough to play a marathon session of Pong.

Biological computing is the new frontier of computational power efficiency, the website says.

By the way, this wasnt the first time Pong got scientific star power. A.I. company DeepMind used it, along with other early Atari games that might be collecting dust in your basement somewhere, to demo how algorithms modeled after human neuron functions could perform. DeepMinds software scored high enough to convince Google into buying it. Now Google is using that tech to control the monster air conditioning units in its data centers, where it gets unbearably hot from servers devouring enough energy to keep entire cities running.

Cortical Labs is currently using mouse neurons on its quest to get hybrid chips to play Pong, but it probably wont be long before they use mutant human neurons. Gnarly.

(via Business Insider/Cortical Labs)

Visit link:
Cyborg computer chips will get their brain from human neurons - SYFY WIRE

Germline mutation of MDM4, a major p53 regulator, in a familial syndrome of defective telomere maintenance – Science Advances

Abstract

Dyskeratosis congenita is a cancer-prone inherited bone marrow failure syndrome caused by telomere dysfunction. A mouse model recently suggested that p53 regulates telomere metabolism, but the clinical relevance of this finding remained uncertain. Here, a germline missense mutation of MDM4, a negative regulator of p53, was found in a family with features suggestive of dyskeratosis congenita, e.g., bone marrow hypocellularity, short telomeres, tongue squamous cell carcinoma, and acute myeloid leukemia. Using a mouse model, we show that this mutation (p.T454M) leads to increased p53 activity, decreased telomere length, and bone marrow failure. Variations in p53 activity markedly altered the phenotype of Mdm4 mutant mice, suggesting an explanation for the variable expressivity of disease symptoms in the family. Our data indicate that a germline activation of the p53 pathway may cause telomere dysfunction and point to polymorphisms affecting this pathway as potential genetic modifiers of telomere biology and bone marrow function.

TP53 is the gene most frequently mutated in human tumors (1), and germ lineinactivating p53 mutations cause the Li-Fraumeni syndrome of cancer predisposition (2). In addition, accelerated tumorigenesis has been associated with polymorphisms increasing the expression of MDM2 or MDM4, the essential p53 inhibitors (3, 4). Alterations of the p53/MDM2/MDM4 regulatory node are, thus, mainly known to promote cancer. Unexpectedly, however, we recently found that mice expressing p5331, a hyperactive mutant p53 lacking its C terminus, recapitulated the complete phenotype of patients with dyskeratosis congenita (DC) (5).

DC is a telomere biology disorder characterized by the mucocutaneous triad of abnormal skin pigmentation, nail dystrophy, and oral leukoplakia; patients are also at very high risk of bone marrow failure, pulmonary fibrosis, and cancer, especially head and neck squamous cell carcinoma (HNSCC) and acute myeloid leukemia (AML) (6). Patients with DC are known to exhibit disease diversity in terms of age of onset, symptoms, and severity due to the mode of inheritance and causative gene (7, 8). DC is caused by germline mutations in genes encoding key components of telomere biology: the telomerase holoenzyme (DKC1, TERC, TERT, NOP10, and NHP2), the shelterin telomere protection complex (ACD, TINF2, and POT1), telomere capping proteins (CTC1 and STN1), and other proteins interacting with these cellular processes (RTEL1, NAF1, WRAP53, and PARN) (6). Twenty to 30% of affected individuals remain unexplained at the molecular level.

Our finding that p5331/31 mice were remarkable models of DC was initially unexpected for two reasons. First, an increased p53 activity was not expected to cause telomere dysfunction, given the well-accepted notion that p53 acts as the guardian of the genome. However, p53 is now known to down-regulate the expression of many genes involved in genome maintenance (5, 9, 10), and this might actually contribute to its toolkit to prevent tumor formation (11). Second, telomere biology diseases are usually difficult to model in mice because of differences in telomere length and telomerase expression between mice and humans. Mice that lack telomerase exhibited short telomeres only after three or four generations (G3/G4) of intracrosses (12, 13). However, mice with a telomerase haploinsufficiency and a deficient shelterin complex exhibited telomere dysfunction and DC features in a single generation (G1) (14). Because DC features were observed in G1 p5331/31 mice, we supposed that p53 might exert pleiotropic effects on telomere maintenance. Consistent with this, we found that murine p53 down-regulates several genes implicated in telomere biology (5, 9). Because some of these genes were also down-regulated by p53 in human cells (5, 9), our data suggested that an activating p53 mutation might cause features of DC in humans. However, this conclusion remained speculative in the absence of any clinical evidence.

Here, we report the identification of a germline missense mutation in MDM4, encoding an essential and specific negative regulator of p53, in a family presenting some DC-like phenotypic traits. We used a mouse model to demonstrate that this mutation leads to p53 activation, short telomeres, and bone marrow failure. Together, our results provide compelling evidence that a germline mutation affecting a specific p53 regulator may cause DC-like features in both humans and mice.

Family NCI-226 first enrolled in the National Cancer Institute (NCI) inherited bone marrow failure syndrome (IBMFS) cohort in 2008 (Fig. 1A and table S1). At the time, the proband (226-1) was 17 years of age and had a history of neutropenia, bone marrow hypocellularity, vague gastrointestinal symptoms, and chronic pain. His mother (226-4) also had intermittent neutropenia and a hypocellular bone marrow. Notably, his maternal aunt (226-7) had a history of melanoma and died at age 52 because of AML. The maternal aunts daughter (probands cousin, 226-8) had HNSCC at age 27 years, intermittent neutropenia, and bone marrow hypocellularity, while her son (probands cousin, 226-9) was diagnosed with metastatic HNSCC at 42 years of age. The probands father (226-3) was healthy with the exception of hemochromatosis. An IBMFS was suspected on the basis of the family history of cancer and neutropenia. Chromosome breakage for Fanconi anemia was normal, while lymphocyte telomeres were between the 1st and 10th percentiles in the proband and maternal cousin (226-8) (Fig. 1, B and C). The proband was tested for mutations in known DC-causing genes, and a TERT variant (p.W203S) was identified. Unexpectedly, however, the variant was found to be inherited from his father. TERT p.W203S is not present in gnomAD, but it is predicted to be tolerated by MetaSVM (15).

(A) Pedigree of family NCI-226. Arrow indicates proband. Cancer histories include oral squamous cell carcinoma for 226-8 at age 27 years and for 226-9 at age 42 years, and melanoma at 51 years and AML at 52 years for 226-7 (see table S1 for further details). 226-5 had lung cancer at age 69 years. 226-6 had non-Hodgkin lymphoma at age 91 years. In addition, four siblings of 226-6 had cancer: one with breast, two with lung, and one with ovary or uterus (not specified). Sequencing of 226-5, 226-6, 226-7, and 226-9 was not possible because of lack of available DNA. (B and C) Lymphocyte telomere lengths (TL) of study participants. Total lymphocyte telomere lengths are shown and were measured by flow cytometry with in situ hybridization. (B) Graphical depiction of telomere length in relation to age. Four individuals had telomeres measured twice. Legend is in (C). Percentiles (%ile) are based on 400 healthy individuals (50). (C) Age at measurement(s) and telomere length in kilobases. (D) Sequence of the MDM4 RING domain (residues 436 to 490) with secondary structure residues indicated (black boxes). The P-loop motif is highlighted in gray, and the mutated residue in red. (E) The mutant RING domain retains ATP-binding capacity. Wild-type (WT) and mutant (TM) glutathione S-transferase (GST)RING proteins, or GST alone, were incubated with 10 nM ATP and 5 Ci ATP-32P for 10 min at room temperature, filtered through nitrocellulose, and counted by liquid scintillation CPM, counts per minute. Results from two independent experiments. (F) The mutant MDM4 RING domain has an altered capacity to dimerize with the MDM2 RING. Two-hybrid assays were carried out as described (47). -LW, minus leucine and tryptophan; -LWHA, minus leucine, tryptophan, histidine and adenine; OD, optical density. Growth on the -LWHA medium indicates protein interaction, readily observed between MDM2 (M2-BD) and WT MDM4 (M4-AD WT) but faintly visible between MDM2 and MDM4T454M (M4-AD TM). (G) Impact of the mutation in transfected human cells. U2OS cells were transfected with an empty vector (EV) or an expression plasmid encoding a Myc-tagged MDM4 (WT or T454M) protein and then treated or not with cycloheximide (CHX) to inhibit protein synthesis, and protein extracts were immunoblotted with antibodies against Myc, p21, or actin. Bands were normalized to actin, and a value of 1 was assigned to cells transfected with the WT MDM4 expression plasmid (for Myc) or with the empty vector (for p21).

Since the TERT variant did not track with disease inheritance, whole-exome sequencing (WES) was performed to search for a causal gene. The whole-exome data were filtered by maternal autosomal inheritance and revealed three genes with heterozygous missense mutations potentially deleterious according to bioinformatics predictions: MDM4, KRT76, and REM1 (table S2). Given the limited knowledge of the function of KRT76 and REM1, and our prior knowledge of a DC-like phenotype in p5331/31 mice, we chose to focus on the mutation affecting MDM4 because it encodes a major negative regulator of p53. Although the T454M mutation does not affect the p53 interaction domain of MDM4, it might affect p53 regulation because it affects the MDM4 RING domain: Residue 454 is both part of a P-loop motif thought to confer adenosine triphosphate (ATP)binding capacity (16) and part of a strand important for MDM2-MDM4 heterodimerization (Fig. 1D) (17). The mutant RING domain had fully retained its capacity to bind ATP specifically (Fig. 1E and fig. S1A) but exhibited an altered capacity to interact with the MDM2 RING domain in a yeast two-hybrid assay (Fig. 1F). We next used transfection experiments to evaluate the consequences of this mutation on the full-length protein in human cells. We transfected U2OS cellsknown to have a functional but attenuated p53 pathway due to MDM2 overexpression (18)with either an empty vector or an expression plasmid encoding a Myc-tagged MDM4WT or MDM4T454M protein. Compared with cells transfected with the empty vector, cells transfected with a MDM4WT or a MDM4T454M expression plasmid exhibited decreased p21 levels, indicating MDM4-mediated p53 inhibition in both cases (Fig. 1G). However, the decrease in p21 levels was less pronounced in cells expressing MDM4T454M than in cells expressing MDM4WT (Fig. 1G) despite similar transfection efficiencies (fig. S1B). The lower expression levels of the MDM4T454M protein likely contributed to its decreased capacity to inhibit p53 (Fig. 1G). In this experimental setting, the treatment with cycloheximide did not reveal any significant difference in stability between the mutant and wild-type (WT) MDM4 proteins (Fig. 1G and quantification in fig. S1C), raising the possibility that the observed lower MDM4T454M protein levels might result from differences in mRNA translation efficiency. Together, these preliminary results argued for an impact of the mutation on MDM4 function, leading to p53 activation.

The MDM4 RING domain is remarkably conserved throughout evolution, e.g., with 91% identity between the RING domains of human MDM4 and mouse Mdm4 (19). Thus, we decided to create a mouse model to precisely evaluate the physiological impact of the human mutation. We used homologous recombination in embryonic stem (ES) cells to target the p.T454M mutation at the Mdm4 locus (Fig. 2A). Targeted recombinants were identified by long-range polymerase chain reaction (PCR) (Fig. 2B), confirmed by DNA sequencing (Fig. 2C), and the structure of the recombinant allele was further analyzed by Southern blots with probes located 5 and 3 of the targeted mutation (Fig. 2D). Recombinant ES clones were then microinjected into blastocysts to generate chimeric mice, and chimeras were mated with PGK-Cre mice to excise the Neo gene. PCR was used to verify transmission through the germ line of the Mdm4T454M (noted below Mdm4TM) mutation and to genotype the mouse colony and mouse embryonic fibroblasts (MEFs) (Fig. 2E). We first isolated RNAs from Mdm4TM/TM MEFs and sequenced the entire Mdm4 coding sequence: The Mdm4TM sequence was identical to the WT Mdm4 sequence except for the introduced missense mutation (not shown). Furthermore, like its human counterpart, the Mdm4 gene encodes two major transcripts: Mdm4-FL, encoding the full-length oncoprotein that inhibits p53, and Mdm4-S, encoding a shorter, extremely unstable protein (20, 21). We observed, in unstressed cells as well as in cells treated with Nutlin [a molecule that activates p53 by preventing Mdm2-p53 interactions (22) without altering Mdm4-p53 interactions (23, 24)], that the Mdm4TM mutation affected neither Mdm4-FL nor Mdm4-S mRNA levels (Fig. 2F). In Western blots, however, Mdm4-FL was the only detectable isoform, and it was expressed at lower levels in the mutant MEFs (Fig. 2G).

(A) Targeting strategy. Homologous recombination in ES cells was used to target the T454M mutation at the Mdm4 locus. For the Mdm4 WT allele, exons 9 to 11 are shown [black boxes, coding sequences; white box, 3 untranslated region (3UTR)] and Bam HI (BH) restriction sites. Above, the targeting construct contains the following: (i) a 2.9-kb-long 5 homology region encompassing exon 10, intron 10, and exon 11 sequences upstream the mutation; (ii) the mutation (asterisk) within exon 11; (iii) a 2.6-kb-long fragment encompassing the 3 end of the gene and sequences immediately downstream; (iv) a neomycin selection gene (Neo) flanked by loxP sequences (gray arrowheads) and an additional BH site; (v) a 2.1-kb-long 3 homology region containing sequences downstream Mdm4; and (vi) the Diphtheria toxin a gene (DTA) for targeting enrichment. (B to D) screening of G418-resistant ES clones as described in (A), with asterisks (*) indicating positive recombinants: (B) PCR with primers a and b; (C) sequencing after PCR with primers c and d: the sequence for codons 452 to 456 demonstrates heterozygosity at codon 454; (D) Southern blot of Bam HIdigested DNA with the 5 (left) or 3 (right) probe. (E) Examples of fibroblast genotyping by PCR with primers e and f. (F) The Mdm4T454M mutation does not alter Mdm4 mRNA levels. Mdm4-FL (left) and Mdm4-S (right) mRNAs were extracted from WT and Mdm4TM/TM MEFs before or after treatment for 24 hours with 10 M Nutlin, quantified using real-time PCR, and normalized to control mRNAs, and then the value in Nutlin-treated WT MEFs was assigned a value of 1. Results from five independent experiments and >4 MEFs per genotype. ns, not significant in a Students t test. (G) Decreased Mdm4 protein levels in Mdm4TM/TM MEFs. Protein extracts, prepared from MEFs treated as in (F), were immunoblotted with antibodies against Mdm4 or actin. Bands were normalized to actin, and then the values in Nutlin-treated WT cells were assigned a value of 1. p53P/P Mdm4E6/E6 MEFs do not express a full-length Mdm4 protein (20): They were loaded to unambiguously identify the Mdm4(-FL) band in the other lanes.

Mdm4TM/TM MEFs contained higher mRNA levels for the p53 targets p21(Cdkn1a) and Mdm2, indicating increased p53 activity (Fig. 3A). Consistent with this, Mdm4TM/TM MEFs exhibited increased p21 and Mdm2 protein levels (Fig. 3B and fig. S2). Moreover, Mdm4TM/TM MEFs prematurely ceased to proliferate when submitted to a 3T3 protocol (Fig. 3C), which also suggests an increased p53 activity. The mean telomere length was decreased by 11% in Mdm4TM/TM MEFs, and a subset of very short telomeres was observed in these cells, hence demonstrating a direct link between the Mdm4TM mutation, p53 activation, and altered telomere biology (Fig. 3D). In p5331/31 MEFs, subtle but significant decreases in expression were previously observed for several genes involved in telomere biology, and in particular, small variations in Rtel1 gene expression were found to have marked effects on the survival of p5331/31 mice (5, 9). Similarly, Mdm4TM/TM MEFs exhibited subtle but significant decreases in expression for Rtel1 and several other genes contributing to telomere biology (Fig. 3E). We previously showed that p53 activation correlates with an increased binding of the E2F4 repressor at the Rtel1 promoter (9). Hence, the decreased Rtel1 mRNA levels in Mdm4TM/TM MEFs most likely resulted from increased p53 signaling. Consistent with this, a further increase in p53 activity, induced by Nutlin, led to further decreases in Rtel1 mRNA and protein levels, in both WT and Mdm4TM/TM cells (fig. S3A). Recently, in apparent contradiction with our finding that p53 activation can cause telomere shortening (5), p53 was proposed to prevent telomere DNA degradation by inducing subtelomeric transcripts, including telomere repeat-containing RNA (TERRA) (25, 26), which suggested a complex, possibly context-dependent impact of p53 on telomeres (27). This led us to compare TERRA transcripts in WT and Mdm4TM/TM cells. Consistent with an earlier report (26), p53 activation led to increased TERRA at the mouse Xq subtelomeric region in WT cells (fig. S3B). However, Mdm4TM/TM cells failed to induce TERRA in response to stress (fig. S3B). Together, our data suggest that the telomere shortening observed in Mdm4TM/TM cells results from a p53-dependent decrease in expression of several telomere-related genes and, notably, Rtel1, a gene mutated in several families with DC (6). In addition, although evidence that altered TERRA levels can cause DC is currently lacking, we cannot exclude that an altered regulation of TERRA expression might contribute to telomere defects in Mdm4TM/TM cells.

(A) Quantification of p21 and Mdm2 mRNAs extracted from WT, Mdm4+/TM, and Mdm4TM/TM MEFs, treated or not for 24 hours with 10 M Nutlin. mRNA levels were quantified using real-time PCR and normalized to control mRNAs, and then the value in Nutlin-treated WT MEFs was assigned a value of 1. Results from 10 independent experiments. (B) Protein extracts, prepared from p53/, WT, and Mdm4TM/TM MEFs treated as in (A), were immunoblotted with antibodies against Mdm2, Mdm4, p53, p21, or actin. Bands were normalized to actin, and then the values in Nutlin-treated WT MEFs were assigned a value of 1. (C) Proliferation of MEFs in a 3T3 protocol. Each point is the average value of three independent MEFs. (D) Decreased telomere length in Mdm4TM/TM MEFs, as measured by quantitative FISH with a telomeric probe. Results from two MEFs per genotype, and 68 to 75 metaphases per MEF [means + 95% confidence interval (CI) are shown in yellow]. a.u., arbitrary units. (E) Telomere-related genes down-regulated in Mdm4TM/TM MEFs. mRNAs were extracted from unstressed WT and Mdm4TM//TM MEFs, quantified using real-time PCR, and normalized to control mRNAs, and the value in WT MEFs was assigned a value of 1. Results from >3 independent experiments and two MEFs per genotype. In relevant panels: P = 0.08, *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001 by Students t (A, C at passage 7, and E) or Mann-Whitney (D) statistical tests.

Mdm4TM/TM mice were born in Mendelian proportions from Mdm4+/TM intercrosses (Fig. 4A) but were smaller than their littermates and died within 0 to 30 min after birth, with signs of severe respiratory distress (Fig. 4, B and C). Consistent with this, Mdm4TM/TM pups at postnatal day 0 (P0) appeared hypoxic (Fig. 4C), and their lungs were very small and dysfunctional (Fig. 4D). Thus, Mdm4TM/TM pups most likely died from neonatal respiratory failure. Tissues from Mdm4TM/TM pups exhibited increased p21 mRNA levels, suggesting an increase in p53 activity in these animals (fig. S4). We next used flowFISH (fluorescence in situ hybridization) with a telomere-specific probe to evaluate the impact of the mutation on telomere length in vivo. Lung cells from Mdm4TM/TM pups (and control G3 Terc/ mice) exhibited a 25% decrease in mean telomere length compared with cells from WT or Mdm4+/TM littermates, indicating altered telomere biology in G1 homozygous mutants (Fig. 4E). Notably, p53 loss or haploinsufficiency rescued the perinatal lethality of Mdm4TM/TM pups, illustrating that the premature death of Mdm4TM/TM mice likely resulted from increased p53 activity (Fig. 4F). However, p53/ and Mdm4TM/TM p53/ mice exhibited similar survival curves, with a fraction of the mice (respectively 4 of 12 and 1 of 6) succumbing to thymic lymphoma in less than 180 days. In contrast, after 180 days, all the p53+/ mice remained alive, whereas most Mdm4TM/TM p53+/ mice had died. Mdm4TM/TM p53+/ mice were smaller than their littermates (Fig. 4G) and exhibited hyperpigmentation of the footpads (Fig. 4H), and 120-day-old Mdm4TM/TM p53+/ mice exhibited abnormal hemograms (Fig. 4I). Furthermore, the Mdm4TM/TM p53+/ mice that died 60 to 160 days after birth exhibited bone marrow hypocellularity (Fig. 4J), indicating bone marrow failure as the likely cause for their premature death.

(A) Mendelian distribution of the offspring from 8 Mdm4+/TM intercrosses. (B) Mdm4TM/TM mice die at birth. Cohort sizes are in parentheses. (C) Mdm4TM/TM neonates are smaller than their littermates and appear hypoxic. (D) Lungs from Mdm4TM/TM P0 pups are hypoplastic and sink in phosphate-buffered saline owing to a lack of air inflation. (E) Flow-FISH analysis of P0 lung cells with a telomere-specific peptide nucleic acid (PNA) probe. Top: Representative results from a WT, a Mdm4+/TM, a Mdm4TM/TM, and a G3 Terc/ mouse are shown. Right: Green fluorescence (fluo.) with black histograms for cells without the probe (measuring cellular autofluorescence) and green histograms for cells with the probe. The shift in fluorescence intensity is smaller in Mdm4TM/TM and Terc/ cells (c or d < a or b), indicating reduced telomere length. Left: Propidium iodide (PI) fluorescence histograms are superposed for cells with or without the probe. Below: Statistical analysis of green fluorescence shifts (see Materials and Methods). Means + 95% CI are shown; data are from two to three mice and >3800 cells per genotype. (F) Impact of decreased p53 activity on Mdm4TM/TM animals. Cohort sizes are in parentheses. (G) Examples of littermates with indicated genotypes. (H) Hind legs of mice with indicated genotypes. (I) Mdm4TM/TM p53+/ mice exhibit abnormal hemograms. Counts for white blood cells (WBC), red blood cells (RBC), and platelets (PLT) for age-matched (120 days old) animals are shown. (J) Hematoxylin and eosin staining of sternum sections from WT and Mdm4TM/TM p53+/ mice. In relevant panels: ns, not significant; *P < 0.05, ***P < 0.001, and ****P < 0.0001 by Mantel-Cox (B and F), Students t (C, D, G, and I), or Mann-Whitney (E) statistical tests. Photo credits: E.T. and R.D., Institut Curie (C, G, and H); R.D., Institut Curie (D).

Although Mdm4TM/TM MEFs and mice were useful to demonstrate that the Mdm4T454M mutation leads to p53 activation and short telomeres, a detailed analysis of Mdm4+/TM mice appeared more relevant to model the NCI-226 family, in which all affected relatives were heterozygous carriers of the MDM4T454M mutation. Unlike Mdm4TM/TM mice, most Mdm4+/TM animals remained alive 6 months after birth and had no apparent phenotype, similarly to WT mice (Fig. 5A). This was consistent with our analyses in fibroblasts because Mdm4+/TM MEFs behaved like WT cells in a 3T3 proliferation assay (Fig. 3C). However, p53 target genes appeared to be transactivated slightly more efficiently in Mdm4+/TM than in WT cells (Fig. 3A), and 30% of Mdm4+/TM mice exhibited a slight hyperpigmentation of the footpads, suggesting a subtle increase in p53 activity (Fig. 5B). We reasoned that a further, subtle increase in p53 activity might affect the survival of Mdm4+/TM mice. We tested this hypothesis by mating Mdm4+/TM animals with p53+/31 mice. p53+/31 mice were previously found to exhibit a slight increase in p53 activity and to remain alive for over a year (5). Notably, unlike Mdm4+/TM or p53+/31 heterozygous mice, Mdm4+/TM p53+/31 compound heterozygotes died in less than 3 months (Fig. 5A) and exhibited many features associated with strong p53 activation. Mdm4+/TM p53+/31 mice exhibited intense skin hyperpigmentation (Fig. 5C), were much smaller than their littermates (Fig. 5D), and exhibited heart hypertrophy (Fig. 5E) and thymic hypoplasia (Fig. 5F) and the males had testicular hypoplasia (Fig. 5G). Bone marrow failure was the likely cause for the premature death of Mdm4+/TM p53+/31 mice, as indicated by abnormal hemograms of 18-day-old (P18) compound heterozygotes (Fig. 5H) and bone marrow hypocellularity in the sternum sections of moribund Mdm4+/TM p53+/31 animals (Fig. 5I). We next used flow-FISH to analyze telomere length in the bone marrow cells of P18 WT, Mdm4+/TM, p53+/31, and Mdm4+/TM p53+/31 mice. We found no significant difference between telomere lengths in cells from five WT and three Mdm4+/TM mice with normal skin pigmentation, whereas cells from two Mdm4+/TM mice with increased skin pigmentation (or from p53+/31 mice) exhibited marginal (5 to 7%) decreases in mean telomere length. Notably, in G1 Mdm4+/TM p53+/31 cells, the average telomere length was decreased by 34% (Fig. 5J). Together, these results demonstrate that Mdm4+/TM mice are hypersensitive to subtle increases in p53 activity. Consistent with this, Mdm4+/TM p53+/31 MEFs also exhibited increased p53 signaling and accelerated proliferation arrest in a 3T3 protocol (fig. S5). In sum, the comparison between Mdm4TM/TM and Mdm4TM/TM p53+/ mice, or between Mdm4+/TM and Mdm4+/TM p53+/31 animals, indicated that subtle variations in p53 signaling had marked effects on the phenotypic consequences of the Mdm4T454M mutation (table S3).

(A) Impact of increased p53 activity on Mdm4+/TM animals. Cohort sizes are in parentheses. (B) Footpads from Mdm4+/TM mice appear normal (top) or exhibit a subtle increase in pigmentation (bottom). (C) Mdm4+/TM p53+/31 mice exhibit strong skin hyperpigmentation. (D) Mdm4+/TM p53+/31 mice are smaller than age-matched WT mice. (E to G) Mdm4+/TM p53+/31 mice exhibit heart hypertrophy (E) as well as thymic (F) and testicular (G) hypoplasia. (H) Mdm4+/TM p53+/31 mice exhibit abnormal hemograms. Counts for white blood cells, red blood cells, and platelets for five age-matched (P18) animals per genotype are shown. (I) Hematoxylin and eosin staining of sternum sections from mice of the indicated genotypes. (J) Flow-FISH analysis of P18 bone marrow cells with a telomere-specific PNA probe. Top: Representative results for a WT, a Mdm4+/TM with normal skin pigmentation (nsp), a Mdm4+/TM with increased footpad skin pigmentation (isp), a p53+/31, and a Mdm4+/TM p53+/31 mouse are shown; black histograms, cells without the probe; green histograms, cells with the probe. The smallest shift in fluorescence intensity (e) was observed with Mdm4+/TM p53+/31 cells. Bottom: Statistical analysis of green fluorescence shifts. Means + 95% CI are shown; data are from >1500 cells per genotype. In relevant panels: ns, not significant; *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001 by Mantel-Cox (A), Students t (D and E to H), or Mann-Whitney (J) statistical tests. Photo credits: R.D. and P.L., Institut Curie (B); E.T. and R.D., Institut Curie (C and D).

The carriers of the MDM4T454M mutation exhibited considerable heterogeneity in their phenotypes (Fig. 1 and table S1). The data from our mouse model suggested that variations in p53 activity might account for the variable expressivity and penetrance of clinical features among the NCI-226 MDM4+/T454M relatives. Hence, we analyzed nine known common polymorphisms reported to affect p53 activity and tumorigenesis (four at the TP53 locus, two at the MDM2 locus, and three at the MDM4 locus) (3,4,2832). Among the four MDM4+/T454M relatives, the proband (NCI-226-1) is more difficult to interpret because the potential contribution of the TERT p.W203S variant to his phenotype cannot be ruled out (even though it appears unlikely according to in silico predictions). The MDM4 allele encoding the mutant protein (p.T454M) appears associated with the C allele of single-nucleotide polymorphism (SNP) rs4245739, the G allele of SNP rs11801299, and the G allele of SNP rs1380576 (Fig. 6A). These three MDM4 variant alleles are associated with increased p53 activity (4,32) and might, thus, synergize with the MDM4T454M mutation in this family.

(A) Genotyping of polymorphisms that may affect the p53 pathway. The SNPs rs1800371 and rs1042522 modify the p53 protein sequence (28,29), whereas rs17878362 and rs17880560 are singlets (A1) or doublets (A2) of G-rich sequences in noncoding regions of TP53 that affect p53 expression (30). SNPs rs117039649 and rs2279744, in the MDM2 promoter, affect MDM2 mRNA levels (3,31). Three SNPs are at the MDM4 locus: rs4245739 in the 3UTR region affects MDM4 protein levels (4), whereas rs11801299 and rs1380576 were associated with an increased risk of developing retinoblastoma (32), a cancer type with frequent MDM4 alterations (51). Polymorphisms that differ among family members are in bold, with the allele (or haplotype) associated with increased p53 activity in green (because it may synergize with the effects of the MDM4T454M mutation). Alleles (or haplotypes) for which there is evidence of decreased p53 activity, or for which the effect is uncertain, are highlighted in red or blue, respectively. Please note that the clinical effects of the TP53 rs1042522 SNP have recently been contested (33), so that all alleles for this SNP were labeled in blue. MAF, minor allele frequency reported for all gnomAD populations combined. https://gnomad.broadinstitute.org (52). (B) Comparative analysis of primary fibroblasts from family members 226-4 and 226-8. p21 and RTEL1 mRNAs, extracted from cells from relatives NCI 226-4 and NCI 226-8 or two unrelated patients with DC carrying a TINF2 or a TERT mutation, were quantified using real-time PCR, normalized to control mRNAs, and then expressed relative to the mean values in TINF2 and TERT mutant cells. ns, not significant, **P < 0.01 and ***P < 0.001 in a Students t test.

The probands affected cousin (226-8) exhibited a very early onset of disease, with lymphocyte telomere length within or below the first percentile of age-matched control participants and tongue squamous cell carcinoma at age 27 (Fig. 1 and table S1). The WT MDM4 allele of 226-8 carried the rs4245739 C, the rs11801299 G, and the rs1380576 G variants associated with increased p53 activity. This suggests a potential disease-modifying effect of these MDM4 SNPs. In contrast, the probands mother (226-4) was much less severely affected, with telomere length between the 10th and 50th percentiles (Fig. 1). Although we cannot rule out that disease anticipation might contribute to her milder phenotype, note that her WT MDM4 allele carried variants that might correlate with decreased p53 activity and could antagonize the MDM4T454M mutation (rs4245739 A, rs11801299 A, and rs1380576 C; Fig. 6A). Family members 226-4 and 226-8 shared the same genotypes for all the other tested variants, except for TP53 rs1042522, a SNP first reported to affect apoptotic or cell cycle arrest responses (28), but with a clinical effect that now appears controversial (33). The probands sister (226-2), with a B cell deficiency and telomere lengths around the 10th percentile, also appeared less affected than 226-8. All the tested variants at the MDM2 and MDM4 loci were identical between 226-2 and 226-8. However, unlike 226-8, 226-2 exhibited a TP53 allele with an A1A1 haplotype for variants rs17878362 and rs17880560 that might decrease p53 activity (30) and antagonize the effects of the MDM4T454M mutation (Fig. 6A).

We had primary fibroblasts available for two of these family members, 226-4 and 226-8, allowing us to directly assess the functional effect of the MDM4T454M variant in these cells. These fibroblasts were grown in parallel with primary fibroblasts from patients with DC carrying either a TINF2K280E mutation or a TERTP704S mutation, and mRNA levels for p21 and RTEL1 were quantified. In agreement with the notion that a MDM4T454M heterozygous mutation activates p53 signaling in NCI-226 family members, fibroblasts from both 226-4 and 226-8 exhibited increased p21 mRNA levels compared with TINF2 or TERT mutant cells (Fig. 6B). However, cells from 226-4 only exhibited a 2-fold increase in p21 levels, whereas a 12-fold increase was observed for cells from 226-8, consistent with the notion that SNPs affecting the p53 pathway might counteract (for 226-4) or strengthen (for 226-8) the effect of the MDM4T454M mutation. Furthermore, we previously showed that RTEL1 mRNA levels are down-regulated upon p53 activation in human cells (5). RTEL1 mRNA levels appeared normal in cells from 226-4 but were markedly decreased in cells from 226-8, raising the possibility that a threshold in p53 activation might be required to affect RTEL1 expression (Fig. 6B).

Although MDM4 is primarily known for its clinical relevance in cancer biology, our study shows that a germline missense MDM4 mutation may cause features suggestive of DC. In humans, the MDM4 (p.T454M) mutation was identified in this family with neutropenia, bone marrow hypocellularity, early-onset tongue SCC, AML, and telomeres between the 1st and 10th percentiles in the younger generation. In mice, the same Mdm4 mutation notably correlated with increased p53 activity, short telomeres, and bone marrow failure. In both human transfected cells and MEFs, the mutant protein was expressed at lower levels than its WT counterpart, likely contributing to increased p53 activity. Together, these results demonstrate the importance of the MDM4/p53 regulatory axis on telomere biology and DC-like features in both species. Notably, p5331/31 mice were previously found to phenocopy DC (5), but whether this finding was relevant to human disease had remained controversial. When a mutation in PARN was found to cause DC (34), it first appeared consistent with the p5331 mouse model because PARN, the polyadenylate-specific ribonuclease, had been proposed to regulate p53 mRNA stability (35). However, whether PARN regulates the stability of mRNAs is now contested (36). Rather, PARN would regulate the levels of over 200 microRNAs, of which only a few might repress p53 mRNA translation (37). Furthermore, PARN regulates TERC, the telomerase RNA component (38), and TERC overexpression increased telomere length in PARN-deficient cells (39). Thus, whether a germline mutation that specifically activates p53 can cause DC-like features remained to be demonstrated in humans, and our report provides compelling evidence for this, because unlike PARN, MDM4 is a very specific regulator of p53.

A germline antiterminating MDM2 mutation was recently identified in a patient with a Werner-like syndrome of premature aging. Although multiple mechanisms might contribute to the clinical features in that report, a premature cellular senescence resulting from p53 hyperactivation was proposed to play a major role in his segmental progeroid phenotype (40). In that regard, our finding that increased p53 activity correlates with short telomeres appears relevant because telomere attrition is a primary hallmark of aging, well known to trigger cellular senescence (41). Furthermore, germline TP53 frameshift mutations were recently reported in two patients diagnosed with pure red blood cell aplasia and hypogammaglobulinemia, resembling but not entirely consistent with Diamond Blackfan anemia (DBA) (42). In addition to the pure red cell aplasia diagnostic of DBA, those patients were found to exhibit relatively short telomeres (although not as short as telomeres from patients with DC), which may also seem consistent with our results. Our finding of an MDM4 missense mutation in a DC-like family, together with recent reports linking an antiterminating MDM2 mutation to a Werner-like phenotype and TP53 frameshift mutations to DBA-like features, indicates that the clinical impact of germline mutations affecting the p53/MDM2/MDM4 regulatory network is just emerging. An inherited hyperactivation of the p53 pathwayvia a germline TP53, MDM2, or MDM4 mutationmay thus cause either DBA, Werner-like, or DC-like features, but additional work will be required to determine whether mutations in any of these three genes can cause any of these three syndromes. Likewise, several mouse models have implicated p53 deregulation in features of other developmental syndromes including the CHARGE, Treacher-Collins, Waardenburg, or DiGeorge syndrome (43), and it will be important to know whether germline mutations in TP53, MDM2, or MDM4 may cause these additional syndromes in humans.

Heterozygous Mdm4+/TM mice appeared normal but were hypersensitive to variations in p53 activity, and, perhaps most notably, Mdm4+/TM p53+/31 compound heterozygous mice rapidly died from bone marrow failure. Thus, the p5331 mutation acted as a strong genetic modifier of the Mdm4TM mutation. It is tempting to speculate that similarly, among the NCI-226 family members heterozygous for the MDM4T454M allele, differences in the severity of phenotypic traits (e.g., lymphocyte telomere length and bone marrow cellularity) may result, in part, from modifiers affecting the p53 pathway and synergize or antagonize with the effects of the MDM4T454M mutation. To search for potentially relevant modifiers, we looked at nine polymorphisms at the TP53, MDM2, and MDM4 loci that were previously reported to affect p53 activity. Notably, we found that the family member most severely affected (226-8, the probands cousin) carried a TP53 haplotype, as well as SNPs on the WT MDM4 allele, that might synergize with the effects of the MDM4T454M mutation. Conversely, a TP53 haplotype for the probands sister (226-2), or SNPs at the WT MDM4 locus for the probands mother (226-4), might antagonize the impact of MDM4T454M allele. Consistent with this, primary fibroblasts from 226-4 and 226-8 exhibited increased p53 activity, but p53 activation was much stronger in cells from 226-8. Our data, thus, appear consistent with the existence of genetic modifiers at the TP53 and MDM4 loci that may affect DC-like phenotypic traits among family members carrying the MDM4 (p.T454M) mutation. However, this remains speculative given the small number of individuals that could be analyzed. Furthermore, nonexonic variants affecting other genes might also contribute to DC-like traits (44). Last, the TP53 and MDM4 polymorphisms considered here were previously evaluated for their potential impact on tumorigenic processes, rather than DC-like traits such as telomere length or bone marrow hypocellularity. Our data suggest that polymorphisms at the TP53 and MDM4 (and possibly MDM2) loci should be evaluated for their potential impact on bone marrow function and telomere biology.

The individuals in this study are participants in an Institutional Review Boardapproved longitudinal cohort study at the NCI entitled Etiologic Investigation of Cancer Susceptibility in Inherited Bone Marrow Failure Syndromes (www.marrowfailure.cancer.gov, ClinicalTrials.gov NCT00027274) (7). Patients and their family members enrolled in 2008 and completed detailed family history and medical history questionnaires. Detailed medical record review and thorough clinical evaluations of the proband, his sister, parents, and maternal cousin were conducted at the National Institutes of Health (NIH) Clinical Center. Telomere length was measured by flow cytometry with in situ hybridization (flow-FISH) (45) in leukocytes of all patients and family members reported. DNA was extracted from whole blood using standard methods. DNA was not available from 226-7 or 226-9 (Fig. 1). Given the time frame of participant enrollment, Sanger sequencing of DKC1, TINF2, TERT, TERC, and WRAP53 was performed first, followed by exome sequencing.

WES of blood-derived DNA for family NCI-226 was performed at the NCIs Cancer Genomics Research Laboratory as previously described (46). Exome enrichment was performed with NimbleGens SeqCap EZ Human Exome Library v3.0 + UTR (Roche NimbleGen Inc., Madison, WI, USA), targeting 96 Mb of exonic sequence and the flanking untranslated regions (UTRs) on an Illumina HiSeq. Annotation of each exome variant locus was performed using a custom software pipeline. WES variants of interest were identified if they met the following criteria: heterozygous in the proband, his mother, and maternal cousin; nonsynonymous; had a minor allele frequency <0.1% in the Exome Aggregation Consortium databases; and occurred <5 times in our in house database of 4091 individuals. Variants of interest were validated to rule out false-positive findings using an Ion 316 chip on the Ion PGM Sequencer (Life Technologies, Carlsbad, CA, USA).

Primers flanking the MDM4 RING domain were used to amplify RING sequences, and PCR products were cloned (or cloned and mutagenized) in the pGST-parallel2 plasmid. Glutathione S-transferase (GST) fusion proteins were expressed in BL21 (DE3) cells. After induction for 16 hours at 20C with 0.2 mM IPTG (isopropyl--d-thiogalactopyranoside), soluble proteins were extracted by sonication in lysis buffer [50 mM tris (pH 7.0), 300 mM LiSO4, 1 mM dithiothreitol (DTT), 0.5 mM phenylmethylsulfonyl fluoride (PMSF), 0.2% NP-40, complete Protease inhibitors (Roche) 1]. The soluble protein fraction was incubated with Glutathione Sepharose beads (Pharmacia) at 4C for 2 hours, and the bound proteins were washed with 50 mM tris (pH 7.0), 300 mM LiSO4, and 1 mM DTT and then eluted with an elution buffer [50 mM tris-HCl (pH 7.5), 300 mM NaCl, 1 mM DTT, and 15 mM glutathione]. WT and mutant GST-RING proteins (0, 1, 2, 4, or 8 g) or GST alone (0 or 8 g) was incubated with 10 nM ATP and 5 Ci ATP-32P for 10 min at room temperature, filtered through nitrocellulose, and counted by liquid scintillation. Alternatively, 7 g of either WT or mutant GST-RING proteins was incubated with 5 Ci ATP-32P for 10 min at room temperature and increasing amounts (0, 0.02, 2, 20, and 200 M) of ATP or guanosine triphosphate (GTP), filtered through nitrocellulose, and counted by liquid scintillation.

The yeast two-hybrid assays were performed as described (47). Briefly, MDM4 and MDM2 RING open reading frames were cloned in plasmids derived from the two-hybrid vectors pGADT7 (Gal4-activating domain) and pGBKT7 (Gal4-binding domain) creating N-terminal fusions and transformed in yeast haploid strains Y187 and AH109 (Clontech). Interactions were scored, after mating and diploid selection on dropout medium without leucine and tryptophan, as growth on dropout medium without leucine, tryptophan, histidine, and adenine.

U2OS cells (106) were transfected by using Lipofectamine 2000 (Invitrogen) with pCDNA3.1 (6 g), or 5 106 cells were transfected with 30 g of pCDNA3.1-MycTag-MDM4WT or pCDNA3.1-MycTag-MDM4TM. Twenty-four hours after transfection, cells were treated with cycloheximide (50 g/ml; Sigma-Aldrich, C4859), then scratched in phosphate-buffered saline (PBS) after 2, 4, or 8 hours, pelleted, and snap frozen in liquid nitrogen before protein or RNA extraction with standard protocols.

The targeting vector was generated by recombineering from the RP23-365M5 BAC (bacterial artificial chromosome) clone (CHORI BACPAC Resources) containing mouse Mdm4 and downstream sequences of C57Bl6/J origin. A loxP-flanked neomycin cassette (Neo) and a diphtheria toxin gene (DTA) were inserted downstream of the Mdm4 gene, respectively, for positive and negative selections, and a single-nucleotide mutation encoding the missense mutation T454M (TM) was targeted in the exon 11 of Mdm4. The targeting construct was fully sequenced before use.

CK-35 ES cells were electroporated with the targeting construct linearized with Not I. Recombinant clones were identified by long-range PCR, confirmed by Southern blot, PCR, and DNA sequencing (primer sequences in table S4). Two independent recombinant clones were injected into blastocysts to generate chimeras, and germline transmission was verified by genotyping their offspring. Reverse transcription PCR (RT-PCR) of RNAs from Mdm4TM/TM MEFs showed that the mutant complementary DNA (cDNA) differed from an Mdm4 WT sequence only by the engineered missense mutation. The genotyping of p53+/, p53+/31, and G3 Terc/ mice was performed as previously described (5, 12). All experiments were performed according to Institutional Animal Care and Use Committee regulations.

MEFs isolated from 13.5-day embryos were cultured in a 5% CO2 and 3% O2 incubator, in Dulbeccos modified Eagles medium GlutaMAX (Gibco), with 15% fetal bovine serum (Biowest), 100 M 2-mercaptoethanol (Millipore), 0.01 mM Non-Essential Amino Acids, and penicillin/streptavidin (Gibco) for five or fewer passages, except for 3T3 experiments, performed in a 5% CO2 incubator for seven passages. Cells were treated for 24 hours with 10 M Nutlin 3a (Sigma-Aldrich) (22) or 15 M cisplatin (Sigma-Aldrich). Primary human fibroblasts at low passage (p.2 for TINF2K280E, p.3 for NCI-226-4 and NCI-226-8, and p.4 for TERTP704S) were thawed and cultured in fibroblast basal medium (Lonza) with 20% fetal calf serum, l-glutamin, 10 mM Hepes, penicillin/streptavidin, and gentamicin before quantitative PCR (qPCR) analysis.

Total RNA, extracted using NucleoSpin RNA II (Macherey-Nagel), was reverse transcribed using SuperScript IV (Invitrogen), with, for TERRA quantification, a (CCCTAA)4 oligo as described (48). Real-time qPCRs were performed with primer sequences as described (5, 9, 48) on a QuantStudio using Power SYBR Green (Applied Biosystems).

Protein detection by immunoblotting was performed using antibodies against Mdm2 (4B2), Mdm4 (M0445; Sigma-Aldrich), p53 (AF1355, R&D Systems), actin (A2066; Sigma-Aldrich), p21 (F5; Santa Cruz Biotechnology), Myc-Tag (SAB2702192; Sigma-Aldrich), and Rtel1 (from J.-A.L.-V.). Chemiluminescence revelation was achieved with SuperSignal West Dura (Perbio). Bands of interest were quantified by using ImageJ and normalized with actin.

Cells were treated with colcemide (0.5 g/ml) for 1.5 hours, submitted to hypotonic shock, fixed in an (3:1) ethanol/acetic acid solution, and dropped onto glass slides. Quantitative FISH was then carried out as described (5) with a TelC-Cy3 peptide nucleic acid (PNA) probe (Panagene). Images were acquired using a Zeiss Axioplan 2, and telomeric signals were quantified with iVision (Chromaphor).

Flow-FISH with mouse cells was performed as described (45). For each animal, either the lungs were collected or the bone marrow from two tibias and two femurs was collected and red blood cells were lysed; then, 2 106 cells were fixed in 500 l of PNA hybridization buffer [70% deionized formamide, 20 mM tris (pH 7.4), and 0.1% Blocking reagent; Roche] and stored at 20C. Either nothing (control) or 5 l of probe stock solution was added to cells [probe stock solution: 10 M TelC-FAM PNA probe (Panagene), 70% formamide, and 20 mM tris (pH 7.4)], and samples were denatured for 10 min at 80C before hybridization for 2 hours at room temperature. After three washes, cells were resuspended in PBS 1, 0.1% bovine serum albumin, ribonuclease A (1000 U/ml), and propidium iodide (12.5 g/ml) and analyzed with an LSR II fluorescence-activated cell sorter. WT and G3 Terc/ mice were included in all flow-FISH experiments, respectively, as controls of normal and short telomeres. For fluorescence shift analyses, the green histograms (corresponding to cells with the telomeric probe) were sliced into 18 windows of equal width and numbered 0 to 17 according to their distance from the median value in cells without the probe, and the number of cells in each window was quantified with ImageJ. The data from two to five mice per genotype were typically used to calculate mean telomere lengths, expressed relative to the mean in WT cells.

Organs were fixed in formol 4% for 24 hours and then ethanol 70% and embedded in paraffin wax. Serial sections were stained with hematoxylin and eosin using standard procedures (49). For hemograms, 100 l of blood from each animal was recovered retro-orbitally in a 10-l citrate-concentrated solution (S5770; Sigma-Aldrich) and analyzed using an MS9 machine (Melet Schloesing Laboratoires).

DNA extracted from Epstein-Barr virustransformed lymphocytes of NCI-226 family members was amplified with primers flanking nucleotide polymorphisms of interest (primer sequences in table S5), and then PCR products were analyzed by Sanger DNA sequencing.

Analyses with Students t, Mann-Whitney, or Mantel-Cox statistical tests were performed by using GraphPad Prism, and values of P < 0.05 were considered significant.

This is an open-access article distributed under the terms of the Creative Commons Attribution license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Acknowledgments: We are grateful to the family for valuable contributions to this study. We thank I. Grandjean, C. Caspersen, A. Fosse, and M. Garcia from the Animal Facility, C. Alberti and C. Roulle from the Transgenesis Platform, M. Richardson and A. Nicolas from the Pathology Service, and Z. Maciorowski from the Cell-Sorting Facility of the Institut Curie. We thank A. Chor for help with qPCRs, A. Pyanitskaya, C. Adam, V. Borde, M. Schertzer, and M. Perderiset for plasmids and technical advices, and A. Fajac for comments on the manuscript. F.T. would like to acknowledge the talent, kindness, and loyal support of I. Simeonova and S.J., two exceptional PhD students whose pioneering work led to this study. Funding: The Genetics of Tumor Suppression laboratory received funding from the Ligue Nationale contre le Cancer (Labellisation 2014-2018 and Comit Ile-de-France), the Fondation ARC and the Gefluc. PhD students were supported by fellowships from the Ministre de lEnseignement Suprieur et de la Recherche (to S.J., E.T., and R.D.), the Ligue Nationale contre le Cancer (to S.J.), and the Fondation pour la Recherche Mdicale (to E.T.). The work of S.A.S., N.G., and B.P.A. was supported by the intramural research program of the Division of Cancer Epidemiology and Genetics, NCI, and the NIH Clinical Center. Author contributions: V.L. created the Mdm4T454M mouse model, genotyped mouse cohorts, and performed transfections, yeast two-hybrid assays, protein purifications, and molecular cloning. E.T., R.D., and V.L. managed mouse colonies. E.T., R.D., and P.L. performed mouse anatomopathology. I.D., E.T., R.D., F.T., and J.-A.L.-V. determined mouse telomere lengths. V.L. and S.J. genotyped human polymorphisms and analyzed human fibroblasts. E.T. and R.D. genotyped MEFs and performed 3T3 assays. V.L., R.D., and E.T. performed Western blots. E.T., R.D., V.L., S.J., and P.L. performed qPCRs. B.B. and V.L. performed ATP-binding assays. B.P.A. supervised the NCI IBMFS study. N.G. and S.A.S. evaluated study participants. S.A.S. analyzed the exome sequencing data. F.T. and S.A.S. supervised the project and wrote the manuscript. Competing interests: The authors declare that they have no competing interests. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. Additional data related to this paper may be requested from the authors. The human samples can be provided by S.A.S. pending scientific review and a completed material transfer agreement. Requests for human cells should be submitted to S.A.S.

Follow this link:
Germline mutation of MDM4, a major p53 regulator, in a familial syndrome of defective telomere maintenance - Science Advances

A New Way to Study HIV’s Impact on the Brain – Global Health News Wire

By culturing astrocytes, microglia, and neuronsall derived from human-induced pluripotent stem cellsin one dish, researchers have created an effective model to study the cognitive impacts of HIV and other diseases. (Image: Sean Ryan)

Though many negative repercussions of human immunodeficiency virus infection can be mitigated with the use of antiretroviral therapy (ART), one area where medical advances havent made as much progress is in the reduction of cognitive impacts. Half of HIV patients have HIV-associated neurocognitive disorders (HAND), which can manifest in a variety of ways, from forgetfulness and confusion to behavior changes and motor deficiencies.

To better understand the mechanisms underlying HAND, researchers from Penns School of Dental Medicine and Perelman School of Medicine and from the Childrens Hospital of Philadelphia (CHOP) brought together their complementary expertise to create a laboratory model system using three of the types of brain cells thought to be involved. Led by doctoral student Sean Ryan, who was co-mentored by Kelly Jordan-Sciutto of Penn Dental Medicine and Stewart Anderson of CHOP and Penn Medicine, the model recapitulates important features of how HIV infection and ART affect the brain.

Frankly the models we generally use in the HIV field have a lot of weaknesses, says Jordan-Sciutto, co-corresponding author on the paper, which appears in the journalStem Cell Reports. The power of this system is it allows us to look at the interaction between different cell types of human origin in a way that is more relevant to patients than other models.

In addition to studying HIV, members of the team plan to use the same model to shed light on the neurological mechanisms that underlie other conditions, such as schizophrenia, Alzheimers, and even normal aging.

Were collaborating with a variety of colleagues to use this system to study Alzheimers disease as well as schizophrenia, says Anderson, co-corresponding author on the paper. We have the components in a dish that we know are interacting in these diseases, and this gives us a new mix-and-match way to understand how certain cells are contributing to neuronal damage.

Indeed, the impetus to create the model grew not out of HIV research but work that Ryan was pursuing in Andersons lab on schizophrenia.

We had been looking at the role of microglia, the resident immune cells of the central nervous system, says Ryan, first author on the work. We wanted to see if we could see the mechanistic changes that occur with microglia in schizophrenia.

To do so, Ryan and Anderson were interested in using human-induced pluripotent stem cellsadult cells that are reprogrammed to resemble embryonic stem cellswhich can be coaxed into differentiating into a variety of different cell types.

But schizophrenia is a complicated disease with a variety of contributing genetic and environmental factors and a broad spectrum of presentations. Rather than looking at something complex, they sought to apply their new system to a disease that likewise causes neurological damage but does so in a more dramatic way and in which microglia are also implicated: HIV/AIDS infection.

They reached out to Jordan-Sciutto, who has deep experience investigating the mechanisms of HAND and was eager for the opportunity to develop a model superior to those currently available. Together, the scientists identified the three cell types they were most interested in studying: neurons, astrocytes, and microglia.

Neurons arent directly infected by HIV but are known to be damaged during infection. Meanwhile astrocytes are believed to interact with neurons, causing damage by sending pro-inflammatory factors into the spaces between cells, called synapses. And microglia, which are responsible for maintaining a healthy environment in the absence of disease, are seen to expand and contribute to inflammation during HIV infection.

After nailing the technical challenge of creating this tractable model in which each cell type is generated independently and then mixed together, the team used it to probe how HIV infection and ART impact the cells, both alone and in combination.

A lot of people are taking PreEP [pre-exposure prophylaxis] if theyre in a situation where their risk of contracting HIV is heightened, says Ryan. Just as we want to understand the cognitive impacts of HIV, we also want to see whether these drugs alone are impacting the brain health of otherwise healthy people.

The researchers looked at RNA expression in their cultures to get a sense of what proteins and signaling pathways were becoming activated in each scenario. During infection, they saw inflammatory pathways that had previously been implicated in HIV in earlier research. When they introduced the antiretroviral drug EFZ, which is not in common use in the United States but remains a frontline therapy in many other areas of the world, with an infection, the activity of most of these pathways was reduced.

But this scenario involved its own unique response, says Ryan. Certain pathways associated with inflammation and damage remained despite the introduction of EFZ.

EFZ treatment of the tri-cultures that included HIV-infected microglia reduces inflammation by around 70%, Ryan says. Interestingly, EFZ by itself also triggered inflammation, though to a lesser extent than infection.

It seems a combination of infection and ART is creating its own unique response that is different from the sum of its parts, Ryan says. Knowing what pathways are still active due to ART could help us appropriately target additional therapies so patients dont develop HAND.

Many features of infection seen in the three-cell culture mirror what is known from HIV infection and ART treatment in people, giving the researchers confidence in the reliability of their model.

Just looking at the microglia, says Anderson, we see in our system that they are taking on both of their normal roles in keeping key signaling systems balanced during their normal state and activating and causing damage when theyre fighting infection. Were able to model normality and abnormality in a way we havent been able to before.

For Jordan-Sciutto, the new system is really going to change the way my lab operates going into the future. Shes hopeful many other HIV scientists will take it up to further their studies as she also explores more aspects of HIVs impact on the brain, such as how it navigates through the blood-brain barrier that normally protects the central nervous system from inflammation and infection.

The study authors give credit to the collaborative environment at Penn for this cross-disciplinary project. Tentacles of this project extend from CHOP to the dental school to the vet school to the medical school, says Anderson. Penn is a very special place where people seem to be more likely to share their technologies around and let other people work with and develop them. This project is a great example of that.

Read the rest here:
A New Way to Study HIV's Impact on the Brain - Global Health News Wire

Turning Back the Clock on Aging Cells – The New York Times

Researchers at Stanford University report that they can rejuvenate human cells by reprogramming them back to a youthful state. They hope that the technique will help in the treatment of diseases, such as osteoarthritis and muscle wasting, that are caused by the aging of tissue cells.

A major cause of aging is thought to be the errors that accumulate in the epigenome, the system of proteins that packages the DNA and controls access to its genes. The Stanford team, led by Tapash Jay Sarkar, Dr. Thomas A. Rando and Vittorio Sebastiano, say their method, designed to reverse these errors and walk back the cells to their youthful state, does indeed restore the cells vigor and eliminate signs of aging.

In their report, published on Tuesday in Nature Communications, they described their technique as a significant step toward the goal of reversing cellular aging and could produce therapies for aging and aging-related diseases.

Leonard P. Guarente, an expert on aging at M.I.T., said the method was one of the most promising areas of aging research but that it would take a long time to develop drugs based on RNA, the required chemical.

The Stanford approach utilizes powerful agents known as Yamanaka factors, which reprogram a cells epigenome to its time zero, or embryonic state.

Embryonic cells, derived from the fertilized egg, can develop into any of the specialized cell types of the body. Their fate, whether to become a skin or eye or liver cell, is determined by chemical groups, or marks, that are tagged on to their epigenome.

In each type of cell, these marks make accessible only the genes that the cell type needs, while locking down all other genes in the DNAs. The pattern of marks thus establishes each cells identity.

As the cell ages, it accumulates errors in the marking system, which degrade the cells efficiency at switching on and off the genes needed for its operations.

In 2006 Dr. Shinya Yamanaka, a stem-cell researcher at Kyoto University, amazed biologists by showing that a cells fate could be reversed with a set of four transcription factors agents that activate genes that he had identified. A cell dosed with the Yamanaka factors erases the marks on the epigenome, so the cell loses its identity and reverts to the embryonic state. Erroneous marks gathered during aging are also lost in the process, restoring the cell to its state of youth. Dr. Yamanaka shared the 2012 Nobel Prize in medicine for the work.

But the Yamanaka factors are no simple panacea. Applied to whole mice, the factors made cells lose their functions and primed them for rapid growth, usually cancerous; the mice all died.

In 2016, Juan Carlos Izpisua Belmonte, of the Salk Institute for Biological Studies in San Diego, found that the two effects of the Yamanaka factors erasing cell identity and reversing aging could be separated, with a lower dose securing just age reversal. But he achieved this by genetically engineering mice, a technique not usable in people.

In their paper on Tuesday, the Stanford team described a feasible way to deliver Yamanaka factors to cells taken from patients, by dosing cells kept in cultures with small amounts of the factors.

If dosed for a short enough time, the team reported, the cells retained their identity but returned to a youthful state, as judged by several measures of cell vigor.

Dr. Sebastiano said the Yamanaka factors appeared to operate in two stages, as if they were raising the epigenomes energy to one level, at which the marks of aging were lost, and then to a higher level at which cell identity was erased.

The Stanford team extracted aged cartilage cells from patients with osteoarthritis and found that after a low dosage of Yamanaka factors the cells no longer secreted the inflammatory factors that provoke the disease. The team also found that human muscle stem cells, which are impaired in a muscle-wasting disease, could be restored to youth. Members of the Stanford team have formed a company, Turn Biotechnologies, to develop therapies for osteoarthritis and other diseases.

The study is definitively a step forward in the goal of reversing cellular aging, Dr. Izpisua Belmonte said.

Follow this link:
Turning Back the Clock on Aging Cells - The New York Times

Human Embryonic Stem Cell Market Analysis and Forecasts to 2027 By Recent Trends, Developments In Manufacturing Technology And Regional Growth…

An off-the-shelf report onHuman Embryonic Stem Cell Marketwhich has been compiled after an in-depth analysis of the market trends prevailing across five geographies (North America, Europe, Asia-Pacific, Middle-East and Africa, and South America). Various segments of the market such as type/components/ application/industry verticals/ end-users are analyzed with robust research methodology which includes three step process starting with extensive secondary research to gather data from company profiles, global/regional associations, trade journals, technical white papers, paid databases etc. followed by primary research (interviews) with industry experts/KOLs to gain their insights and views on current scenarios and future scope of the market as well as validating the secondary information, further internal statistical model is used to estimate the market size and forecasts till 2027.

Get sample PDF copy at:https://www.theinsightpartners.com/sample/TIPRE00005165/

The human embryonic stem cells are obtained from the undifferentiated inner mass cell of the human embryo and human fetal tissue. The human embryonic stem cell can replicate indefinitely and produce non-regenerative tissue such as myocardial and neural cells. This potential of human embryonic stem cell allows them to provide an unlimited amount of tissue for transplantation therapies to treat a wide range of degenerative diseases. Hence, human embryonic stem cells are used in the treatment of various diseases such as Alzheimers disease, cancer, blood and genetic disorders related to the immune system and others.

The key players influencing the market are:

This report contains:

The global human embryonic stem cell market is segmented on the basis of product type, application and end user. Based on product type, the market is segmented as totipotent stem cell, pluripotent stem cell and unipotent stem cell. On the basis of application, the global human embryonic stem cell market is segmented into regenerative medicine, stem cell biology research, tissue engineering and toxicology testing. Based on end users, the market is segmented as therapeutics companies, cell & tissue banks, tools & reagents companies and others.

Human Embryonic Stem Cell Market- Global Analysis to 2027 is an expert compiled study which provides a holistic view of the market covering current trends and future scope with respect to product/service, the report also covers competitive analysis to understand the presence of key vendors in the companies by analyzing their product/services, key financial facts, details SWOT analysis and key development in last three years. Further chapter such as industry landscape and competitive landscape provides the reader with recent company level insights covering mergers and acquisitions, joint ventures, collaborations, new product developments/strategies taking place across the ecosystem. The chapters also evaluate the key vendors by mapping all the relevant products and services to exhibit the ranking/ position of top 5 key vendors.

Human Embryonic Stem Cell Market is a combination of qualitative as well as quantitative analysis which can be broken down into 40% and 60% respectively. Market estimation and forecasts are presented in the report for the overall global market from 2018 2027, considering 2018 as the base year and 2018 2027 forecast period. Global estimation is further broken down by segments and geographies such as North America, Europe, Asia-Pacific, Middle East & Africa and South America covering major 16 countries across the mentioned regions. The qualitative contents for geographical analysis will cover market trends in each region and country which includes highlights of the key players operating in the respective region/country, PEST analysis of each region which includes political, economic, social and technological factors influencing the growth of the market.

Key Benefits

Purchase This Report @https://www.theinsightpartners.com/buy/TIPRE00005165/

About Us:The Insight Partners is a one stop industry research provider of actionable intelligence. We help our clients in getting solutions to their research requirements through our syndicated and consulting research services. We are a specialist in Technology, Semiconductors, Healthcare, Manufacturing, Automotive and Defense.

Contact Us:Call: +1-646-491-9876Email:[emailprotected]

Read the original here:
Human Embryonic Stem Cell Market Analysis and Forecasts to 2027 By Recent Trends, Developments In Manufacturing Technology And Regional Growth...

Laboratory model looking at how a HIV infection impacts the brain – Health Europa

The Human Immunodeficiency Virus (HIV) infection impacts the human body in a variety of ways, however medical advances have made progress in mitigating the impact of the infection using antiretroviral therapy (ART). One area of impact which is yet to see much progress is the impact of the infection on cognition.

Half of HIV patients have HIV-associated neurocognitive disorders (HAND), which can manifest in a variety of ways, from forgetfulness and confusion to behaviour changes and motor deficiencies.

To better understand the mechanisms underlying HAND, researchers from Penns School of Dental Medicine and Perelman School of Medicine and from the Childrens Hospital of Philadelphia (CHOP) brought together their complementary expertise to create a laboratory model system using three of the types of brain cells thought to be involved.

Led by doctoral student Sean Ryan, who was co-mentored by Kelly Jordan-Sciutto of Penn Dental Medicine and Stewart Anderson of CHOP and Penn Medicine, the model recapitulates important features of how HIV infection and ART affect the brain.

The research was published in the journal Stem Cell Reports.

Jordan-Sciutto, co-corresponding author on the paper, said: Frankly the models we generally use in the HIV field have a lot of weaknesses. The power of this system is that it allows us to look at the interaction between different cell types of human origin in a way that is more relevant to patients than other models.

Anderson, co-corresponding author on the paper, said: Were collaborating with a variety of colleagues to use this system to study Alzheimers disease as well as schizophrenia.

We have the components in a dish that we know are interacting in these diseases, and this gives us a new mix-and-match way to understand how certain cells are contributing to neuronal damage.

We had been looking at the role of microglia, the resident immune cells of the central nervous system, says Ryan. We wanted to see if we could see the mechanistic changes that occur with microglia in schizophrenia.

Ryan and Anderson were interested in using human-induced pluripotent stem cells, which are adult cells that are reprogrammed to resemble embryonic stem cells, and which can be coaxed into differentiating into a variety of different cell types.

The scientists identified the three cell types they were most interested in studying: neurons, astrocytes, and microglia.

Neurons arent directly infected by HIV but are known to be damaged during infection. Meanwhile astrocytes are believed to interact with neurons, causing damage by sending pro-inflammatory factors into the spaces between cells, called synapses. Microglia, which are responsible for maintaining a healthy environment in the absence of disease, are seen to expand and contribute to inflammation during HIV infection.

A lot of people are taking PreEP [pre-exposure prophylaxis] if theyre in a situation where their risk of contracting HIV is heightened, says Ryan. Just as we want to understand the cognitive impacts of HIV, we also want to see whether these drugs alone are impacting the brain health of otherwise healthy people.

The researchers looked at RNA expression in their cultures to see what proteins and signalling pathways were becoming activated in each scenario. During infection, they saw inflammatory pathways that had previously been implicated in HIV in earlier research. When they introduced the antiretroviral drug EFZ, which is not in common use in the United States but remains a frontline therapy in many other areas of the world, with an infection, the activity of most of these pathways was reduced.

Ryan said: EFZ treatment of the tri-cultures that included HIV-infected microglia reduces inflammation by around 70%.

It seems a combination of infection and ART is creating its own unique response that is different from the sum of its parts. Knowing what pathways are still active due to ART could help us appropriately target additional therapies so patients dont develop HAND.

Many features of infection seen in the three-cell culture mirror what is known from HIV infection and ART treatment in people, giving the researchers confidence in the reliability of their model.

Just looking at the microglia, says Anderson, we see in our system that they are taking on both of their normal roles in keeping key signalling systems balanced during their normal state and activating and causing damage when theyre fighting infection. Were able to model normality and abnormality in a way we havent been able to before.

For Jordan-Sciutto, the new system is really going to change the way my lab operates going into the future.

She is hopeful many other HIV scientists will take it up to further their studies as she also explores more aspects of HIVs impact on the brain, such as how it navigates through the blood-brain barrier that normally protects the central nervous system from inflammation and infection.

In addition to studying HIV, members of the team plan to use the same model to shed light on the neurological mechanisms that underlie other conditions, such as schizophrenia, Alzheimers, and even normal ageing.

See original here:
Laboratory model looking at how a HIV infection impacts the brain - Health Europa