Category Archives: Adult Stem Cells

New Models in Organoids Market Open New Vistas in Stem Cell Research for Cancer, Global Valuation to Reach US$ 12.8 Bn by 2030: TMR – PRNewswire

ALBANY, N.Y., Jan. 12, 2021 /PRNewswire/ -- Organoids are stem cell-derived 3D culture systems and are usually derived from induced pluripotent stem cells (iPSCs) and multipotent adult tissue stem cells (ASCs). The technologies in the organoids market have emerged as a novel culture used for human disease modelling. Their amazing capability in recapitulating in vivo anatomy and physiology of organs is utilized to open new paradigms in cell biology areas such as in gene therapy, regenerative medicine, and cancer research. Most prominently, researchers and industry players have harnessed the potential of organoids in regenerative medicine and tissue engineering.

Advent of new methods in generating 3D structures are opening new vistas in human disease modelling, particularly in virology. The utilization of these in drug discovery and personalized medicine will transform medical care in years to come. Europe and North America have emerged as the new hotspots for patient-derived human organoid studies in the global organoids market.

Request for Analysis of COVID-19 Impact on Organoids Market https://www.transparencymarketresearch.com/covid19.php

The revenue of global organoid market is projected to climb from US$ 1.7 Bn in 2019 to touch the mark of US$ 12.8 Bn by 2030.

Key Findings of Organoids Market

In the backdrop of the need for new approaches of studying the pathogenesis of currently emerging Covid-19, organoids market is replete with incredible revenue potential for stakeholders. Researchers are relentlessly working toward new organoids approaches for understanding tissue tropism of SARS-CoV-2. In the last few years, the strides in the organoids market has unarguably expanded the armamentarium of virologists studying infectious diseases. A case in point was Zika virus infection.

Patient-derived human organoids are increasingly being leveraged upon by researchers to open new avenues in tissue engineering and regenerative medicine. These 3D-based cultures have been able to overcome the limitations of 2D cancer-derived cell lines, notably in bladder, colorectal, brain, and liver cancer. There is demand for new patient-derived cell lines for cancer sample biobanking. Integrating biobanking with tumor modelling has undoubtedly expanded the avenue in cancer care. This is also expanding the avenue for precision medicine, the relevance of which is gather traction in patient care.

Request Brochure of Organoids Market Report - https://www.transparencymarketresearch.com/brochure.php

Over the years, the organoid market has made some remarkable strides on the back of collaborations between researchers in universities and medical experts in healthcare institutes. Next-gen organoid development for Covid-19 is a case in point where there has been surge in research funding. Giant leaps made by genome editing systems have expanded the avenue in genome engineering of human stem cells. This will test new methods of generating human organoid models. Another researcher directions attracting investments are in development of cerebral organoids for neurological diseases.

Organoids Market: Key Driving Factors and Promising Avenues

Purchase the Organoids Market Report- https://www.transparencymarketresearch.com/checkout.php

Organoids Market: Competitive Dynamics

Explore Transparency Market Research's award-winning coverage of the global Healthcare Industry:

Gene Therapy Market:https://www.transparencymarketresearch.com/gene-therapy-market.html

Genome Editing Market:https://www.transparencymarketresearch.com/genome-editing-market.html

About Us

Transparency Market Research is a next-generation market intelligence provider, offering fact-based solutions to business leaders, consultants, and strategy professionals.

Our reports are single-point solutions for businesses to grow, evolve, and mature. Our real-time data collection methods along with ability to track more than one million high growth niche products are aligned with your aims. The detailed and proprietary statistical models used by our analysts offer insights for making right decision in the shortest span of time. For organizations that require specific but comprehensive information we offer customized solutions through adhoc reports. These requests are delivered with the perfect combination of right sense of fact-oriented problem solving methodologies and leveraging existing data repositories.

TMR believes that unison of solutions for clients-specific problems with right methodology of research is the key tohelp enterprises reach right decision."

Browse More Upcoming Reports by Transparency Market Research:https://www.transparencymarketresearch.com/upcoming.htm

Contact

Mr. Rohit Bhisey Transparency Market Research State Tower, 90 State Street, Suite 700, Albany NY - 12207 United States USA - Canada Toll Free: 866-552-3453 Email: [emailprotected] Press Release Source:https://www.transparencymarketresearch.com/pressrelease/organoids-market.htm Website: https://www.transparencymarketresearch.com/

SOURCE Transparency Market Research

Read this article:
New Models in Organoids Market Open New Vistas in Stem Cell Research for Cancer, Global Valuation to Reach US$ 12.8 Bn by 2030: TMR - PRNewswire

Health Canada Approves ONUREG (azacitidine tablets), First Maintenance Therapy for Patients in Remission from Acute Myeloid Leukemia – Canada NewsWire

AML is a heterogeneous clonal disorder characterized by immature myeloid cell proliferation and bone marrow failure, and is the most common form of acute leukemia in adults, accounting for approximately 80 per cent of adult cases.2,3,4 An estimated 40-60 per cent of patients aged 60 years and older and 60-80 per cent of patients under 60 years old will obtain complete remission through induction chemotherapy (IC); however, 50 per cent will relapse within a year.5,6 Once a relapse occurs, long-term survival averages at six months.7 In 2015, an estimated 1,235 Canadians were diagnosed with AML and the overall incidence rate in Canada is 3.46/100,000 people.8,9

"While the majority of patients with AML achieve a complete remission with intensive chemotherapy, many remission patients will experience disease relapse, especially if they were not eligible for a stem cell transplant. Until now, there has been no established standard of care for Canadians who are in remission from AML, but are not eligible for a stem cell transplant," noted Dr. Andre Schuh, Princess Margaret Cancer Centre, Toronto. "The approval of ONUREG is significant because it gives transplant ineligible patients with AML in remission a new treatment option that may improve their survival".

ONUREG is a nucleoside metabolic inhibitor that is taken orally and works by preventing cancer cells from growing. ONUREG becomes incorporated into the building blocks of cells (deoxyribonucleic acid (DNA) and ribonucleic acid (RNA)), which interferes with the production of new DNA and RNA. This is thought to kill cancerous cells in leukemia.10

"The approval of ONUREG is an extension of our ongoing commitment to Canadians living with blood cancer," said Al Reba, General Manager, Bristol Myers Squibb Canada. "We are proud that this therapy will help to fill a significant need for Canadians living in remission from AML and hope that it will have a positive impact on their everyday life."

Health Canada's approval of ONUREG is based upon findings from the QUAZAR AML-001 clinical trial. The QUAZAR study, a double-blind, randomized, placebo-controlled, multicenter Phase III study, involved adult patients 55 years or older living with AML. In the study, patients were randomized to Onureg or placebo within four months of achieving first CR/CRi following intensive induction chemotherapy and were not eligible for a stem cell transplant.11In the study, results showed the median overall survival (OS) was significantly longer with ONUREG versus placebo: 24.7 months versus 14.8 months [HR 0.69 (95% CI: 0.55, 0.86); p=0.0009], indicating a 31 per cent reduction in the risk of death in the ONUREG arm. Relapse-free survival (RFS), the key secondary endpoint in the study, supports the OS results. The median RFS was 10.2 months for ONUREG versus 4.8 months for placebo [HR 0.65 (95% CI: 0.52, 0.81); p=0.0001].12

About Bristol Myers Squibb CanadaBristol Myers Squibb Canada Co. is an indirect wholly-owned subsidiary of Bristol Myers Squibb Company, a global biopharmaceutical company whose mission is to discover, develop and deliver innovative medicines that help patients prevail over serious diseases. For more information about Bristol Myers Squibb global operations, visitwww.bms.com. Bristol Myers Squibb Canada Co. delivers innovative medicines for serious diseases to Canadian patients in the areas of cardiovascular health, oncology, and immunoscience. Bristol Myers Squibb Canada Co. employs close to 400 people across the country. For more information, please visitwww.bms.com/ca.

About Bristol Myers SquibbBristol Myers Squibb is a global biopharmaceutical company whose mission is to discover, develop and deliver innovative medicines that help patients prevail over serious diseases. For more information about Bristol Myers Squibb, visit us atBMS.comor follow us on LinkedIn, Twitter, YouTube, Facebookand Instagram.

References

_________________________

1 ONUREG Product Monograph, January 2021.

2 Saultz JN, Garzon R. J Clin Med 2016;5:33.

3Leukemia & Lymphoma Society of Canada. Acute Myeloid Leukemia. Available from https://www.llscanada.org/sites/default/files/National/CANADA/Pdf/InfoBooklets/AML%20Fact%20Sheet%2012-2019.pdf. Accessed December 11, 2020.

4De Kouchkovsky I, Abdul-Hay M. Blood Cancer J 2016;e441:DOI:10.1038/bcj.2016.50.

5Dohner et al. Blood. 2017;129(4):42447.

6SEER Cancer Statistics, 2007-2013.

7Xu J, et al. Medicine (Baltimore) 2018;97:e12102.

8Statistics Canada. Population estimates on July 1st, by age and sex. Available from https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=1710000501&pickMembers%5B0%5D=1.1&pickMembers%5B1%5D=2.1&cubeTimeFrame.startYear=2015&cubeTimeFrame.endYear=2016&referencePeriods=20150101%2C20160101. Accessed December 11, 2020.

9Shysh et al. BMS Public Health (2018) 18:94.

10ONUREG Product Monograph, January 2021.

11ONUREG Product Monograph, January 2021.

12 ONUREG Product Monograph, January 2021.

SOURCE Bristol Myers Squibb Canada Co.

For further information: For media requests, please contact: Rachel Yates, Lead, Corporate Affairs, Bristol Myers Squibb Canada, [emailprotected]; Alannah Nugent, Account Executive, Health, Edelman, [emailprotected]

Original post:
Health Canada Approves ONUREG (azacitidine tablets), First Maintenance Therapy for Patients in Remission from Acute Myeloid Leukemia - Canada NewsWire

Stem Cells Market 2020 Research Study including Growth Factors, Types and Application to 2026| Covid-19 Impact – Farming Sector

Global Stem Cells Market Report mainly includes sales, revenue, trade, competition, investment, forecast and marketing of the product and the segments here include companies, types, applications, regions, countries, etc. The regions of Stem Cells market industry contain all Global market, especially in North America, Europe, Asia Pacific, Latin America and MEA.

Get Sample Copy of Stem Cells Market Research Report at: https://www.absolutereports.com/enquiry/request-sample/14325305

Data and information by Stem Cells market trends, by manufacturer, by region, by type, by application and etc., and custom research can be added according to specific requirements.

By Market Players: Osiris Therapeutics, Inc., Cytori Therapeutics, Inc., BrainStorm Cell Therapeutics Inc., U.S. Stem Cell, Inc., Takara Bio Inc., BioTime Inc., Cellular Engineering Technologies Inc., Astellas Pharma Inc., Caladrius Biosciences, Inc., STEMCELL Technologies Inc.

By Product Adult Stem Cell, Human Embryonic Stem Cell, Induced Pluripotent Stem Cell

By Source Autologous, Allogeneic,

By Application Regenerative Medicine, Drug Discovery and Development,

By End User Therapeutic Companies, Cell and Tissue Banks, Tools and Reagent Companies, Service Companies,

Stem Cells Market by Regions:

The Stem Cells Market contains the SWOT analysis of the market. Finally, the report contains the conclusion part where the opinions of the industrial experts are included.

Inquire or Share Your Questions If Any Before the Purchasing This Report :-https://www.absolutereports.com/enquiry/pre-order-enquiry/14325305

Points Covered in The Report:

Key Reasons to Purchase

Detailed TOC of 2019-2024 Global and Regional Stem Cells Production, Sales and Consumption Status and Prospects Professional Market Research Report

Chapter 1 Industry Overview of Stem Cells Market

1.1 Definition

1.2 Brief Introduction by Major Type

1.3 Brief Introduction by Major Application

1.4 Brief Introduction by Major Regions

1.4.1 United States

1.4.2 Europe

1.4.3 China

1.4.4 Japan

1.4.5 India

Chapter 2 Production Market Analysis of Stem Cells Market

2.1 Global Production Market Analysis

2.1.1 2013-2020 Global Capacity, Production, Capacity Utilization Rate, Ex-Factory Price, Revenue, Cost, Gross and Gross Margin Analysis

2.1.2 2013-2020 Major Manufacturers Performance and Market Share

2.2 Regional Production Market Analysis

2.2.1 2013-2020 Regional Market Performance and Market Share

2.2.2 United States Market

2.2.3 Europe Market

2.2.4 China Market

2.2.5 Japan Market

2.2.6 India Market

2.2.7 Market

Chapter 3 Sales Market Analysis of Stem Cells Market

3.1 Global Sales Market Analysis

3.2 Regional Sales Market Analysis

Chapter 4 Consumption Market Analysis of Stem Cells Market

4.1 Global Consumption Market Analysis

4.2 Regional Consumption Market Analysis

Chapter 5 Production, Sales and Consumption Market Comparison Analysis

5.1 Global Production, Sales and Consumption Market Comparison Analysis

5.2 Regional Production, Sales Volume and Consumption Volume Market Comparison Analysis

Chapter 6 Major Manufacturers Production and Sales Market Comparison Analysis

6.1 Global Major Manufacturers Production and Sales Market Comparison Analysis

6.2 Regional Major Manufacturers Production and Sales Market Comparison Analysis

Chapter 7 Major Type Analysis

7.1 2013-2020 Major Type Market Share

Chapter 8 Major Application Analysis

8.1 2013-2020 Major Application Market Share

Chapter 9 Industry Chain Analysis

9.1 Up Stream Industries Analysis

9.2 Manufacturing Analysis

9.3 Industry Chain Structure Analysis

Chapter 10 Global and Regional Stem Cells Market Forecast

10.1 Production Market Forecast

10.1.1 Global Market Forecast

10.1.2 Major Region Forecast

10.2 Sales Market Forecast

10.2.1 Global Market Forecast

10.2.2 Major Classification Forecast

10.3 Consumption Market Forecast

10.3.1 Global Market Forecast

10.3.2 Major Region Forecast

10.3.3 Major Application Forecast

Chapter 11 New Project Investment Feasibility Analysis

11.1 New Project SWOT Analysis

11.2 New Project Investment Feasibility Analysis

Chapter 12 Conclusions

Chapter 13 Appendix

Purchase This Report (Price 3500 USD for single user license) https://www.absolutereports.com/purchase/14325305

About Absolute Reports:

Absolute Reports is an upscale platform to help key personnel in the business world in strategizing and taking visionary decisions based on facts and figures derived from in depth market research. We are one of the top report resellers in the market, dedicated towards bringing you an ingenious concoction of data parameters.

Contact Info:

Name: Ajay More

Email: [emailprotected]

Organization: Absolute Reports

Phone: +14242530807/+442032398187

Our Other report : Sarcosine Sodium Market Overview, Manufacturing Cost Structure Analysis, Growth Opportunities and Restraint to 2026

Liquid Paraffin Wax Market Analysis, Growth, Size, Share, Trends, Forecast, Supply Demand and Sales to 2026

Global Elevator Travel Cables Market Share, Growth, Trend Analysis and Forecast from 2021-2026; Consumption Capacity by Volume and Production Value

Global Carbonic Anhydrase Market Entry Strategies, Countermeasures of Economic Impact and Marketing Channels to 2026

Quadricycle Market 2021: Global Industry Share, Size, Share, Demand, Key Findings, Regional Analysis, Key Players Profiles, Future Prospects and Forecasts to 2026

Worldwide Natural Pet Foods Market Outlook to 2025: Emerging Trends and Will Generate New Growth Opportunities Status

Sports Fishing Equipment Industry Global Market Size, Share, Supply, Demand, Segments and Forecast 2021-2025

Kitchen Hand Tools Market Analysis, Growth, Size, Share, Trends, Forecast, Supply Demand and Sales to 2026

Prothrombin Complex Concentrates Market Analysis, Size, Share, Growth, Trends and Forecast 2021 2026

Router Bits Market Professional Survey, Growth, Shares, Opportunities and Forecast to 2026

CDEA/CMEA Market 2021, Global Industry Size, Segments, Share and Growth Factor Analysis Research Report 2024

Global Chrome Pigments Sales Market 2021: Market Growth, Trends, Revenue, Share and Demands Research Report|Coronavirus Impact

Global Slope Stabilisation & Erosion Control Product Market 2021: Industry Size, Growth, Segments, Revenue, Manufacturers and 2024 Forecast Research Report

Flat Panel Display Wet Chemicals Market Analysis including Size, Share, Key Drivers, Growth Opportunities and Trends 2021 2026

Global High Barrier Lidding Film Market 2020: Industry Size, Outlook, Share, Demand, Manufacturers and 2026 Forecast Researchs|Coronavirus Impact

https://farmingsector.co.uk/

Read this article:
Stem Cells Market 2020 Research Study including Growth Factors, Types and Application to 2026| Covid-19 Impact - Farming Sector

The real reason behind goosebumps – Jill Lopez

If you've ever wondered why we get goosebumps, you're in good company -- so did Charles Darwin, who mused about them in his writings on evolution. Goosebumps might protect animals with thick fur from the cold, but we humans don't seem to benefit from the reaction much -- so why has it been preserved during evolution all this time?

In a new study, Harvard University scientists have discovered the reason: the cell types that cause goosebumps are also important for regulating the stem cells that regenerate the hair follicle and hair. Underneath the skin, the muscle that contracts to create goosebumps is necessary to bridge the sympathetic nerve's connection to hair follicle stem cells. The sympathetic nerve reacts to cold by contracting the muscle and causing goosebumps in the short term, and by driving hair follicle stem cell activation and new hair growth over the long term.

Published in the journalCell, these findings in mice give researchers a better understanding of how different cell types interact to link stem cell activity with changes in the outside environment.

"We have always been interested in understanding how stem cell behaviors are regulated by external stimuli. The skin is a fascinating system: it has multiple stem cells surrounded by diverse cell types, and is located at the interface between our body and the outside world. Therefore, its stem cells could potentially respond to a diverse array of stimuli -- from the niche, the whole body, or even the outside environment," said Ya-Chieh Hsu, the Alvin and Esta Star Associate Professor of Stem Cell and Regenerative Biology, who led the study in collaboration with Professor Sung-Jan Lin of National Taiwan University. "In this study, we identify an interesting dual-component niche that not only regulates the stem cells under steady state, but also modulates stem cell behaviors according to temperature changes outside."

A system for regulating hair growth

Many organs are made of three types of tissue: epithelium, mesenchyme, and nerve. In the skin, these three lineages are organized in a special arrangement. The sympathetic nerve, part of our nervous system that controls body homeostasis and our responses to external stimuli, connects with a tiny smooth muscle in the mesenchyme. This smooth muscle in turn connects to hair follicle stem cells, a type of epithelial stem cell critical for regenerating the hair follicle as well as repairing wounds.

The connection between the sympathetic nerve and the muscle has been well known, since they are the cellular basis behind goosebumps: the cold triggers sympathetic neurons to send a nerve signal, and the muscle reacts by contracting and causing the hair to stand on end. However, when examining the skin under extremely high resolution using electron microscopy, the researchers found that the sympathetic nerve not only associated with the muscle, but also formed a direct connection to the hair follicle stem cells. In fact, the nerve fibers wrapped around the hair follicle stem cells like a ribbon.

"We could really see at an ultrastructure level how the nerve and the stem cell interact. Neurons tend to regulate excitable cells, like other neurons or muscle with synapses. But we were surprised to find that they form similar synapse-like structures with an epithelial stem cell, which is not a very typical target for neurons," Hsu said.

Next, the researchers confirmed that the nerve indeed targeted the stem cells. The sympathetic nervous system is normally activated at a constant low level to maintain body homeostasis, and the researchers found that this low level of nerve activity maintained the stem cells in a poised state ready for regeneration. Under prolonged cold, the nerve was activated at a much higher level and more neurotransmitters were released, causing the stem cells to activate quickly, regenerate the hair follicle, and grow new hair.

The researchers also investigated what maintained the nerve connections to the hair follicle stem cells. When they removed the muscle connected to the hair follicle, the sympathetic nerve retracted and the nerve connection to the hair follicle stem cells was lost, showing that the muscle was a necessary structural support to bridge the sympathetic nerve to the hair follicle.

How the system develops

In addition to studying the hair follicle in its fully formed state, the researchers investigated how the system initially develops -- how the muscle and nerve reach the hair follicle in the first place.

"We discovered that the signal comes from the developing hair follicle itself. It secretes a protein that regulates the formation of the smooth muscle, which then attracts the sympathetic nerve. Then in the adult, the interaction turns around, with the nerve and muscle together regulating the hair follicle stem cells to regenerate the new hair follicle. It's closing the whole circle -- the developing hair follicle is establishing its own niche," said Yulia Shwartz, a postdoctoral fellow in the Hsu lab. She was a co-first author of the study, along with Meryem Gonzalez-Celeiro, a graduate student in the Hsu Lab, and Chih-Lung Chen, a postdoctoral fellow in the Lin lab.

Responding to the environment

With these experiments, the researchers identified a two-component system that regulates hair follicle stem cells. The nerve is the signaling component that activates the stem cells through neurotransmitters, while the muscle is the structural component that allows the nerve fibers to directly connect with hair follicle stem cells.

"You can regulate hair follicle stem cells in so many different ways, and they are wonderful models to study tissue regeneration," Shwartz said. "This particular reaction is helpful for coupling tissue regeneration with changes in the outside world, such as temperature. It's a two-layer response: goosebumps are a quick way to provide some sort of relief in the short term. But when the cold lasts, this becomes a nice mechanism for the stem cells to know it's maybe time to regenerate new hair coat."

In the future, the researchers will further explore how the external environment might influence the stem cells in the skin, both under homeostasis and in repair situations such as wound healing.

"We live in a constantly changing environment. Since the skin is always in contact with the outside world, it gives us a chance to study what mechanisms stem cells in our body use to integrate tissue production with changing demands, which is essential for organisms to thrive in this dynamic world," Hsu said.

Read this article:
The real reason behind goosebumps - Jill Lopez

Synthetic lethality across normal tissues is strongly associated with cancer risk, onset, and tumor suppressor specificity – Science Advances

Abstract

Various characteristics of cancers exhibit tissue specificity, including lifetime cancer risk, onset age, and cancer driver genes. Previously, the large variation in cancer risk across human tissues was found to strongly correlate with the number of stem cell divisions and abnormal DNA methylation levels. Here, we study the role of synthetic lethality in cancer risk. Analyzing normal tissue transcriptomics data in the Genotype-Tissue Expression project, we quantify the extent of co-inactivation of cancer synthetic lethal (cSL) gene pairs and find that normal tissues with more down-regulated cSL gene pairs have lower and delayed cancer risk. Consistently, more cSL gene pairs become up-regulated in cells treated by carcinogens and throughout premalignant stages in vivo. We also show that the tissue specificity of numerous tumor suppressor genes is associated with the expression of their cSL partner genes across normal tissues. Overall, our findings support the possible role of synthetic lethality in tumorigenesis.

Cancers of different human tissues have markedly different molecular, phenotypic, and epidemiological characteristics, known as the tissue specificity in cancer. Various aspects of this intriguing phenomenon include a considerable variation in lifetime cancer risk, cancer onset age, and the genes driving the cancer across tissue types. The variation in lifetime cancer risk is known to span several orders of magnitude (1, 2). Such variation cannot be fully explained by the difference in exposure to carcinogens or hereditary factors and has been shown to strongly correlate with differences in the number of lifetime stem cell divisions (NSCD) estimated across tissues (2, 3). As claimed by Tomasetti and Vogelstein (2), these findings are consistent with the notion that tissue stem cell divisions can propagate mutations caused either by environmental carcinogens or random replication error (4). In addition, the importance of epigenetic factors in carcinogenesis has long been recognized (5), and Klutstein et al. (6) have recently reported that the levels of abnormal CpG island DNA methylation (LADM) across tissues are highly correlated with their cancer risk. Although both global (e.g., smoking and obesity) and various cancer typespecific (e.g., HCV infection for liver cancer) risk factors are well known (7), no factors other than NSCD and LADM have been reported to date to explain the across-tissue variance in lifetime cancer risk.

Besides lifetime cancer risk, cancer onset age, as measured by the median age at diagnosis, also varies among adult cancers (1). Although most cancers typically manifest later in life [more than 40 years old (1, 8)], some such as testicular cancer often have earlier onset (1). Many tumor suppressor genes (TSGs) and oncogenes are also tissue specific (911). For example, mutations in the TSG BRCA1 are predominantly known to drive the development of breast and ovarian cancer but rarely other cancer types (12). In general, factors explaining the overall tissue specificity in cancer could be tissue intrinsic (10, 13), and their elucidation can further advance our understanding of the forces driving carcinogenesis.

Synthetic lethality/sickness (SL) is a well-known type of genetic interaction, conceptualized as cell death or reduced cell viability that occurs under the combined inactivation of two genes but not under the inactivation of either gene alone. The phenomenon of SL interactions was first recorded in Drosophila (14) and then in Saccharomyces cerevisiae (15). In recent years, much effort has been made to identify SL interactions specifically in cancer, since targeting these cancer SLs (cSLs) has been recognized as a highly valuable approach for cancer treatment (1619). The effect of cSL on cancer cell viability has led us to investigate whether it plays an additional role even before tumors manifest, i.e., during carcinogenesis. In this study, we quantify the level of cSL gene pair co-inactivation in normal (noncancerous) human tissue as a measure of resistance to cancer development (termed cSL load, explained in detail below). We show that cSL load can explain a considerable level of the variation in cancer risk and cancer onset age across human tissues, as well as the tissue specificity of some TSGs. Together, these correlative findings support the effect of SL in impeding tumorigenesis across human tissues.

To study the potential effects of cSL in normal, noncancerous tissues, we define a measure called cSL load, which quantifies the level of cSL gene pair co-inactivation based on gene expression of normal human tissues from the Genotype-Tissue Expression (GTEx) dataset (20). Specifically, we used a recently published reference set of genome-wide cSLs that are common to many cancer types, identified from both in vitro and The Cancer Genome Atlas (TCGA) cancer patient data (21) via the identification of clinically relevant synthetic lethality (ISLE) (table S1A) (22, 23). For each GTEx normal tissue sample, we computed the cSL load as the fraction of cSL gene pairs (among all the genome-wide cSLs) that have both genes lowly expressed in that sample (Methods; illustrated in Fig. 1). We further defined tissue cSL load (TCL) as the median cSL load value across all samples of each tissue type in GTEx (Methods and table S2A). We then proceed to test our hypothesis that TCL can be a measure of the level of resistance to cancer development intrinsic to each human tissue (outlined in Fig. 1).

This diagram illustrates the computation of cSL load for each sample and each tissue type (i.e., TCL) and depicts the outline of this study, where we attempted to explain the tissue-specific lifetime cancer risk, cancer onset age, and TSGs using TCL. See main text and Methods for details.

SL is widely known to be context specific across species, tissue types, and cellular conditions (24). In theory, a cancer-specific cSL gene pair can be co-inactivated in the normal tissue without reducing normal cell fitness, while conferring resistance to the emergence of malignantly transformed cells due to the lethal effect specifically on the cancer cells. Different normal tissues can have varied TCLs (representing the levels of cSL gene pair co-inactivation) as a result of their specific gene expression profiles, and we hypothesized that normal tissues with higher TCLs should have lower cancer risk, as transforming cancerous cells in these tissues will face higher cSL-mediated vulnerability and lethality. To test this hypothesis, we obtained data on the tissue-specific lifetime cancer risk in humans (Methods) and correlated that with the TCL values computed for the different tissue types. We find a strong negative correlation between the TCL (computed from older-aged GTEx samples, age 50 years) and lifetime cancer risk across normal tissues (Spearmans = 0.664, P = 1.59 104; Fig. 2A and table S2A). This correlation is robust, as comparable results are obtained when this analysis is carried out in various ways (e.g., different cutoffs for low expression of genes, different cSL network sizes, and different cancer typenormal tissue mappings; fig. S1 and note S3). We also showed that this correlation is not confounded by the number of poised genes associated with bivalent chromatin, variation in cancer driver gene expression, and immune cell or fibroblast abundance (notes S11 to S13 and figs. S12 to S14). Notably, the cSL load varies with age due to age-related gene expression changes, and the correlation with lifetime cancer risk is not found when the TCL is computed on samples from the young population (20 age < 50 years, Spearmans = 0.0251, P = 0.901; fig. S2A); this is consistent with the observation that lifetime cancer risk is mostly contributed by cancers occurring in older populations (1). We still see a marked negative correlation between TCL and lifetime cancer risk when analyzing samples from all age groups together (Spearmans = 0.49, P = 0.01; fig. S2B). Repeating these analyses using different control gene pairs including (i) random gene pairs, (ii) shuffled cSL gene pairs, and (iii) degree-preserving randomized cSL network (same size as the actual cSL network; note S4) results in significantly weaker correlations (empirical P < 0.001; fig. S3, A to C, and note S4), confirming that the associations found with cancer risk results from a cSL-specific effect.

(A) Scatterplot showing Spearmans correlations between lifetime cancer risk and TCL computed for the older population (age 50 years) (ranked values are used as lifetime cancer risk spans several orders of magnitude.) (B) Lifetime cancer risks across tissues were predicted using linear models (under cross-validation) containing different sets of explanatory variables: (i) TCL only, (ii) the number of stem cell divisions (NCSD) only, and (iii) TCL and NSCD (27 data points). The prediction accuracy is measured by Spearmans , shown by the bar plots. The result of a likelihood ratio test between models (ii) and (iii) is also displayed. (C) A similar bar plot as in (B) comparing the predictive models for cancer risk involving the following variables: (i) TCL only, (ii) the LADM only, and (iii) TCL and LADM combined (21 data points only due to the smaller set of LADM data). A model containing all the three variables does not increase the prediction power (Spearmans = 0.77 under cross-validation) and is not shown. (D) Bar plot showing the correlations between lifetime cancer risk with TCLs computed (age 50 years) using subsets of cSLs: hcSLs, lcSLs, and all cSLs. Spearmans and P values are shown. The hcSLs and lcSLs are identified using data of matched TCGA cancer types and GTEx normal tissues (Methods), which correspond to only a subset of tissue types. To facilitate comparison, here, the correlation for all cSLs was also computed for the same subset of tissues, and therefore, the resulting correlation coefficient is different from that in (A).

While the randomized cSL networks used in the control tests described above provide significantly weaker correlations with cancer risk than those observed with cSLs, many of these correlations are still significant by themselves (fig. S3, B and C). This suggests that there may be a possible association between the expression of single genes in the cSL network (cSL genes) and cancer risk. To investigate this, we computed the tissue cSL single-gene load (SGL; the fraction of lowly expressed cSL genes) for each tissue (Methods). We do find a significant negative correlation between tissue SGL levels and cancer risk (Spearmans = 0.49, P = 0.01; fig. S3D and note S5). This correlation vanishes when we use random sets of single genes (fig. S3F). However, after controlling for the single-gene effect, the partial correlation between TCL and cancer risk is still highly significant (Spearmans = 0.69, P = 6.10 105; fig. S3G), pointing to the dominant role of the SL genetic interaction effect (note S5).

We next compared the predictive power of TCL to those obtained with the previously reported measures of NSCD (2, 3) and LADM (6), using the set of GTEx tissue types investigated here (Methods). We first confirmed the strong correlations of NSCD and LADM with tissue lifetime cancer risk in our specific dataset (Spearmans = 0.72 and 0.74, P = 2.6 105 and 1.3 104, respectively; fig. S4). These correlations are stronger than the one we reported above between TCL and cancer risk. However, adding TCL to either NSCD or LADM in linear regression models leads to enhanced predictive models of cancer risk compared to those obtained with NSCD or LADM alone [log-likelihood ratio (LLR) = 2.18 and 2.39, P = 0.037 and 0.029, respectively]. Furthermore, adding TCL to each of these factors increases their prediction accuracy under cross-validation (Spearmans s from 0.67 and 0.69 with NSCD and LADM alone to 0.71 and 0.77, respectively; Fig. 2, B and C). LADM and NSCD are significantly correlated (Spearmans = 0.66, P = 0.02), while the TCL correlates only in a borderline significant manner with either NSCD (Spearmans = 0.57, P = 0.06) or LADM (Spearmans = 0.52, P = 0.08). Together, these observations support the hypothesis that TCL is associated with tissue cancer risk, with a partially independent role from either NSCD or LADM.

We have shown results that support the role of TCL in impeding cancer development, and we reason that such an effect is dependent on the notion that many of the cSLs are specific to cancer while having weaker or no lethal effects in normal tissues. We tested and found that the co-inactivation of cSL gene pairs is under much weaker negative selection in GTEx normal tissues versus matched TCGA cancers [Wilcoxon rank sum test P = 2.93 106 (fig. S5A), also shown using cross-validation (note S7)]. Moreover, we hypothesize that those cSLs with the highest specificity to cancer (i.e., with the strongest SL effect in cancer and no or the weakest effect on normal cells) should have the strongest effect on cancer development. To test this, we identified the subset of such cSLs (termed highly specific cSLs or hcSLs) and those with the lowest specificity to cancer (termed lowly specific cSLs or lcSLs; Methods) and recomputed the TCLs of all normal GTEx tissues using these two cSL subsets, respectively. The TCLs computed from the hcSLs correlate much stronger with cancer lifetime risk than those computed from the lcSLs (Spearmans = 0.593 versus 0.319; Fig. 2D), testifying that these cSLs with high functional specificity to cancer are more relevant to carcinogenesis. These hcSLs are enriched for cell cycle, DNA damage response, and immune-related genes [false discovery rate (FDR) < 0.05; table S5 and Methods], which are known to play key roles in tumorigenesis.

We have thus established that TCL in the older population is inversely correlated with lifetime cancer risk across tissues. We next hypothesized that higher cSL load in a given normal tissue in the young population may delay cancer onset, which typically occurs later (age >40 years) (1). To test this, we use the median age at cancer diagnosis (1) of a certain tissue as its cancer onset age (table S3 and Methods). We find that the TCL values (for age 40 years) are markedly correlated with cancer onset age (Spearmans = 0.502, P = 0.011; Fig. 3A). This result is again robust to variations in our methods to compute TCL and cancer onset age (fig. S6, table S3, and note S3). We note that the cancer onset age is not significantly correlated with lifetime cancer risk (Spearmans = 0.279, P = 0.28).

(A) Scatterplot showing Spearmans correlations between cancer onset age and TCL (age 40 years). (B) Bar plot showing the correlations between cancer onset age with TCLs computed (age 40 years) using subsets of cSLs: hcSLs, lcSL, and all cSLs. Spearmans and P values are shown. As in Fig. 2D, this analysis was done for a subset of GTEx normal tissues for which we had matched TCGA cancer types to identify the hcSLs and lcSLs (Methods); therefore, the correlation result for all cSLs is also different from that in (A).

Similar to our earlier analysis, we see that the TCLs computed from the hcSLs correlate much stronger with onset age than those from the lcSLs or all cSLs (Spearmans = 0.603 versus 0.157; Fig. 3B and fig. S7A) and also stronger than those obtained from control tests performed as before (empirical P < 0.001; fig. S7, B to D). As with the case of cancer risk, the observed correlation is dominated by the SL genetic interaction effects rather than the single-gene effects (fig. S7, E to G, and note S5).

To further corroborate the relevance of cSL load to carcinogenesis, we next investigated whether carcinogen treatment in normal (noncancer) cell lines and primary cells in vitro can lead to cSL load decrease. First, we analyzed gene expression data from a recent study where human primary hepatocytes, renal tube epithelial cells, and cardiomyocytes were treated with the carcinogen and hepatotoxin thioacetamide-S-oxide (25). We computed the cSL load in each cell type after treatment versus control and found a significant decrease of cSL load only in the hepatocytes (Wilcoxon rank sum test P = 0.014; Fig. 4A), which is consistent with thioacetamide-S-oxides role as a hepatotoxin and a carcinogen primarily in the liver. Second, we collected the gene expression signatures of chemotherapy drug treatments in a total of four primary cells and normal cell lines from the Connectivity Map (CMAP) (26). We quantified the drug-induced cSL load changes indirectly from the gene signatures (Methods), comparing the strongly mutagenic DNA-targeting drugs (n = 6) including alkylating agents and DNA topoisomerase inhibitors to the weak/nonmutagenic taxanes and vinca alkaloids (n = 5), which act on the cytoskeleton and not directly on DNA (27). We find that the strong mutagenic chemotherapy drugs lead to a significantly larger decrease in cSL load (Fig. 4B, P = 0.03 from a linear model controlling for cell type; Methods). The strong mutagenicity of alkylating agents and DNA topoisomerase inhibitors is consistent with their mechanisms of actions; they are also World Health Organization class I carcinogens (28), supported by incidence of secondary cancers in patients treated by these drugs for their primary cancers (29). In contrast, taxanes and vinca alkaloids have shown negative or weak/inconclusive results in mutagenic tests (27, 30). These results are not likely affected by cell death, as the cSL decreased specifically only for the two classes among all tested chemotherapy drugs. Although the CMAP dataset used for this analysis does not include cell viability information, the gene expression of the cells does not show an apoptotic signature after the drug treatment.

(A) Box plots showing the cSL loads in control versus thioacetamide-S-oxidetreated samples in human primary hepatocytes (liver), renal tube epithelial cells (kidney), and cardiomyocytes (heart), using the data from (25). One-sided Wilcoxon rank-sum test P values are shown. (B) Box plots showing the cSL load changes after treatment by different classes of chemotherapy drugs in four cell types, using the CMAP data (26). Asterisk indicates that the cSL load change is estimated indirectly from the CMAP drug treatment gene expression signatures (Methods). Strongly mutagenic drugs (n = 6), including alkylating agents (green points) and DNA topoisomerase inhibitors (purple points), lead to a significantly larger cSL load decrease compared to weak or nonmutagenic drugs (n = 5), including taxanes (red points) and vinca alkaloids (blue points); P = 0.03 from a linear model controlling for cell type. HA1E is an immortalized kidney cell line; PHH, primary human hepatocyte; ASC, adipose-derived stem cell; SKB, human skeletal myoblast. (C) Box plots showing the cSL load in samples of different stages of premalignant lesions in the lung (including normal tissue and lung squamous cell carcinoma) (28). The cSL load shows an overall decreasing trend from normal to different pre-cancer stages to cancer (one-sided Wilcoxon rank sum test of normal versus cancer P = 4.47 105; ordinal logistic regression has negative coefficient 28.7, P = 5.89 107).

Further beyond these in vitro findings, analyzing a recently published lung cancer dataset (31), we find that cSL load decreases progressively as cancers develop from normal tissues throughout the multiple stages of premalignant lesions in vivo (normal versus cancer Wilcoxon rank sum test P = 4.47 105, ordinal logistic regression P = 5.89 107 with negative coefficient 28.7; Fig. 4C). These results provide further evidence supporting cSL as a factor that may be involved in cancer development.

Given the role of cSLs in cancer development, we turned to ask whether cSL may also contribute to the tissue/cancer-type specificity of TSGs (10, 32). Specifically, we reasoned that the loss of function of a gene is unlikely to have cancer-driving effects in tissues where its cSL partner genes are lowly expressed, due to the synthetic lethal effect of such co-inactivation on the emerging cancer cells. In other words, this gene is unlikely to be a TSG in such tissues. To study this hypothesis, we obtained a list of TSGs together with the tissues in which their loss is annotated to have a tumor-driving function from the COSMIC database (table S6A) (11). We further identified the cSL partner genes of each such TSG using ISLE (Methods and table S6B) (22). In total, there are 23 TSGs for which we were able to identify more than one cSL partner gene. Consistent with our hypothesis, we find that in most of the cases, the cSL partner genes of TSGs have higher expression levels in the tissues where the TSGs are known drivers compared to the tissues where they are not established drivers (binomial test for the direction of the effect P = 0.023; Fig. 5A). We identified 10 TSGs whose individual effects are significant (FDR < 0.05) and cSL specific (as shown by the random control test), and all these 10 cases exhibit the expected direction of effect (labeled in Fig. 5A and table S6C; two example TSGs, FAS and BRCA1, are shown in Fig. 5B, details are in fig. S8 and Methods). Reassuringly, these findings disappear under randomized control tests involving random partner genes of the TSGs and shuffled TSGtissue type mappings (note S9), further consolidating the role of cancer-specific cSLs of normal tissues in cancer risk and development.

(A) For each tissue-specific TSG gene Gi, the expression levels of its cSL partner genes in the tissue type(s) where gene Gi is a TSG were compared to those where gene Gi is not an established TSG, using GTEx normal tissue expression data. The volcano plot summarizes the result of comparison with linear models. Positive linear model coefficients (x axis) mean that the expression levels of the cSL partner genes are, on average, higher in the tissue(s) where gene Gi is a TSG. Many cases have near-zero P values and are represented by points (half-dots) on the top border line of the plot. Overall, there is a dominant effect of the cSL partner genes of TSGs having higher expression levels in the tissues where the TSGs are known drivers (binomial test P = 0.023). All TSGs with FDR < 0.05 that also passed the random control tests are labeled. (B) Examples of two well-known TSGs, FAS and BRCA1, are given. The heatmaps display the normalized expression levels of their cSL partner genes (rows) in tissues of where these two genes are known to be TSGs [according to the annotation from the COSMIC database (11)] and in tissues where they are not established TSGs (columns), respectively. High and low expressions are represented by red and blue, respectively. For clarity, one typical tissue type where the TSG is a known driver (e.g., testis for FAS) and three other tissue types where the TSG is not an established driver (and the least frequently mutated) are shown.

In this work, we show that the cSL load in normal tissues is a strong predictor of tissue-specific lifetime cancer risk and is much stronger than the pertaining predictive power observed on the individual gene level. Consistently, we find that higher cSL load in the normal tissues from young people is associated with later onset of the cancers of that tissue. As far as we know, no other factor has been previously reported to be predictive of cancer onset age across tissues. Furthermore, cSL load decreases upon carcinogen treatment in vitro and during cancer development through stages of precancerous lesions in vivo. Last, we show that the activity status of cSL partners of TSGs can explain their tissue-specific inactivation.

We have shown that the correlation between cSL and cancer risk in normal tissues may be explained by the fact that many of the cSLs are specific to cancer and have weak or no functional lethal effect in the normal tissues (Figs. 2D and 3B and fig. S5); therefore, normal tissues can bear relatively high cSL loads without being detrimentally affectedquite to the contrary, they become more resistant to cancer due to the latent effect of these cSLs on potentially emerging cancer cells. We emphasize that while we quantified the cSL loads using the normal tissue data from GTEx, the set of cSLs we used was derived exclusively in cancer from completely independent cancer datasets (and without using any information regarding lifetime cancer risk, onset, or tumor suppressor tissue specificity), so there is no circularity involved. The cSL load in normal tissues was computed to reflect the summed effects of individual cSL gene pairs. The underlying assumption is that the low expression of each cSL gene pair is synthetic sick (i.e., reducing cell fitness to some extent) and that the effects from different cSL gene pairs are additive, consistent with the ISLE method of cSL identification (22). Many experimental screenings of SL interactions also rely on techniques such as RNA interference that inhibits gene expression rather than completely knocks out a gene (33), and it is evident that most of the resulting SL gene pairs have milder than lethal effects. While these cSLs likely act via a diverse range of biological pathways and thus do not provide pathway-specific mechanisms, the additive cancer-specific lethal effect of such cSL gene pairs, however, could form a negative force impeding cancer development from normal tissues.

Obviously, as we are studying the across-tissue association between cSL load and cancer risk, it is essential to focus on cSLs that are common to many cancer types (i.e., pan-cancer). Therefore, we focused on cSLs identified computationally by ISLE via the analysis of the pan-cancer TCGA patient data (22). In contrast, most experimentally identified cSLs are obtained in specific cancer cell lines and are thus less likely to be pan-cancer [and possibly, less clinically relevant (22)]. However, for completeness, we also compiled a set of experimentally identified cSLs from published studies (22, 34) (note S1 and table S1B). The corresponding TCL values computed using this set of cSLs correlate significantly with lifetime cancer risk but not with cancer onset age; the correlation with cancer risk is also markedly weaker than that obtained from ISLE-derived cSLs [Spearmans = 0.433, P = 0.024 (fig. S9A), control tests and detailed analysis are explained in note S4]. These experimentally identified cSLs can explain some cases of tissue-specific TSGs including BRCA1 and BRCA2 (fig. S9E) but do not result in overall significant accountability for a large proportion of TSGs present in the analysis (like in Fig. 5A). This corroborates the importance of pan-cancer cSLs and their relevance to cancer risk.

TCL is not likely to be a corollary of NSCD and LADM [while LADM was thought to be closely related to NSCD (6)], as the cSL load is computed by analyzing expression data of bulk tissues, where stem cells occupy only a minor proportion. We have shown that TCL significantly adds to either NSCD or LADM in predicting lifetime cancer risk (Fig. 2, B and C), which also suggests that cSL load is an independent factor correlated with cancer risk with unique underlying mechanisms. Furthermore, NSCD is measured as the product of the rate of tissue stem cell division and the number of stem cells residing in a tissue (2), and we confirmed that TCL is correlated with lifetime cancer risk independent of both of these components (partial Spearmans = 0.510 and 0.567, P = 0.007 and 0.002, respectively; fig. S10, A and B). We additionally tested and verified that proliferation indices computed for the bulk normal tissues do not correlate with lifetime cancer risk across tissues (Spearmans = 0.062, P = 0.77; fig. S10C and note S10). Furthermore, we verified that our observed correlations are not confounded by the number of samples from each cancer or tissue type (fig. S11).

Since cSL load can vary with age, one may wonder whether cSL load could be extended to correlate with age-specific cancer risk within a tissue (as opposed to across tissues). However, variations in cancer risk across tissues and across ages can be driven by different factors. We did not find a consistent correlation between cSL load computed by age range and age-specific cancer risk in all tissue types (note S14 and fig. S15). Another extension to our current research question is studying the effect of higher-order genetic interactions on cancer risk, which is plausible but challenging to study due to the limited knowledge available on such complex interactions.

While revealing cSL as a previously unknown factor associated with cancer development, our study has several limitations. First, because of the importance of using pan-cancer cSLs as discussed above, we mainly relied on the cSLs computationally inferred by ISLE (22) as one of the most comprehensive pan-cancer cSL datasets. However, current cSL prediction algorithms are far from perfect and should not be regarded as the gold standard for general cSL identification. Only a minor fraction of the large number of predicted cSLs have been experimentally validated only in specific cell types. The cSLs inferred by ISLE should be best viewed as a set of candidate cSL pairs that emerge from genetic screen data in vitro but with further support from patient and phylogenetic data. Future studies that provide experimentally validated pan-cancer cSLs are needed to consolidate our current findings. Second, we have relied on analyzing the gene expression data of bulk tissues from GTEx and not the expression data of the specific cells of origin of the corresponding cancers. More refined future analysis is desirable using single-cell data across normal human tissues as such data becomes more widely available. Last, our study does not establish a causal relationship between the cSL load and the risk of cancer, as it is challenging to experimentally perturb a large number of cSLs simultaneously. The results shown are descriptive and association based, and the causal role of SLs in carcinogenesis remains to be studied mechanistically.

Together, our findings demonstrate strong associations between SL and cancer risk, onset time, and context specificity of tumor suppressors across human tissues. This suggests that beyond the effect on cancer after it has developed, cSL could also play an important role during the entire course of carcinogenesis, although further studies are needed to establish causality. While SL has been attracting tremendous attention as a way to identify cancer vulnerabilities and target them, this is the first time that its potential role in mediating cancer development is uncovered.

The cSL gene pairs computationally identified by the ISLE (identification of clinically relevant SL) pipeline were obtained from (22). We used the cSL network identified with FDR < 0.2 for the main text results, containing 21,534 cSL gene pairs, which is a reasonable size representing only about one cSL partner per gene on average. This also allows us to capture the effects of many weak genetic interactions. Nevertheless, we also used the cSL network with FDR < 0.1 (only 2326 cSLs) to demonstrate the robustness of the results to this parameter (notes S1 and S3). Each gene pair is assigned a significance score [the SL-pair score defined in (22)], that a higher score indicates that there is stronger evidence that the gene pair is SL in cancer. Out of these, we used 20,171 cSL gene pairs whose genes are present in the GTEx data (table S1A). The experimentally identified cSL gene pairs were collected from 18 studies [obtained from the supplementary data 1 of Lee et al. (22) except for those from Horlbeck et al. (34)]. Horlbeck et al. (34) provided a gene interaction (GI) score for each gene pair in two leukemia cell lines. Gene pairs with GI scores of <1 in either cell line were selected as cSLs. A total of 27,975 experimentally identified cSLs were obtained, out of which 27,538 have both their genes present in the GTEx data (table S1B).

The V6 release of GTEx (20) RNA sequencing (RNA-seq) data [gene-level reads per kilobase of transcript, per million mapped reads (RPKM) values] was obtained from the GTEx Portal (https://gtexportal.org/home/). The associated sample phenotypic data were downloaded from dbGaP (35) (accession number phs000424.vN.pN). For comparing the level of negative selection to co-inactivation of cSL gene pairs between normal and cancer tissues, the RNA-seq data of TCGA and GTEx as RNA-seq by expectation-maximization (RSEM) values that have been processed together with a consistent pipeline that helps to remove batch effects were downloaded from UCSC Xena (36). The expression data for each tissue type (normal or cancer) was normalized separately (inverse normal transformation across samples and genes) before being used for the downstream analyses. We mapped the GTEx tissue types to the corresponding TCGA cancer types (table S2B), resulting in one-on-many mappings, e.g., the normal lung tissue was mapped to both lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC).

Lifetime cancer risk denotes the chance a person has of being diagnosed with cancer during his or her lifetime. Lifetime cancer risk data (table S2A) are from Tomasetti and Vogelstein (2), which are based on the U.S. statistics from the SEER (Surveillance, Epidemiology, and End Results) database (1). We derived the cancer onset age based on the age-specific cancer incidence data from the SEER database with the standard formula (37). Specifically, for each cancer type, SEER provides the incidence rates for 5-year age intervals from birth to 85+ years old. The cumulative incidence (CI) for a specific age range S is computed from the corresponding age-specific incidence rates (IRi, i S) as CI = 5i SIRi, and the corresponding risk is computed as risk = 1 exp(CI). The onset age for each cancer type (table S3) was computed as the age when the CI from birth is 50% of the lifetime CI (i.e., birth to 85+ years old). Usually, the onset age defined as such is between two ages where the actual CI data are available, so the exact onset age was obtained by linear interpolation. Alternative parameters were used to define onset age (note S3) to show the robustness of the correlation between TCL and cancer onset age based on different definitions.

For each sample, we computed the number of cancer-derived SL gene pairs that have both genes lowly expressed and divided it by the total number of cSLs available to get the cSL load per sample. In the ISLE method described in (22), low expression was defined as having expression levels below the 33 percentile in each tissue or cell type. Thus, the ISLE-derived cSL gene pairs were shown to exhibit synthetic sickness effects when both genes in the gene pair are expressed at levels below the 33 percentile in each tissue, even though this appears to be a very tolerant cutoff (22). We therefore adopted the same criterion for low expression for the main results, although we also explored other low expression cutoffs to demonstrate the robustness of the results (note S3).

TCL of each tissue type is the median value of the cSL loads of all the samples (or a subpopulation of samples) in that tissue, with the cSL load of a sample computed as above. For example, TCL for the older population (age 50 years) is the median cSL load for the samples of age 50 years in each tissue type. For analyzing the correlation between the TCLs computed from GTEx normal tissues and cancer risk, we mapped the GTEx tissue types to the corresponding cancer types for which lifetime risk data are available from Tomasetti and Vogelstein (2), resulting in 16 GTEx types mapped to 27 cancer types (table S2A). Gallbladder nonpapillary adenocarcinoma and osteosarcoma of arms, head, legs, and pelvis are not mapped to GTEx tissues and excluded from our analysis. Similarly for the correlation between TCLs and cancer onset age, we mapped GTEx tissue types to the tissue sites from the SEER database (as given in the data slot site recode ICD-O-3/WHO 2008) by their names (table S3).

To investigate the effect on the single-gene level, we computed the cSL SGL in a paralleling way to the computation of the cSL load. Among all the unique genes constituting the cSL network (i.e., cSL genes), we computed the fraction of lowly expressed cSL genes for each sample as the cSL SGL, where low expression was defined in the same way as the computation of cSL load as elaborated above. Similarly, tissue cSL SGL is the median value of the cSL SGLs of all the samples in a tissue.

The lifetime cancer risks across tissue types were predicted with linear models containing three different sets of explanatory variables: (i) the number of total stem cell divisions (NSCD) alone, (ii) TCL alone, and (iii) NSCD together with TCL. LLR test was used to determine whether model (iii) (the full model) is significantly better than model (i) (the null model) in predicting lifetime cancer risks. The three models were also used to predict the lifetime cancer risks with a leave-one-out cross-validation procedure, and the prediction performances were measured by Spearman correlation coefficient. A similar analysis was performed to predict lifetime cancer risks across tissue types with three linear models involving the level of abnormal DNA methylation levels of the tissues (6): (i) the number of LADM alone, (ii) TCL alone, and (iii) LADM together with TCL.

For each pair of GTEx normalTCGA cancer of the same tissue type (table S2B), we computed the fraction of samples where a cSL gene pair i has both genes lowly expressed (defined above) among the normal samples (fni) and cancer samples (fci) and computed a specific score as rsi = fni fci. We selected the hcSLs as those whose specific scores are greater than the 75% percentile of all scores and lcSLs as those with a score below the 25% percentile (table S4, A and B). We compared SL significance scores between the hcSLs and lcSLs in each tissue using a Wilcoxon rank sum test. For each type of the GTEx normal tissues used in this analysis (i.e., those that can be mapped to TCGA cancer types), we also computed the TCL as above but using the hcSLs, lcSLs, or all cSLs, respectively, and analyzed their correlation with lifetime cancer risk or cancer onset age across the tissues.

We designed an empirical enrichment test as below to account for the fact that each cSL consists of two genes. For the hcSLs in each tissue type and each given pathway from the Reactome database (38), we computed the odds ratio (OR) for the overlap between the genes in hcSLs and the genes within the pathway based on the Fishers exact test procedure, with the background being all the genes in the ISLE-inferred cSLs. A greater than 1 OR indicates that the hcSLs are positively enriched for the genes of the pathway. To determine the significance of the enrichment, we repeatedly and randomly sampled the same number of cSLs as that of the hcSLs, computed the ORs similarly, and computed the empirical P value as the fraction of cases where the OR from the random cSLs is greater than that from the hcSLs. We corrected for multiple testing across pathways with the Benjamini-Hochberg method.

The phase I CMAP (26) data were downloaded from the Gene Expression Omnibus database (GSE92742). Level 5 data that represent the consensus perturbation-induced differential expression signature were used. We focused on CMAP data that involve treatment by specific classes of chemotherapy drugs (mutagenic: alkylating agents and DNA topoisomerase inhibitors; nonmutagenic: taxanes and vinca alkaloids) in normal cell lines or primary cells. We identified a total of 11 drugs tested in four cell types. Given the signature (z score) of a drug treatment in a cell, we estimated the drug-induced cSL load change as follows1|S|((i,j)SI(zi<0.5zj<0.5)(i,j)SI(zi>0.5zj<0.5))where S is the set of cSLs, and |S| is the total number of cSL gene pairs. A gene pair is denoted by (i, j), and zi and zj are the z scores of gene i and gene j, respectively. I() is the indicator function. Intuitively, the above formula quantifies the number of cSL gene pairs where both genes are down-regulated with a z score cutoff of 0.5 (i.e., contributing to cSL load increase), minus the number of cSL gene pairs where either gene is up-regulated with a z score cutoff of 0.5 (i.e., contributing to cSL load decrease), normalized by the total number of cSL gene pairs. We then tested whether the mutagenic drugs lead to a larger decrease in cSL load compared to nonmutagenic drugs with a linear model that controls for both cell type and drug.

We obtained the list of TSGs and their associated tissue types from the COSMIC database (11) (https://cancer.sanger.ac.uk/cosmic/download, the Cancer Gene Census data; table S6A). For each TSG, their cSL partner genes were identified using the ISLE pipeline (22) with an FDR cutoff of 0.1 (table S6B). Here, the FDR cutoff is more stringent than that used for the pan-cancer genome-wide cSL network (FDR < 0.2 for the main results) since, here, FDR correction was performed for each TSG, corresponding to a much lower number of multiple hypotheses. As a result, the FDR correction has more power, and a relatively more stringent cutoff can give rise to a more reasonable number of cSL partner genes per TSG. We focused our analysis on 23 TSGs for which more than one cSL partner genes were identified (no cSL partner was identified for most of the other TSGs). The expression levels of the cSL partner genes were then compared between tissue type(s) where the TSG is a known driver and the rest of the tissues where the TSG is not an established driver with linear models. Specifically, the expression levels of the cSL partners were modeled with two explanatory variables: (i) driver status of the TSG in the tissue (binary) and (ii) cSL partner gene (categorical, indicating each of the cSL partner genes of a TSG). The coefficient and P value associated with variable (i) were used to analyze the general trend of differential expression among the cSL partner genes. Positive coefficients of variable (i) means that the expression levels of the cSL partner genes are, on average, higher in the tissue(s) where the TSG is a known driver compared to those in the tissues where the TSG is not an established cancer driver.

Read the original here:
Synthetic lethality across normal tissues is strongly associated with cancer risk, onset, and tumor suppressor specificity - Science Advances

New Approaches to the Treatment of Relapsed or Refractory Diffuse Large B-cell Lymphoma – Targeted Oncology

In the United States, the most common of the aggressive non-Hodgkin lymphomas (NHLs) is diffuse large B-cell lymphoma (DLBCL), which accounts for between 22% and 24% of newly diagnosed B-cell NHL cases.1 Although DLBCL can affect children and young adults, it is most commonly diagnosed in individuals between the ages of 65 and 74 years, with a median age at diagnosis of 66 years.2,3 Given the aggressive nature of DLBCL, patients often present with lymphadenopathy, extranodal involvement, and other constitutional symptoms that require immediate treatment.1

The treatment spectrum for DLBCL has expanded significantly in recent years, particularly for patients with relapsed or refractory (R/R) disease. Mechanisms of action differ greatly among agents, reflecting the complex pathophysiology and genetic variations of the disease. This article reviews the advances in DLBCL understanding that have led to the approval of new agents and subsequent utilization of new mechanisms.

The current standards of care for first-line DLBCL treatment include the combination chemoimmunotherapy regimen of rituximab, cyclophosphamide, doxorubicin hydrochloride, vincristine sulfate, and prednisone (R-CHOP). The varying numbers of cycles and use in combination with or without radiotherapy (RT) depends upon the stage of disease at presentation.1 The addition of rituximab to CHOP was associated with a 2-year event-free survival of 57% in elderly patients in a 2002 randomized trial (LNH-98.5), which, along with results of other trials, led to the FDA approval of this combination therapy.4,5 Although durable remission can be achieved with R-CHOP in about 60% of patients, its use has resulted in poorer long-term outcomes for patients with double-hit and triple-hit lymphomas (DHL and THL).1

In 2007, the International Harmonization Project issued guidelines on malignant lymphoma response criteria, defining relapsed disease as consisting of new lesions greater than 1.5 cm in any axis during or after the completion of therapy or a 50% or greater increase in the sum of the product of diameters of a previously involved node(s) or other lesion(s).6 The authors also defined refractory, or progressive, disease as entailing a 50% or greater increase in the size of a lymph node with a prior short-axis diameter of less than 1.0 cm to a size of 1.5 cm 1.5 cm (or a long-axis size of > 1.5 cm).6

For patients with R/R disease, high-dose chemotherapy and autologous stem cell transplant (ASCT) may offer the chance for cure, but several factors may limit the utility of this approach. For example, in the treatment of patients with MYC-positive R/R DLBCL, ASCT is considered controversial because it has produced poorer outcomes in patients with DHL.1 Additionally, patients who are older or have comorbidities may be inappropriate candidates for this approach,7 and patients with disease that is unresponsive to second-line chemotherapy may have poorer prognoses (ie, poorer rates of long-term survival) and incur added toxicity from the chemotherapy.7 Even when including patients who undergo high-dose, salvage chemotherapy and subsequent ASCT, patients with R/R DLBCL have a 1-year survival rate of 28%.1 Hence, in a search for improved outcomes in the R/R setting, clinical studies have focused on DLBCL subtypes, especially in those ineligible for transplant or who have relapsed following transplant.1

Another option for patients in the relapsed setting is chimeric antigen receptor (CAR) T-cell therapy, which entails the genetic modification of autologous T cells via cloned DNA plasmids carrying a viral recombinant vector in addition to T-cell receptor-expressing genes. CAR T-cell therapy plays an important role in the R/R DLBCL setting, with reported 2-year remissions and a complete response (CR) rate in 40% of patients and 25% DHL/THL patients.1 Other therapeutic classes that have been explored for DLBCL include phosphoinositide 3-kinase (PI3K) inhibitors, B-cell lymphoma 2 (BCL2) inhibitors, and checkpoint inhibitors.1,8-10

Given reduced survival in patients who are unresponsive to subsequent lines of therapy and the toxicity involved, a great need exists for novel agents in the R/R DLBCL setting. Recent entrants to the R/R DLBCL treatment landscape include the antibody-drug conjugate (ADC) polatuzumab vedotin-piiq, the selective inhibitor of nuclear export, selinexor, and the monoclonal antibody tafasitamab-cxix (TABLE 111-20).

Polatuzumab vedotin-piiq was approved by the FDA in 2019 and is indicated in combination with bendamustine and rituximab in adults with RR DLBCL not otherwise specified, following at least 2 previous therapies.11 It is an ADC wherein the monoclonal antibody is linked to an antimitotic agent, monomethyl auristatin E (MMAE). The ADC targets the B-cell surface protein CD79B and, after binding to the surface protein, is internalized by the cell. Lysosomal enzymes then cleave the link between the antibody and MMAE, the latter of which binds microtubules, thereby inhibiting cell division and inducing apoptosis.11

A 2020 phase 1b/2 study (NCT02257567) randomized patients with R/R DLBCL who were ineligible for ASCT to receive polatuzumab vedotin-piiq with bendamustine and rituximab (pola-BR) or bendamustine and rituximab (BR) alone.12 The phase 2 primary end point was CR; secondary end points included overall response rate (ORR) at end of treatment, superior overall response, duration of response (DOR), and progression-free survival (PFS) assessed per independent review committee (IRC).12 With a median follow-up of 22.3 months, the CR was significantly higher in the pola-BR group (40% vs 17.5% in the BR group; P = .026).12 Overall survival rate was also significantly higher in the pola-BR group (12.4 vs 4.7 months in the BR group; HR, 0.42; 95% CI, 0.24-0.75; P = .002).12 Similarly, median PFS was significantly longer at 9.5 months in the pola-BR group compared with 3.7 months in the BR group (HR, 0.36; 95% CI, 0.21-0.63; P < .001).12 Also, DOR was longer at 12.6 months in the pola-BR group vs 7.7 months in the BR group (HR, 0.47; 95% CI, 0.19-1.14).12 Finally, the pola-BR group had a 58% reduction in risk of death compared with the BR group (HR, 0.42; 95% CI, 0.24-0.75; P = .002).12 In terms of safety, grade 3/4 anemia, neutropenia, thrombocytopenia, and peripheral neuropathy occurred more frequently in the pola-BR group than in the BR group.12 Polatuzumab vedotin-piiq was deemed an effective agent that might provide a therapeutic option for patients with R/R DLBCL who were not ideal candidates for CAR T-cell therapy.12

In 2020, selinexor was approved by the FDA for use in adult patients with R/R DLBCL (including follicular lymphoma-derived DLBCL) after at least 2 lines of systemic treatment.13 Selinexor inhibits nuclear export of tumor suppressor proteins by blocking exportin 1.13

The FDA approval was based on results of the open-label single-arm phase 2 SADAL trial (NCT02227251), which included patients 18 years or older with DLBCL (based on pathologic confirmation) with an Eastern Cooperative Oncology Group (ECOG) score of 2 or less, who had 2 to 5 lines of prior therapy, and who had progressed following or were ineligible for ASCT.14 The primary end point of the SADAL trial was ORR (comprising patients with CR or PR per 2014 Lugano criteria), with secondary end points consisting of DOR and disease control rate.14 Patients received the 60-mg oral selinexor on the first and third day of each week until disease progression or unacceptable toxicity occurred.14

The updated phase 2b ORR was 28.3% with a disease control rate of 37% (95% CI, 28.6-46.0). Of 36 responders, CRs were reported in 13 evaluable patients and PRs were reported in 23 patients. At a median follow-up of 11.1 months, the median DOR was 9.3 months (95% CI, 4.8-23.0). For those with a CR, median DOR was 23.0 months (95% CI, 10.4-23.0); median DOR was 4.4 months for those with a PR (95% CI, 2.0not evaluable).14,15 To address potential differences by subtype, the SADAL trial also included a subgroup analysis of patients with the germinal center B-cell (GCB)like subtype (n = 59), which demonstrated an ORR of 33.9%, a 14% CR rate, and a 20% PR rate, whereas the patients with a non-GCB subtype (n = 63) had an ORR of 20.6%. At the time of data cutoff, 7% (n = 9) of patients showed continuing response.14,15 The SADAL trial also included 5 patients with the unclassified subtype, in 1 of whom a CR was achieved and in 2 of whom a PR was achieved.15 With respect to safety, 98% of patients in the SADAL trial had at least 1 treatment-emergent adverse event (TEAE). The most frequent grade 3/4 events were thrombocytopenia, neutropenia, anemia, fatigue, hyponatremia, and nausea.14 Among serious AEs affecting 48% of patients, the most common were pyrexia, pneumonia, and sepsis.14 Gastrointestinal AEs were reported in 80% of patients, hyponatremia in 61%, and central neurologic events (which included dizziness and altered mental status) in 25%.16 Trial investigators concluded that selinexor improved survival considerably and that it presented a nonchemotherapy oral option for patients with R/R DLBCL.14

Tafasitamab-cxix is a CD19-targeting monoclonal antibody that gained FDA approval in 2020 for use with lenalidomide in adults with R/R DLBCL who are ineligible for ASCT, including patients with low-grade lymphoma derived DLBCL.17 Tafasitamab-cxix binds to the pre-B and mature B-lymphocyte surface antigen CD19, which is expressed in DLBCL and other B-cell malignancies.17 Tafasitamab-cxix, once bound to CD19, facilitates B-lymphocyte lysis via apoptosis and immune effector mechanisms that encompass antibody-dependent cellular cytotoxicity and antibody-dependent cellular phagocytosis.17

The FDA approval of tafasitamab-cxix was based on data from the phase 2, single-arm, multicenter, open-label L-MIND trial (NCT02399085).17,18 The L-MIND trial included patients 18 years or older with R/R DLBCL who had received 1 to 3 previous therapies ( 1 of which incorporated a CD20-directed regimen), had an ECOG score of 0 to 2, and were ASCT ineligible.18 Patients were administered tafasitamab-cxix and lenalidomide in 28-day cycles and continued to receive tafasitamab-cxix every 2 weeks after cycle 12 until disease progression.18 Objective response rate (ie, PR and CR) was the primary end point per IRC, which implemented PET imaging; secondary end points included investigator-assessed objective response rate, DOR, OS, PFS, biomarker analyses, and safety.18 Eighty patients were included in the full analysis set (FAS), receiving tafasitamab-cxix plus lenalidomide.18 Of the FAS, the objective response rate was 60.0% (95% CI, 48.4%-70.8%) and the CR rate was 42.5% (34/80).18 The rate of patients achieving a 12-month DOR rate was comparable across subgroups, with 70.5% of patients who received 1 prior line of therapy achieving a 12-month DOR (95% CI, 47.2%-85.0%) and 72.7% of patients who had 2 or more prior lines of therapy achieving a 12-month DOR (95% CI, 46.3%-87.6%).18

Outcomes in patients with GCB DLBCL (n = 37) were promising, with an objective response rate of 48.6%, a 12-month DOR rate of 53.5%, and a 12-month OS rate of 65.4% (based upon the Hans algorithm). Outcomes in patients with non-GCB DLBCL (n = 21) were an improvement over those with the GCB subtype, with an objective response rate of 71.4%, a 12-month DOR rate of 83.1%, and a 12-month OS rate of 84.2%.18 IRC-evaluated data from a 2-year follow up of the L-MIND trial showed an objective response rate of 58.8% (47/80) and CR rate of 41.3% (33/80).19 The 2-year follow up data also showed a median DOR of 34.6 months, with a 31.6-month median OS and a 16.2-month median PFS.19

Safety data from the preliminary L-MIND trial results showed that the most frequent TEAEs (of any grade) were neutropenia (48%), thrombocytopenia (32%), anemia (31%), diarrhea (30%), pyrexia (22%), and asthenia (20%).20 A lenalidomide dose reduction was required in 42% of patients; 72% of patients could remain on daily lenalidomide at 20 mg or higher.20 Trial investigators concluded that the combination of tafasitamab-cxix and lenalidomide was well tolerated and did not lead to compounded AEs.20

The promising data from recent trialsparticularly from their DLBCL subtype based subgroupsunderscore the importance of understanding the unique prognoses and responses that these subtypes confer on patient outcomes. The establishment of DLBCL subtypes as prognostic and therapeutic response factors has fueled a search for more specific molecular targets in the disease process. In addition, the importance of subtype characterization is evidenced by ongoing diagnostic assay development (for use in conjunction with immunohistochemistry). As exemplified by the patient populations in these trials, new therapeutic options with distinct mechanisms of actions are needed for patients with R/R DLBCL who are ineligible for ASCT. Multiple studies of targeted agents in the R/R DLBCL setting are under way that include CAR T-cell, bispecific T-cell engager, programmed death receptor 1 (PD-1) inhibitor, and BCL2 inhibitor therapies.1 Continued development of clinically applicable diagnostics holds promise for improved prognostic capability and assessment of therapeutic response. With improved diagnostics, further elucidation of DLBCL-driver mutations can continue to provide additional DLBCL subtype-specific options and, hence, more treatments tailored to individual patients.

References 1. Liu Y, Barta SK. Diffuse large B-cell lymphoma: 2019 update on diagnosis, risk stratification, and treatment. Am J Hematol. 2019;94(5):604-616. doi:10.1002/ajh.25460 2. Diffuse large B-cell lymphoma. Lymphoma Research Foundation. Accessed October 12, 2020. https://lymphoma.org/aboutlymphoma/nhl/dlbcl/ 3. Cancer stat facts: NHL diffuse large B-cell lymphoma (DLBCL). National Cancer Institute. Accessed October 12, 2020. https://seer.cancer.gov/statfacts/html/dlbcl.html 4. Coiffier B, Lepage E, Briere J, et al. CHOP chemotherapy plus rituximab compared with CHOP alone in elderly patients with diffuse large B-cell lymphoma. N Engl J Med. 2002;346(4):235-242. doi:10.1056/NEJMoa011795 5. Rituxan plus CHOP approved for diffuse large B-cell lymphoma. Cancer Network. February 28, 2006. Accessed November 6, 2020. https://www.cancernetwork.com/view/rituxan-plus-chop-approved-diffuse-large-b-cell-lymphoma 6. Cheson BD, Pfistner B, Juweid ME, et al; International Harmonization Project on Lymphoma. Revised response criteria for malignant lymphoma. J Clin Oncol. 2007;25(5):579-586. doi:10.1200/JCO.2006.09.2403 7. Elstrom RL, Martin P, Ostrow K, et al. Response to second-line therapy defines the potential for cure in patients with recurrent diffuse large B-cell lymphoma: implications for the development of novel therapeutic strategies. Clin Lymphoma Myeloma Leuk. 2010;10(3):192-196. doi:10.3816/CLML.2010.n.030 8. Oki Y, Kelly KR, Flinn I, et al. CUDC-907 in relapsed/refractory diffuse large B-cell lymphoma, including patients with MYC-alterations: results from an expanded phase I trial. Haematologica. 2017;102(11):1923-1930. doi:10.3324/haematol.2017.172882 9. Ansell S, Gutierrez ME, Shipp MA, et al. A phase 1 study of nivolumab in combination with ipilimumab for relapsed or refractory hematologic malignancies (CheckMate 039). Blood. 2016; 128(22):183. doi:10.1182/blood.V128.22.183.183 10. Lesokhin AM, Ansell SM, Armand P, et al. Nivolumab in patients with relapsed or refractory hematologic malignancy: preliminary results of a phase Ib study. J Clin Oncol. 2016;34(23):2698-2704. doi:10.1200/JCO.2015.65.9789 11. POLIVY. Prescribing information. Genentech, Inc; 2020. Accessed October 22, 2020. https://www.gene.com/download/pdf/polivy_prescribing.pdf 12. Sehn LH, Herrera AF, Flowers CR, et al. Polatuzumab vedotin in relapsed or refractory diffuse large B-cell lymphoma. J Clin Oncol. 2020;38(2):155-165. doi:10.1200/JCO.19.00172 13. XPOVIO. Prescribing information. Karyopharm Therapeutics, Inc; 2020. Accessed October 22, 2020. https://www.karyopharm.com/wp-content/uploads/2019/07/NDA-212306-SN-0071-Prescribing-Information-01July2019.pdf 14. Kalakonda N, Maerevoet M, Cavallo F, et al. Selinexor in patients with relapsed or refractory diffuse large B-cell lymphoma (SADAL): a single-arm, multinational, multicentre, open-label, phase 2 trial. Lancet Haematol. 2020;7(7):e511-e522. doi:10.1016/S2352-3026(20)30120-4 15. Karyopharm reports updated data from the phase 2b SADAL study at the 2019 International Conference on Malignant Lymphoma. News release. Karyopharm. June 19, 2019. Accessed June 28, 2020. https://www.globenewswire.com/news-release/2019/ 06/19/ 1871363/0/en/Karyopharm-Reports-Updated-Data-from-the-Phase-2b-SADAL-Study-at-the-2019-International-Conference-on-Malignant-Lymphoma.html 16. FDA approves selinexor for relapsed/refractory diffuse large B-cell lymphoma. News release. FDA. June 22, 2020. Accessed June 28, 2020. https://www.fda.gov/drugs/resources-information-approved-drugs/fda-approves-selinexor-relapsedrefractory-diffuse-large-b-cell-lymphoma 17. Monjuvi. Prescribing information. MorphoSys US Inc; 2020. Accessed October 22, 2020. https://www.monjuvi.com/pi/monjuvi-pi.pdf 18. Duell J, Maddocks KJ, Gonzalez-Barca E, et al. Subgroup analyses from L-Mind, a phase II study of tafasitamab (MOR208) combined with lenalidomide in patients with relapsed or refractory diffuse large B-cell lymphoma. Blood. 2019;134(suppl 1):1582. doi:10.1182/blood-2019-122573 19. MorphoSys and Incyte announce long-term follow-up results from L-MIND study of tafasitamab in patients with r/r DLBCL. News release. Morpho-Sys. May 14, 2020. Accessed June 26, 2020. https://www.morphosys.com/media-investors/media-center/morphosys-and-incyte-announce-long-term-follow-up-results-from-l-mind 20. Salles GA, Duell J, Gonzlez-Barca E, et al. Single-arm phase II study of MOR208 combined with lenalidomide in patients with relapsed or refractory diffuse large B-cell lymphoma: L-Mind. Blood. 2018;132(suppl 1):227. doi:10.1182/blood-2018-99-113399

More:
New Approaches to the Treatment of Relapsed or Refractory Diffuse Large B-cell Lymphoma - Targeted Oncology

CAR T-Cell Therapies Are Set to Expand Into More Hematologic Malignancy Indications – Targeted Oncology

Multiple chimeric antigen receptor (CAR) T-cell therapies for the treatment of lymphomas and multiple myeloma have moved forward in the regulatory process, with 1 new FDA approval in 2020 and others anticipated in the near future.

In July, brexucabtagene autoleucel (Tecartus; KTEX19) received accelerated approval for the treatment of adult patients with relapsed or refractory mantle cell lymphoma (MCL) based on the results of the phase 2 ZUMA-2 trial (NCT02601313), bringing the treatment landscape of this hematologic malignancy into a new era.1

This approval is only the very beginning, and we are walking into a sophisticated CAR T-cell therapy era with many constructs being designed with [different mechanisms of action], Michael Wang, MD, said in an interview with Targeted Therapies in Oncology (TTO).

Additional actions by the FDA this year included granting priority review designations to lisocabtagene maraleucel (liso-cel) for the treatment of adult patients with relapsed or refractory (R/R) large B-cell lymphoma, after at least 2 prior therapies,2 as well as to idecabtagene vicleucel (ide-cel; bb2121)as treatment of adult patients with multiple myeloma who have received at least 3 prior therapies, including an immunomodulatory drug (IMiD), a proteasome inhibitor (PI), and an anti-CD38 antibody.3

The approval of brexucabtagene autoleucel, an antiCD19 CAR T-cell product, in MCL was based on objective response rate (ORR) data from patients treated on a single-arm trial who had previously received anthracycline- or bendamustine-containing chemotherapy, an anti-CD20 antibody, and a Bruton tyrosine kinase inhibitor (n = 74).2,4 Eligible patients received leukapheresis and optional bridging therapy, followed by conditioning chemotherapy and a single infusion of brexucabtagene autoleucel 2 106CAR T cells/kg.

The results of ZUMA-2 were published in the New England Journal of Medicine in April and demonstrated a 93% (95% CI, 84%-98%) ORR in 60 response-evaluable patients, 67% (95% CI, 53%-78%) of whom had a complete response (CR). ORRs were consistent across key patient subgroups. Two patients (3%) each had stable and progressive disease.

Progression-free and overall survival (OS) rates at 12 months were 61% and 83%, respectively, and 57% of patients remained in remission at the 12.3-month median follow-up.4 Cytokine release syndrome (CRS) was the most concerning adverse event, occurring in 91% of patients; grade 3 or higher CRS occurred in 15%.

Notably, the patient cohort comprised patients with a median of 3 prior lines of therapy (range, 1-5) and more than half (56%) were considered to have intermediateor high-risk features by the simplified Mantle Cell Lymphoma International Prognostic Index at baseline.

Before CAR T-cell therapy, we did not have any effective means [of getting patients with high-risk MCL into remission]. We used allogeneic transplantation [and] were able to put some of the patients into a long-term remission, but at a heavy price of mortality, said Wang, a professor in the Department of Lymphoma & Myeloma, Division of Cancer Medicine at The University of Texas MD Anderson Cancer Center in Houston. Overall, this brings hope to the high-risk patient population. It looks as though fewer patients are relapsing.

Lisocabtagene Maraleucel In February, the FDA granted liso-cel a priority review designation, an action supported by the safety and efficacy findings of the phase 1 TRANSCEND-NHL-001 trial (NCT02631044).2

Histologic subtypes eligible for treatment included diffuse large B-cell lymphoma (DLBCL); high-grade double- or triple-hit B-cell lymphoma; transformed DLBCL from indolent lymphoma; primary mediastinal B-cell lymphoma; and grade 3B follicular lymphoma. Patients were administered 2 sequential infusions of CD8+ and CD4+ CAR T cells following optional bridging therapy and lymphodepleting chemotherapy and were assigned to 1 of 3 target dose levels: 50 106 (1 or 2 doses), 100 106 , or 150 106 CAR-positive T cells. Investigators determined that the recommended target dose was 100 106 CAR-positive T cells.

In the 256 patients who received at least 1 dose of liso-cel and were included in the efficacy-evaluable group, the ORR was 73% (95% CI, 67%-78%), with 53% (95% CI, 47%-59%) achieving a CR. Investigators observed all-grade CRS (42%) and neurological events (30%), but most cases were grade 1 or 2 in severity.

Due to relatively low rates of CRS and neurological events, the administration of liso-cel has been explored in both the inpatient and outpatient settings. One that included a cohort of patients treated in the outpatient setting with proper monitoring versus the traditional inpatient setting demonstrated consistent safety.6

Based on these results, the indication is that you can deliver [liso-cel] in the outpatient setting and the outcomes are good compared with those treated in the inpatient setting, explained study author Carlos R. Bachier, MD, the director of cellular research at Sarah Cannon in Nashville, Tennessee, in an interview with TTO. Aside from that, they also showed that liso-cel could be safely administered outside of university programs and in more community-based programs, most of them being aligned [with] or part of stem cell and bone marrow transplant programs.

The target action date for a decision on the biologics license application (BLA) for liso-cel was extended twice in 2020 and remains under review. In May, the FDA moved the Prescription Drug User Fee Act (PDUFA) goal date out 3 months from its original August deadline.2,7 Bristol Myers Squibb, the company responsible for developing the product, submitted additional information to the agency following the initial BLA submission, which resulted in more review time. Once again, the target action date was pushed in November, this time due to incomplete manufacturing facility inspections resulting from ongoing travel restrictions due to COVID-19. The FDA provided no new action date.8

For patients with multiple myeloma, the B-cell maturation antigen (BCMA)-targeting CAR T-cell therapy idecel is currently under review for approval in patients who have received at least 3 prior therapiesincluding an immunomodulatory drug (IMiD), a proteasome inhibitor (PI), and an anti-CD38 antibodybased on results of the phase 2 KarMMa trial (NCT03361748).9

Updated trial results were presented at the American Society of Clinical Oncology 2020 Virtual Scientific Program, and showed that both the primary and key secondary end points of ORR and CR rate were 75% and 33%, respectively. The median duration of response was 10.7 months, and the median progression-free survival was 8.8 months in all patients receiving ide-cel. Corresponding medians were 19.0 and 20.2 months among those achieving a CR or stringent CR. The median OS was 19.4 months in all treated patients.

The 128 patients treated received 1 of 3 target dose levels: 150, 300, or 450 106 CAR-positive T cells. The investigators noted that the highest efficacy outcomes were seen in patients in the 450 106 CAR-positive T-cell group, with an ORR of 82% and a 39% CR rate.

The incidence of CRS was 84% across the treatment cohort and increased with higher target doses. Overall, less than 6% of patients have grade 3 or higher CRS and only 1 patient in the highest target dose cohort had a grade 5 event. Neurological toxicity was low across target doses, with no grade 4 or 5 events reported.

At baseline, the majority of patients (51%) had high tumor burden, 39% had extramedullary disease, and 35% had high-risk cytogenetics including deletion 17p or translocations in t(4;14) or t(14;16).

In May, the FDA issued a refusal letter regarding the BLA for ide-cel because the Chemistry, Manufacturing, and Control (CMC) module required more information before they could complete the review.10 In September, the resubmitted application received a priority review and the agency assigned a PDUFA action date of March 27, 2021.11

If approved, ide-cel would be the first CAR T-cell therapy available for the treatment of patients with multiple myeloma.

References:

1. FDA approves brexucabtagene autoleucel for relapsed or refractory mantle cell lymphoma. FDA. Updated July 27, 2020. Accessed November 18, 2020. https://bit. ly/3pEDQV5

2. US Food and Drug Administration (FDA) accepts for priority review Bristol-Myers Squibbs biologics license application (BLA) for lisocabtagene maraleucel (liso-cel) for adult patients with relapsed or refractory large B-cell lymphoma. Press release. Bristol Myers Squibb. February 13, 2020. Accessed November 18, 2020. https:// bit.ly/37ruQbs

3. US Food and Drug Administration (FDA) accepts for priority review Bristol Myers Squibb and bluebird bio application for anti-BCMA CAR T cell therapy idecabtagene vicleucel (ide-cel, bb2121). Press release. Bristol Myers Squibb. September 22, 2020. Accessed November 18, 2020. https://bit.ly/3kDhakH

4. Wang M, Munoz J, Goy A, et al. KTE-X19 CAR T-cell therapy in relapsed or refractory mantle-cell lymphoma. N Engl J Med. 2020;382(14):1331-1342. doi:10.1056/ NEJMoa1914347

5. Abramson JS, Palomba ML, Gordon LI, et al. Lisocabtagene maraleucel for patients with relapsed or refractory large B-cell lymphomas (TRANSCEND NHL 001): a multicentre seamless design study. Lancet. 2020;396(10254):839-852. doi:10.1016/ S0140-6736(20)31366-0

6. Bachier CR, Palomba ML, Abramson JA, et al. Outpatient treatment with lisocabtagene maraleucel (liso-cel) in 3 ongoing clinical studies in relapsed/refractory (R/R) large B cell non-Hodgkin lymphoma (NHL), including second-line transplant noneligible (TNE) patients: Transcend NHL 001, Outreach, and PILOT. Paper presented at: 2020 Transplantation & Cellular Therapy Meetings; February 19-23, 2020; Orlando, FL. Abstract 29. Accessed November 18, 2020. bit.ly/37I7DC9

7. Bristol Myers Squibb provides update on biologics license application (BLA) for lisocabtagene maraleucel (liso-cel). Press release. Bristol Myers Squibb. May 6, 2020. Accessed November 18, 2020.https://bit.ly/2YFWAs8

8. Bristol Myers Squibb provides regulatory update on lisocabtagene maraleucel (liso-cel). News release. Business Wire. November 16, 2020. Accessed November 18, 2020. https://bwnews.pr/3pKQMZI

9. Bristol Myers Squibb and bluebird bio announce submission of biologics license application (BLA) for anti-BCMA CAR T cell therapy idecabtagene vicleucel (ide-cel, bb2121) to FDA. Press release. Bristol Myers Squibb. March 31, 2020. Accessed November 18, 2020. https://bit.ly/2JwKbxO

10. Bristol Myers Squibb and bluebird bio provide regulatory update on idecabtagene vicleucel (ide-cel, bb2121) for the treatment of patients with multiple myeloma. News release. Business Wire. May 13, 2020.Accessed November 18, 2020. https:// bwnews.pr/3cpgJa1

11. US Food and Drug Administration (FDA) accepts for priority review Bristol Myers Squibb and bluebird bio application for anti-BCMA CAR T cell therapy idecabtagene vicleucel (ide-cel, bb2121). Press release. Bristol Myers Squibb. September 22, 2020. Accessed November 18, 2020. https://bit.ly/3kDhakH

Read more:
CAR T-Cell Therapies Are Set to Expand Into More Hematologic Malignancy Indications - Targeted Oncology

ElevateBio’s HighPassBio Presents on Novel T Cell Receptor Cell Therapy for Leukemia Relapse at 62nd Annual ASH Meeting – Business Wire

CAMBRIDGE, Mass.--(BUSINESS WIRE)--HighPassBio, an ElevateBio portfolio company dedicated to advancing novel targeted T cell immunotherapies, today discussed the ongoing Phase 1 trial of the companys lead product candidate, an engineered T cell receptor (TCR) T cell therapy targeting HA-1 expressing cancer cells in an oral presentation at the 62nd American Society of Hematology (ASH) Annual Meeting. The Phase 1 clinical trial, which is being conducted by researchers at Fred Hutchinson Cancer Research Center, is designed to assess the feasibility, safety, and efficacy of this novel cell therapy in the treatment of leukemia following hematopoietic stem cell transplant (HSCT).

The prognosis for leukemia patients whove relapsed or who have residual disease following allogeneic hematopoietic stem cell transplantation is often poor, but we believe that by targeting the minor H antigen, HA-1, through a novel T cell immunotherapy, we can potentially treat and prevent subsequent relapse, said Elizabeth Krakow, M.D., MSc., Assistant Professor, Clinical Research Division, Fred Hutchinson Cancer Research Center, principal investigator of the study, and presenting author. We have observed early promising indicators of anti-leukemic activity following treatment in this trial. We are eager to expand the trial to additional patients as we continue to research the feasibility, safety, and efficacy of this approach.

The abstract for the presentation titled Phase 1 Study of Adoptive Immunotherapy with HA-1-Specific CD8+ and CD4+ Memory T Cells for Children and Adults with Relapsed Acute Leukemia after Allogeneic Hematopoietic Stem Cell Transplantation (HCT): Trial in Progress, can be found on the ASH website under the abstract number 137726.

To date, four patients, including one pediatric patient, have received a total of six infusions in the Phase 1 clinical trial. Patient characteristic data was shared in the oral presentation at ASH, including documented HA-1 TCR T cell persistence in blood and bone marrow up to 18 months. In some patients, clear in vivo anti-leukemic activity was observed at the first dose level, including a subject with aggressive, highly refractory T-ALL and early post-HCT relapse. No significant toxicities attributed to the T cells have been observed, including no infusion reactions or evidence of cytokine release syndrome or graft versus host disease.

The Phase 1 clinical trial is currently recruiting adult and pediatric patients who have residual disease or relapsed leukemia or related conditions following HSCT. As part of the trial, transplant patients and prospective donors may be recruited to participate in the genetic screening portion to determine eligibility. More details are available on clinicaltrials.gov under the study ID number NCT03326921.

About TCR-Engineered T Cell Therapy

A key role of the immune system is to detect tumor antigens, engage T cells, and eradicate the tumor. However, the immune response to tumor antigens varies and is often insufficient to prevent tumor growth and relapse. An approach known as adoptive T cell therapy, using T cell receptors, or TCRs, can overcome some of the obstacles to establishing an effective immune response to fight off the target tumor. TCRs are molecules found on surface of T cells that can recognize tumor antigens that are degraded to small protein fragments inside tumor cells. Unlike CAR T cells that recognize only surface antigens, TCRs can recognize small protein fragments derived from intracellular and surface antigens offering a more diverse way to attack tumors. These small protein fragments show up on the tumor cell surface, with another protein called major histocompatibility complex (MHC), that are recognized by the TCRs and consequently signal the bodys immune system to respond to fight off and kill the tumor cells.

Tumor-specific TCRs can be identified and then engineered into T cells that recognize and attack various types of cancers, representing a novel approach to treating and potentially preventing disease.

Adoptive T cell therapy can be applied to tackling relapse of leukemia post hematopoietic stem cell transplant (HSCT) by targeting the antigens expressed only by the patients native cells, and not by the cells from the stem cell transplant donor. HA-1, a known minor histocompatibility antigen, is expressed predominantly or exclusively on hematopoietic cells, including leukemic cells. There is evidence that T cells specific for HA-1 can induce a potent and selective antileukemic effect. HA-1 TCR T cell therapy is a new investigational immunotherapy for the management of post transplantation leukemia relapse.

About Leukemia post HSCT Treatment and the Risk of Relapse

Leukemia, a cancer of the blood or bone marrow characterized by an abnormal proliferation of blood cells, is the tenth most common type of cancer in the U.S. with an estimated 60,140 new cases and 24,400 deaths in 2016. Leukemia arises from uncontrolled proliferation of a specific type of hematopoietic (blood) cell that is critical for a functional immune system. As a result, when patients are given very high doses of chemotherapy to eradicate leukemic cells, most normal cells are killed as well, necessitating a transplant of hematopoietic stem cells from a donor to reconstitute the patients bone marrow and circulating hematopoietic cells. In some cases, the transplanted T cells from the donor can also recognize and eliminate the hematopoietic cells, including leukemia, from the recipient, thus preventing relapse. This can be described as a graft versus leukemia effect. Other hematologic disorders related to leukemia, like myelodysplastic syndrome (MDS), can also be treated in this way.

While HSCT can be curative, it is estimated that 25-50 percent of HSCT recipients relapse; leukemia relapse remains the major cause of allogeneic HSCT failure, and the prognosis for patients with post-HCT relapse is poor. Relapse occurs following allogeneic HSCT in approximately one-third of patients with acute leukemia who undergo the procedure, and most patients subsequently die of their disease.

About HighPassBio

HighPassBio, an ElevateBio portfolio company, is working to advance a novel approach to treating hematological malignancies by leveraging T cell receptor (TCR)-engineered T cells, known as TCR T cells. The companys lead program is designed to treat or potentially prevent relapse of leukemia in patients who have undergone hematopoietic stem cell transplant (HSCT). The technology was born out of research conducted at Fred Hutchinson Cancer Research Center by world renowned expert, Dr. Marie Bleakley.

About ElevateBio

ElevateBio, LLC, is a Cambridge-based creator and operator of a portfolio of innovative cell and gene therapy companies. It begins with an environment where scientific inventors can transform their visions for cell and gene therapies into reality for patients with devastating and life-threatening diseases. Working with leading academic researchers, medical centers, and corporate partners, ElevateBios team of scientists, drug developers, and company builders are creating a portfolio of therapeutics companies that are changing the face of cell and gene therapy and regenerative medicine. Core to ElevateBios vision is BaseCamp, a centralized state-of-the-art innovation and manufacturing center, providing fully integrated capabilities, including basic and translational research, process development, clinical development, cGMP manufacturing, and regulatory affairs across multiple cell and gene therapy and regenerative medicine technology platforms. ElevateBio portfolio companies, as well as select strategic partners, are supported by ElevateBio BaseCamp in the advancement of novel cell and gene therapies.

ElevateBios investors include F2 Ventures, MPM Capital, EcoR1 Capital, Redmile Group, Samsara BioCapital, The Invus Group, Surveyor Capital (A Citadel company), EDBI, and Vertex Ventures.

ElevateBio is headquartered in Cambridge, Mass, with ElevateBio BaseCamp located in Waltham, Mass. For more information, please visit http://www.elevate.bio.

View original post here:
ElevateBio's HighPassBio Presents on Novel T Cell Receptor Cell Therapy for Leukemia Relapse at 62nd Annual ASH Meeting - Business Wire

CRISPR and another genetic strategy fix cell defects in two common blood disorders – Science Magazine

Victoria Gray (right), shown with researcher Haydar Frangoul, was the first patient to be treated with the gene-editing tool CRISPR for sickle cell disease.

By Jocelyn KaiserDec. 5, 2020 , 12:30 PM

It is a double milestone: new evidence that cures are possible for many people born with sickle cell disease and another serious blood disorder, beta-thalassemia, and a first for the genome editor CRISPR.

In todays issue of The New England Journal of Medicine (NEJM) and tomorrow at the American Society of Hematology (ASH) meeting, teams report that two strategies for directly fixing malfunctioning blood cells have dramatically improved the health of a handful of people with these genetic diseases. One relies on CRISPR, marking the first inherited disease treated with the powerful tool created just 8 years ago. And both treatments are among a wave of genetic strategies poised to widely expand who can be freed of the two conditions. The only current cure, a bone marrow transplant, is risky, and appropriately matched donors are often scarce.

The novel genetic treatments still need longer folllow up, have the same safety issues as bone marrow transplants for now, and may also be extraordinarily expensive, but there is hope those risks can be eliminated and the costs pared down. This is an amazing time, and its exciting because its happening all at once, says hematologist Alexis Thompson of Northwestern University, who with a company called Bluebird Bio continues to test yet another genetic strategy that first demonstrated a sickle cell fix several years ago.

People born with sickle cell disease have mutations in their two copies of a gene for hemoglobin, the oxygen-carrying protein in red blood cells. The altered proteins stiffen normally flexible red blood cells into a sicklelike shape. The cells can clog blood vessels, triggering severe pain and raising the risk of organ damage and strokes. Sickle cell disease is among the most common inherited diseases, affecting 100,000 Black people in the United States alone. (The sickling mutations became widespread in African people, as one copy protects blood cells from malaria parasites.)

People with beta-thalassemia make little or no functioning hemoglobin, because of other mutations that affect the same subunit of the protein. About 60,000 babies are born each year globally with symptoms of the disease, largely of Mediterranean, Middle Eastern, and South Asian ancestry. Blood transfusions are standard treatment for both diseases, relieving the severe anemia they can cause, and drugs can somewhat reduce the debilitating crises that often send sickle cell patients to the hospital.

In the two new treatments, investigators have tinkered with genes to counter the malfunctioning hemoglobin. They remove a patients blood stem cells and, in the lab, disable a genetic switch called BCL11A that, early in life, shuts off the gene for a fetal form of hemoglobin. The patient then receives chemotherapy to wipe out their diseased cells, and the altered stem cells are infused. With the fetal gene now active, the fetal proteinrestores missing hemoglobin in thalassemia.In sickle cell disease it replaces some of the flawed adult sickling hemoglobin, and also blocks any remaining from forming sticky polymers.

Its enough to dilute the effect, says Samarth Kulkarni, CEO of CRISPR Therapeutics, which partnered with Vertex Pharmaceuticals on using the genome editor.

They engineered CRISPRs DNA-cutting enzyme and guide RNA to home in on and break the BCL11A gene. In a more traditional gene therapy effort, a team led by gene therapy researcher David Williams of Boston Childrens Hospital achieved the same goal. They used a harmless virus to paste into the blood stem cells genome a stretch of DNA coding for a strand of RNA that silences the fetal hemoglobin off switch.

Patients treated in both trials have begun to make sufficiently high levels of fetal hemoglobin and no longer have sickle cell crises or, in all but a single case, a need for transfusions. In one NEJM paper today, the Boston Childrens team reports on the success of its virus gene therapy in six sickle cell patients treated for at least 6 months. They include a teenager who can now go swimming without pain, and a young man who once needed transfusions but has gone without them nearly 2.5 years, says Erica Esrick of Boston Childrens. He feels perfectly normal.

CRISPR appears to have done at least as well. The first sickle cell patient to receive CRISPR 17 months ago, a Mississippi mother of four named Victoria Gray, has called the results wonderful. We have amelioratedthe symptoms, says Haydar Frangoul, a hematologist at the Sarah Cannon Research Institute who treated Gray as part of the CRISPR trial. Every time I call her on the phone or see her in the clinic, she feels great.

CRISPR Therapeutics and Vertex describe the results for Gray and one beta-thalassemia patient treated 22 months ago today in another NEJM paper, and Frangoul will report on seven beta-thalassemia and three sickle cell patients tomorrow at the online ASH meeting. The CRISPR results are really very impressive, says Boston Children's stem cell biologist Stuart Orkin, whose lab discovered the BCL11A switch that led to both trials. (He is not directly involved with either.)

The results are comparable to the older strategy from Bluebird that relies on a different genetic alteration: adding a gene for an adult hemoglobin that has been tweaked so it reduces polymerization of the sickling form. At the ASH meeting, Thompson will give an update on about two dozen sickle cell disease patients who received the treatment within the past 3 years. As of March, the 14 with a follow-up of 6 months or more had experienced just a single mild pain crisis overall.

The Bluebird treatment was approved in Europe in 2019 for certain beta-thalassemia patients, and the company expects to seek Food and Drug Administration approval in the United States for its products for both diseases within the next few years. Bluebird chief scientific officer Philip Gregory says the long-term data for the firm's treatment give it an advantage over the newer approaches. Weve set a very high bar, he says.

Others who treat these diseases say its too early to crown a specific genetic treatment the winner. For example, reversing the fetal hemoglobin off switch, as the new CRISPR and RNA-based gene therapy strategies do, allows blood cells to make natural levels of the protein. But so far there are no signs that Bluebirds treatment results in excess adult hemoglobin that causes problems, Williams says. And although a virus-carrying gene can land in the wrong place and trigger cancer, CRISPR could similarly make harmful off-target edits. There has been no sign of that. Still, We need long-term follow-up for all the strategies, says the National Institutes of Healths (NIHs) John Tisdale, a coleader of the Bluebird study.

None of these genetic treatments seems likely to immediately help the many patients in places like Africa and India who dont have access to sophisticated health care. Itswonderful, but it wont solve the global health problem, Orkin says. Bluebird expects to charge $1.8 million for LentiGlobin in Europea sum it derived from looking at a patients gains in life span and quality of lifeand the other genetic treatments are likely to be similarly expensive. Costs will also include the chemotherapy needed to eliminate patients diseased blood stem cells, and the attendant hospital stay.

Bluebird and other groups are exploring whether antibodies, instead of harsh chemotherapy, can wipe out a patients diseased cells. In a bolder effort, NIH and the Bill & Melinda Gates Foundation last year announced a plan to put at least $100 million into developing technologies that would modify blood stem cells in a patients bone marrow by injecting the gene-editing tools themselves into the body. Its a big hairy goal, but its an engineering challenge, says gene therapy researcher Donald Kohn of the University of California, Los Angeles, who leads another sickle cell treatment trial. Well get there.

Read more:
CRISPR and another genetic strategy fix cell defects in two common blood disorders - Science Magazine

Multiple sclerosis iPS-derived oligodendroglia conserve their properties to functionally interact with axons and glia in vivo – Science Advances

Abstract

Remyelination failure in multiple sclerosis (MS) is associated with a migration/differentiation block of oligodendroglia. The reason for this block is highly debated. It could result from disease-related extrinsic or intrinsic regulators in oligodendroglial biology. To avoid confounding immune-mediated extrinsic effect, we used an immune-deficient mouse model to compare induced pluripotent stem cellderived oligodendroglia from MS and healthy donors following engraftment in the developing CNS. We show that the MS-progeny behaves and differentiates into oligodendrocytes to the same extent as controls. They generate equal amounts of myelin, with bona fide nodes of Ranvier, and promote equal restoration of their host slow conduction. MS-progeny expressed oligodendrocyte- and astrocyte-specific connexins and established functional connections with donor and host glia. Thus, MS oligodendroglia, regardless of major immune manipulators, are intrinsically capable of myelination and making functional axo-glia/glia-glia connections, reinforcing the view that the MS oligodendrocyte differentiation block is not from major intrinsic oligodendroglial deficits.

Remyelination occurs in multiple sclerosis (MS) lesions but its capacity decreases over time (13). Failed remyelination in MS leads to altered conduction followed by axon degeneration, which, in the long run, results in severe and permanent neurological deficits (4). MS lesions may or may not harbor immature oligodendroglia (oligodendrocyte progenitors and pre-oligodendrocytes), with these cells failing to differentiate into myelin-forming cells, suggesting that oligodendrocyte differentiation is blocked (57). So far, the mechanism underlying this block is poorly understood. It may result from adverse environmental conditions or the failed capacity of oligodendrocyte progenitors/pre-oligodendrocytes to migrate or mature efficiently into myelin-forming cells or even a combination of these conditions, all of which may worsen with aging. It has been shown that increasing remyelination either through manipulating the endogenous pool (8, 9) or by grafting competent myelin forming oligodendroglia (10, 11) or both (12) can restore the lost axonal functions, improve the clinical scores, and protect from subsequent axonal degeneration in experimental (13, 14) or clinical (3) settings.

There are multiple ways to investigate the oligodendroglial lineage in disease. Cells can be studied in postmortem tissue sections or purified from postmortem adult human brain for in vitro and transcriptomic/proteomic analysis. In this respect, in vitro experiments highlighted the heterogeneity of the adult human oligodendrocyte progenitor population in terms of antigen and microRNA expression, suggesting that remyelination in the adult human brain involves multiple progenitor populations (15). Moreover, single-cell transcriptomics characterized in detail the heterogeneity of human oligodendroglial cells, emphasizing changes in MS, with some subpopulations expressing disease-specific markers that could play a role in disease onset and/or aggravation (16, 17).

Yet, this MS signature could preexist or be acquired early at disease onset. Moreover, most of these MS postmortem analyses or experimental models cannot overlook the involvement of extrinsic factors such as immune factors that might add more complexity toward understanding the behavior of MS oligodenroglial cells.

Little is known about the biology of the MS oligodendroglial lineage, primarily due to the impossibility, for ethical reasons, to harvest oligodendroglial populations from patients and study the diseased cells and their matching controls in vitro or in vivo after cell transplantation. While cell-cell interactions and cell heterogeneity in diseased conditions generate more complexity when comparing control and pathological samples, the induced pluripotent stem cell (iPSC) technology provides a unique opportunity to study homogeneous populations of human oligodendroglial cells and gain further insights into monogenetic diseases and multifactorial diseases, such as MS. The iPSC technology has unraveled differences in oligodendroglia biology, in Huntingtons disease (18), and schizophrenia (19, 20), indicating that these cells can contribute autonomously to multifactorial diseases outcome. However, so far, little is known about the potential contribution of MS oligodendroglia to failed remyelination. While senescence affects iPSCneural precursor cells (NPCs) derived from patients with primary progressive MS (PPMS) (21), only few preliminary reports alluded to the fate of PPMS (22, 23) or relapsing-remitting (RRMS) (24) iPSC-derived oligodendroglia after experimental transplantation and did not study per se their capacity to differentiate into functional myelin-forming cells. We exploited a robust approach (25) to generate large quantities of iPSCs-derived O4+ oligodendroglial cells from skin fibroblasts (hiOLs) of three RRMS and three healthy subjects, including two monozygous twin pairs discordant for the disease. As a critical feature of the pluripotent-derived cells should be their ability to fully integrate and function in vivo, we compared the capacity of healthy and MS-hiOL derivatives to integrate and restore axo-glial and glial-glial functional interactions after engraftment in the developing dysmyelinated murine central nervous system (CNS). Our data show that in noninflammatory conditions, the intrinsic properties of iPSC-oligodendroglial cells to differentiate, myelinate, and establish functional cell-cell interactions in vivo are not altered in MS, making them candidates of interest for personalized drug/cell therapies as pluripotency maintains MS oligodendroglial cells in a genuine nonpathological state.

Fibroblasts were isolated from three control and three patients with MS and reprogrammed into iPSC. Pluripotent cells were differentiated into NPCs and further into O4+ hiOLs for 12 days in vitro under glial differentiation medium (GDM) conditions as previously described (25). hiOL cells were selected using flow cytometry for O4 before transplantation. Because our aim was to study the intrinsic properties of MS cells, we chose to engraft O4+ hiOLs in the purely dysmyelinating Shi/Shi:Rag2/ mouse model to avoid confounding immune-mediated extrinsic effects.

We first questioned whether MS-hiOLs differed from control-hiOLs wild type (WT) in their capacity to survive and proliferate in vivo. To this aim, we grafted MS- and control-hiOLs in the forebrain of neonatal Shi/Shi:Rag2/ mice. MS cells engrafted (one injection per hemisphere) in the rostral forebrain, spread primarily through white matter, including the corpus callosum and fimbria, as previously observed using control human fetal (11, 26, 27) and iPSC (25, 28) progenitors. With time, cells also spread rostrally to the olfactory bulb and caudally to the brain stem and cerebellum (fig. S1). Examining engrafted brains at 8, 12, and 16 weeks postgraft (wpg), we found that MS-hiOLs expressing the human nuclear marker STEM101 and the oligodendroglial-specific transcription factor OLIG2 maintained a slow proliferation rate at all times (5 to 19% of STEM+ cells), with no difference in Ki67+ MS-hiOLs compared to control (Fig. 1, A and C). Moreover, immunostaining for cleaved Caspase3 at 8 wpg indicated that MS cells survived as well as control-hiOLs (Fig. 1, B and D). Evaluation of the cell density of human cells based on STEM positivity at each stage revealed no significant difference between grafted MS-hiOLs and control cells (fig. S2).

(A and C) Immunodetection of the human nuclei marker STEM101 (red) combined with OLIG2 (green) and the proliferation marker Ki67 (white) shows that a moderate proportion of MS-hiOLs sustains proliferation (empty arrowheads in the insets) following transplantation in their host developing brain, with no significant difference in the rate of proliferation between MS- and control-hiOLs over time. (B and D) Immunodetection of the apoptotic marker Caspase3 (green) indicates that MS-hiOLs survive as well as control-hiOLs 8 wpg. Two-way analysis of variance (ANOVA) followed by Tukeys multiple comparison or Mann-Whitney t tests were used for the statistical analysis (n = 3 to 4 mice per group). Error bars represent SEMs. H, Hoechst dye. Scale bars, 100 m.

Because MS-hiOLs and control cells proliferated and survived to the same extent, we next questioned whether their differentiation potential into mature oligodendrocytes could be affected. We used the human nuclei marker STEM101 to detect all human cells in combination with SOX10, a general marker for the oligodendroglial lineage, and CC1 as a marker of differentiated oligodendrocytes. We found that the number of MS oligodendroglial cells (SOX10+) increased slightly but significantly with time, most likely resulting from sustained proliferation (Fig. 2, A and B). Moreover, they timely differentiated into mature CC1+ oligodendrocytes with a fourfold increase at 12 wpg and a fivefold increase at 16 wpg when compared to 8 wpg and with no difference with control-hiOLs (Fig. 2, B and C).

(A) Combined immunodetection of human nuclei marker STEM101 (red) with CC1 (green) and SOX10 (white) for control (top) and MS-hiOLs (bottom) at 8, 12, and 16 wpg. (B and C) Quantification of SOX10+/STEM+ cells (B) and CC1+ SOX10+ over STEM+ cells (C). While the percentage of human oligodendroglial cells increased only slightly with time, the percentage of mature oligodendrocytes was significantly time regulated for both MS- and control-hiOLs. Two-way ANOVA followed by Tukeys multiple comparison tests were used for the statistical analysis of these experiments (n = 3 to 4 mice per group). Error bars represent SEMs. *P < 0.05 and ****P < 0.0001. Scale bar, 100 m.

The absence of abnormal MS-hiOL differentiation did not exclude a potential defect in myelination potential. We further investigated the capacity of MS-hiOLs to differentiate into myelin-forming cells. We focused our analysis on the core of the corpus callosum and fimbria. MS-hiOLs, identified by the human nuclear and cytoplasmic markers (STEM101 and STEM121), evolved from a bipolar to multibranched phenotype (Fig. 3A and fig. S3: compare 4 wpg to 8 and 12 wpg) and differentiated progressively into myelin basic proteinpositive (MBP+) cells associated, or not, with T-shaped MBP+ myelin-like profiles of increasing complexity (Fig. 3A and figs. S3 and S4B). Myelin-like profiles clearly overlapped with NF200+ axons (fig. S4A) and formed functional nodes of Ranvier expressing ankyrin G and flanked by paranodes enriched for CASPR (fig. S4B) or neurofascin (fig. S4C), as previously observed with control-hiOLs (25).

(A) Combined detection of human nuclei (STEM101) and human cytoplasm (STEM 121) (red) with MBP (green) in the Shi/Shi Rag2/ corpus callosum at 8, 12, and 16 wpg. General views of horizontal sections at the level of the corpus callosum showing the progressive increase of donor-derived myelin for control- (top) and MS- (bottom) hiOLs. (B) Evaluation of the MBP+ area over STEM+ cells. (C and D) Quantification of the percentage of (C) MBP+ cells and (D) MBP+ ensheathed cells. (E) Evaluation of the average sheath length (m) per MBP+ cells. No obvious difference was observed between MS and control-hiOLs. Two-way ANOVA followed by Tukeys multiple comparison tests were used for the statistical analysis of these experiments (n = 6 to 14 mice per group). Error bars represent SEMs. *P < 0.05, **P < 0.01, and ***P < 0.001. Scale bar, 200 m. See also figs. S3 and S5.

We further analyzed, in depth, the myelinating potential of MS-hiOLs, applying automated imaging and analysis, which provided multiparametric quantification of MBP as established in vitro (29) for each donor hiOL (three controls and three RRMS) at 4, 8, 12, 16, and 20 wpg in vivo (Fig. 3, B to D). We first examined the MBP+ surface area generated by the STEM+ cell population (Fig. 3B). While MS-hiOLs generated very low amount of myelin at 4 wpg, they generated significantly more myelin at 12, 16, and 20 wpg, with similar findings for control-hiOLs, highlighting the rapid progress in the percentage of myelin producing STEM+ cells in MS group over time. Detailed MBP+ surface area generated by the STEM+ cell population per donor is presented in fig. S5 and shows differences among hiOLs in the control and MS groups, respectively.

We also quantified the percentage of STEM+ cells expressing MBP and the percentage of MBP+ with processes associated with linear myelin-like features, which we called MBP+ ensheathed cells. Both parameters increased significantly with time for control-hiOLs, reaching a plateau at 16 wpg. The same tendency was achieved for MS-hiOLs with no significant differences between the control- and MS-hiOL groups (Fig. 3, C and D).

Myelin sheath length is considered to be an intrinsic property of oligodendrocytes (30). We analyzed this paradigm in our MS cohort at 12 and 16 wpg, time points at which sheaths were present at a density compatible with quantification. For those time points, we found that the average MS MBP+ sheath length was equivalent to that of control with 25.86 0.98 and 27.74 1.52 m for MS-hiOLs and 24.52 1.48 and 27.65 0.96 m for control-hiOLs at 12 and 16 wpg, respectively (Fig. 3F). In summary, our detailed analysis of immunohistochemically labeled sections indicates that MS-hiOLs did not generate abnormal amounts of myelin in vivo when compared to control-hiOLs.

Moreover, the myelinating potential of MS-hiOLs was further validated after engraftment in the developing spinal cord (4 weeks of age). Immunohistological analysis 12 wpg revealed that STEM+ cells not only populated the whole dorsal and ventral columns of the spinal cord with preferential colonization of white matter but also generated remarkable amounts of MBP+ myelin-like internodes that were found on multiple spinal cord coronal sections (fig. S6), thus indicating that their myelination potential was not restricted to only one CNS structure.

The presence of normal amounts of donor MBP+ myelin-like structures in the shiverer forebrain does not exclude potential structural anomalies. Therefore, we examined the quality of MS derived myelin at the ultrastructural level at 16 wpg in the Shi/Shi:Rag2/ forebrain. In the corpus callosum of both MS and control-hiOLs grafted mice, we detected numerous axons surrounded by electron dense myelin, which at higher magnification was fully compacted compared to the uncompacted shiverer myelin (Fig. 4, A to F) (25, 31). Moreover, MS myelin reached a mean g ratio of 0.76 1.15 comparable to that of control myelin (0.75 1.56) (Fig. 4G) and thus a similar myelin thickness. This argues in favor of (i) MS-hiOLs having the ability to produce normal compact myelin and thus its functional normality and (ii) a similar rate of myelination between the two groups and, consequently, an absence of delay in myelination for MS-hiOLs.

(A to F) Ultrastructure of myelin in sagittal sections of the core of the corpus callosum 16 wpg with control-hiOLs (A to C) and MS-hiOLs (D to F). (A and D) General views illustrating the presence of some electron dense myelin, which could be donor derived. (B, C, E, and F) Higher magnifications of control (B and C) and MS (E and F) grafted corpus callosum validate that host axons are surrounded by thick and compact donor derived myelin. Insets in (C) and (F) are enlargements of myelin and show the presence of the major dense line. No difference in compaction and structure is observed between the MS and control myelin. (G) Quantification of g-ratio revealed no significant difference between myelin thickness of axons myelinated by control- and MS-hiOLs. Mann-Whitney t tests were used for the statistical analysis of this experiment (n = 4 mice per group). Error bars represent SEMs. Scale bars, (A and D) 5 m , (B and E) 2 m, and (C and F) 500 nm [with 200 and 100 nm, respectively in (C) and (F) insets].

Myelin compaction has a direct impact on axonal conduction with slower conduction in shiverer mice compared to WT mice (10, 32). We therefore questioned whether newly formed MS-hiOLderived myelin has the ability to rescue the slow axon conduction velocity of shiverer mice in vivo (Fig. 5). As previously performed with fetal glial-restricted progenitors (11), transcallosal conduction was recorded in vivo at 16 wpg in mice grafted with MS- and control-hiOLs and compared with nongrafted shiverer and WT mice. As expected, conduction in nongrafted shiverer mice was significantly slower compared to WT mice. However, axon conduction velocity was rescued by MS-hiOLs and, to the same extent, by control-hiOLs.

(A) Scheme illustrating that intracallosal stimulation and recording are performed in the ipsi- and contralateral hemisphere, respectively. (B) N1 latency was measured following stimulation in different groups of Shi/Shi:Rag2/: intact or grafted with control or MS-hiOLs and WT mice at 16 wpg. MS-hiOLderived myelin significantly restored transcallosal conduction latency in Shi/Shi:Rag2/ mice to the same extent than control-derived myelin (P = 0.01) and close to that of WT levels. One-way ANOVA with Dunnetts multiple comparison test for each group against the group of intact Shi/Shi:Rag2/ was used. Error bars represent SEMs. *P < 0.05. (C) Representative response profiles for each group. Scales in Y axis is equal to 10 V and in the X axis is 0.4 ms.

Rodent oligodendrocyte progenitors and oligodendrocytes can be distinguished by cell stagespecific electrophysiological properties (33, 34). To assess the electrophysiological properties of oligodendroglial lineage cells derived from human grafted control- and MS-hiOLs, red fluorescent protein (RFP)hiOLs were engrafted in the Shi/Shi:Rag2/ forebrain and recorded with a K-gluconatebased intracellular solution in acute corpus callosum slices at 12 to 15 wpg (Fig. 6A). As previously described for rodent cells, hiOLs in both groups were identified by their characteristic voltage-dependent current profile recognized by the presence of inward Na+ currents and outwardly rectifying steady-state currents (Fig. 6B). We found that ~60 and ~44% of recorded cells were oligodendrocyte progenitors derived from MS and control progenies, respectively. No significant differences were observed in the amplitude of Na+ currents measured at 20 mV (Fig. 6D) or steady-state currents measured at +20 mV between MS- and control-derived oligodendrocyte progenitors (Isteady = 236.70 19.45 pA and 262.10 31.14 pA, respectively; P = 0.8148, Mann Whitney U test). We further confirmed the identity of these cells by the combined expression of SOX10 or OLIG2 with STEM101/121 and the absence of CC1 in biocytin-loaded cells (Fig. 6F, top). The remaining recorded cells (MS and control) did not show detectable Na+ currents after leak subtraction and were considered to be differentiated oligodendrocytes by their combined expression of SOX10, STEM101/121, and CC1 in biocytin-loaded cells (Fig. 6F, bottom). The I-V curve of these differentiated oligodendrocytes displayed a variable profile that gradually changed from voltage dependent to linear as described for young and mature oligodendroglial cells in the mouse (33). Figure 6C illustrates a typical linear I-V curve of fully mature MS-derived oligodendrocytes. No significant differences were observed in the amplitude of steady-state currents measured at +20 mV between MS- and control-derived oligodendrocytes (Fig. 6E). Overall, the electrophysiological profile of oligodendrocyte progenitors and oligodendrocytes derived from control and MS was equivalent and showed similar characteristics to murine cells (33, 34).

(A) Schematic representation of the concomitant Biocytin loading and recording of single RFP+ hiOL derivative in an acute coronal brain slice prepared from mice engrafted with hiOLs (control or MS) and analyzed at 12 to 14 wpg. (B and C) Currents elicited by voltage steps from 100 to +60 mV in a control-oligodendrocyte progenitor (B, left) and a MS-oligodendrocyte (C, left). Note that the presence of an inward Na+ current obtained after leak subtraction in the oligodendrocyte progenitor, but not in the oligodendrocyte (insets). The steady-state I-V curve of the oligodendrocyte progenitor displays an outward rectification (B, right) while the curve of the oligodendrocyte has a linear shape (C, right). (D) Mean amplitudes of Na+ currents measured at 20 mV in control and MS iPSCs-derived oligodendrocyte progenitors (n = 8 and n = 9, respectively, for four mice per condition; P = 0.743, Mann-Whitney U test). (E). Mean amplitudes of steady-state currents measured at +20 mV in control and patient differentiated iPSC-derived oligodendrocytes (n = 10 and n = 6 for 3 and four mice, respectively; P = 0.6058, Mann-Whitney U test). (F) A control iPSC-derived oligodendrocyte progenitor loaded with biocytin and expressing OLIG2, STEM101/121, and lacking CC1 (top) and an MS iPSCderived oligodendrocyte loaded with biocytin and expressing SOX10, CC1, and STEM101/121 (bottom). Scale bar, 20 m.

(A) Z-stack identifying a target and connected cell. One single grafted human RFP+ cell (per acute slice) was loaded with biocytin by a patch pipette and allowed to rest for 30 min. The white arrowheads and insets in (A) illustrate biocytin diffusion up to the donut-shaped tip of the human oligodendrocyte processes. Another biocytin-labeled cell (empty yellow arrowhead) was revealed at different morphological level indicating diffusion to a neighboring cell and communication between the two cells via gap junctions. (B and C) Split images of (A) showing the target (B) and connected (C) cell separately at different levels. Immunolabeling for the combined detection of the human markers STEM101/121 (red), OLIG2 (blue), and CC1 (white) indicated that the target cell is of human origin (STEM+) and strongly positive for OLIG2 and CC1, a mature oligodendrocyte, and that the connected cell is of murine origin (STEM-) and weakly positive for OLIG2 and CC1, most likely an immature oligodendrocyte. Scale bars, 30 m. See also fig. S7.

Studies with rodents have reported that oligodendrocytes exhibit extensive gap-junctional intercellular coupling between other oligodendrocytes and astrocytes (35). Whether oligodendrocytes derived from grafted human cells can be interconnected with cells in the adult host mouse brain was not known, and whether MS-hiOLs maintain this intrinsic property was also not addressed. Because biocytin can pass through gap junctions, we inspected biocytin-labeled cells for dye coupling (Figs. 6A and 7, A and B).

We found that two of seven MS-derived oligodendrocytes (~29%) and 5 of 21 control-derived oligodendrocytes (~24%) were connected with a single neighboring cell, which was either human or murine (Fig. 7), except in one case where three mouse cells were connected to the biocytin-loaded human cell. These findings reveal that gap junctional coupling can occur between cells from the same or different species, and MS-hiOLs can functionally connect to other glial cells to the same extent as their control counterparts.

To validate the presence of glial-glial interactions, we investigated whether the grafted hiOL-derived progeny had the machinery to be connected to one another via gap junctions. To this end, we focused on oligodendrocyte-specific Cx47 and astrocyte-specific Cx43 as Cx43/47 channels, which are important for astrocyte/oligodendrocyte cross talk during myelination and demyelination (36, 37). Combined immunolabeling for hNOGOA, CC1, OLIG2, and Cx47 revealed that MS-derived oligodendrocyte cell bodies and processes were decorated by Cx47+ gap junction plaques, which were often shared by exogenous MS-derived oligodendrocytes or by MS and endogenous murine oligodendrocytes (fig. S7A). In addition, colabeling exogenous myelin for MBP and Cx43 identified the presence of several astrocyte-specific Cx43 gap junction plaques between human myelin internodes, highlighting contact points between astrocyte processes and axons at the human-murine chimeric nodes of Ranvier (fig. S7B).

Last, colabeling of hNOGOA, with Cx47 and the astrocyte-specific Cx43, revealed coexpression of oligodendrocyte- and astrocyte-specific connexins at the surface of MS-derived oligodendrocyte cell bodies and at the level of T-shaped myelin-like structures (fig. S7C), thus implying connections between human oligodendrocytes and murine and/or human astrocytes, as a small proportion of the grafted hiOLs differentiated into astrocytes. Immunolabeling for human glial fibrillary acidic protein (GFAP), and Cx43 showed that these human astrocytes were decorated by Cx43+ aggregates, as observed in the host subventricular zone (fig. S8A).

Furthermore, immunolabeling for human GFAP, mouse GFAP, and Cx43 indicated that Cx43+ gap junctions were shared between human and mouse astrocytes as observed at the level of blood vessels (fig. S8B). These data validate interconnections between the grafted-derived human glia (MS and controls) with murine host glial cells and confirm their interconnection with the pan-glial network.

Two main hypotheses have been considered in understanding MS pathology and etiology: the outside-in hypothesis highlighting the role of immune regulators and environmental inhibitors as extrinsic key players in MS pathology and possibly its repair failure or the inside-out hypothesis pointing to the intrinsic characteristics of neuroglia including oligodendroglial cells as the main contributors in the MS scenario. Single-cell transcriptomic analysis revealed the presence of disease-specific oligodendroglia expressing susceptibility genes in MS brains (16) and altered oligodendroglia heterogeneity in MS (17). The question remains open as to whether these altered oligodendroglial phenotypes are acquired in response to the disease environment or whether they reflect intrinsic traits of the MS oligodendroglial population. On the other hand, the whole exome sequencing analysis in 132 patients from 34 multi-incident families identified 12 candidate genes of the innate immune system and provided the molecular and biological rational for the chronic inflammation, demyelination, and neurodegeneration observed in patients with MS (38) and revealed the presence of epigenetic variants in immune cells and in a subset of oligodendrocytes contributing to risk for MS (39).

While none of these hypotheses have been fully proven or rejected, research efforts for a better understanding of this multifactorial disease have continued. Impaired remyelination or oligodendrocyte differentiation block in MS is still considered a potentially disease-relevant phenotype (40, 41). Many histological and experimental studies suggest that impaired oligodendrocyte progenitor to oligodendrocyte differentiation may contribute to limited remyelination in MS, although some reports question the contribution of newly generated oligodendrocytes to remyelination (17, 42, 43). Understanding MS oligodendrocyte biology has been challenging mainly due to the following reasons: (i) oligodendroglial cells are not easily accessible to be studied in vivo; (ii) dynamic remyelination observed in patients with MS, which points to their individual remyelination potential, is inversely correlated with their clinical disability (3), highlighting even more complexity in oligodendrocyte heterogeneity between patients with MS; and (iii) exclusion of the role of immune system players in understanding MS oligodendrocyte biology being inevitable in most of clinical or experimental studies.

In such a complex multifactorial disease, one of the most accessible and applicable approaches to overcome these problems is the generation of large quantities of disease and control oligodendroglia using the iPSC technology, and to investigate their genuine behavior in vivo after engraftment in a B and T cellfree system. Using a very efficient reprogramming method (25), and the purely dysmyelinating Shi/Shi:Rag2/ mouse model to avoid confounding immune-mediated extrinsic effects, we show that MS-hiOLs derivatives survive, proliferate, migrate, and timely differentiate into bona fide myelinating oligodendrocytes in vivo as efficiently as their control counterparts. Nicaise and colleagues reported that iPSC-NPCs from PPMS cases did not provide neuroprotection against active CNS demyelination compared to control iPSC-NPCs (44) and failed to promote oligodendrocyte progenitor genesis due to senescence without affecting their endogenous capacity to generate myelin-forming oligodendrocytes (21, 22). However, their myelinating potential was not evaluated against control cells. Generation of iPSC-oligodendrocyte progenitors from patients with PPMS or RRMS has also been reported by other groups, yet with no evidence for their capacity to become functional oligodendrocytes in vivo (23, 24). Thus, so far, no conclusion could be made regarding the potential impact of disease severity (PPMS verses RRMS) on the functionality of the iPSC-derived progeny.

We compared side by side, and at different time points after engraftment, hiOLs from patients with RRMS and controls including two pairs of homozygous twins discordant for disease. We found no significant difference in their capacity to timely differentiate (according to the human tempo of differentiation) and efficiently myelinate axons in the shiverer mouse in terms of the percentage of MBP+ cells generated, amount of myelin produced, length of MBP+ sheaths, and the ultrastructure and thickness of myelin sheaths. MS-hiOLs also reconstructed nodes of Ranvier expressing nodal components key to their function. We not only verified that the grafted MS-hiOLs derivatives were anatomically competent but also established their functionality at the electrophysiological level using (i) in vivo recordings of transcallosal evoked potentials and (ii) ex vivo recordings of the elicited current-voltage curves of the grafted MS-hiOLs verses controls. Our data show that the grafted MS-hiOLs were able to rescue the established delayed latency of shiverer mice to the same extent as control cells, as previously reported for human fetal glial progenitors grafted in the same model (11). Moreover, at the single-cell level, MS-hiOLderived oligodendrocyte progenitors and oligodendrocytes did not harbor aberrant characteristics in membrane currents compared to control cells ex vivo. Thus, iPSC-derived human oligodendroglial cells shift their membrane properties with maturation as previously observed in vitro (45) and these properties are not impaired in MS.

The absence of differences among control and MS-derivatives might be due to different causes. One might consider that pluripotency induction could by in vitro manipulation, erase cell epigenetic traits and/or reverse cells to an embryonic state, and as a result, modulate their intrinsic characteristics. Yet, several reports have highlighted differences in the behavior of diseased iPSC-derived oligodendrocytes in comparison to those from healthy controls using the same technology in multifactorial diseases such as schizophrenia (19, 20), Huntingtons disease (18), and others (46). In this regard, direct reprogramming of somatic cells into the desired cell type, bypassing the pluripotent stage, could be an attractive alternative. However, so far only mouse fibroblasts have been successfully directly converted into oligodendroglial cells, and with relatively low efficiency (47, 48).

iPSCs were transduced with three transcription factors to generate hiOLs in a fast and efficient way (25). While we cannot rule out that the use of these three transcription factors may have obscured differences between MS and controls, results for controls are quite comparable to our previously published data based on human fetal oligodendrocyte progenitor engraftment in the Shi/Shi:Rag2/ developing forebrain (49) or fetal NPC engrafted in the Shi/Shi:Rag2/ demyelinated spinal cord (50), suggesting that transduction with the three transcription factors does not overly modify the behavior of the grafted human cells. It could also be argued that the absence of differences between control and MS monozygous twins is not surprising given their equal genetic background. Yet, comparing controls with nonsibling MS hiOLS (compare C1 with RRMS2 and RRMS3; C2 with RRMS1, RRMS2, and RRMS3; and C3 with RRMS1 and RRMS2) revealed no defect in myelination for MS cells as well.

Analysis of hiOLs from each donor showed differences within each group. This could result from phenotypic instability, heterogeneity among donors, or disease subtype. Yet, the clinical history of each patient suggests a certain homogeneity among the MS disease phenotype, all being RRMS. In addition, the equal survival and proliferation rates between both groups argue in favor of cell stability. These confounding observations sustain that differences in terms of myelination are most likely due to heterogeneity among individuals rather than phenotypic instability or disease subtype.

While most preclinical transplantation studies have focused on myelination potential as the successful outcome of axo-glia interactions, less is known about the capacity of the grafted cells to fulfill glial-glial interactions in the pan-glial syncytium, which could ensure maintenance of newly generated myelin (51) and cell homeostasis (52). Oligodendrocytes are extensively coupled to other oligodendrocytes and oligodendrocyte progenitors through the homologous gap junctions Cx47 (35). These intercellular interactions between competing oligodendroglial cells influence the number and length of myelin internodes and the initiation of differentiation (53, 54). Oligodendrocytes are also coupled to astrocytes through heterologous gap junctions such as Cx32/Cx30 and Cx47/Cx43 (55). Disruption of oligodendrocytes from each other and from astrocytes, i.e., deconstruction of pan-glial network, has been observed in experimental models of demyelination (unpublished data) and frequently reported in MS and neuromyelitis optica (37, 56, 57). Mutations in Cx47 and Cx32 result in developmental CNS and PNS abnormalities in leukodystrophies (58, 59). Moreover, experimental ablation of Cx47 results in aberrant myelination (60) and significantly abolished coupling of oligodendrocytes to astrocytes (35).

In view of the major role of Cx-mediated gap junctions among oligodendrocytes and between oligodendrocytes and astrocytes during myelin formation (55), we asked whether the MS-hiOL progeny was capable of making functional gap junctions with other glial cells, and integrating into the host panglial network. We show that grafted MS-hiOLs, in common with rodent oligodendrocytes, express Cx47 that was frequently shared not only between the human and murine oligodendrocytes (through Cx47-Cx47) but also in conjunction with the astrocyte Cx43 (via Cx47/Cx43). The dye-coupling study highlighted that MS-hiOLs, similar to control cells, were capable of forming functional gap junctions with neighbor murine or human glial cells, indicating that MS-hiOLs retained the intrinsic property, not only to myelinate host axons but also to functionally integrate into the host pan-glial network. While our study focused mainly on oligodendroglial cells, a small proportion of the grafted hiOLs differentiated into astrocytes expressing Cx43. These human astrocytes were detected associated with blood vessels or the subventricular zone, where they were structurally gap-junction coupled to mouse astrocytes as observed after engraftment of human fetal glial restricted progenitors (61).

Together, our data highlight that human skinderived glia retain characteristics of embryonic/fetal brainderived glia as observed for rodent cells (10). In particular, we show that MS-hiOLs timely differentiate into mature oligodendrocytes, functionally myelinate host axons and contribute to the human-mouse chimeric pan-glial network as efficiently as control-hiOLs. These observations favor a role for extrinsic rather than intrinsic oligodendroglial factors in the failed remyelination of MS. The International Multiple Sclerosis Genetics Consortium after analyzing the genomic map of more than 47,000 MS cases and 63,000 control subjects, implicated microglia, and multiple different peripheral immune cell populations in disease onset (62). Moreover, neuroinflammation appears to block oligodendrocyte differentiation and to alter their properties and thereby aggravate the autoimmune process (63). Furthermore, MS lymphocytes are reported to exhibit intrinsic capacities that drive myelin repair in a mouse model of demyelination (64). On the other hand, a recent study highlighted the presence of disease-specific oligodendroglia in MS (16, 17). However, it should be considered that most of the data in the later were collected using single nuclei RNA sequencing of postmortem tissues from MS or control subjects of different ages that were suffering from other disorders ranging from cancer to sepsis and undergoing various treatment, and so died for different reasons, that may have influenced the type or level of RNA expression by the cells. In addition, the presence of genetic variants that alter oligodendrocyte function in addition to that of immune cells was also found (39). While this oligodendrocyte dysfunction contributes to MS risk factor, whether it is involved in other aspects of MS such as severity, relapse rate, and rate of progression is not yet known.

Numerous factors may cause the failure of oligodendrocyte progenitor maturation comprising factors such as axonal damage and/or altered cellular and extracellular signaling within the lesion environment (65) without neglecting aged-related environmental and cellular changes (40). Although the cells generated in this study are more of an embryonic nature, and did not experienced the kind of inhibitory environment that is present in MS, our data provide valuable findings in the scenario of MS pathology highlighting that RRMS-hiOLs, regardless of major manipulators of the immune system, do not lose their intrinsic capacity to functionally myelinate and interact with other neuroglial cells in the CNS under nonpathological conditions. Whether RRMS-hiOLs or oligodendroglial cells directly reprogrammed from MS fibroblasts would behave similarly well, if challenged with neuropathological inflammatory conditions as opposed to conditions wherein the immune system is intact (presence of T and B cells), or whether they would reflect intrinsic aging properties will require further investigation.

In summary, our findings provide valuable insights not only into the biology of MS oligodendroglia but also their application for cell-based therapy and should contribute to the establishment of improved preclinical models for in vivo drug screening of pharmacological compounds targeting the oligodendrocyte progenitors, oligodendrocytes, and their interactions with the neuronal and pan-glial networks.

We examined side by side the molecular, cellular, and functional behavior of MS hiOLs with their control counterparts after their engraftment in a dysmyelinating animal model to avoid the effect of major immune modulators. We used three MS and three control hiOLs including two monozygous twin pairs discordant for the disease. We performed in vivo studies in mouse with sample size between three to six animals per donor/time point/assay required to achieve significant differences. Numbers of replicates are listed in each figure legend. Animals were monitored carefully during all the study time, and animal welfare criteria for experimentation were fully respected. All experiments were randomized with regard to animal enrollment into treatment groups. The same experimenter handled the animals and performed the engraftment experiments to avoid errors. The data were analyzed by a group of authors.

Shiverer mice were crossed to Rag2 null immunodeficient mice to generate a line of Shi/Shi:Rag2/ dysmyelinating-immunodeficient mice to (i) prevent rejection of the grafted human cells and allow detection of donor-derived WT myelin and (ii) investigate the original behavior of MS-derived oligodendrocytes in a B cell/T cellfree environment. Mice were housed under standard conditions of 12-hour light/12-hour dark cycles with ad libitum access to dry food and water at the ICM animal facility. Experiments were performed according to European Community regulations and INSERM ethical committee (authorization 75-348; 20/04/2005) and were approved by the local Darwin ethical committee.

Fibroblasts were obtained under informed consent from three control and three RRMS subjects including two monozygous twin pairs discordant for the disease. They were reprogrammed into iPSCs using the replication incompetent Senda virus kit (Invitrogen) according to manufacturers instructions. Table S1 summarizes information about the human cell lines used in this study. The study was approved by the local ethical committees of Mnster and Milan (AZ 2018-040-f-S, and Banca INSpe).

Human iPSCs were differentiated into NPC by treatment with small molecules as described (66, 67). Differentiation of NPCs into O4+ oligodendroglial cells used a poly-cistronic lentiviral vector containing the coding regions of the human transcription factors Sox10, Olig2, and Nkx6.2 (SON) followed by an IRES-pac cassette, allowing puromycin selection for 16 hours (25). For single-cell electrophysiological recordings, the IRES-pac cassette was replaced by a sequence encoding RFP. Briefly, human NPCs were seeded at 1.5 105 cells per well in 12-well plates, allowed to attach overnight and transduced with SON lentiviral particles and protamine sulfate (5 g/ml) in fresh NPC medium. After extensive washing, viral medium was replaced with glial induction medium (GIM). After 4 days, GIM was replaced by differentiation medium (DM). After 12 days of differentiation, cells were dissociated by accutase treatment for 10 min at 37C, washed with phosphate-buffered saline (PBS) and resuspended in PBS/0.5% bovine serum albumin (BSA) buffer, and singularized cells were filtered through a 70-m cell strainer (BD Falcon). Cells were incubated with mouse immunoglobulin M (IgM) antiO4-APC antibody (Miltenyi Biotech) following the manufacturers protocol, washed, resuspended in PBS/0.5% BSA buffer (5 106 cells/ml), and immediately sorted using a FACS Aria cell sorter (BD Biosciences). Subsequently, human O4+ hiOLs were frozen and stored in liquid nitrogen. Media details were provided in (25). hiOLS from each donor was assayed individually (no cell mix) and studied as follows for forebrain engraftment: immunohistochemistry (all donors, three to seven mice per time point), electron microscopy (C1 and RRMS1, four mice per donor at 16 wpg), in vivo electrophysiology (C1 and RRMS1, six mice per donor and eight mice per medium at 16 wpg), dye coupling, and ex-vivo electrophysiology (C1-RFP and RRMS3-RFP, six to seven mice per donor at 16 wpg). For spinal cord engraftment: immuno-histochemistry (C1 and RRMS3, 3 and 4 mice respectively at 12 wpg).

RRMS1: Disease duration at biopsy was 11 years. Started on Rebif 22 and switched to Rebif 44 because of relapses. Relapse was treated with bolus of cortisone 20 to 30 days before biopsy and then switched to natalizumab.

RRMS2: Disease duration at biopsy was 16 months. Relapse at disease onset. On Rebif 22 from disease onset until biopsy with no episodes. A new lesion was identified 3 months after biopsy. At the time of biopsy, the patient reported cognitive difficulties, no motor dysfunctions.

RRMS3: Disease duration at biopsy was 15 months. Relapse 6 months before biopsy with dysesthesias and hypoesthesia right thigh and buttock. Active lesion identified by magnetic resonance imaging at day 10. On Rebif smart 44 mcg, 50 days later, and skin biopsy 4 months later. A new gadolinium negative temporal lesion identified 2 months after biopsy and the patient switched to Tecfidera.

To assay hiOL contribution to forebrain developmental myelination, newborn Shi/Shi:Rag2/ pups (n = 148) were cryo-anesthetized, and control and RRMS hiOLs were transplanted bilaterally, rostral to the corpus callosum. Injections (1 l in each hemisphere and 105 cells/l) were performed 1 mm caudally, 1 mm laterally from the bregma, and to a depth of 1 mm as previously described (49, 68). Animals were sacrificed at 4, 8, 12, 16, and, when indicated, 20 wpg for immunohistological studies and at one time point for electron microscopy (16 wpg), ex vivo (12 to 15 wpg), and in vivo (16 wpg) electrophysiology.

To assay the fate of hiOLs in the developing spinal cord, 4-week-old mice (n = 4) were anesthetized by intraperitoneal injection of a mixture of ketamine (100 mg/kg) (Alcyon) and xylazine (10 mg/kg) (Alcyon) and received a single injection at low speed (1 l/2 min) of hiOLs (1 l, 105 cells/l) at the spinal cord thoracic level using a stereotaxic frame equipped with a micromanipulator and a Hamilton syringe. Animals were sacrificed at 12 wpg for immunohistological studies.

Immunohistochemistry. Shi/Shi:Rag2/ mice grafted with control and RRMS hiOLs (n = 3 to 6 per group, donor and time point) were sacrificed by transcardiac perfusion-fixation with 4% paraformaldehyde in PBS. Tissues were postfixed in the same fixative for 1 hour and incubated in 20% sucrose in 1 PBS overnight before freezing at 80C. Serial horizontal brain and spinal cord cross sections of 12 m thickness were performed with a cryostat (CM3050S, Leica). Transplanted hiOLs were identified using anti-human cytoplasm [1:100; STEM121; Takara, Y40410, IgG1], anti-human nuclei (1:100; STEM101; Takara, Y40400, IgG1), and anti-human NOGOA (1:50; Santa Cruz Biotechnology, sc-11030, goat) antibodies. In vivo characterization was performed using a series of primary antibodies listed in tableS2. For MBP staining, sections were pretreated with ethanol (10 min, room temperature). For glial-glial interactions, oligodendrocyte-specific connexin was detected with anti-connexin 47 (1:200; Cx47; Invitrogen, 4A11A2, IgG1) and astrocyte-specific connexin, with anti-connexin 43 (1:50; Cx43; Sigma-Aldrich, C6219, rabbit), and sections were pretreated with methanol (10 min, 20C). Secondary antibodies conjugated with fluorescein isothiocyanate, tetramethyl rhodamine isothiocyanate (SouthernBiotech), or Alexa Fluor 647 (Life Technologies) were used, respectively, at 1:100 and 1:1000. Biotin-conjugated antibodies followed by AMCA AVIDIN D (1:20; Vector, A2006). Nuclei were stained with 4,6-diamidino-2-phenylindole (DAPI) (1 g/ml; Sigma-Aldrich) (1:1000). Tissue scanning, cell visualization, and imaging were performed with a Carl Zeiss microscope equipped with ApoTome 2.

Electron microscopy. For electron microscopy, Shi/Shi:Rag2/ mice grafted with control and RRMS hiOLs (n = 4 per group) were perfused with 1% PBS followed by a mixture of 4% paraformaldehyde/5% glutaraldehyde (Electron Microscopy Sciences) in 1% PBS. After 2-hour postfixation in the same solution, 100-m-thick sagittal sections were cut and fixed in 2% osmium tetroxide (Sigma-Aldrich) overnight. After dehydration, samples were flat-embedded in Epon. Ultra-thin sections (80 nm) of the median corpus callosum were examined and imaged with a HITACHI 120 kV HT-7700 electron microscope.

Electrophysiological recordings were performed in mice grafted with MS- and control-hiOLs, and compared with nongrafted intact or medium injected Shi/Shi:Rag2/ mice and WT mice 16 weeks after injection (n = 4 to 6 per group) as described (11). Briefly mice were anesthetized with 2 to 4% isoflurane performed under analgesia (0.1 mg/kg buprecare) and placed in a stereotaxic frame (D. Kopf, Tujunga, CA, USA). Body temperature was maintained at 37C by a feedback-controlled heating blanket (CMA Microdialysis). Electrical stimulation (0.1 ms at 0 to 0.1 mA) was applied using a bipolar electrode (FHC- CBBSE75) inserted to a depth of 200 m into the left cortex at 2 mm posterior to bregma and 3 mm from the midline. At the same coordinates in the contralateral hemisphere, homemade electrodes were positioned for recording local field potentials (LFPs) generated by transcallosal electric stimulation. Electrical stimulation and evoked LFPs were performed by the data acquisition system apparatus (Neurosoft, Russia), and signals were filtered at 0.01 to 1 000 Hz. Each response latency (in ms) was measured as the time between the onset of stimulus artifact to the first peak for each animal. A ground electrode was placed subcutaneously over the neck.

Slice preparation and recordings. Acute coronal slices (300 m) containing corpus callosum were made from Shi/Shi:Rag2/ mice grafted with control (n = 7) and RRMS (n = 6) RFP+ hiOLs. They were prepared from grafted mice between 12 and 15 wpg as previously described (69). Briefly, slices were performed in a chilled cutting solution containing 93 mM N-methyl-d-glucamine, 2.5 mM KCl, 1.2 mM NaH2PO4, 30 mM NaHCO3, 20 mM Hepes, 25 mM glucose, 2 mM urea, 5 mM Na-ascorbate, 3 mM Na-pyruvate, 0.5 mM CaCl2, and 10 mM MgCl2 (pH 7.3 to pH 7.4; 95% O2 and 5% CO2) and kept in the same solution for 8 min at 34C. Then, they were transferred for 20 min to solution at 34C containing 126 mM NaCl, 2.5 mM KCl, 1.25 mM NaH2PO4, 26 mM NaHCO3, 20 mM glucose, 5 mM Na-pyruvate, 2 mM CaCl2, and 1 mM MgCl2 (pH 7.3 to pH 7.4; 95% O2 and 5% CO2). Transplanted RFP+ hiOLs were visualized with a 40 fluorescent water-immersion objective on an Olympus BX51 microscope coupled to a CMOS digital camera (TH4-200 OptiMOS) and an light-emitting diode light source (CoolLed p-E2, Scientifica, UK) and recorded in voltage-clamp mode with an intracellular solution containing 130 mM K-gluconate, 0.1 mM EGTA, 2 mM MgCl2, 10 mM Hepes, 10 mM -aminobutyric acid, 2 mM Na2-adenosine 5-triphosphate, 0.5 mM Na-guanosine 5-triphosphate, 10 mM Na2-phosphocreatine, and 5.4 mM biocytin (pH 7.23). Holding potentials were corrected by a junction potential of 10 mV. Electrophysiological recordings were performed with Multiclamp 700B and Pclamp10.6 software (Molecular Devices). Signals were filtered at 3 kHz, digitized at 10 kHz, and analyzed off-line.

Immunostainings and imaging of recorded slices. For analysis of recorded cells, one single RFP+ cell per hemisphere was recorded in a slice and loaded with biocytin for 25 min in whole-cell configuration. After gently removing the patch pipette, biocytin was allowed to diffuse for at least 10 min before the slice was fixed 2 hours in 4% paraformaldehyde at 4C. Then, the slice was rinsed three times in PBS for 10 min and incubated with 1% Triton X-100 and 10% normal goat serum (NGS) for 2 hours. After washing in PBS, slices were immunostained for SOX10, CC1, and STEM101/121. Tissues were incubated with primary antibodies for 3 days at 4C. Secondary antibodies were diluted in 2% NGS and 0.2% Triton X-100. Tissues were incubated with secondary antibodies for 2 hours at room temperature. Biocytin was revealed with secondary antibodies using DyLight-488 streptavidin (Vector Laboratories, Burlingame, USA, 1:200). Images of biocytin-loaded cells were acquired either with a Carl Zeiss microscope equipped with ApoTome 2 or a LEICA SP8 confocal microscope (63 oil objective; numerical aperture, 1.4; 0.75-m Z-step) and processed with National Institutes of Health ImageJ software (70).

We adapted the heuristic algorithm from (29) to identify STEM+ MBP+ OLs in tissue sections. The foundations of the quantitative method remained the same. A ridge-filter extracted sheath-like objects based on intensity and segments associated to cell bodies using watershed segmentation. Two additional features adapted the workflow beyond its original in vitro application. First, we added functionality to allow colocalization of multiple fluorescent stains, as we needed to quantify triple positive STEM+/MBP+/DAPI+ cell objects. Second, because oligodendrocyte sheaths are not parallel and aligned in situ as they are in dissociated nanofiber cell cultures, we adapted the algorithm to report additional metrics about MBP production locally and globally that do not rely on the dissociation of sheaths in dense regions.

Cell nuclei were identified using watershed segmentation of DAPI+ regions and then colocalized pixel-wise with STEM+ objects. The DAPI+ nuclei were then used as local minima to seed a watershed segmentation of the STEM+ stain to separate nearby cell bodies. Last, the identified STEM+ cell bodies were colocalized with overlapping MBP+ sheath-like ridges to define ensheathed cells. We reported the area of MBP overlapping with STEM fluorescence in colocalized regions associated with individual cells, as well as the number of single, double, and triple fluorescently labeled cells. In addition, different cellular phenotypes were noted in situ that were then captured with the adapted algorithm. Qualitatively, we observed cells with expansive MBP production without extended linear sheath-like segments that were not observed in previous applications of the algorithm. These cells were denoted as tuft cells, and were quantitatively defined as STEM+/MBP+/DAPI+ cells without fluorescent ridges that could be identified as extended sheath-like objects.

The myelination potential of three control and 3 MS hiOLs was evaluated at 4, 8, 12, 16, and 20 wpg (n = 2 to 7 per line and per time point; n = 6 to 14 per time point). For each animal, six serial sections at 180-m intervals were analyzed. The percentage of MBP+ cells (composed of ensheathed or tuft cells) was evaluated. Total MBP+ area per STEM+ cells and the average length of MBP+ sheaths per MBP+ cells were analyzed.

Cell survival, proliferation, and differentiation in vivo. The number of STEM101+ grafted cells expressing Caspase3, or Ki67, or SOX10 and CC1 was quantified in the core of the corpus callosum at 8, 12, and 16 wpg. For each animal (n = 3 per group), six serial sections at 180-m intervals were analyzed. Cell counts were expressed as the percentage of total STEM101+ cells.

Myelination by electron microscopy. G ratio (diameter of axon/diameter of axon and myelin sheath) of donor-derived compact myelin was measured as previously described (10). Briefly, the maximum and minimum diameters of a given axon and the maximum and minimum axon plus myelin sheath diameter were measured with the ImageJ software at a magnification of 62,000 for a minimum of 70 myelinated axons per animal. Data were expressed as the mean of the maximal and minimal values for each axon for mice from each group (n = 4 mice per group). Myelin compaction was confirmed at a magnification of 220,000.

Data are presented as means + SEM. Statistical significance was determined by two-tailed Mann Whitney U test when comparing two statistical groups, and with one-way or two-way analysis of variance (ANOVA) followed by Tukeys or Dunnetts (in vivo electrophysiology) multiple comparison tests for multiple groups. Because electrophysiological data in brain slices do not follow a normal distribution after a DAgostino-Pearson normality test, we also performed two-tailed Mann-Whitney U test for comparison between groups. Statistics were done in GraphPad Prism 5.00 and GraphPad Prism 8.2.1 (GraphPad Software Inc., USA). See the figure captions for the test used in each experiment.

Acknowledgments: Funding: This work was supported by the Progressive MS Alliance [PMSA; collaborative research network PA-1604-08492 (BRAVEinMS)] to G.M., J.P.A., A.B.-V.E., and T.K., the National MS Society (NMSS RG-1801-30020 to T.K. and A.B.-V.E.), INSERM and ICM grants to A.B.-V.E., the German Research Foundation (DFG CRC-TR-128B07 to T.K.), and the Italian Multiple Sclerosis Foundation (FISM) (project no. Neural Stem Cells in MS to G.M.). M.C.A. was supported by grants from Fondation pour laide la recherche sur la Sclrose en Plaques (ARSEP) and a sub-award agreement from the University of Connecticut with funds provided by grant no. RG-1612-26501 from National Multiple Sclerosis Society. During this work, S.M. was funded by European Committee for Treatment and Research in Multiple Sclerosis (ECTRIMS). B.G.-D. and M.J.F.L. were supported by the PMSA, PA-1604-08492 and the National MS Society (RG-1801-30020), respectively. B.M.-S. was supported by a Ph.D. fellowship from the French Ministry of Research (ED BioSPC). A.B. and M.C.A. thank respective imaging facilities, ICM Quant and IPNP NeurImag and their respective funding sources Institut des Neurosciences Translationnelles ANR-10-IAIHU-06 Fondation Leducq. Author contributions: Conceptualization: S.M. and A.B.-V.E. Methodology: S.M., L.S., B.M.-S., Y.K.T.X., B.G.-D., M.J.F.L., D.R., L.O., K.-P.K., H.R.S., J.P.A., T.K., G.M., T.E.K., M.C.A., and A.B.V.-E. Formal analysis: S.M., B.M-S., Y.K.T.X., M.C.A., and A.B.-V.E. Writing: S.M. and A.B.V.-E, with editing and discussion from all coauthors Funding acquisition: S.M. and A.B.V.-E. Supervision: A.B.V.-E. Competing interests: T.K. has a pending patent application for the generation of human oligodendrocytes. 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.

Original post:
Multiple sclerosis iPS-derived oligodendroglia conserve their properties to functionally interact with axons and glia in vivo - Science Advances