RESULTS SMAR1 expression declines with progression in breast cancers
When we evaluated the expression of SMAR1 in various cancers by screening in silico GEPIA (Gene Expression Profiling Interactive Analysis) database, SMAR1 was found to be reduced in the tumor tissues of several cancers compared to counterpart normal tissues (fig. S1A) and, in the Oncomine database, SMAR1 was substantially reduced in invasive breast carcinomas (fig. S1B). We then evaluated the correlation between SMAR1 mRNA levels with disease prognosis in breast cancer patients by Kaplan-Meier (Km) plots using the publicly available Km plotter database (https://kmplot.com/analysis). High SMAR1 expression correlated with longer RFS (Fig. 1A) and with overall survival (OS) and progression-free survival (PFS) (fig. S1C). However, the P values for OS and PFS were not as substantial as RFS, which could be due to the smaller sample sizes for both OS (397 subjects) and PFS (165 subjects) as compared to that of RFS (1764 subjects). Furthermore, immunofluorescence and Western blotting analyses also revealed reduced SMAR1 expression in stage III as compared to stage II breast tumor tissues (Fig. 1, B and C). These results indicate that SMAR1 expression decreases with advancement of breast cancer.
(A) Kaplan-Meier analysis plot (Km plot) representing correlation of SMAR1 expression with relapse-free survival (RFS) of patients with breast cancer. The intrinsic subtype has been kept as follows: all; the hazard ratios (HR) with 95% confidence intervals and P value are noted (n = 1764). (B) Tissue immunofluorescence (B) and Western blotting (C) for the expression of SMAR1 (red) in stage II versus stage III human tumor samples (n = 5 patients for each stage). Nuclei were stained with DAPI. Scale bars, 200 m; magnification, 10. The graph in (B) shows the corrected total cell fluorescence (CTCF) value of SMAR1 between stages II and III in samples, as calculated using ImageJ. (n = 5 for each stage). (D) Bar diagram depicting relative mRNA level of SMAR1 in mouse tumor tissues on days 7, 14, and 21 as calculated by real-time PCR (n = 3 mice in each group). (E) Bar diagram depicting percentage of SMAR1+ cells on days 7, 14, and 21 mouse tumor tissues as detected by flow cytometry (n = 3 in each group). (F and G) Representative tissue immunofluorescence (F) and immunohistochemistry (G) images staining for SMAR1 in mouse tumor tissues on days 7 and 21 (n = 3 in each group). Scale bars, (F) 200 m; magnification, 10; (G) 1 mm, magnification 20. (H) Bar diagram depicting the percentage of CSCs (% each of CD44+/CD24, Oct4+, and Sox2+ cells) in mouse tumor tissues on days 7, 14, and 21, respectively, as determined by flow cytometry (n = 3 in each group). (I) Correlation plot depicting the relationship between % CSCs (CD44+/CD24) and % SMAR1+ cells in mouse tumor tissues on days 7, 14, and 21. R is the correlation coefficient. (J) Correlation plot between SMAR1 and ALDH1 obtained from the R2 database, specifically the tumor breast invasive carcinoma-TCGA-1097 dataset. (K) t-SNE plot of SMAR1 and ALDH1 obtained from the R2 database (using tumor breast invasive carcinoma-TCGA-1097 dataset). (L) Scatter plot assessing relative SMAR1 mRNA expression in flow cytometrically sorted pure NSCCs and CSCs from human breast tumor samples (n = 4). (M) Representative Western blot assessing SMAR1 expression in adherent cells and primary spheres of MCF-7, MDA-MB-468, and MDA-MB-231 cell lines (n = 3). (N) Immunofluorescence images of SMAR1 expression in adherent cells and primary spheres of the MCF-7 and MDA-MB-468 lines. Scale bars, 100 m; magnification, 20 (n = 3). (O) From left: % SMAR1+ cells (left); mean fluorescence intensity (MFI) of Oct4, Sox2, and Nanog (center); and % cytokeratin 18 (CK18)+ cells (right) in adherent cells, secondary spheres, and differentiated (diff.) spheres of MCF-7 cell line (n = 3 to 5 experiments). Data in (A) to (O) are mean SD or representative of three independent experiments unless otherwise noted. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001 by unpaired t test (B), Mann-Whitney U test (C), Kruskal-Wallis test (D), two-way analysis of variance (ANOVA) (L), or ordinary one-way ANOVA (E, H, and O).
Next, we orthotopically inoculated 4T1 tumor cells in the mammary fat pad of female BALB/c mice, and tumor tissues were collected on the 7th, 14th, and 21st days thereafter. Examination of SMAR1 expression at these time points of progressive tumor growth revealed a stark decrease in SMAR1 expression with increased tumor burden in mice (Fig. 1, D to G). These results together indicate a negative association of SMAR1 with tumor progression and a positive connection with RFS.
Given our findings that SMAR1 expression negatively correlates with disease progression in breast cancer, and previous reports from others and our laboratory (3, 15) demonstrating positive correlation of CSCs with breast cancer progression and therapeutic resistance, we postulated a possible inverse relationship between SMAR1 and CSCs.
To validate our hypothesis, tumor tissues were collected from BALB/c mice at weekly time intervals (days 7, 14, and 21), and the cells were harvested and subjected to flow cytometry. Our flow cytometric analysis revealed gradual increase in the percentage of CD44+/24/low CSCs (16) in total tumor mass from days 7 to 21 (Fig. 1H) with significant decrease in SMAR1 expression level (Fig. 1D). In addition, when the percentage of SMAR1+ cells was plotted against the percentage of CD44+/24/low CSCs present in the total tumor mass of days 7, 14, and 21, respectively, a significant, negative correlation between SMAR1 and the CSC population was observed (Fig. 1I). An increase in the population of Oct4+ and Sox2+ cells were also marked by flow cytometry in the tumor mass from days 7 to 21 (Fig. 1H) that comes in line with our previous CD44+/24/low data. This negative correlation of SMAR1 with CSC content was further supported by in silico correlation plot from two databasesthe GEPIA database and the R2 Genomics Analysis and Visualization Platform database (fig. S1D and Fig. 1J) and t-SNE (t-distributed stochastic neighbor embedding) plots from the R2 database (Fig. 1K)where in breast cancer, SMAR1 had a significantly negative correlation with ALDH1, a CSC marker (17, 18). Next, flow cytometry gating of CSCs (CD44+/24/low) and nonstem cancer cells (NSCCs; CD44+/24+, CD44/24, and CD44/24+) from tumor tissues of BALB/c mice revealed a lower expression of SMAR1 in CSCs as compared to NSCCs (fig. S1E). Together, these findings support our hypothesis that SMAR1 may be attenuated in CSCs.
To further corroborate these results, CSCs and NSCCs were isolated from breast cancer patient tissues using flow cytometry, and the expression of SMAR1 was detected by semiquantitative polymerase chain reaction (PCR). The results indicated lower expression of SMAR1 in patient-derived CSCs than in their nonstem counterpart (Fig. 1L).
To confirm our hypothesis in vitro, breast cancer cell lines MCF-7, MDA-MB-468, and MDA-MB-231 were cultured in serum-free, growth factorsupplemented media on ultralow attachment surface for 6 to 7 days to obtain primary spheres, which was then cultured in serum-free conditions for an additional 7 to 8 days to acquire secondary spheres to further enrich the CSC population. When characterized for pluripotency markers in comparison to adherent cells, the primary spheres showed increased abundance of four core stemness markers: Oct4, Sox2, Nanog, and ALDH1 (fig. S1F). Secondary spheres, which displayed more CSCs (CD44+/24/low, Oct4+, and Sox2+) than did primary spheres (fig. S1G), had additionally greater expression of ALDH1 (fig. S1G). Pure CSCs, which were sorted out from secondary spheres as CD44+/24/low, also displayed significantly higher ALDH1 levels than did NSCCs (fig. S1H).
Western blot and immunofluorescence analyses showed a significant decrease in SMAR1 expression in primary spheres derived from the MCF-7, MDA-MB-468, and MDA-MB-231 cell lines compared to their respective cultures of adherent cells (Fig. 1, M and N). SMAR1 expression further declined in secondary spheres (fig. S1, I and J). This correlates with our hypothesis that SMAR1 decreases with increasing stemness. When these secondary spheres were redifferentiated by culturing them in 10% serum-containing complete media, an increase in the percentage of SMAR1+ cells was observed (Fig. 1O, left), coincident with significantly decreased expression of Oct4, Sox2, and Nanog (Fig. 1O, middle) and restored/augmented expression of the differentiation marker cytokeratin 18 (CK18) (Fig. 1O, right).
We also further characterized the CSCs by comparing different cell cycle stages of adherent cells with secondary spheres as a measure of cellular quiescence, a signature of CSCs. It is well established that CSCs are maintained in a poised, quiescent state characterized by slow cell cycling that confers them resistance to cytotoxic drugs (19, 20). Supporting our hypothesis, secondary spheres showed significantly higher percentages of G0-G1 population than the adherent cells (fig. S2A). When NSCCs were transfected with Oct4 and Sox2 complementary DNA (cDNA) plasmids, there was an enhancement of the G0-G1 population (fig. S2B), indicating enrichment of CSC-like properties in them and thus supporting the contribution of these two pluripotency markers in the maintenance of stemness.
We next transfected control or Oct4 and Sox2 cDNA into MDA-MB-468 cells and, 24 hours afterward, performed sphere formation assays. On the 10th day of sphere formation, the transfected set showed greater quiescence per measurement of the G0-G1 cell populations (fig. S2C). The G0-G1 population of the control set gradually increased over 12th to14th day, and the control set reached about the same level of quiescence as the transfected set on the 14th day (which was also the time required for secondary sphere formation) (fig. S2C), indicating that Oct4 and Sox2 transfection increased stemness character, thus expediting sphere formation.
Apart from these, to further validate the CSCs, we also evaluated the level of reactive oxygen species (ROS) in adherent cells versus secondary spheres by 2,7dichlorofluorescein diacetate (DCFDA) assay, as it is already well reported by various previous studies that CSCs display low ROS level (21, 22). Our results showed significantly lower expression of ROS in secondary spheres as compared to the adherent cells (fig. S2D).
Furthermore, we compared the tumor formation potential of MDA-MB-468 cells and secondary spheres in BALB/c athymic nude mice. In line with the reports that CSCs have higher ability than NSCCs in forming a tumor (23), after 30 days of tumor inoculation, mice inoculated with secondary spheres showed greater tumor volume and weight than the mice inoculated with cells (fig. S2E). Together, these results provide support of the stem-like nature of the cells used and further validate our hypothesis that SMAR1 is repressed in breast CSCs.
The above results showing the low expression of SMAR1 in CSCs raised the possibility of SMAR1 having an anti-CSC role. Previous findings from our group and others have established that the CSCs are resistant to conventional chemotherapy (3). Considering all these, we next aimed at exploring the role of SMAR1, if any, in drug resistance of CSCs.
Although the chemotherapeutic drug doxorubicin failed to induce apoptosis in breast cancer stem cellenriched secondary spheres derived from MCF-7 and MDA-MB-468 cell line, it could do so in SMAR1-overexpressed ones (Fig. 2A). This led us to hypothesize that SMAR1 might have the ability to sensitize CSCs by altering their chemo-resistance. To confirm our hypothesis, we transfected the secondary spheres derived from MCF-7, MDA-MB-468, and MDA-MB-231 cell lines, with SMAR1 overexpression plasmid (SMAR1 cDNA). Overexpression of SMAR1 in these spheres led to a significant decrease in both mRNA (Fig. 2B) and protein levels (Fig. 2C) of ATP-binding cassette super-family G member 2 (ABCG2), one of the most crucial drivers of breast CSC drug resistance. However, there was no significant change in the expression levels of multidrug resistance-associated protein 1 (MRP1) and multidrug resistance protein 1 (MDR1) (fig. S3A), two other important drug resistance pumps following SMAR1 overexpression. Likewise, augmentation of SMAR1 also led to a significant decrease in the ABCG2+ cell population in the secondary spheres (fig. S3B). In addition, when the pure CSCs (sorted as CD44+/24/low from secondary spheres) were transfected with SMAR1 cDNA, the ABCG2 expression within them was considerably declined (fig. S3C).
(A) Bar diagram depicting percentage of apoptosis after SMAR1 cDNA transfection and doxorubicin treatment in MCF-7 and MDA-MB-468 secondary spheres as analyzed by flow cytometry (n = 3 biological replicates). (B) RelativeABCG2 mRNA expression quantified by real-time PCR in MCF-7, MDA-MB-468, and MDA-MB-231 secondary spheres after SMAR1 cDNA transfection (n = 3 biological replicates). (C) Western blot displaying ABCG2 expression after SMAR1 cDNA transfection in MCF-7, MDA-MB-231, and MDA-MB-468 secondary spheres (n = 3 independent experiments). Transfection efficiency was determined also by Western blotting for SMAR1 and GFP. (D) The relative ABCG2 mRNA expression was determined after knock-down of SMAR1 using shRNA in MCF-7, MDA-MB-468, and MDA-MB-231 adherent cells by real-time PCR (n = 3 biological replicates). (E) Western blot depicting changes in ABCG2 level in MCF-7 and MDA-MB-468 adherent cells after SMAR1 shRNA transfection (n = 3 independent experiments). Knockdown efficiency of SMAR1 shRNA is shown. (F) t-SNE plot of SMAR1 and ABCG2 obtained from R2 database (using the tumor breast invasive carcinoma-TCGA-1097 dataset). (G) Correlation plot between SMAR1 and ABCG2 as obtained from R2 database using the same dataset; R = 0.252, P = 2.09 1017. (H) Bar diagram depicting the fold change of SMAR1 binding on ABCG2 promoter as determined by ChIP assay and real-time PCR in MCF-7, MDA-MB-468, and MDA-MB-231 adherent cells and secondary spheres (n = 3 biological replicates). (I) Semiquantitative PCR depicting the changes in binding of SMAR1 on ABCG2 promoter after SMAR1 cDNA transfection in MCF-7 secondary spheres, as determined by ChIP assay. (n = 3 biological replicates). (J) In silico docking of SMAR1 on the target region of ABCG2 promoter by HDOCK. Data are mean SD or representative of three independent experiments unless otherwise noted. ***P < 0.001 and ****P < 0.0001 by ordinary one-way ANOVA (A) or by Mann-Whitney U test (B, D, and H).
In contrast, knocking down SMAR1 expression in these cell lines using short hairpin RNA (shRNA) led to enhancement of ABCG2 expression to a heightened extent as determined by real-time PCR (Fig. 2D) and Western blot (Fig. 2E), but no change was observed for MRP1 and MDR1 (fig. S3D). This indicates that SMAR1 may be acting as an inhibitor of ABCG2 but not of MRP1 and MDR1. When we screened the secondary spheres of MCF-7 and MDA-MB-468 for the expression of these three drug resistance pumps, the secondary spheres derived from both these cell lines showed a significantly higher percentage of ABCG2+ cell population than MRP1 and MDR1 (fig. S3E), indicating that ABCG2 might serve as the most crucial contributor of drug resistance in breast cancer. When the expression of ABCG2 was knocked down in the secondary spheres, a significant rise in apoptosis was seen after doxorubicin treatment (fig. S3F), indicating the significance of ABCG2 in breast cancer stem cell chemoresistance and the hint that SMAR1 might serve as a repressor of ABCG2 fascinated us. Moreover, comparing the in silico R2 databasederived t-SNE plot for ABCG2 with the previously derived SMAR1 t-SNE plot (as shown in Fig. 1J) showed that the patients showing higher expression of SMAR1 displayed lower ABCG2 level, which further strengthened our hypothesis (Fig. 2F). In addition, in silico correlation plot of SMAR1 and ABCG2 displayed a significant negative correlation (R = 0.252; Fig. 2G).
Next, in an effort to identify a potential binding site of SMAR1 on ABCG2 promoter, we obtained 2000 to +100base pair (bp)long ABCG2 promoter sequence from the eukaryotic promoter database and scrutinized it using the Genomatix SMARTest (www.genomatix.de). A 405-bp spanning putative S/MAR was identified at 1149 to 745 upstream of the transcription start site on ABCG2 promoter. Overlapping primer pairs were designed against the predicted S/MAR, and chromatin immunoprecipitation (ChIP) assay was performed to validate the binding of SMAR1 on this putative S/MAR. The results revealed SMAR1 binding on the ABCG2 promoter (Fig. 2H) at the site of primer pair 2 in all the three cell lines MCF-7, MDA-MB-231, and MDA-MB-468. Moreover, the binding of SMAR1 was significantly lesser in the secondary spheres than their corresponding adherent cell lines (Fig. 2H). In addition, when these secondary spheres were transfected with the SMAR1 overexpression plasmid, a significant rise in the SMAR1 binding to the given region on ABCG2 promoter was recorded (Fig. 2I). These data come in line with our previous observation that rise in SMAR1 expression leads to significant attenuation of ABCG2 expression as described in Fig. 2 (B and C). We also performed in silico docking experiments to visualize the binding of SMAR1 on ABCG2 promoter using HDOCK server. The docking results showed that SMAR1 binds to the ABCG2 promoter using the interactions with DNA backbone, although it shows preference to the major groove of the DNA (Fig. 2J and fig. S3G). These results validated that SMAR1 represses drug efflux pump ABCG2, thus raising the possibility of sensitizing drug-resistant CSCs by augmenting SMAR1.
Reports indicate that SMAR1 recruits various histone deacetylases (HDACs) to the promoters of target genes to facilitate histone deacetylation and chromatin condensation which ultimately leads to the repression of the target gene (8, 24). To unveil the mechanism underlying SMAR1-induced repression of ABCG2, we subsequently aimed at identifying the type of HDAC, if any, recruited by SMAR1 on ABCG2 promoter. To that end, ChIP assays were performed using the major class I HDACs, among which HDAC2 was found to be binding along with SMAR1 on the given region of ABCG2 promoter. Furthermore, when these secondary spheres were transfected with SMAR1 overexpression construct, the binding of HDAC2 was significantly enhanced, suggesting that SMAR1 recruits HDAC2 to the promoter (Fig. 3A). Protein coimmunoprecipitation (CoIP) assay further proved physical interaction between SMAR1 and HDAC2 (Fig. 3B), and the association increased when SMAR1 was overexpressed in the secondary spheres, hence supporting the above findings (Fig. 3B). One of the major histone moieties deacetylated by HDACs is H3 lysine 9 (H3K9), which otherwise remains acetylated in active chromatins and deacetylation of which leads to chromatin condensation and repression of transcription (25). The S/MAR region of ABCG2 promoter showed a higher extent of H3K9 acetylation in secondary spheres derived from both MCF-7 and MDA-MB-468 cell lines than their adherent counterparts (Fig. 3C), indicating a more active chromatin signature of ABCG2 in CSCs that confer them high chemotherapy resistance. Transfection of SMAR1 cDNA in these secondary spheres led to a significant decline in H3K9 acetylation indicating possible deacetylation of the moiety by HDAC2 due to presence of SMAR1 (Fig. 3D). Treating the SMAR1 cDNAtransfected secondary spheres with potent class I HDAC inhibitors, either trichostatin A (TSA) (26) or sodium butyrate (NaBu) (27), rescued H3K9 from deacetylation, thereby resulting in an increase in the acetylation of H3K9 in these HDAC inhibitortreated SMAR-overexpressed secondary spheres than the untreated SMAR1-overexpressed ones (Fig. 3E).
(A) Bar diagram depicting the relative binding of HDAC2 on SMAR1 binding region of ABCG2 promoter after SMAR1 cDNA transfection in MCF-7 and MDA-MB-468 secondary spheres, as determined by ChIP assay and real-time PCR (left). Semiquantitative PCR data of HDAC2 binding on ABCG2 promoter in the same sample set (middle). The transfection efficiency of SMAR1 cDNA plasmid (right) (n = 3 biological replicates). (B) Coimmunoprecipitation assay showing physical association of SMAR1 with HDAC2. SMAR1 was immunoprecipitated from cell lysates of control and SMAR1 cDNA transfected MCF-7 and MDA-MB-468 secondary spheres. Western blot was done to detect both SMAR1 and HDAC2. Input represents whole cell lysates, (n = 3 independent experiments). (C) ChIP assay followed by real-time PCR was performed to determine the acetylation of H3K9 (AcH3K9) in the SMAR1 binding region of ABCG2 promoter in MCF-7 and MDA-MB-468 adherent cells and secondary spheres (n = 3 biological replicates). (D) ChIP assay followed by real-time PCR was performed to determine the change in AcH3K9 level on SMAR1 binding region of ABCG2 promoter after SMAR1 cDNA transfection in MCF-7 and MDA-MB-468 secondary spheres (n = 3 biological replicates). (E) Real-time PCR was performed to detect the fold change of AcH3K9 ChIP on ABCG2 promoter after SMAR1 cDNA transfection and trichostatin A (TSA)/sodium butyrate (NaBu) treatment in MCF-7 secondary spheres (n = 3 biological replicates). (F) Bar diagram depicting relative fold change of AcH3K9 ChIP on ABCG2 promoter after SMAR1 cDNA transfection, SMAR1 cDNA + HDAC2 siRNA transfection, and SMAR1 cDNA transfection + romidepsin treatment in MCF-7 secondary spheres as detected by real-time PCR (n = 3 biological replicates). (G) Western blot assessing the changes in expression of ABCG2 and AcH3K9 in control, SMAR1 cDNAtransfected, SMAR1 cDNA + HDAC2 siRNAtransfected, and SMAR1 cDNAtransfected + romidepsin-treated MCF-7 secondary spheres (n = 3 independent experiments). (H) Western blot data showing changes ABCG2 and AcH3K9 level in MCF-7 and MDA-MB-468 secondary spheres after SMAR1 cDNA transfection and TSA treatment (n = 3 independent experiments). (I) In silico docking of SMAR1-HDAC2 on target region of ABCG2 promoter. (J) Diagrammatic representation of ABCG2 promoter deacetylation via HDAC2 recruitment by SMAR1. Data are mean SD or representative of three independent experiments unless otherwise noted. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001 by Mann-Whitney U test (A, C, and D) or by Kruskal-Wallis test followed by Dunns multiple comparisons post hoc test (E and F).
Moreover, we used HDAC2 small interfering RNA (siRNA) to specifically knock down HDAC2 or used HDAC2 inhibitor romidepsin, which specifically inhibits HDAC2 (and also HDAC1) without affecting other class I HDACs (28, 29) and is reported to be more potent than both TSA and NaBu (30). In line with the data in Fig. 3E, the HDAC2 siRNAtransfected or romidepsin-treated SMAR1-overexpressed secondary spheres showed significantly higher acetylation of H3K9, reconfirming our hypothesis (Fig. 3F and fig. S4A). In HDAC2 siRNAtransfected or romidepsin-treated sets, SMAR1, although overexpressed, failed to repress ABCG2 expression, thus confirming the contribution of HDAC2 in SMAR1-mediated repression of ABCG2 (Fig. 3G and fig. S4A). TSA-treated SMAR1-overexpressed secondary spheres furnished similar result where inhibition of HDAC2 led to failure of ABCG2 repression by SMAR1 (Fig. 3H). Furthermore, the level of acetylated H3K9 (AcH3K9) was higher in HDAC2-inhibited SMAR1-overexpressed spheres than the untreated SMAR1-overexpressed ones (Fig. 3, G and H).
The in silico docking (Fig. 3I) of SMAR1 with HDAC2 revealed that HDAC2 docks onto SMAR1 majorly using its N-terminal domain. The major interaction with the ABCG2 promoter is caused by SMAR1 protein by its residues 327 to 333. Residues 282 to 286 and 292 to 293 are buried into the major groove of the promoter showing significant baseamino acid interactions. The results thus far support our hypothesis that SMAR1 uses HDAC2 to repress ABCG2 transcription (Fig. 3J) and suggests that augmenting SMAR1 expression in CSCs may prove to be a CSC-sensitizing approach.
To delineate the mechanism underlying SMAR1 repression in CSCs, we analyzed the SMAR1 promoter for predicted binding sites of various transcription factors. The SMAR1 promoter sequence (2000 to +100 bp) was obtained from the eukaryotic promoter database and scrutinized using the promoter analyzing tool JASPAR (http://jaspar.genereg.net/). The screening revealed a putative Oct4-Sox2 joint binding domain on SMAR1 promoter at 604 to 590 bp with a binding score of 11.785 and relative score 0.844, indicating a strong possibility of binding (Fig. 4A). Given that Oct4 and Sox2 are two of the most crucial drivers of stemness and pluripotency of embryonic stem cells and CSCs (31, 32), and our previous observation that overexpression of Oct4 and Sox2 led to enhanced stemness phenotype and expedited sphere formation of adherent breast cancer cells (fig. S2, B and C), abovementioned prediction indicates that they might be the master contributors toward the reduced expression of SMAR1 in breast CSCs.
(A) Diagrammatic representation of Oct4-Sox2 complex binding on SMAR1 promoter. (B) Bar diagram depicting relative SMAR1 mRNA expression after Oct4 cDNA or Sox2 cDNA transfection in MCF-7, MDA-MB-468, and MDA-MB-231 adherent cells (left). The transfection efficiency of Oct4 cDNA and Sox2 cDNA was checked by real time (n = 3 biological replicates) (middle and right). (C) Western blot assessing the change in expression of SMAR1 in Oct4 cDNA and Sox2 cDNAtransfected MCF-7 adherent cells. (n = 3 independent experiments). Transfection efficiency was determined by Western blot. (D) Western blot depicting the changes in SMAR1 level after Oct4 and Sox2 knockdown using shRNA in MCF-7 secondary spheres. (n = 3 independent experiments) Knockdown efficiency was confirmed also by Western blot. (E) Expression of SMAR1 was assessed by Western blot in control and different treatment conditions such as Oct4 cDNAtransfected, Sox2 cDNAtransfected, Oct4 shRNA + Sox2 cDNAtransfected, Sox2 shRNA + Oct4 cDNAtransfected MCF-7 adherent cells. (n = 3 independent experiments). (F) In silico docking of Oct4-Sox2 complex on target region of SMAR1 promoter. (G) ChIP assay followed by semiquantitative PCR displaying the binding of Oct4 and Sox2 on target region of SMAR1 promoter in MCF-7 secondary spheres (n = 3 biological replicates). (H) ChIP assay depicting the changes in binding of Oct4 and Sox2 on SMAR1 promoter after knockdown of either Oct4 or Sox2 in MCF-7 secondary spheres as determined by real-time PCR (n = 3 biological replicates). The knockdown efficiency of Oct4 and Sox2 shRNA was determined by Western blot (inset). (I) Representative semiquantitative PCR data of the same sample set (n = 3 biological replicates). (J) Diagrammatic representation of SMAR1 repression by Oct4-Sox2 complex. Data are mean SD or representative of three independent experiments unless otherwise mentioned. *P < 0.05, **P < 0.01, and ***P < 0.001 by Mann-Whitney U test [(B), middle, right] or by Kruskal-Wallis test followed by Dunns multiple comparisons post hoc test [(B), left; (H)].
To validate the above indications, first, we transfected MCF-7, MDA-MB-468, and MDA-MB-231 adherent cells with Oct4 and Sox2 cDNA plasmids and examined the expression of SMAR1 by real-time PCR. Overexpression of Oct4 and Sox2 in these cell lines led to significant reduction in SMAR1 mRNA expression, confirming Oct4- and Sox2-dependent repression of SMAR1 at the point of transcription (Fig. 4B). We confirmed a decrease at the protein level as well by Western blotting analysis (Fig. 4C). In contrast, knocking down Oct4 and Sox2 by shRNAs in the secondary spheres resulted in a considerable rise in SMAR1 expression (Fig. 4D). To determine whether Oct4 and Sox2 are individually capable of repressing SMAR1, we knocked down either Oct4 or Sox2 using shRNA while overexpressing the other. In both scenarios (Oct4 shRNA + Sox2 cDNA and Sox2 shRNA + Oct4 cDNA), the decrease in SMAR1 expression was hindered, indicating that both Oct4 and Sox2 are necessary for the inhibition of SMAR1 transcription in breast CSCs (Fig. 4E).
The results, so far, strengthened our hypothesis that CSCs inherently repress SMAR1 expression and that Oct4 and Sox2 serve as the critical inhibitors of SMAR1 expression in CSCs. We next performed in silico docking experiments to visualize the binding of the proposed Oct4-Sox2 complex on the SMAR1 promoter. Docking of Oct4-Sox2 complex with the SMAR1 promoter (Fig. 4F) revealed that Oct4 binds to the minor groove of DNA with residues from 337 to 341 and to major groove with residues from 302 to 307. Sox2 binds to the phosphate backbone of the SMAR1 promoter with its two Lys58 and Lys66 residues. To validate the promoter binding prediction from JASPAR, ChIP assay was performed in MCF-7 secondary spheres with primer pairs designed against the putative Oct4-Sox2 complex binding site on SMAR1 promoter. The result showed binding of both Oct4 and Sox2 on the predicted region of the SMAR1 promoter (Fig. 4G).
Next, to validate whether the formation of Oct4-Sox2 complex is crucial for the transcriptional inhibition of SMAR1, we knocked down Oct4 by shRNA in secondary spheres, which led to significantly reduced binding Sox2 to the predicted site on SMAR1 promoter. Likewise, knocking down Sox2 decreased Oct4 binding to the SMAR1 promoter to a significant extent (Fig. 4, H and I). As mentioned previously, the expression of SMAR1 was greatly enhanced in both the Oct4 shRNA and Sox2 shRNAtransfected sets (Fig. 4D). These results validated the requirement of Oct4-Sox2 complex formation to bind to SMAR1 promoter and repress its transcription. The findings so far support the hypothesis that Oct4 and Sox2, two crucial pluripotency factors, jointly attenuate the expression of SMAR1 in CSCs as an escape strategy against the chemosensitivity role of SMAR1 (Fig. 4J).
Oct4 and Sox2 are reported to recruit various coactivator or corepressor complexes to regulate the expression of their target genes (33, 34). Previous reports have already established the involvement of HDACs and polycomb repressor complexes (PRCs) in Oct4-, Sox2-, and Nanog-mediated gene repression (35, 36). To find the epigenetic modifiers used by Oct4-Sox2 complex to repress SMAR1, we performed ChIP assays using various HDACs and PRC proteins in secondary spheres derived from MCF-7 and MDA-MB-468 cells. Our results revealed the binding of HDAC1 along with Oct4 and Sox2 on the predicted region of the SMAR1 promoter (Fig. 5A). When Oct4 and Sox2 were knocked down, a significant decline in HDAC1 binding to the predicted promoter region was observed (Fig. 5B), indicating that Oct4 and Sox2 may serve as HDAC1 recruiters in the secondary spheres. Similarly, CoIP experiments showed a physical interaction between Oct4, Sox2, and HDAC1 in these secondary spheres (Fig. 5C). As described above, overexpression of Oct4 and Sox2 in the adherent cells leads to a decline in SMAR1 expression (Fig. 4B); however, when these Oct4 + Sox2overexpressed cells were treated with class I HDAC inhibitors TSA or NaBu, Oct4 and Sox2 failed to repress SMAR1 expression (Fig. 5D).
(A) Binding of HDAC1 along with Oct4 and Sox2 on SMAR1 promoter assessed by ChIP and ChIP-re-ChIP assays in MCF-7 and MDA-MB-468 secondary spheres. Primer pair specific for Oct4-Sox2 binding site on SMAR1 promoter was used (n = 3 independent experiments). (B) Bar diagrams depicting changes in binding of HDAC1 on SMAR1 promoter after Oct4 and Sox2 knockdown using shRNA, as determined by ChIP and real-time PCR in MCF-7 secondary spheres (n = 3 biological replicates). Knockdown efficiency of Oct4 and sox2 shRNA was determined using Western blot. Data are mean SD or representative of three independent experiments unless otherwise mentioned. **P < 0.01 and ***P < 0.001 by Kruskal-Wallis test followed by Dunns multiple comparisons post hoc test. (C) CoIP with Western blotting to assess physical association between Oct4, Sox2, and HDAC1 immunoprecipitated from cell lysates of MCF-7 secondary spheres (n = 3 independent experiments). (D) Western blotting to assess SMAR1 expression in MCF7 adherent cells after Oct4 cDNA + Sox2 cDNA transfection and TSA/NaBu treatment. The transfection efficiency of Oct4 cDNA and Sox2 cDNA was confirmed also by Western blot (right) (n = 3 independent experiments). (E) Western blotting to evaluate changes in SMAR1 and AcH3K9 levels in control and various conditions, including Oct4 cDNA + Sox2 cDNAtransfected, Oct4 cDNA + Sox2 cDNA + HDAC1 siRNAtransfected, and Oct4 cDNA + Sox2 cDNAtransfected + romidepsin-treated MCF-7 adherent cells. Knockdown efficiency of HDAC1 siRNA was confirmed also by Western blot (n = 3 independent experiments). (F) ChIP assay followed by semiquantitative PCR was performed to assess the changes in AcH3K9 ChIP on Oct4-Sox2 binding site of SMAR1 promoter after Oct4 or Sox2 knockdown in MCF7 secondary spheres (n = 3 independent experiments). (G) Changes in AcH3K9 ChIP on SMAR1 promoter after Oct4 cDNA + Sox2 cDNA transfection and TSA/NaBu treatment in MCF7 adherent cells (n =3 independent experiments). (H) Changes in AcH3K9 ChIP on Oct4-Sox2 binding site of SMAR1 promoter after Oct4 cDNA + Sox2 cDNA transfection and HDAC1 siRNA/romidepsin treatment in MCF-7 adherent cells (n = 3 independent experiments). (I) Protein complex of Oct4, Sox2, and HDAC1 alone (upper) and bound to the target region of the SMAR1 promoter (lower), as derived from in silico docking models. (J) Diagrammatic representation of SMAR1 repression by promoter deacetylation due to HDAC1 recruitment by Oct4 and Sox2. All blots are representative of three independent experiments unless otherwise noted.
Furthemore, we knocked down HDAC1 using siRNA or inhibited it with romidepsin (which inhibits HDAC1 and HDAC2 with greater potency than either TSA or NaBu, as mentioned above with Fig. 3F) (2830) in the Oct4 + Sox2overexpressed adherent cells. In both the HDAC1 siRNA and romidepsin-treated cells, Oct4 and Sox2 failed to repress SMAR1 expression (Fig. 5E), thus supporting the involvement of HDAC1 in Oct4-Sox2mediated repression of SMAR1.
One of the major histone moieties deacetylated by HDAC1 is H3K9 (37). Knocking down Oct4 and Sox2 in secondary spheres led to a significant rise in H3K9 acetylation on the predicted region of SMAR1 promoter (Fig. 5F and fig. S4B). This corresponds to the augmented expression of SMAR1 after Oct4 and Sox2 knockdown as shown in Fig. 4D. Similarly, overexpression of Oct4 + Sox2 in adherent cells led to a decline in H3K9 acetylation on SMAR1 promoter; however, treating the Oct4 + Sox2overexpressed cells with either TSA or NaBu rescued H3K9 from deacetylation (Fig. 5G). Similarly, knocking down HDAC1 using siRNA or inhibiting HDAC1 by romidepsin in Oct4 + Sox2overexpressed adherent cells led to significant rise in AcH3K9 level on SMAR1 promoter (Fig. 5H and fig. S4C), validating the involvement of HDAC1 in Oct4- and Sox2-mediated deacetylation of H3K9 on SMAR1 promoter and its repression. This corresponds to the heightened AcH3K9 levels in HDAC1 siRNAtransfected or romidepsin-treated Oct4 + Sox2overexpressing cells in comparison to the untreated counterparts (Fig. 5E).
Docking of Oct4-Sox2-HDAC1 complex on SMAR1 promoter revealed that Oct4 binds to the major groove of DNA composed of residues 1 to 5 and 25 to 30 and that HDAC1 interacts with both Sox2 and Oct4, wherein Sox2 lodges itself in the groove between the Oct4 and HDAC1 (Fig. 5I), indicating the deacetylation of H3K9 on SMAR1 promoter through HDAC1 by Oct4-Sox2 complex (Fig. 5J). Together, these results unveiled a hitherto unknown role of stemness factors in repressing SMAR1 to bestow drug resistance in CSCs.
The above findings bring us closer to our objective of targeting the therapy-resistant CSCs by augmentation of SMAR1. Because these results support the candidature of Oct4 and Sox2 in repressing SMAR1 in CSCs, they might be a suitable target for enhancing SMAR1 and, thus, sensitizing CSCs. Our search of the existing literature to find natural and synthetic compounds that might inhibit Oct4 and Sox2 to augment that of SMAR1 expression suggested the candidature of aspirin. Some studies have reported that aspirin is an inhibitor of stemness and pluripotency-related gene expression (3840), and this common, over-the-counter drug reportedly inhibits chemotherapy-induced increases in CSC numbers and sensitizes these typically drug-resistant cells (3). Therefore, we explored its effect on SMAR1. Real-time PCR analysis showed that treating CSC-enriched secondary spheres of human breast cancer cells with aspirin (3) led to a significant rise in SMAR1 mRNA levels (Fig. 6A) and a significant decline in those of Oct4 and Sox2 mRNA (Fig. 6B), whereas Western blotting showed a decline in ABCG2 and an increase in SMAR1 protein level after aspirin treatment (Fig. 6C). Flow cytometric analysis of control versus aspirin-treated secondary spheres depicted a significant rise in the number of SMAR1+ cells along with a decline in that of Oct4+ and Sox2+ cells (Fig. 6D). ChIP assays further revealed a significantly lower binding of Oct4 and Sox2 on the target region of the SMAR1 promoter in aspirin-treated secondary spheres (Fig. 6E, left). Alongside the rise in SMAR1 expression described above (Fig. 6A), aspirin-treated secondary spheres showed a greater binding of SMAR1 on the ABCG2 promoter (Fig. 6E, right).
(A) Bar diagram depicting real-time PCR data assessing relative SMAR1 mRNA expression in control and aspirin-treated MDA-MB-468 and MCF-7 secondary spheres (n = 3 biological replicates). (B) Real-time PCR data showing relative Oct4 and Sox2 mRNA expression in control and aspirin-treated MCF-7 secondary spheres (n = 3 biological replicates). (C) Western blot displaying SMAR1 and ABCG2 expression in control and aspirin-treated MDA-MB-468 and MCF-7 secondary spheres (n = 3 independent experiments). (D) Bar diagram showing flow cytometry data depicting % Oct4+, % Sox2+, and % SMAR1+ cells in MDA-MB-468 and MCF-7 secondary spheres after aspirin treatment (n = 3 biological replicates). (E) ChIP assay followed by real-time PCR depicting the alternation in binding of Oct4 and Sox2 on SMAR1 promoter (left) and SMAR1 on ABCG2 promoter (right) after aspirin treatment in MCF-7 secondary spheres (n = 3 biological replicates). (F) Western blot displaying SMAR1 level in control, Oct4 cDNA + Sox2 cDNAtransfected, aspirin-treated, and Oct4 cDNA + Sox2 cDNAtransfected + aspirin-treated MCF-7 secondary spheres (n = 3 independent experiments). (G) Western blot and densitometric quantification showing relative SMAR1 expression in control, aspirin-treated, HDAC1 cDNAtransfected, and HDAC1cDNAtransfected + aspirin-treated MCF-7 secondary spheres (n = 3 independent experiments). (H) Bar diagram displaying changes in HDAC2 ChIP on SMAR1 binding region of ABCG2 promoter after aspirin treatment in MCF-7 secondary spheres, as determined by real-time PCR. (n = 3 biological replicates). (I) Western blot displaying ABCG2 level in control, aspirin-treated, SMAR1 shRNAtransfected, and SMAR1 shRNAtransfected + aspirin-treated MCF-7 secondary spheres (n = 3 independent experiments). (J) Western blot displaying ABCG2 expression in control, aspirin-treated, HDAC2 siRNAtransfected, and HDAC2 siRNAtransfected + aspirin-treated MCF-7 secondary spheres (n = 3 independent experiments). (K) Bar diagram displaying the percentage of apoptosis in MDA-MB-468 and MCF-7 secondary spheres after doxorubicin (Dox), aspirin, and aspirin + Dox treatment (n = 3 independent experiments). (L) Bar diagram depicting the changes in percentage of apoptosis in control, aspirin + Doxtreated and Oct4 cDNA + Sox2 cDNAtransfected + aspirin + Doxtreated MDA-MB-468 and MCF-7 secondary spheres (n = 3 independent experiments). (M) Bar diagrams displaying changes in percentage of apoptosis in control, aspirin + Doxtreated, ABCG2 cDNAtransfected + aspirin + Doxtreated, HDAC2 siRNAtransfected + aspirin + Doxtreated MDA-MB-468 and MCF-7 secondary spheres (n = 3 independent experiments). Data are mean SD or representative of three independent experiments unless otherwise noted. N.S., P > 0.05; *P < 0.05; **P < 0.01; ***P < 0.001; and ****P < 0.0001 by Mann-Whitney U test (A, B, E, and H), by unpaired t test (D), by Kruskal-Wallis test along with Dunns multiple comparison post hoc test (G), or by ordinary one-way ANOVA alone (K) and with Dunnetts multiple comparison post hoc test (L and M).
In secondary spheres that were transfected to overexpress Oct4 and Sox2, aspirin failed to enhance SMAR1 expression (Fig. 6F and fig. S4D), suggesting that aspirin augments SMAR1 in CSCs by repressing the expression of its major transcriptional attenuators. Next, to validate the involvement of HDAC1 in this axis, we overexpressed HDAC1 then treated the secondary spheres with aspirin. Our results revealed that while aspirin alone could significantly enhance SMAR1 expression, it failed to do so in HDAC1-overexpressed secondary spheres (Fig. 6G and fig. S4E). These data corroborate the inhibition of Oct4-Sox2-HDAC1 axis during aspirin-mediated enhancement of SMAR1 expression.
Next, we proceeded to determine the effect of aspirin on SMAR1-HDAC2 axis, which ultimately may lead to ABCG2 repression. Our results have already furnished that aspirin increases the binding of SMAR1 on ABCG2 promoter (as shown in Fig. 6E, right). Next, our ChIP data revealed that aspirin treatment significantly increased HDAC2 binding to the ABCG2 promoter (Fig. 6H). Furthermore, while aspirin alone could repress ABCG2 expression, in the presence of SMAR1 shRNAmeaning less SMAR1 (fig. S4F)it did not (Fig. 6I), indicating the requirement of SMAR1 in aspirin-mediated ABCG2 repression. Similarly, when HDAC2 was knocked down (fig. S4G), aspirin did not reduce ABCG2 expression, confirming the requirement of HDAC2 in the aspirin-SMAR1 mechanism (Fig. 6J).
Furthermore, aspirin-treated secondary spheres underwent significant apoptosis upon treatment with doxorubicin, to which these cells were otherwise resistant (Fig. 6K). Here again, there was a significant reduction in the percentage of apoptotic cells after Oct4 + Sox2 overexpression before aspirin + doxorubicin treatment (Fig. 6L). When ABCG2 was overexpressed or HDAC2 was knocked down during aspirin + doxorubicin treatment (fig. S4H), the amount of apoptosis significantly declined (Fig. 6M). These results indicate that the effect of aspirin in hindering CSC survival is through repressing drug resistance pumps like ABCG2 through enhancement of a SMAR1-HDAC2 axis. Together, the results indicate the potential of aspirin as a two-pronged attack in sensitizing CSCs toward chemotherapeutic drug doxorubicin by attenuating the stemness factors Oct4 and Sox2 and augmenting SMAR1 to ultimately regress ABCG2.
Last, we validated the above in vitro results in vivo using BALB/c mice inoculated orthotopically with 4T1-derived spheres into the mammary fat pad. After 7 days of tumor inoculation, the mice were subjected to intraperitoneal injection of aspirin and doxorubicin, each alone or in combination, every alternate day up to 2 weeks (Fig. 7A). Our results depict that, when treated alone, aspirin failed to make much difference in tumor size when compared with control ones (Fig. 7, B and C). However, aspirin treatment resulted in a significant rise in SMAR1 expression, as determined by Western blot (Fig. 7D). Furthermore, in comparison to tumors from control mice, those from aspirin-treated mice had significantly lower Oct4, Sox2, and ABCG2 expression and greater SMAR1 expression (Fig. 7E), as determined by real-time PCR. The expression of SMAR1 was attenuated in tumors from mice treated with doxorubicin alone; however, combining doxorubicin with aspirin resulted in an increase in SMAR1 expression (Fig. 7, D and E). Likewise, the expression of Oct4, Sox2, and ABCG2, which were augmented upon treatment with doxorubicin alone, showed a stark decline in tumors from dual-treated mice (Fig. 7E), together suggesting that aspirin may counter the CSC-associated effects of doxorubicin. Moreover, the dual-treated mice displayed the greatest reduction in tumor size among the four groups (Fig. 7, B and C). These results are in line with a previous report (3) from our laboratory that aspirin enhances the magnitude of CSC apoptosis after treatment with doxorubicin. The present work has thus revealed the mechanism behind such sensitization.
(A) Flowchart depicting the scheme of protocol of the animal study. Female BALB/c mice were inoculated with 4T1 spheres. From the seventh day after tumor inoculation, aspirin (100 mg/kg), doxorubicin (Dox) (5 mg/kg), or aspirin (100 mg/kg) + Dox (5 mg/kg) was given intraperitoneally every alternate day up to 2 weeks (n = 5 for each group). After treatment, the mice were sacrificed, tumor volume was measured, and tumor tissue was collected. (B) Representative images of the tumors of each group. (C) Scatter plots depicting the tumor volume (cm3) in control, aspirin-treated, Dox-treated, and aspirin + Doxtreated mice. (D) Western blot data and densitometry showing SMAR1 expression in control, aspirin-treated, Dox-treated, and aspirin + Doxtreated mice tumor tissues. (E) Bar diagrams displaying real-time PCR data performed to assess the changes in expression of Oct4, Sox2, SMAR1, and ABCG2 in control, aspirin-treated, Dox-treated, and aspirin + Doxtreated mice tumor tissues. Data are mean SD or representative of five independent biological replicates. N.S., P > 0.05; *P < 0.05; **P < 0.01; ***P < 0.001; and ****P < 0.0001 by ordinary one-way ANOVA with Dunnetts multiple comparison post hoc test (C), by Kruskal-Wallis test alone (E), and with Dunns multiple comparison post hoc test (D).
Drug resistance and frequent occurrences of relapse are the major hurdles in anticancer therapies(41). CSCs not only play a pivotal role in drug-resistant phenotype of the tumors but also are practically nontargetable, leading to recurrence of the tumor and, in many cases, fatality of the patient (42, 43). Therefore, sensitizing CSCs may increase the success of cancer therapy. CSCs show high expression of a variety of oncogenes that drive the hallmarks of cancer. Oct4, Sox2, Nanog, and ALDH1the core regulators of stemness or pluripotencyare augmented in CSCs(44), so are the various drug efflux pumps like ABCG2, MRP1, and MDR1 (45). To specifically target CSCs, the intricate signaling networks that are essential for driving the CSC function and phenotype thus need to be unraveled.
SMAR1, previously known to function in chromatin remodeling, tissue-specific gene regulation, and tissue-specific metabolism (46), has been shown to induce tumor regression (47), and a diminished expression of SMAR1 is frequently associated with poor prognosis of various cancers (9). This protein not only serves as a attenuator of tumor proliferation and metastasis but also is an inducer of p53-mediated apoptosis (9). Its role as a repressor of cyclin D1, Slug, and the Wnt/-catenin pathway supports its antitumor role (8, 10). In more advance cancer stages, expression of SMAR1 is markedly reduced (9), suggesting that SMAR1 is negatively correlated with tumor aggression, a feature driven in part by CSCs. Given that CSCs are reportedly adept at escaping or repressing various tumor suppressor factors to ensure their survival, we thought it is highly plausible that CSCs might also hinder SMAR1 functions.
Thus, we aimed at unveiling its role in breast CSCs specifically in the context of drug resistance. CSCs isolated from tumors of multiple breast cancer patients and mice showed reduced expression of SMAR1 compared with isolated nonstem-like cancer cells. Nakka et al. (14) have also reported that SMAR1-depleted MCF-7 cells have increased CD44 variant exon inclusion and a greater metastatic propensity in mice. Considering that breast CSCs express CD44 as one of their major surface markers (48, 49), their report is not only aligned with our results but also strengthens the possibility of existence of an inverse relationship between SMAR1 and stemness and thus of SMAR1 having some anti-CSC role. Further to a previous report from our laboratory showing that CSC-enriched spheres were insensitive to doxorubicin due to their abundant expression of the drug efflux pumps ABCG2, MDR1, MRP1, and others (50), here we found that doxorubicin could induce apoptosis in CSCs when they overexpressed SMAR1. We also found that the promoter of one of the aforementioned drug resistance pumps, and a reportedly potent one in breast cancer (3, 51), ABCG2, harbors a MAR-binding domain, which mediates SMAR1 binding to its target genes (10). ABCG2 is also crucial for maintaining stem cell proliferation and stem cell phenotypes (52), and its expression is augmented with tumor progression (53). Multiple reports from our laboratory and others had previously established that SMAR1 exerts its inhibitory effect by chromatin condensation and deacetylation of histones through the recruitment of different HDACs (10, 12, 14). These and our results here together suggest that SMAR1 recruits HDAC2 to deacetylate H3K9 on ABCG2 promoter, thereby inhibiting ABCG2 transcription and chemoresistance.
Furthermore, SMAR1 was found to be transcriptionally attenuated in CSCs by co-operative action of stemness markers Oct4 and Sox2, indicating that possibly this mechanism maintains an augmented multidrug resistance feature of CSCs. Oct4 and Sox2 recruit various corepressor complexes, like HDACs and PRC proteins, as an aid of gene regulation. Our experiments also revealed the involvement of HDAC1 along with deacetylation of H3K9 in this case. HDAC1 has already been described as a regulator of embryonic stem cell differentiation that acts in aid with various pluripotency factors (54). Both Oct4 and Sox2 are reported to colocalize with HDAC1, which acts as a mediator of Oct4- and Sox2-derived gene repression that has been previously established (55, 56), further supporting our findings. These findings together indicate that SMAR1 is a modulatory target molecule, enhancing the expression of which sensitizes CSCs by restraining their drug resistance. The anticancer properties of aspirin, including that it inhibits the stemness factors Oct4, Sox2, and Nanog, have been highlighted for some years now (3840). Here, we found that aspirin treatment leads to reduction of Oct4 and Sox2 along with significant augmentation of SMAR1 expression, which epigenetically decreases ABCG2 expression, which may underlie the resulting drug sensitization of otherwise resistant CSCs to the common chemotherapeutic doxorubicin both in vitro and in vivo. Thus, aspirin here acts in two ways, inhibiting tumor stemness and repressing chemoresistance, both through enabling SMAR1 expression. Aspirin might therefore be explored as a way to improve the efficacy of chemotherapy in patients with CSC burdened tumors.
Breast cancer cell lines MCF-7, MDA-MB-468, and MDA-MB-231 were obtained from National Centre for Cell Science, Pune, India. All cell lines were passaged for fewer than 6 months after resuscitation. The cells were routinely maintained in complete RPMI medium at 37C in a humidified incubator containing 5% CO2 as previously described (57). Cells were allowed to reach confluence before use.
For sphere culture, the cells were seeded at 2.5 104 cells per well in six-well Ultra-Low Adherence plates (Corning) in Dulbeccos modified Eagles medium/F12 with bovine insulin (5 g/ml) (Sigma-Aldrich), recombinant epidermal growth factor (20 ng/ml), basic fibroblast growth factor (20 ng/ml), B27 supplement (BD Biosciences), and 0.4% bovine serum albumin (BSA) as previously described (50, 57). Primary spheres were subjected to secondary sphere formation by weekly trypsinization and dissociation followed by reseeding in serum-free media at 2.5 104 cells per well into Ultra-Low Adherence six-well plates.
Healthy secondary spheres were treated with 2.5 mM aspirin (3) (Merck Millipore) for specific experiments. Aspirin, being sparingly soluble in distilled water, 1 M stock solution was prepared in dimethyl sulfoxide (DMSO). For all in vitro assays with aspirin, DMSO was used as control. The secondary spheres were treated with chemotherapeutic agent doxorubicin (2.5 M) (MP Biomedicals) alone or in combination with aspirin for specific experiments (50). TSA (Sigma-Aldrich) and NaBu (Merck Millipore) were used as class I HDAC inhibitors at 2.5 nM and 0.4 mM, respectively (26, 27), for 24 hours. Romidepsin was used at 10 ng/ml for 24 hours as a specific inhibitor of HDAC1 and HDAC2 (29).
For whole cell lysates, cells were homogenized in lysis buffer [20 mM Hepes, (pH7.5), 10 mM KCl, 1.5 mM MgCl2, 1 mM Na-EDTA, and 1 mM dithiothreitol]. All buffers were supplemented with protease inhibitor mixtures (Thermo Fisher Scientific). Protein concentrations were estimated using Lowry method. The lysates containing 50 g of protein were mixed with an equal volume of 2 SDSpolyacrylamide gel electrophoresis (SDS-PAGE) sample buffer, heated at 90C for 2 min, and loaded onto 8 to 15% SDS-PAGE gel (depending on the molecular weight of the protein of interest). An equal amount of protein (50 g) was loaded in each well. For the experiments detecting SMAR1 in control and transfected/treated secondary spheres, in which SMAR1 expression was low, we loaded 80 g of protein in each well. The proteins were transferred to a polyvinylidenedifluoride membrane (Merck Millipore), which was then blocked with 5% nonfat milk in tris-buffered saline containing 0.05% Tween 20 before antibody treatments. The membranes were probed with specific primary antibodies followed by respective HRP-tagged secondary antibodies and visualized by chemiluminescence. The antibodies used are SMAR1 (Bethyl Laboratories), ABCG2 (Novus Biologicals/Santa Cruz Biotechnology), Sox2/ Ac-H3k9/HDAC2/HDAC1/GFP (green fluorescent protein) (Cell Signaling Technology), and Oct4/Sox2 (Santa Cruz Biotechnology). Equivalent protein loading was verified using -actin (Cell Signaling Technology) or -tubulin (Thermo Fisher Scientific). For densitometric analysis of Western blots, the intensity of the protein of interest was normalized to that of a loading control (-actin or -tubulin).
To determine the direct physical interaction between SMAR1 and HDAC2 or Oct4/Sox2 and HDAC1, CoIP experiments were performed. Immune complexes from whole cell lysates were purified using SMAR1 or Oct4/Sox2 antibody and Protein A Sepharose beads (Sigma-Aldrich). The immunopurified proteins were immunoblotted for both protein of interest that coprecipitated (HDAC2/HDAC1) and the protein being pulled down (SMAR1/Oct4/Sox2). The protein of interest was visualized by chemiluminescence.
One microgram of the total RNA, extracted from cells with TRIzol reagent (Ambion) was reverse transcribed using a Verso cDNA Synthesis kit (Thermo Fisher Scientific) and then subjected to either semiquantitative PCR with ExPrime Taq 2x Master Mix (GeNet Bio) using GeneAmp-PCR System 2720 (Applied Biosystems) or real-time PCR using SYBR Green Master mix (Roche) in Roche Light Cycler 96 system. The cDNAs were amplified with the following primers specific for SMAR1 human (forward: 5-GGCCATCCAGATTCAGTGAG-3; reverse: 5-AGCAGGACTCAAACGAAAGG-3), SMAR1 mouse (forward: 5GCATTGAGGCCAAGCTGCAAGCTC-3; reverse: 5-CGGAGTTCAGGG-TGATGAGTGTGAC-3), ABCG2 human (forward: 5-CTTACAGTTCTCAGCAGCTCTTCG-3; reverse: 5-CGAGGCTGATGAATGGAGAAG-3), MRP1 human (forward: 5-ACCATCCACGACCCTAAT-3; reverse: 5CCACCTTGGAACTCTCTTTC-3), MDR1 human (forward: 5-GGAGATAGGCTGG-TTTGATG-3; reverse: 5-GTCCAAGAACAGGACTGATG-3), Oct4 human (forward: 5-GGGCTCTCCCATGCATTCAAAC-3; reverse: 5-CACCTTCCCTCCAACCAGTTGC-3), Oct4 mouse (forward: 5-TCTTTCCACCAGGCCCCCGGCTC-3; reverse: 5-TGCGGGCGGACATGGGGAGATCC-3), Sox2 human (forward: 5-CCATGCAGGTTGACACCGTTG-3; reverse: 5-TCGGCAGACTGATTCAAATAATACAG-3), Sox2 mouse (forward: 5-CCGCGTCAAGAGGCCCATGAA-3; reverse: 5-CCCGCTTCTCGGTCTCGGACAA-3), ABCG2 mouse (forward: 5-TCGCAGAAGGAGATGTGTTGAG-3; reverse: 5-CCAGAATAGCATTAAGGCCAGG-3), -actin (forward: 5-AGGTCATCACCATTGGCAAT-3; reverse: 5-ACTCGTCATACTCCTGCTTG-3), glyceraldehyde-3-phosphate dehydrogenase (GAPDH) human (forward: 5-CCTGCACCACCAACTGCTTA-3reverse: 5-GGCCATCCACAGTCTTCTGGG3), and GAPDH mouse (forward: 5-CATCACTGCCACCCAGAAGACTG-3; reverse: 5-ATGCCAGTGAGCTTCCCGTTCAG-3).
The PCR products of semiquantitative PCR were analyzed by 2% agarose gel electrophoresis. For real-time PCR, relative expression was calculated using Ct method with 2Ct as fold change (58).
ChIP assays were performed using standard protocol of Millipore. PCR assay for identification of SMAR1 binding site on ABCG2 promoter and Oct4 and Sox2 binding on SMAR1 promoter was performed using the following different primer sets: SMAR1 on ABCG2 promoter: (for 5CCGTGCTGGCCTTAATTT-3/Rev. 5ATGATGCGC-CCAAACATT-3); Oct4-Sox2 on SMAR1 promoter: (For 5GGACGCTGACATTTGAGTT-3/Rev. 5GCTCTCCACCTGCTTCTA-3). Extracted DNA was used for either semiquantitative or real-time PCR. The products of semiquantitative PCR were analyzed by 2% agarose gel electrophoresis. The fold change of real-time PCR was calculated using ddCt method(58).
The overexpression constructs of Oct4 (pcDNA 3.3 OCT4, plasmid no. 26816), Sox2 (pSin-EF2-Sox2-Pur, plasmid no. 16577), HDAC1 (HDAC1 Flag, plasmid no. 13820), and the shRNAs against Oct4 (LL-HOCT4i, plasmid no. 12198), and Sox2 (pLKO.1 Sox2 3H b, plasmid no. 26352) were purchased from Addgene. The ABCG2 siRNA (NM_004827), HDAC1 siRNA (NM_004964), and HDAC2 siRNA (NM_001527) were purchased from Sigma-Aldrich. The SMAR1 overexpression plasmid (SMAR1 cDNA) and SMAR1 shRNA were gifts from S. Chattoadhyay (10, 14). The SMAR1 overexpression plasmid produces a GFP-tagged SMAR1 protein that gives a separate band of external SMAR1-GFP when visualized in Western blot (10).
The plasmids and control vectors were introduced into cells and spheres using Lipofectamine-2000 (Invitrogen) according to the protocol provided by the manufacturer. Stably expressing clones were isolated by limiting dilution and selection with puromycin dihydrochloride (1 g/ml; Sigma-Aldrich) or G418 Sulfate (1 mg/ml; Sigma-Aldrich), and the resistant cells were cloned and screened by Western blotting with specific antibodies. The siRNA were transfected using Lipofectamine-2000, and cells were harvested after 34 to 36 hours after which the knockdown efficiency was determined using Western blot.
The cells were fixed in 4% paraformaldehyde, permeabilized in 0.1% Triton X-100, and blocked in blocking buffer [5% BSA in phosphate-buffered saline (PBS)]. Cells were then incubated with 1% BSA containing SMAR1 antibody (Bethyl Laboratories) or ABCG2 antibody (Santa Cruz Biotechnology) overnight at 4C in a humid atmosphere. After washing in PBS, cells were incubated with secondary antibodies conjugated with either Alexa Fluor 546 (red) or Alexa Fluor 488 (green). The 4,6-diamidino-2-phenylindole (DAPI) was used as nuclear stain (blue). Images were acquired using a confocal microscope (Leica) (13).
Primary human breast cancer tissue samples were obtained with informed consents from all patients from the Department of Surgery, IPGMER and SSKM Hospital, Kolkata, India in accordance with the Research Oversight Committee of IPGMER and associated research and analyses were done in Bose Institute, Kolkata, India in accordance with the Institutional Human Ethics Committee (BIHEC/2017-18/5). These tumors were exclusively primary site cancers that had not been treated with either chemotherapy or radiotherapy. For comparison of SMAR1 expression between stage II and stage III tumor tissues, n = 5 samples for each group were collected. SMAR1 expression was detected in these tissues by either immunofluorescence or Western blot. For Western blot, the tissues were first mechanically disaggregated on ice, then homogenized in ice-cold radioimmunoprecipitation assay lysis buffer (Sigma-Aldrich) supplemented with protease inhibitor cocktail (Thermo Fisher Scientific) at 4C. After homogenization, the tissues were centrifuged at 10,000 rpm for 15 to 20 min at 4C, and the supernatant was collected for further Western blot analysis.
To obtain pure CSC and NSCC population, the tissues (n = 4) were subjected to flow cytometric sorting of NSCCs and CSCs. For sorting, the tissues were mechanically disaggregated, digested with collagenase, and filtered through a 30-m filter (42).The CSCs were sorted as CD44+/24 population after staining with allophycocyanin (APC)CD44 and phycoerythrin (PE)-CD24 antibodies (BD Biosciences). The rest of the quadrants (CD44/24, CD44+/24+, and CD44/24+) were sorted as NSCCs. The cells were sorted twice, and the purity of sorted populations was verified by flow cytometry. The sorted CSCs and NSCCs were subjected to further RNA isolation and PCR.
Human and mice tissue samples were dissected out, fixed in Bouins fixative overnight, and cryo-protected, and serial sections were cut on a cryostat (CM1850, Leica) at 4 to 5 m thickness.
For immunohistochemistry, the tissue sections were washed with PBS, antigen retrieval was done with enzymatic retrieval method using trypsin-CaCl2 solution. Sections were blocked with 1% BSA at 37C. Sections were incubated overnight at 4C in a humid atmosphere with primary antibodies against SMAR1 (1:1000; Bethyl Laboratories). The sections were and then incubated with biotinylated anti-rabbit immunoglobulin G followed by peroxidase conjugate ExtrAvidin (1:100; Sigma-Aldrich) for 60 min and 3,3-diaminobenzidine was used as chromogen (1:100; Sigma-Aldrich, AEC101-1KT) to visualize the reaction product and counterstained with hematoxylin (1:1; HiMedia, India). Last, sections were washed in distilled water and mounted in glycerol gelatin. Images were acquired with a bright-field microscope at 20 magnification.
For immunofluorescence, the tissue sections were washed with PBS, antigen retrieval was done using 10 mM sodium citrate buffer (pH 6.0) at a subboiling temperature for 10 to 15 min. The tissues were permeabilized using 0.4% Triton X-100 in PBS for 10 min followed by blocking in 5% BSA in PBS Tween 20. Sections were incubated overnight at 4C in a humid atmosphere with primary antibody against SMAR1 (1:1000; Bethyl Laboratories). After washing in PBS, the sections were incubated with secondary antibodies conjugated with Alexa Fluor 546 (red). The DAPI was used as nuclear stain (blue). Images were acquired using a confocal microscope (Leica). All immunohistochemistry and immunofluorescence experiments and their analysis were performed in a blinded manner.
Expression of breast cancer stem cell marker CD44 and CD24 was assessed by flow cytometric analysis of cells and spheres using CD44-APC and CD24-PE antibodies (BD Biosciences). CD44+/CD24 CSCs were gated from spheres on the basis of the cell surface phenotype by flow cytometry. To study the pluripotency markers Oct4, Sox2, Nanog, and ALDH1; differentiation marker CK18; and drug resistance marker ABCG2, the following antibodies were used: Oct4PerCP-Cy5.5 (BD Biosciences), Sox2Alexa Fluor 647 (BD Biosciences), Nanog-PE (BD Biosciences), CK18-PE (BD Biosciences), ALDH1fluorescein isothiocyanate (FITC) (Santa Cruz Biotechnology), and ABCG2-PE (BD Biosciences). Mean fluorescence intensities of Oct4PerCP-Cy5.5, Sox2Alexa Fluor 647, and Nanog-PE were quantified (3). To determine the expression of SMAR1, samples were incubated with SMAR1 antibody (Bethyl Laboratories) in 1% BSA in PBS solution, followed by tagging with FITC-conjugated secondary antibody. The percentage of cells expressing SMAR1 and the mean fluorescence intensity were recorded. To study the percentage of apoptosis by flow cytometry, the FITC-annexin V apoptosis detection kit (BD Biosciences) was used as per the manufacturers protocol.
For cell cycle analysis, the cells were harvested, washed with PBS, and fixed with chilled 70% ethanol. After fixation, the cells were washed and resuspended in PBS, treated with ribonuclease A, and, lastly, stained with propidium iodide (PI). The percentages of cells at different cell cycle stages (G0-G1, S, and G2-M) were determined on the basis of DNA content by flow cytometry using FACSVerse Flow Cytometer (BD Biosciences) using histogram plot of normalized count (y axis) versus PI (linear x axis)(59).
To study the role of aspirin in augmenting the expression of SMAR1 in vivo, female BALB/c mice bearing syngeneic breast cancer cells 4T1 were used. Female BALB/c mice weighing 20 to 25 g were maintained in a temperature-controlled room with light-dark cycle. All animal experiments were performed following principles of laboratory animal care (NIH publication no. 85-23, revised in 1985) and Indian laws on Protection of Animals under the provision of the ethics committee for the purpose of control and supervision of experiments on animals (reg. no. 95/99/CPCSEA; approval no: IAEC/BI/94/2018), Bose Institute. The following two experiments were performed using the BALB/c mice.
In the first, to evaluate the effect of aspirin, mice (n = 20) were inoculated within the mammary fat pad with 1 106 4T1 cells derived from secondary spheres. For that, the 4T1 secondary spheres were first trypsinized to form single cells, followed by a cell viability assay using trypan blue exclusion method, and a total number of 1 106 viable cells were inoculated in the mice. On the seventh day after tumor inoculation, tumor-bearing mice were divided into four groups (n = 5 in each group): control set, aspirin-treated set, doxorubicin-treated set, and aspirin + doxorubicintreated set. From that day onward, the mice were intraperitoneally treated with PBS (control set), aspirin (100 mg/kg), doxorubicin (5 mg/kg), or aspirin (100 mg/kg) + doxorubicin (5 mg/kg) every alternate day for 2 weeks (seven doses at 48-hour intervals) (60, 61). After 2 weeks of treatment, all four groups of mice were sacrificed, tumor volume was measured, the expression of SMAR1 was detected using Western blot, and the expression of SMAR1, ABCG2, Oct4, and Sox2 mRNAs was measured by real-time PCR.
In the second experiment, to evaluate the changes in CSC percentage and SMAR1 expression along different time points of progressive tumor growth, the female BALB/c mice were inoculated with 1 106 4T1 cells, as mentioned above. The mice were divided into three groups and one group each was sacrificed on the 7th, 14th, and 21st days, respectively, after the day of tumor inoculation. The percentage of CSCs within the tumors of each group was measured as CD44+/24/low (16), Oct4+, and Sox2+ cells. The percent of SMAR1+ cells was determined by flow cytometry, and expression of SMAR1 mRNA was determined by real-time PCR. All tagged antibodies for flow cytometry were purchased from BD Biosciences.
For the nude mouse xenograft model, to determine the tumor formation potential of grafted MDA-MB-468 cells and secondary spheres, female BALB/c athymic nude mice (4 to 5 weeks old, each weighing 18 to 22 g) were used. These mice were obtained from the Centre for Translational Animal Research, Bose Institute, and all experiments were performed following the guidelines of the Bose Institute animal ethics committee in accordance with CPCSEA guidelines (reg. no. 95/99/CPCSEA; approval no: IAEC/BI/94/2018). The mice were raised in pathogen-free temperature-controlled environment with light-dark cycle. Prior inoculation, the cell viability was assessed by trypan blue exclusion method. The mice were orthotopically inoculated in mammary fat pad with either 6 106 viable MDA-MB-468 cells or 6 106 viable cells from MDA-MB-468 secondary spheres (n = 3 for each group). The mice were regularly observed for tumor formation, and the tumor volume was measured every other day. Thirty days after the day of tumor inoculation, the mice were sacrificed, tumor tissues were collected, and the tumor volumes and weights were measured (6264).
The full-length structure of SMAR1 (NP_001167010.1) and Oct4 (NP_001167002.1) was modeled in I-TASSER web server (65). The predicted structure was prepared and minimized using Schrodinger PRIME module (66). X-ray crystallographic structures of Sox2 [Protein Data Bank (PDB) ID: 2LE4], HDAC2 (PDB ID: 3MAX), and HDAC1 (PDB ID: 4BKX) were already available, so the co-ordinate file was downloaded from The Research Collaboratory for Structural Bioinformatics (RCSB) PDB and further processed in PyMOL. To analyze the interaction of Oct4-Sox2, they were docked upon each other in ZDOCK (67). The same method was followed for docking SMAR1-HDAC2 proteins. To study the binding with the SMAR1 promoter, Oct4-Sox2 complex was docked on SMAR1 promoter (5-TTTTAAAATGTAAAACCCA-3) in HDOCK (68). The same method was followed to dock SMAR1-HDAC2 on ABCG2 promoter (5-CATTTTAAGACAAAATTAAGG-CCAGCACGG-3) and SMAR1 on ABCG2 promoter (5-CATTTTAAGACAAAATTAAGG-CCAGCACGG-3. The final predicted docked structures of all the complexes were viewed and analyzed with PyMOL (69, 70).
The normal versus tumor expression of SMAR1 in various cancers and the correlation plot between SMAR1 and ALDH1 in breast cancer were obtained from the GEPIA database using single gene analysis in The Cancer Genome Atlas (TCGA) tumors dataset (71). The t-SNE plots of SMAR1, ALDH1, and ABCG2 and the correlation plot between SMAR1, ALDH1 and SMAR1, and ABCG2 in invasive breast carcinomas (n = 1097 samples) were obtained from the R2 database (R2 Genomics Analysis and Visualization Platform) using tumor breast invasive carcinoma-TCGA-1097 dataset (72). Km analysis was performed using the publicly available database at http://kmplot.com/analysis/ with the following options: Affy id: 233186_s_at; splitting patients by Autoselect best cut off; survival: RFS (n = 1764), OS (n = 397), PFS (n = 165); probe set option: only Jetset best probe set; ER/PR/HER2 status: all; TP53 status: all; and intrinsic subtype: all. The normal versus tumor SMAR1 expression analysis in invasive breast carcinoma was also obtained from Oncomine database (Finak dataset of breast cancer) (73) using the following filters: cancer versus normal analysis; cancer type, breast cancer; and dataset, Finak breast.
The 2000- to +100-bp spanning promoter sequence of human ABCG2 and SMAR1 genes was obtained from the Eukaryotic Promoter Database (74). The S/MAR domain on the ABCG2 promoter was determined using Genomatix software suite using the SMARTest tool (www.genomatix.de/online_help/help_gems/SMARTest.html). The SMARTest identifies potential S/MARs by performing a density analysis based on the S/MAR matrix library (75). The Oct4 and Sox2 binding region on SMAR1 promoter was determined by JASPAR transcription factor binding profile database (http://jaspar.genereg.net/) (76).
Values are shown as mean and SD, unless otherwise indicated. All quantitative figures were constructed using GraphPad Prism version 7.00 with the alpha level set at 0.05 for all tests (GraphPad Prism 7.00). All experiments were independently repeated at least three times, data were analyzed, and significance (P < 0.05) of the differences between mean values was determined by statistician-confirmed, suitable statistical tests. Data with normal distribution were analyzed by either Students t test or analysis of variance (ANOVA) as appropriate. For multiple comparisons where applicable, one-way ANOVA with Dunnetts multiple comparison of post hoc test was performed for normal data. To analyze normalized data, like real-time PCR data that do not follow normal distribution, nonparametric tests are used. For nonnormal data with two unpaired groups, Mann-Whitney U test was performed; for nonnormal data with three or more groups, Kruskal-Wallis test was performed. For multiple comparisons of nonnormal data, Dunns multiple comparison post hoc test was used along with Kruskal-Wallis test.
Acknowledgments: We thank A. Adhikary at the Centre for Research in Nanoscience and Nanotechnology, University of Calcutta for thoughtful comments on this manuscript, D. Chakraborty for the help in the animal and IHC experiments, and U. K. Ghosh and R. Dutta for the technical assistance. Funding: This work was supported by research grants from Department of Science and TechnologyScience and Engineering Research Board (DST-SERB), Government of India (grant number EMR/2016/003607). The first author A.B. is under UGC-SRF fellowship, Government of India, the contingency grant of which has also supported the work. Author contributions: T.D. conceptualized the project, designed the experiments, and reviewed and edited the manuscript. A.B. carried out most of the experiments, analyzed data, wrote the manuscript, and prepared the figures. S.M., P.K., and S.B. reviewed the data and reviewed and edited the manuscript. Apratim Dutta carried out the CoIP experiments, performed the R2 and GEPIA database study, and prepared the figures. N.B. and S. Chatterjee performed in silico docking experiments. D.S. did the Km plotter and Oncomine database study. U.B. and S. Chakraborty performed cell culture. Abhishek Dutta carried out cell cycle experiments. S. Chattopadhyay provided the SMAR1 cDNA and SMAR1 shRNA plasmids and reviewed the manuscript. K.J. supervised the in vivo mice model experiments. D.K.S. provided the primary human tissue samples. Competing interest: The authors declare that they have no competing interests. Data and materials availability: All the data needed to evaluate the conclusions in the paper are present in the paper or the Supplementary Materials.
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