Category Archives: Somatic Stem Cells

Somatic Cells: Meaning, Characteristics, Types and Examples

Somatic cells account for all the cells of the body except reproductive cells. Other than gametes, stem cells and germs cells, all the cells of a multicellular organism are known as somatic cells.

Diploid somatic cells undergo mitosis and are responsible for growth, repair and regeneration.

Somatic Cells Meaning

Somatic terms originate from the word Soma, which means body. They make up the entire organism other than cells, which have a reproductive function or are undifferentiated, e.g. stem cells.

Somatic Cells Characteristics

Somatic Cells Types and Examples

There are numerous types of somatic cells. In our body, there are 220 types of somatic cells. Many cells are differentiated to perform various specific functions.

Some of the specialised somatic cells are:

Explore all the important topics aligned with the updated NEET syllabus, only at BYJUS. Check NEET Important topics and Preparation Tips for all the important concepts and related topics.

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Somatic Cells: Meaning, Characteristics, Types and Examples

Takeda and the New York Academy of Sciences Announce 2020 Innovators in Science Award Winners – BusinessGhana

The 2020 award celebrates outstanding research in rare diseases Takeda Pharmaceutical Company Limited (Takeda) (TSE:4502/NYSE:TAK) and the New York Academy of Sciences announced today the Winners of the third annual Innovators in Science Award for their excellence in and commitment to innovative science that has significantly advanced the field of rare disease research.

Each Winner receives a prize of US $200,000.

This press release features multimedia.

View the full release here: https://www.

businesswire.

com/news/home/20200708005039/en/ The 2020 Winner of the Senior Scientist Award is Adrian R.

Krainer, Ph.

D.

, St.

Giles Foundation Professor at Cold Spring Harbor Laboratory.

Prof.

Krainer is recognized for his outstanding research on the mechanisms and control of RNA splicing, a step in the normal process by which genetic information in DNA is converted into proteins.

Prof.

Krainer studies splicing defects in patients with spinal muscular atrophy (SMA), a devastating, inherited pediatric neuromuscular disorder caused by loss of motor neurons, resulting in progressive muscle atrophy and eventually, death.

Prof.

Krainers work culminated notably in the development of the first drug to be approved by global regulatory bodies that can delay and even prevent the onset of an inherited neurodegenerative disorder.

Collectively, rare diseases affect millions of families worldwide, who urgently need and deserve our help.

Im extremely honored to receive this recognition for research that my lab and our collaborators carried out to develop the first approved medicine for SMA, said Prof.

Krainer.

As basic researchers, we are driven by curiosity and get to experience the thrill of discovery; but when the fruits of our research can actually improve patients lives, everything else pales in comparison.

The 2020 Winner of the Early-Career Scientist Award is Jeong Ho Lee, M.

D.

, Ph.

D, Associate Professor, Korea Advanced Institute of Science and Technology (KAIST).

Prof.

Lee is recognized for his research investigating genetic mutations in stem cells in the brain that result in rare developmental brain disorders.

He was the first to identify the causes of intractable epilepsies and has identified the genes responsible for several developmental brain disorders, including focal cortical dysplasias, Joubert syndromea disorder characterized by an underdevelopment of the brainstemand hemimegalencephaly, which is the abnormal enlargement of one side of the brain.

Prof.

Lee also is the Director of the National Creative Research Initiative Center for Brain Somatic Mutations, and Co-founder and Chief Technology Officer of SoVarGen, a biopharmaceutical company aiming to discover novel therapeutics and diagnosis for intractable central nervous system (CNS) diseases caused by low-level somatic mutation.

It is a great honor to be recognized by a jury of such globally respected scientists whom I greatly admire, said Prof.

Lee.

More importantly, this award validates research into brain somatic mutations as an important area of exploration to help patients suffering from devastating and untreatable neurological disorders.

The 2020 Winners will be honored at the virtual Innovators in Science Award Ceremony and Symposium in October 2020.

This event provides an opportunity to engage with leading researchers, clinicians and prominent industry stakeholders from around the world about the latest breakthroughs in the scientific understanding and clinical treatment of genetic, nervous system, metabolic, autoimmune and cardiovascular rare diseases.

At Takeda, patients are our North Star and those with rare diseases are often underserved when it comes to the discovery and development of transformative medicines, said Andrew Plump, M.

D.

, Ph.

D.

, President, Research & Development at Takeda.

Insights from the ground-breaking research of scientists like Prof.

Krainer and Prof.

Lee can lead to pioneering approaches and the development of novel medicines that have the potential to change patients lives.

Thats why we are proud to join with the New York Academy of Sciences to broadly share and champion their workand hopefully propel this promising science forward.

Connecting science with the world to help address some of societys most pressing challenges is central to our mission, said Nicholas Dirks, Ph.

D.

, President and CEO, the New York Academy of Sciences.

In this third year of the Innovators in Science Award we are privileged to recognize two scientific leaders working to unlock the power of the genome to bring innovations that address the urgent needs of patients worldwide affected by rare diseases.

About the Innovators in Science Award The Innovators in Science Award grants two prizes of US $200,000 each year: one to an Early-Career Scientist and the other to a well-established Senior Scientist who have distinguished themselves for the creative thinking and impact of their research.

The Innovators in Science Award is a limited submission competition in which research universities, academic institutions, government or non-profit institutions, or equivalent from around the globe with a well-established record of scientific excellence are invited to nominate their most promising Early-Career Scientists and their most outstanding Senior Scientists working in one of four selected therapeutic fields of neuroscience, gastroenterology, oncology, and regenerative medicine.

Prize Winners are determined by a panel of judges, independently selected by the New York Academy of Sciences, with expertise in these disciplines.

The New York Academy of Sciences administers the Award in partnership with Takeda.

For more information please visit the Innovators in Science Award website.

About Takeda Pharmaceutical Company Limited Takeda Pharmaceutical Company Limited (TSE:4502/NYSE:TAK) is a global, values-based, R&D-driven biopharmaceutical leader headquartered in Japan, committed to bringing Better Health and a Brighter Future to patients by translating science into highly-innovative medicines.

Takeda focuses its R&D efforts on four therapeutic areas: Oncology, Rare Diseases, Neuroscience, and Gastroenterology (GI).

We also make targeted R&D investments in Plasma-Derived Therapies and Vaccines.

We are focusing on developing highly innovative medicines that contribute to making a difference in people's lives by advancing the frontier of new treatment options and leveraging our enhanced collaborative R&D engine and capabilities to create a robust, modality-diverse pipeline.

Our employees are committed to improving quality of life for patients and to working with our partners in health care in approximately 80 countries.

For more information, visit https://www.

takeda.

com.

About the New York Academy of Sciences The New York Academy of Sciences is an independent, not-for-profit organization that since 1817 has been committed to advancing science, technology, and society worldwide.

With more than 20,000 members in 100 countries around the world, the Academy is creating a global community of science for the benefit of humanity.

The Academy's core mission is to advance scientific knowledge, positively impact the major global challenges of society with science-based solutions and increase the number of scientifically informed individuals in society at large.

Please visit us online at www.

nyas.

org.

.

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Takeda and the New York Academy of Sciences Announce 2020 Innovators in Science Award Winners - BusinessGhana

Takeda and the New York Academy of Sciences Announce 2020 Innovators in Science Award Winners – Business Wire

NEW YORK & OSAKA, Japan--(BUSINESS WIRE)--Takeda Pharmaceutical Company Limited (Takeda) (TSE:4502/NYSE:TAK) and the New York Academy of Sciences announced today the Winners of the third annual Innovators in Science Award for their excellence in and commitment to innovative science that has significantly advanced the field of rare disease research. Each Winner receives a prize of US $200,000.

The 2020 Winner of the Senior Scientist Award is Adrian R. Krainer, Ph.D., St. Giles Foundation Professor at Cold Spring Harbor Laboratory. Prof. Krainer is recognized for his outstanding research on the mechanisms and control of RNA splicing, a step in the normal process by which genetic information in DNA is converted into proteins. Prof. Krainer studies splicing defects in patients with spinal muscular atrophy (SMA), a devastating, inherited pediatric neuromuscular disorder caused by loss of motor neurons, resulting in progressive muscle atrophy and eventually, death. Prof. Krainers work culminated notably in the development of the first drug to be approved by global regulatory bodies that can delay and even prevent the onset of an inherited neurodegenerative disorder.

Collectively, rare diseases affect millions of families worldwide, who urgently need and deserve our help. Im extremely honored to receive this recognition for research that my lab and our collaborators carried out to develop the first approved medicine for SMA, said Prof. Krainer. As basic researchers, we are driven by curiosity and get to experience the thrill of discovery; but when the fruits of our research can actually improve patients lives, everything else pales in comparison.

The 2020 Winner of the Early-Career Scientist Award is Jeong Ho Lee, M.D., Ph.D, Associate Professor, Korea Advanced Institute of Science and Technology (KAIST). Prof. Lee is recognized for his research investigating genetic mutations in stem cells in the brain that result in rare developmental brain disorders. He was the first to identify the causes of intractable epilepsies and has identified the genes responsible for several developmental brain disorders, including focal cortical dysplasias, Joubert syndromea disorder characterized by an underdevelopment of the brainstemand hemimegalencephaly, which is the abnormal enlargement of one side of the brain. Prof. Lee also is the Director of the National Creative Research Initiative Center for Brain Somatic Mutations, and Co-founder and Chief Technology Officer of SoVarGen, a biopharmaceutical company aiming to discover novel therapeutics and diagnosis for intractable central nervous system (CNS) diseases caused by low-level somatic mutation.

It is a great honor to be recognized by a jury of such globally respected scientists whom I greatly admire, said Prof. Lee. More importantly, this award validates research into brain somatic mutations as an important area of exploration to help patients suffering from devastating and untreatable neurological disorders.

The 2020 Winners will be honored at the virtual Innovators in Science Award Ceremony and Symposium in October 2020. This event provides an opportunity to engage with leading researchers, clinicians and prominent industry stakeholders from around the world about the latest breakthroughs in the scientific understanding and clinical treatment of genetic, nervous system, metabolic, autoimmune and cardiovascular rare diseases.

At Takeda, patients are our North Star and those with rare diseases are often underserved when it comes to the discovery and development of transformative medicines, said Andrew Plump, M.D., Ph.D., President, Research & Development at Takeda. Insights from the ground-breaking research of scientists like Prof. Krainer and Prof. Lee can lead to pioneering approaches and the development of novel medicines that have the potential to change patients lives. Thats why we are proud to join with the New York Academy of Sciences to broadly share and champion their workand hopefully propel this promising science forward.

Connecting science with the world to help address some of societys most pressing challenges is central to our mission, said Nicholas Dirks, Ph.D., President and CEO, the New York Academy of Sciences. In this third year of the Innovators in Science Award we are privileged to recognize two scientific leaders working to unlock the power of the genome to bring innovations that address the urgent needs of patients worldwide affected by rare diseases.

About the Innovators in Science Award

The Innovators in Science Award grants two prizes of US $200,000 each year: one to an Early-Career Scientist and the other to a well-established Senior Scientist who have distinguished themselves for the creative thinking and impact of their research. The Innovators in Science Award is a limited submission competition in which research universities, academic institutions, government or non-profit institutions, or equivalent from around the globe with a well-established record of scientific excellence are invited to nominate their most promising Early-Career Scientists and their most outstanding Senior Scientists working in one of four selected therapeutic fields of neuroscience, gastroenterology, oncology, and regenerative medicine. Prize Winners are determined by a panel of judges, independently selected by the New York Academy of Sciences, with expertise in these disciplines. The New York Academy of Sciences administers the Award in partnership with Takeda.

For more information please visit the Innovators in Science Award website.

About Takeda Pharmaceutical Company Limited

Takeda Pharmaceutical Company Limited (TSE:4502/NYSE:TAK) is a global, values-based, R&D-driven biopharmaceutical leader headquartered in Japan, committed to bringing Better Health and a Brighter Future to patients by translating science into highly-innovative medicines. Takeda focuses its R&D efforts on four therapeutic areas: Oncology, Rare Diseases, Neuroscience, and Gastroenterology (GI). We also make targeted R&D investments in Plasma-Derived Therapies and Vaccines. We are focusing on developing highly innovative medicines that contribute to making a difference in people's lives by advancing the frontier of new treatment options and leveraging our enhanced collaborative R&D engine and capabilities to create a robust, modality-diverse pipeline. Our employees are committed to improving quality of life for patients and to working with our partners in health care in approximately 80 countries. For more information, visit https://www.takeda.com.

About the New York Academy of Sciences

The New York Academy of Sciences is an independent, not-for-profit organization that since 1817 has been committed to advancing science, technology, and society worldwide. With more than 20,000 members in 100 countries around the world, the Academy is creating a global community of science for the benefit of humanity. The Academy's core mission is to advance scientific knowledge, positively impact the major global challenges of society with science-based solutions and increase the number of scientifically informed individuals in society at large. Please visit us online at http://www.nyas.org.

Continue reading here:
Takeda and the New York Academy of Sciences Announce 2020 Innovators in Science Award Winners - Business Wire

Global Tooth Regeneration Market : Industry Analysis and Forecast (2020-2027)-by Type, Application, Population Demographics and Region. – Morning Tick

Global Tooth Regeneration Market was valued US$ XX Mn in 2019 and is expected to reach US$ XX Mn by 2027, at a CAGR of 6.5% during a forecast period 2020-2027.

Global Tooth Regeneration Market, By Regions

Market Dynamics

The Research Report gives a comprehensive account of the drivers and restraints in the tooth regeneration. Somatic stem cells are composed and reprogrammed to induced pluripotent stem cells which can be placed in the dental lamina directly or placed in an absorbable biopolymer in the shape of the new tooth, which is a main source of the novel bioengineered teeth. Tooth replacement therapy is pondered to be a greatly attractive concept for the next generation bioengineered organ replacement.The report study has analyzed revenue impact of covid-19 pandemic on the sales revenue of market leaders, market followers and disrupters in the report and same is reflected in our analysis.

The global tooth regeneration market is mainly compelled by the high occurrence of dental problems with the new research and development activities. According to WHO, the Global Burden of Disease Study 2017 estimated that oral diseases affect close to 3.5 billion people worldwide, with caries of permanent teeth being the most common condition. Globally, it is likely that 2.3 billion people suffer from caries of permanent teeth and more than 530 million children suffer from caries of primary teeth. Additionally, positive refund policies for instance coverage of Medicaid insurance for dental loss treatment and emergence of new technologies like laser tooth generation techniques are projected to enhance the global tooth generation market throughout the estimated period.

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Different researches are carried out by several academies and corporations to understand the possibility of stem cell-based regenerative medicines tooth regeneration. Though stem cell is the protuberant technology in research for tooth regeneration, several organizations are also leveraging laser, drug, and gel as mediums to regenerate teeth. For example, the Wyss Institute at Harvard University is engaged in research related to tooth regeneration using lasers. Tooth generation using stem cells is now under research through the globe. There are some key stem cells on which research are carried out such as stem cells from human exfoliated deciduous teeth (SHEDs), dental pulp stem cells, dental follicle progenitor cells (DFPCs), periodontal ligament stem cells (PDLSCs), and stem cells from apical papilla (SCAPs). A 2009 nationwide survey by the Nova South-eastern University in the U.S. publicized that around 96% of dentists expect stem cell regeneration to lead the future of the dentistry industry. However, occurrence rates are growing in low and middle-income countries. Though, some factors like the preference for endodontic treatment over tooth regeneration products in key dental surgeries and local inflammatory activity, which results in chronic complications to dental replacements, is anticipated to hamper the market throughout the forecast period.

Global Tooth Regeneration Market Segment analysis

Based on population demographics, the geriatric segment is expected to grow at a CAGR of XX% during the forecast period. According to NIH, the geriatric population has an average 18.9 remaining teeth. About 23% of the geriatric population has no teeth, making a positive market situation for manufacturing companies. The above 18 million dental procedures are anticipated to be carried out amongst the geriatric population between 2019 and 2027. Commercialization of tooth regeneration is expected to create lucrative market opportunities for industry players. Based on Type, the dentin segment accounted for a projecting share of the global tooth regeneration market in 2019, owing to the growing occurrence of dental surgery and the uprising demand for tooth regeneration in cosmetic surgery, particularly from developing economies like India, China, and Brazil.

Global Tooth Regeneration Market Regional analysis

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The Asia Pacific is projected to dominate the global tooth regeneration market throughout the forecast period. Tooth regeneration addressable market is likely to be highest in the Asia Pacific, with China and India located as the major growth engines. The occurrence of tooth regeneration is projected to capture this market. Also, the number of dental procedures is anticipated to grow at the highest CAGR of ~10.8% in the Asia Pacific between 2019 and 2027. Besides, the growing incidence of dental cavities & periodontics, particularly in emerging countries like China and India has led to the rising demand for orthopedic & dental surgery. North America and Europe are estimated to collectively account for the major share of global procedures during the forecast period.

Key Developments

In June 2018, Datum Dental Ltd., the prominent provider of OSSIX brand innovative solutions for bone and tissue regeneration for dentistry, announced clearances for OSSIX Bone with Health Canada and CE Mark approval in Europe. OSSIX Bone received FDA clearance in July 2017 and was launched commercially in the USA. In April 2018, Datum Dental, the leading provider of OSSIX brand innovative solutions for bone and tissue regeneration for dentistry, announced the expansion of its global distribution network. In the USA, Dentsply Sirona Implants is now promoting the full OSSIX line.

The objective of the report is to present a comprehensive analysis of the Global Tooth Regeneration Market including all the stakeholders of the industry. The past and current status of the industry with forecasted market size and trends are presented in the report with the analysis of complicated data in simple language. The report covers all the aspects of the industry with a dedicated study of key players that includes market leaders, followers and new entrants. PORTER, SVOR, PESTEL analysis with the potential impact of micro-economic factors of the market has been presented in the report. External as well as internal factors that are supposed to affect the business positively or negatively have been analysed, which will give a clear futuristic view of the industry to the decision-makers.

The report also helps in understanding Global Tooth Regeneration Market dynamics, structure by analysing the market segments and projects the Global Tooth Regeneration Market size. Clear representation of competitive analysis of key players by Application, price, financial position, Product portfolio, growth strategies, and regional presence in the Global Tooth Regeneration Market make the report investors guide. Scope of the Global Tooth Regeneration Market

Global Tooth Regeneration Market, By Type

Dentin Dental Pulp Tooth Enamel Global Tooth Regeneration Market, By Applications

Hospitals Dental Clinics Others Global Tooth Regeneration Market, By Population Demographics

Geriatric Middle-aged Adults Others Global Tooth Regeneration Market, By Regions

North America Europe Asia-Pacific South America Middle East and Africa (MEA) Key Players operating the Global Tooth Regeneration Market

Unilever Straumann Dentsply Sirona 3M Zimmer Biomet Ocata Therapeutics Integra LifeSciences Datum Dental CryoLife BioMimetic Therapeutic Cook Medical

Major Table of Contents Report

Chapter One: Tooth Regeneration Market Overview

Chapter Two: Manufacturers Profiles

Chapter Three: Global Tooth Regeneration Market Competition, by Players

Chapter Four: Global Tooth Regeneration Market Size by Regions

Chapter Five: North America Tooth Regeneration Revenue by Countries

Chapter Six: Europe Tooth Regeneration Revenue by Countries

Chapter Seven: Asia-Pacific Tooth Regeneration Revenue by Countries

Chapter Eight: South America Tooth Regeneration Revenue by Countries

Chapter Nine: Middle East and Africa Revenue Tooth Regeneration by Countries

Chapter Ten: Global Tooth Regeneration Market Segment by Type

Chapter Eleven: Global Tooth Regeneration Market Segment by Application

Chapter Twelve: Global Tooth Regeneration Market Size Forecast (2019-2026)

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Global Tooth Regeneration Market : Industry Analysis and Forecast (2020-2027)-by Type, Application, Population Demographics and Region. - Morning Tick

REGENERATIVE MEDICINE MARKET ALONG WITH COVID-19 IMPACT ANALYSIS AND CLINICAL OUTLOOK 2022 | STRYKER CORPORATION, ZIMMER BIOMET HOLDINGS INC.,…

The Global Regenerative Medicine Market research report offers an in-depth analysis of the global market, providing relevant information for the new market entrants or well-established players. Some of the key strategies employed by leading key players operating in the market and their impact analysis have been included in this research report. However, the small molecules & biologics segment is anticipated to grow at a highestCAGR of 34.2%from 2022,

Regenerative medicines hold the ability to replace, repair, and regenerate tissues and organs that are affected due to some disease, injury, or natural ageing process. These medicines are capable of restoring the functionality of tissues & cells applicable in a wide range of degenerative disorders such as neurodegenerative diseases, dermatology, cardiovascular and orthopedic applications. Researchers have been focusing on the development of advanced technologies based on genes, biologics, somatic cells and stem cells. Stem cells have the capability to proliferate and differentiate owing to which they are of importance in this field.

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List of Top Key Players Profiled In The Report

Stryker Corporation, Zimmer Biomet Holdings, Inc., Medtronic plc, Baxter International Inc., DePuy Synthes, Organogenesis Inc. (Advanced Biohealing), Integra Lifesciences Holdings Corporation, Acelity Holdings, Inc., Ocata Therapeutics Inc. (Astellas Pharma Inc.), CryoLife Inc.

The Regenerative Medicine Industry is extremely competitive and consolidated because of the existence of several established companies that are adopting different marketing strategies to increase their market share. The vendors engaged in the sector are outlined based on their geographic reach, financial performance, strategic moves, and product portfolio. The vendors are gradually widening their strategic moves, along with customer interaction.

The research on the Regenerative Medicine market concentrates on extracting valuable data on swelling investment pockets, significant growth opportunities, and major market vendors to help understand business owners what their competitors are doing best to stay ahead in the competition. The research also segments the Regenerative Medicine market on the basis of end user, product type, application, and demography for the forecast period 2020-2025.

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Regenerative Medicine market with respect to five major regions, namely; North America, Europe, Asia-Pacific (APAC), Middle East and Africa (MEA) and South America (SAM), which is later sub-segmented by respective countries and segments.

The key questions answered in the report:

-What will be the market size and growth rate in the 2020 year?

-What are the key factors driving the global Regenerative Medicine market?

-What are the risks and challenges in front of the market?

-Who are the key vendors in the global Regenerative Medicine market?

-Trending factors influencing the market shares of Regenerative Medicine?

-What are the key outcomes of Porters five forces model?

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Table of Contents

Global Regenerative Medicine in 2020, by Manufacturers, Regions, Types and Applications

1 Study Coverage

2 Executive Summary

3 Market Size by Manufacturers

4 Production by Regions

5 Consumption by Regions

6 Market Size by Type

7 Market Size by Application

8 Manufacturers Profiles

9 Consumption Forecast

10 Upstream, Industry Chain and Downstream Customers Analysis

11 Opportunities & Challenges, Threat and Affecting Factors

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REGENERATIVE MEDICINE MARKET ALONG WITH COVID-19 IMPACT ANALYSIS AND CLINICAL OUTLOOK 2022 | STRYKER CORPORATION, ZIMMER BIOMET HOLDINGS INC.,...

Outlook on the Worldwide Regenerative Medicine Industry to 2024 – Rising Global Healthcare Expenditure Presents Opportunities – GlobeNewswire

June 22, 2020 06:39 ET | Source: Research and Markets

Dublin, June 22, 2020 (GLOBE NEWSWIRE) -- The "Global Regenerative Medicine Market: Size & Forecast with Impact Analysis of COVID-19 (2020-2024)" report has been added to ResearchAndMarkets.com's offering.

This report provides an in-depth analysis of the global regenerative medicine market with description of market sizing and growth. The analysis includes market by value, by product, by material and by region. Furthermore, the report also provides detailed product analysis, material analysis and regional analysis.

Moreover, the report also assesses the key opportunities in the market and outlines the factors that are and would be driving the growth of the industry. Growth of the overall global regenerative medicine market has also been forecasted for the years 2020-2024, taking into consideration the previous growth patterns, the growth drivers and the current and future trends.

Region Coverage:

Company Coverage:

Regenerative medicines emphasise on the regeneration or replacement of tissues, cells or organs of the human body to cure the problem caused by disease or injury. The treatment fortifies the human cells to heal up or transplant stem cells into the body to regenerate lost tissues or organs or to recover impaired functionality. There are three types of stem cells that can be used in regenerative medicine: somatic stem cells, embryonic stem cells (ES cells) and induced pluripotent stem cells (iPS cells).

The regenerative medicine also has the capability to treat chronic diseases and conditions, including Alzheimer's, diabetes, Parkinson's, heart disease, osteoporosis, renal failure, spinal cord injuries, etc. Regenerative medicines can be bifurcated into different product type i.e., cell therapy, tissue engineering, gene therapy and small molecules and biologics. In addition, on the basis of material regenerative medicine can be segmented into biologically derived material, synthetic material, genetically engineered materials and pharmaceuticals.

The global regenerative medicine market has surged at a progressive rate over the years and the market is further anticipated to augment during the forecasted years 2020 to 2024. The market would propel owing to numerous growth drivers like growth in geriatric population, rising global healthcare expenditure, increasing diabetic population, escalating number of cancer patients, rising prevalence of cardiovascular disease and surging obese population.

Though, the market faces some challenges which are hindering the growth of the market. Some of the major challenges faced by the industry are: legal obligation and high cost of treatment. Whereas, the market growth would be further supported by various market trends like three dimensional bioprinting , artificial intelligence to advance regenerative medicine, etc.

Key Topics Covered:

1. Executive Summary

2. Introduction 2.1 Regenerative Medicine: An Overview 2.2 Regeneration in Humans: An Overview 2.3 Expansion in Peripheral Industries of Regenerative Medicine 2.4 Approval System for Regenerative Medicine Products 2.5 Regenerative Medicine Segmentation

3. Global Market Analysis 3.1 Global Regenerative Medicine Market: An Analysis 3.1.1 Global Regenerative Medicine Market by Value 3.1.2 Global Regenerative Medicine Market by Products (Cell Therapy, Tissue Engineering, Gene Therapy and Small Molecules and Biologics) 3.1.3 Global Regenerative Medicine Market by Material (Biologically Derived Material, Synthetic Material, Genetically Engineered Materials and Pharmaceuticals) 3.1.4 Global Regenerative Medicine Market by Region (North America, Europe, Asia Pacific and ROW)

3.2 Global Regenerative Medicine Market: Product Analysis 3.2.1 Global Cell Therapy Regenerative Medicine Market by Value 3.2.2 Global Tissue Engineering Regenerative Medicine Market by Value 3.2.3 Global Gene Therapy Regenerative Medicine Market by Value 3.2.4 Global Small Molecules and Biologics Regenerative Medicine Market by Value

3.3 Global Regenerative Medicine Market: Material Analysis 3.3.1 Global Biologically Derived Material Market by Value 3.3.2 Global Synthetic Material Market by Value 3.3.3 Global Genetically Engineered Materials Market by Value 3.3.4 Global Regenerative Medicine Pharmaceuticals Market by Value

4. Regional Market Analysis 4.1 North America Regenerative Medicine Market: An Analysis 4.2 Europe Regenerative Medicine Market: An Analysis 4.3 Asia Pacific Regenerative Medicine Market: An Analysis 4.4 ROW Regenerative Medicine Market: An Analysis

5. COVID-19 5.1 Impact of Covid-19 5.2 Response of Industry to Covid-19 5.3 Variation in Organic Traffic 5.4 Regional Impact of COVID-19

6. Market Dynamics 6.1 Growth Drivers 6.1.1 Growth in Geriatric Population 6.1.2 Rising Global Healthcare Expenditure 6.1.3 Increasing Diabetic Population 6.1.4 Escalating Number of Cancer Patients 6.1.5 Rising Prevalence of Cardiovascular Disease 6.1.6 Surging Obese Population 6.2 Challenges 6.2.1 Legal Obligation 6.2.2 High Cost of Treatment 6.3 Market Trends 6.3.1 3D Bio-Printing 6.3.2 Artificial Intelligence to Advance Regenerative Medicine

7. Competitive Landscape 7.1 Global Regenerative Medicine Market Players: A Financial Comparison 7.2 Global Regenerative Medicine Market Players' by Research & Development Expenditure

8. Company Profiles 8.1 Bristol Myers Squibb (Celgene Corporation) 8.1.1 Business Overview 8.1.2 Financial Overview 8.1.3 Business Strategy 8.2 Medtronic Plc 8.2.1 Business Overview 8.2.2 Financial Overview 8.2.3 Business Strategy 8.3 Smith+Nephew (Osiris Therapeutics, Inc.) 8.3.1 Business Overview 8.3.2 Financial Overview 8.3.3 Business Strategy 8.4 Novartis AG 8.4.1 Business Overview 8.4.2 Financial Overview 8.4.3 Business Strategy

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Outlook on the Worldwide Regenerative Medicine Industry to 2024 - Rising Global Healthcare Expenditure Presents Opportunities - GlobeNewswire

Estrogen induces dynamic ER and RING1B recruitment to control gene and enhancer activities in luminal breast cancer – Science Advances

INTRODUCTION

The steroid hormones 17-estradiol (E2) and progesterone (P4) are the major female sex hormones (1). E2 plays essential roles during development of the mammary glands and the reproductive system and is required for brain, skin, and bone homeostasis (2). More than 70% of all human breast cancers express the estrogen receptor (ER), and most of these are E2 dependent for growth (3). Upon E2 stimulation, liganded ER translocates into the nucleus and is recruited to chromatin through multiple mechanisms, including binding to a cognate DNA sequence known as estrogen response elements (EREs). ER directly regulates genes involved in cell proliferation and cell cycle by interacting with a plethora of chromatin remodelers, epigenetic regulators, and transcription factors (TFs) (4). Despite the extensive literature on how E2 and ER cooperate to induce expression of pro-oncogenic regulators of cell growth and survival, a greater understanding of the mechanisms underpinning this process is required to develop new therapeutic strategies for treatment of luminal [ER-positive (ER+)] breast cancer.

Although EREs are found in both promoters and enhancers, ER predominantly binds to EREs at enhancers (5, 6). This observation suggests that liganded ER regulates gene expression via modulation of enhancer-promoter interactions. Cancer cells have permissive chromatin accessibility and an enhancer landscape that instruct oncogenes and cell cycle genes to induce aberrant cell proliferation (7, 8). Enhancer-bound ER is essential for the expression of E2-induced genes (9, 10). Most of our understanding of how hormones regulate gene transcription and chromatin architecture has been derived from studying the effects of acute hormone administration, typically within minutes of exposure to E2 in steroid-deprived cells (11, 12). The impact of prolonged hormone exposure on gene expression and chromatin landscape in breast cancer cells is less studied. In addition, it is still not fully understood how ER target genes and enhancer activity are linked to the maintenance thereof and how the epigenetic landscape is modified following E2 addition, both immediately and in the long term. Addressing these central questions might provide a better understanding of how estrogen influences breast cancer initiation and progression over time.

Polycomb repressive complex 1 and 2 (PRC1 and PRC2) are essential regulators of development and are strongly implicated in cancer (13). Although PRC1/2 are mostly associated with gene repression, increasing evidence indicates that they can also be recruited to actively transcribed genes in multiple biological processes (14). We recently demonstrated that PRC1 complexes are recruited to active enhancers and promoters in several cancer types, including ER+ and triple-negative breast cancer (TNBC). Enhancers containing PRC1 are also co-occupied by ER in ER+ breast cancer cells (15). Independent studies showed that the PRC1 subunits PCGF2 (Polycomb Group Ring Ringer 2) and CBX8 (Chromobox 8) also play important roles in breast cancer: PCGF2 positively regulates expression of ESR1 (encoding ER), and CBX8 regulation of gene expression in breast cancer is both dependent and independent of its association with other PRC1 subunits (16, 17). How PRC1 proteins are recruited to chromatin and the molecular mechanisms that regulate their novel roles as activators of gene transcription in breast cancer remain to be determined.

Here, we show that comprehensive analyses of accessible chromatin and transcriptome landscapes identify unique chromatin stages that are dynamically assembled in response to E2. We found that RING1B is an essential epigenetic factor required for both initiation and maintenance of such chromatin stages both dependently and independently of its enzymatic activity and binding to nucleosomes. Mechanistically, RING1B is recruited to FOXA1-GRHL2-ERbound active enhancers and genes in response to E2 stimulation, is required for full engagement of ER, and is required for E2-induced chromatin opening genome-wide. We further show that RING1B depletion induces an epigenetic reprogramming that results in changes in the enhancer landscape. We also demonstrate that RING1B depletion blocks cell proliferation and diminishes cell fitness. Last, we identified RING1B binding events at single-nucleotide resolution co-occupied by ER and TFs functionally involved in estrogen signaling including FOXA1 and GRHL2. We propose RING1B as a critical factor regulating the E2-ERmediated epigenetic changes that are required for breast cancer cell proliferation.

Hormones induce alterations in the chromatin structure that are accompanied by massive changes in the transcriptional landscape (18). Nevertheless, most studies to date determined the immediate effects in gene transcription and chromatin accessibility after acute administration, typically minutes, of E2 and P4, among others (11, 18). Our previous studies indicated that RING1B regulated genes and enhancers bound by ER in luminal breast cancer cells when cultured in the presence of serum that contains low levels of E2 [referred hereafter as full media (FM)] (fig. S1A) (15). To precisely determine transcription and chromatin accessibility mediated by liganded ER, we deprived cells of E2 by culturing them in media containing charcoal-stripped serum [hereafter defined as hormone-deprived (HD) media] for 72 hours. HD induces growth arrest of ER+ cells, and proliferation can be stimulated by administration of E2 (19). For our studies, we stimulated the cells with 10 nM E2 for 4, 8, 12, and 24 hours and then examined gene expression profile changes by RNA sequencing (RNA-seq) and mapped the chromatin landscape by assay of transposase accessible chromatin sequencing (ATAC-seq). These experiments were performed using control and RING1B-depleted cells from two independent transductions and E2 inductions (fig. S1A).

We first delineated the effects of prolonged administration of E2 in regulating gene expression changes and chromatin accessibility in control cells. RNA-seq revealed that distinct gene expression patterns emerged along the E2 time course [fold change (FC) > 2, q value < 0.01]. While ~100 genes were down-regulated (group 1), ~1200 genes were dynamically up-regulated during the course of E2 (groups 2 to 5). Unexpectedly, a small number of genes was continuously up-regulated from HD to 24 hours after E2 (group 2), with most genes being transcriptionally induced at the 12- and 24-hour time points (groups 3 and 5) (fig. S1B). Notably, a large set of genes was up-regulated specifically at 12 hours and then down-regulated at 24 hours (group 3), suggesting that massive chromatin architecture changes may occur between 8 and 24 hours after E2 administration. Genes up-regulated in each of the clusters were well-known E2-responsive genes including CXCL12 and FMN1 (early response) as well as E2F1 and CCNA2 (late response) (fig. S1C) (20). Gene set enrichment analysis (GSEA) confirmed successful E2 stimulation, since the induced genes were enriched for the early and late E2 response pathways and were also cell cycle and E2F targets (fig. S1D). These results indicated that E2 induced gene expression changes in a time-dependent manner that requires exquisite orchestration and coordination of dynamic changes in gene transcription to induce proliferation of luminal breast cancer cells.

Chromatin is extensively remodeled upon hormone administration (18, 21, 22). We next sought to determine chromatin accessibility changes after estrogen induction and how these changes correlated with gene expression. Distribution of genome-wide ATAC-seq peaks indicated that chromatin was most dynamic at promoters and intergenic regions in response to E2 (fig. S1E). In agreement with the massive changes in gene transcription observed between 8 and 24 hours upon E2 administration (fig. S1B, clusters 3 to 5), TF binding sites of key breast cancer TFs such as FOXA1/2, JUNB, SP1, and GRHL2 (23), as well as the chromatin organization factor CTCF (24), became increasingly accessible after 4 and 8 hours (fig. S1F), suggesting that chromatin accessibility changes primarily occur during the first 8 hours of E2 induction. By clustering genome-wide ATAC-seq peaks (fig. S1G), we confirmed that the most changes in accessibility occur at 8 hours. To determine whether gene expression correlated with chromatin accessibility, we interrogated ATAC-seq peaks 2.5 kb from genome-wide transcription start sites (TSS). The greatest changes in chromatin accessibility around TSS were observed after 8 hours of E2 induction (fig. S1H), suggesting that changes in chromatin landscape occur before differences in gene transcription observed after 12 and 24 hours of E2 administration. However, we did not observe complete correlation between transcription of E2-induced genes and chromatin accessibility changes. For instance, CXCL12 and FMN1 genes, which belong to group 2 in the RNA-seq classification (fig. S1B), exhibited diverse ATAC-seq profiles (fig. S1I). The TSS of CCND1, a gene that was strongly induced at 12 hours but decreased at 24 hours, demonstrated significant accessibility at 8 hours, while GREB1, which was induced at both 12 and 24 hours, was most accessible at 24 hours. Overall, these results indicate that (i) E2 dynamically modulates genetic programs, (ii) massive chromatin accessibility changes occur during the first 8 hours of E2 exposure, and (iii) global correlation of chromatin opening with gene up-regulation was modest, possibly because of secondary effects of the estrogen response.

We recently noted that RING1B may be functionally involved in E2-mediated gene regulation (15). Whether RING1B is required for E2-induced gene expression changes and chromatin accessibility is not known. Analysis of all and unique differentially expressed genes induced by E2 (FC > 2, q value < 0.05) in control cells compared to RING1B-depleted cells (fig. S2A) revealed that E2-mediated gene regulation strongly depends on RING1B (Fig. 1, A and B). RING1B depletion predominantly down-regulated early and late E2-responsive genes, epithelial-to-mesenchymal transition, G2M checkpoints, as well as E2F and MYC targets (Fig. 1C). These results were further confirmed by reverse transcription quantitative polymerase chain reaction (RT-qPCR), by both stable short hairpin RNA (shRNA) and acute (small interfering RNA) RING1B depletion, and also in MCF7 cells, another ER+ breast cancer cell line (fig. S2, B to D). Interferon- and interferon- response were the only pathways up-regulated after RING1B depletion (Fig. 1C). However, interferon genes were not occupied by RING1B or ER, suggesting that RING1B does not directly regulate the interferon pathway.

(A) RNA-seq heat maps of all deregulated genes in control and RING1B-depleted T47D cells. Fold change > 2, q value < 0.05. N = 2. (B) Genome browser screenshots of RNA-seq tracks at TFF1 and GREB1 loci in control and RING1B KD cells. (C) GSEAs of RING1B-depleted cells compared to control cells. NES, normalized enrichment score. (D) Western blot analysis after replacement of RING1B with shRNA-resistant and HA-tagged RING1B mutants. VINCULIN was used as a loading control. RT-qPCR analysis of endogenous RING1B normalized to the housekeeping gene RPO in shCTR and shRING1B cells expressing HA-RING1BR98A or HA-RING1BI53A. N = 2. (E) Volcano plots (adjusted P value) of deregulated genes in T47D-shCTR (RING1BWT) and cells expressing RING1B mutants after 24 hours of E2. (F) Venn diagram of up-regulated genes after 24 hours of E2 in the three cell lines from (E). (G) Western blot of ER, RING1B, and HA, from shCTR and shRING1B cells before and after HA-RING1BWT expression. VINCULIN was used as a loading control. Volcano plots (adjusted P value) of deregulated genes in the RING1B rescue cells after 24 hours of E2. (H) GSEA of RING1B rescue cells 24 hours after 24 hours of E2. (I) Binary ATAC-seq heat map in control and RING1B-depleted cells during E2 administration. (J) Genome browser screenshots of ATAC-seq peaks at the TFF1 locus in control and RING1B KD cells. (K) ATAC-seq signals in control and RING1B KD cells in HD condition and the E2 time course. (L) Genome browser screenshots of ATAC-seq peaks at the GREB1 locus in control and RING1B KD cells.

RING1B is an E3 ligase that can also bind to the histone H2A/H2B dimer. These functions are dictated by specific amino acids on the RING1B protein. Specifically, isoleucine at position 53 (I53) interacts with the E2-ligase, UBCH5C, to ubiquitinate its substrate (25), and mutation to alanine (I53A) disrupts RING1B E3 ligase activity. Similarly, arginine 98 (R98) inserts into an acidic pocket of H2A residues, and mutation of R98 to alanine (R98A) results in a 50-fold decrease in RING1B interaction with the nucleosome concomitant with reduced H2A ubiquitination (26). Thus, we wondered whether these functions are required for the E2-mediated transcriptional response. We generated T47D cells expressing hemagglutinin (HA)tagged versions of RING1B with an alanine at position 53 in place of isoleucine (RING1BI53A) or an alanine at position 98 in place of arginine (RING1BR98A). Cells were transduced with lentiviruses expressing HA-RING1BI53A or HA-RING1BR98A (resistant to shRNA against RING1B) containing an internal ribosomal entry site mCherry. Fluorescence-activated cell sorting (FACS)sorted mCherry+ cells were then transduced with shRNA-RING1B lentivirus to deplete endogenous RING1B (Fig. 1D). In agreement with our previous results, neither RING1B depletion nor the expression of both RING1B mutants affected global H2AK119ub1 levels (fig. S2E). Cellular fractionation assays showed that HA-RING1BR98A was displaced from the insoluble chromatin. Similarly to HA-RING1BWT, HA-RING1BI53A remained at both soluble and insoluble chromatin fractions (fig. S2F). These results confirm that the R98 residue of RING1B is required for strong association of RING1B to chromatin. T47D cells expressing endogenous and wild-type RING1B (RING1BWT), HA-RING1BI53A, or HA-RING1BR98A were cultured in HD media for 72 hours (Fig. 1, A and B, and fig. S1, A and B), and E2 was administered for 24 hours. Cells expressing the RING1B mutants only partially responded to E2 compared to WT, as demonstrated by global gene expression changes (Fig. 1E). Specifically, RING1BR98A mutation significantly down-regulated the E2-mediated transcriptional response compared to RING1BI53A cells (Fig. 1E), suggesting that RING1B nucleosomal binding is more functionally important than its enzymatic activity in mediating the estrogen response. Only ~20% of the genes up-regulated in RING1BWT (171 of 835) were also up-regulated in the mutant cells (Fig. 1F), indicating that some E2-induced genes do not require RING1B enzymatic activity (360 of 427) nor binding to nucleosomes (192 of 223). About 50% of genes up-regulated in RING1BWT (454 of 835) were not induced in the RING1B mutants, confirming that RING1B enzymatic activity and interaction with histone H2A/H2B dimers were required for their transcriptional activation. RNA-seq experiments performed in RING1B rescue cells (shRING1B + HA-RING1BWT) before and after 24 hours of E2 administration showed a similar gene expression profile compared to shCTR cells in the presence of 24 hours of E2 (Fig. 1G and fig. S1D). GSEA revealed a full functional rescue when HA-RING1BWT was ectopically expressed in shRING1B cells (compare Fig. 1H and fig. S1D).

E2 induced dynamic changes in chromatin accessibility and gene transcription (fig. S1). Since RING1B depletion hampered expression of E2-responsive genes, we expected to detect reduced accessibility at these regulatory sites. Thousands of de novo sites that demonstrated increased accessibility upon E2 administration were dependent on RING1B (Fig. 1, I to L). These effects of RING1B loss were not due to defects in cell cycle or proliferation (fig. S2, G and H), further suggesting that RING1B is required for the initiation and maintenance of gene transcription induced by E2 in luminal breast cancer cells.

Chromatin is heavily remodeled during E2 administration (fig. S1); therefore, we sought to determine the enhancer landscape generated upon E2 induction. We first interrogated whether E2 administration following RING1B depletion affected global levels of histone modifications associated with Polycomb-mediated repression (H2AK119ub1 and H3K27me3), gene activation (H3K4me3), and active enhancers (H3K4me1 and H3K27ac). In agreement with our previous report, we did not detect changes in global H2AK119ub1 after RING1B depletion (15), irrespective of E2 induction (Fig. 2A and fig. S2). Although H3K27me3 levels remained constant, accumulation of global H3K27ac following E2 stimulation was hindered in RING1B-depleted cells (Fig. 2A). However, RING1B depletion did not affect either the expression or the protein level of EP300, the main histone acetyltransferase that deposits H3K27ac (fig. S3, A and B) (27). The general genome-wide distribution of H3K27ac was mostly unchanged upon 24 hours of E2 in control and RING1B-depleted cells (Fig. 2B), suggesting a potential role of RING1B in regulating a specific set of enhancers that are mediated by E2.

(A) Western blots of histone modifications in control and RING1B-depleted cells in HD condition and upon E2 administration. Histones were extracted using sulfuric acid. (B) H3K27ac ChIP-seq signal across the right arm of the chromosome 17 in control and RING1B-depleted cells. (C) SEs identified in each E2 time point. (D) Venn diagram of SEs and genes associated with SEs in each E2 time point. (E) Genome browser screenshots of H3K27ac ChIP-seq in SEs identified in the HD and 24 hours of E2 condition (BCAM SE), only after 24 hours of E2 (GREB1 SE), and at all the time points analyzed (DSCAM SE). (F) H3K27ac signal in control and RING1B KD cells at sites that acquired H3K27ac after 24 hours of E2 in control cells. Significance was determined by Mann-Whitney U test. (G) Genome browser screenshots of H3K27ac in control and RING1B KD cells before and after 8 and 24 hours of E2. (H) RT-qPCR analyses of enhancer RNA expression at the GREB1 and E2F6 SEs in control and RING1B-depleted cells in the HD condition and after 24 hours of E2. mRNA expression was normalized to the housekeeping gene RPO. N = 3.

Because super-enhancers (SEs) regulate oncogenic pathways in cancer (28), we focused our attention to SE dynamics (gain and loss) in response to E2. Potential target genes of the 752 SEs identified in hormone-deprived cells included key breast cancer TFs such as FOXA1 and GATA3 (Fig. 2C). In estrogen-treated cells, 598 and 859 SEs were identified with potential target genes including GREB1 and E2F6 (Fig. 2C). There was a relatively high overlap in the three experimental conditions between SEs and SE target genes (Fig. 2, D and E), suggesting that a unique subset of SEs are dynamically regulated upon E2 administration. Genome-wide H3K27ac at de novo enhancers gained in response to E2 was significantly reduced in RING1B-depleted cells compared to control (Fig. 2, F and G) concomitant with a reduction of enhancer RNA levels (Fig. 2H). RING1B depletion did not reduce H3K27ac at sites that were already decorated with high levels of H3K27ac before E2 stimulation (fig. S3, C and D), indicating that RING1B functions primarily at sites of de novo enhancers following E2 induction.

How the Polycomb group of proteins are recruited to chromatin is under constant examination (14, 29). Our previous studies identified co-occupancy of RING1B and ER at enhancers and promoters containing EREs and FOXA1 motifs in luminal breast cancer cells (15). We thus hypothesized that E2 administration may regulate deposition of RING1B at chromatin. Since ER is recruited to chromatin within minutes of E2 addition (9), we mapped genome-wide ER, FOXA1, and RING1B binding following 45 min of E2 stimulation as well as at 8 and 24 hours to investigate potential binding dynamics over prolonged E2 exposure. To minimize potential secondary effects on gene transcription due to stable RING1B depletion, we generated new T47D cells with doxycycline-inducible RING1B knockdown (fig. S4, A and B). RING1B depletion was initiated 48 hours before hormone deprivation for 72 hours and E2 stimulation.

Notably, RING1B binding at chromatin was dependent on estrogen (Fig. 3A). As expected, E2 treatment led to massive ER localization to chromatin (6, 3032), while recruitment of FOXA1 was mostly independent of E2 (33) (Fig. 3A). Upon E2 induction, RING1B was recruited to a large majority of ER/FOXA1 cotargets (Fig. 3, B and C). We also observed RING1B occupancy at genomic sites not cobound by ER/FOXA1 that lose RING1B binding after 45 min of E2 induction (Fig. 3, B to D), indicating a redistribution of RING1B during the early estrogen response. Specifically, we found 455 peaks corresponding to 245 genes occupied by RING1B in the absence of E2, while 4212 peaks corresponding to 2092 genes were found to be RING1B targets after 45 min of E2 induction. In agreement with previous reports, the number of ER binding sites increased ~5-fold after 45 min of E2, while the number of FOXA1 binding sites modestly increased (Fig. 3E).

(A) RING1B, ER, and FOXA1 ChIP-seq signals in control cells before (HD) and after 45 of E2. Number of RING1B peaks in HD = 455, after 45 of E2 = 4212. ER peaks in HD = 328, after 45 of E2 = 2015. FOXA1 peaks in HD = 102,304, after 45 of E2 = 140,846. (B) ChIP-seq heat maps of RING1B, ER and FOXA1 ChIP-seq signal before and after 45 of E2. Heat maps are clustered by RING1B occupancy. (C and D) Genome browser screenshots of RING1B, ER, FOXA1, and H3K27ac in control cells at CT62 (C) and SKOR1 (D) before and after 45 of E2. (E) Venn diagrams of target genes before (HD) and after 45 of E2. (F) ChIP-seq heat maps of RING1B in control and RING1B-depleted cells. (G) RING1B, ER, and FOXA1 ChIP-seq signals in control cells before (HD) and after 45 of E2. Significance was determined by Mann-Whitney U test. (H and I) Genome browser screenshots of ChIP-seqs at ESR1, BCL2L1, and BCL2L1 SEs (H) and GRHL1 (I). (J) FOXA1, RING1B, and ER ChIP-qPCR of RING1B, ER, and FOXA1 cobound sites in control and FOXA1-depleted cells. N = 2. (K) Western blots of ER, FOXA1, and RING1B in MDA-MB-231 cells expressing HA-ER and HA-FOXA1 and after E2 administration. VINCULIN was used as a loading control. (L) RT-qPCR analyses of TFF1 and GREB1 in MDA-MB-231 as in (K). (M) ChIP-qPCR of ER, RING1B, and FOXA1 cotargets in T47D. Results are presented as fold recruitment over cells not transfected with HA-ER and HA-FOXA1. N = 2.

We then asked whether RING1B depletion regulated recruitment of ER and FOXA1. To this end, we first confirmed that knockdown of RING1B diminished chromatin-bound RING1B genome-wide (Fig. 3F). Analysis of RING1B, ER, and FOXA1 co-occupied sites after 45 min of E2 administration revealed that loss of RING1B did not alter FOXA1 binding nor H3K27ac deposition but significantly reduced ER recruitment (Fig. 3G and fig. S4, C and D). We then divided the RING1B chromatin immunoprecipitation sequencing (ChIP-seq) signal in quartiles to determine whether ER and FOXA1 recruitment depended on RING1B binding levels. ER occupancy levels strongly correlated with that of RING1B and were significantly reduced following RING1B depletion in the first two quartiles, whereas FOXA1 occupancy remained relatively unchanged in all four quartiles (fig. S4E). Significant reduction of ER binding was observed at the promoters and enhancers of genes with key oncogenic functions in breast cancer including ESR1, GRHL2, and BCL2L1 (Fig. 3H). We also found that genes co-occupied by RING1B and FOXA1, but not ER, contained EREs (P value of 1 10100) (Fig. 3I), suggesting that RING1B can be recruited to ER binding motifs in the absence of ER. Last, we performed ChIP-seq of the RING1B mutants to determine whether their chromatin occupancy was altered. In agreement with the lack of response to E2 of both cell lines expressing HA-RING1B mutants in a stable shRING1B background (Fig. 1, G and H), neither RING1BI53A nor RING1BR98A was stably associated with chromatin (fig. S4F). These results suggest that interaction of RING1B with the nucleosomes and its enzymatic activity to nonhistone substrates are required for its stabilization to chromatin both in the absence and presence of E2.

The pioneer factor FOXA1 is a key determinant of ER recruitment and function. Since E2 administration also induces massive RING1B recruitment to chromatin, we next asked whether FOXA1 served as a pioneer factor for RING1B. FOXA1 depletion by shRNA (fig. S4G) strongly impaired recruitment of both ER and RING1B (Fig. 3J), indicating that FOXA1 binding is also required for E2-mediated RING1B recruitment to chromatin. Moreover, ectopic expression of HA-tagged ER and FOXA1 in the TNBC cell line MDA-MB-231, in which FOXA1 is repressed by RING1B (15), was sufficient to induce expression of GREB1 and TFF1 concomitant with recruitment of RING1B, ER, and FOXA1 to their promoters and enhancers (Fig. 3, K to M). These results confirm that expression of ER and FOXA1 in TNBC cells can induce expression of estrogen-responsive genes following E2 induction with concomitant RING1B recruitment at the regulatory sites of these genes. These observations highlight the cooperative interplay between RING1B and ER/FOXA1 in regulating E2-induced genes.

ER binding to chromatin during the early estrogen response is cyclic (30); thus, we next sought to determine whether RING1B is recruited to chromatin in a similar manner and whether dynamic chromatin cycling occurs during prolonged E2 stimulation. While FOXA1 binding profiles remained relatively similar along the time course of E2 induction (fig. S5A), RING1B and ER demonstrated dynamic chromatin occupancy following hours of E2 administration (Fig. 4, A and B). We identified six clusters of distinct RING1B binding profiles containing EREs and GRHL2 binding motifs (Fig. 4A) concomitant with significant up-regulation of the associated RING1B target genes after 8 hours of E2 administration (fig. S5B). Notably, cluster 6, which exhibited stable RING1B occupancy at all time points following E2 exposure, also contained genes that were stably up-regulated in response to E2 (Fig. 4A and fig. S5B). We then interrogated the RING1B occupancy at genes that were transcriptionally active in HD and became repressed during E2 administration (Fig. 1A). Only 12% of these genes (23 of 184) were occupied by RING1B. This result indicated that RING1B was not playing a major role as a transcriptional repressor in T47D cells and suggested that the canonical repressive function of PRC1 is mediated by RING1A.

(A and B) ChIP-seq heat maps of RING1B (A) and ER (B) signals before (HD) and after 45, 8 hours, and 24 hours of E2. Six ChIP-seq clusters were identified from 7053 peaks (A) and 5100 peaks (B). The top-enriched motif in each cluster is shown. (C) E2-induced expression changes of genes associated with peaks within each ER ChIP-seq cluster. Box plots are represented by z score. (D) Heat map clustering analysis of RING1B and ER ChIP-seq before (HD) and after 45, 8 hours, and 24 hours of E2. Number of peaks: cluster 1 = 2196, cluster 2 = 1397, cluster 3 = 540, cluster 4 = 1721, cluster 5 = 1960, cluster 6 = 4339. (E) TF motif analysis of the six clusters. (F) Box plots of RNA-seq signal in control and RING1B KD cells at the different E2 time points. TPM, transcripts per million. (G) ATAC-seq peak intensity and dynamics upon E2 at RING1B and ER cotargets in control and RING1B-depleted cells. (H) PRC1 subunits ChIP-qPCR of RING1B/ER cotarget genes before (HD) and after 45 and 24 hours of E2. N = 3. (I) Genome browser screenshots of RING1B, ER, FOXA1, and H3K27ac ChIP-seq and ATAC-seq signals at E2F6 and GREB1 SEs in control and RING1B-depleted cells during E2 administration.

ER followed a similar recruitment pattern as RING1B (ER clusters 1, 2, 4, and 5) but demonstrated more dynamic occupancy profiles at 45 min (cluster 6), 8 hours (cluster 5), and 24 hours (cluster 3). As expected, EREs were strongly enriched at ER target genes (Fig. 4B). Genes stably occupied by ER along the E2 time course, similar to cluster 6 of RING1B occupancy, were significantly up-regulated (Fig. 4C, clusters 1 and 2). Genes with ER bound only at 24 hours (cluster 3) exhibited small changes, albeit significant, in gene expression, whereas genes occupied by ER only at 45 min and 24 hours (clusters 4 and 6) demonstrated significant up-regulation at these time points. The small set of genes containing ER only at 8 hours (cluster 5) appeared to be repressed when compared to the HD condition, suggesting that ER also facilitates gene repression (Fig. 4C) (4, 34).

We then wondered whether RING1B and ER bound the same genomic targets during the E2 response, so we grouped RING1B and ER binding patterns into six clusters (Fig. 4D). Four of these clusters (clusters 2, 3, 4, and 5) contained genomic sites targeted by both RING1B and ER at some point during the E2 time course and contained EREs as the number one TF binding motif (Fig. 4E). Contrastingly, clusters 1 and 6, which have little to no ER binding, primarily contained GRHL2 and FOXA1 binding motifs with substantially less enrichment for EREs (Fig. 4E).

We next determined the impact of RING1B loss on the expression of genes occupied by RING1B and ER containing the highest ERE and FOXA1 binding motifs. We first identified RING1B and ER cotargets up-regulated in shCTR cells after addition of E2 (clusters 2 to 5) and determined their expression following RING1B depletion. We found that RING1B directly regulated genes in clusters 1, 2, and 3 (Fig. 4F and fig. S5C), but RING1B depletion was not sufficient to significantly affect expression of genes in clusters 4 and 5 (fig. S5C). These results indicate that in a set of genes co-occupied by RING1B, ER, and FOXA1 (not shown), RING1B is required for their full transcriptional activation upon E2 administration. Among the down-regulated genes in clusters 2 and 3 were key genes involved in breast cancer progression (e.g., GREB1, FMN1, TFF1, and FKBP4) (Fig. 1, A to D) (3537).

We then assessed whether RING1B and ER induces the expression of their direct targets in response to E2 by increasing chromatin accessibility at these sites. To this end, we restricted our analysis of ATAC-seq peaks to those located at the promoters and TSS of genes up-regulated at any time point during E2 stimulation that are RING1B and ER cotargets. We found that overall chromatin accessibility at E2-stimulated genes in control cells is dynamic with cyclical opening and closing during the E2 response from 0 to 24 hours (Fig. 4G), similar to the cycling of ER on and off the chromatin (30). In contrast, RING1B depletion abrogates this cyclical trend of chromatin accessibility, with a significant reduction in accessibility compared to shCTR at 8 and 12 hours after E2 addition. A cluster of genes gained significant accessibility at 8 hours in RING1B-depleted cells (Fig. 4G). Nonetheless, these results suggest that correlation between chromatin accessibility and gene expression during the estrogen response is gene specific and time dependent.

Once we established the recruitment pattern of RING1B and ER and the impact of RING1B loss on gene transcription and chromatin accessibly, we next asked whether RING1B was recruited to chromatin in a PRC1 context. We recently showed that in T47D cells cultured in FM containing constant E2, RING1B only associated with cPRC1 subunits. Whether RING1B was recruited to chromatin as part of a PRC1 complex upon acute E2 administration was not known. We thus performed ChIP-qPCR experiments using antibodies against cPRC1 (CBX4 and CBX8) and ncPRC1 (RYBP) subunits and PCGF2 and PCGF4 orthologs that can be part of both cPRC1 and ncPRC1 complexes. PCGF2 and CBX4 were recruited to both promoters and enhancers co-occupied by RING1B, ER, and FOXA1 after 24 hours of E2 administration, but not after 45 min of E2. RYBP was not recruited to any of the regulatory sites analyzed, indicating that RING1B only associated with a cPRC1 complex containing CBX4 and PCGF2 24 hours after E2 administration (Fig. 4H). We then sought to determine the role of RING1B in the recruitment of ER and FOXA1 during prolonged E2 administration. We found that after 24 hours of E2 induction, RING1B recruitment was reduced by ~70% in RING1B-depleted cells, and ER recruitment was significantly reduced at the GREB1 SE, concomitant with drastic reduction of ATAC-seq signal and gene expression (Figs. 1B, and 4I and fig. S5D). These results suggest that RING1B may have a strong impact on late ER binding events or stable recruitment during extended exposure to estrogen.

We then interrogated the genome-wide RING1B dependency on ER and FOXA1 recruitment to chromatin at 8 and 24 hours after E2 induction. Since GRHL2 binding sites were strongly enriched in two of the RING1B binding clusters (Fig. 4A), we also asked whether GRHL2 recruitment was dependent on RING1B (Fig. 5A). GRHL2 was recently demonstrated to be bound to FOXA1-occupied enhancers in ER+ cancer cells (38). Similar to FOXA1 binding profiles, GRHL2 was observed to be already bound to chromatin in the absence of E2, and RING1B depletion did not affect its occupancy at randomly selected RING1B-FOXA1-GRHL2 cotarget genes (Fig. 5B).

(A) RING1B is recruited to clusters containing either FOXA1 and GRHL2 or FOXA1 and ER. (B) FOXA1 and GRHL2 ChIP-qPCR of FOXA1/GRHL2 cobound genes in control and RING1B-depleted cells. Immunoglobulin G (IgG) was used as a negative control. N = 2. (C) Dynamics of ER ChIP-seq signals during E2 and effect in ER recruitment upon RING1B depletion at clusters 2 to 5 identified in Fig. 4D. Significance was determined by Mann-Whitney U test. (D) Genome browser screenshots of RING1B, ER, FOXA1, and H3K27ac ChIP-seq at FMN1 and TFF1 loci in HD, 45, 8 hours, and 24 hours of E2 in control and RING1B-depleted cells. The gray box is a zoomed-in view of a genomic region upstream of the TSS of FMN1 containing an ERE and a FOXA1 binding site. (E) Growth curve of T47D and MCF7 control and RING1B KD cells cultured in HD media or HD supplemented with E2. N = 3. ***P < 0.001, two-tailed t-test. (F) Colony formation assay of T47D and MCF7 control and RING1B-depleted cells cultured in HD media or HD supplemented with E2 for 14 days (T47D) and 21 days (MCF7). N = 3. (G) Growth curve of T47D control and RING1B KD cells treated with tamoxifen (TAM; 100 ng/ml) and fulvestrant (30 ng/ml) for 7 days. N = 3.

We next determined whether RING1B modulated FOXA1 and ER recruitment during prolonged exposure to E2 at RING1B-FOXA1-ER cotargets. While FOXA1 recruitment to chromatin was modestly affected by the loss of RING1B (fig. S6A), ER recruitment was diminished by ~50% at 24 hours in clusters 2 to 4 (Fig. 5C). Moreover, clusters 2 and 3 exhibited the strongest ER recruitment (Fig. 5C) and contained genes that were significantly deregulated upon RING1B depletion (Fig. 4F). ER recruitment was severely affected at key genes such as FMN1 and TFF1 upon RING1B depletion (Fig. 5D). The requirement of RING1B in ER recruitment was time dependent: At FMN1, RING1B was required for full ER recruitment after 45 min and 24 hours of E2 treatment, whereas at the TFF1 enhancer, ER recruitment at 45 min was not affected by the loss of RING1B but was strongly affected at 24 hours. RING1B was also recruited to EREs not occupied by ER and with low FOXA1 occupancy upstream of the FMN1 promoter 24 hours after E2 induction (Fig. 5D, right). Reduced ER binding (Figs. 3 and 5), enhancer regulation (Fig. 2), chromatin accessibility, and lack of full response to E2 (Fig. 1) in RING1B-depleted cells resulted in a reduced proliferation over time (Fig. 5E) and decreased cellular fitness (Fig. 5F). Notably, TCGA data from 1082 patients with breast invasive carcinoma showed a positive correlation of RNF2 (encoding RING1B) expression with ESR1 (encoding ER), ER cofactors such as GATA3, FOXA1, EP300, and KMT2C, and RING1B/ER cotarget genes (e.g., TFF1 and FMN1) (fig. S7, A to C). Moreover, RING1B depletion enhanced the negative effect in cell proliferation mediated by tamoxifen and fulvestrant, selective ER modulator and downregulator, respectively, further supporting a cooperative role of RING1B in regulating the ER pathway. In FOXA1-depleted cells where RING1B exhibits reduced chromatin binding (Fig. 3G), we also observed a strong impairment in cell fitness, corroborating the importance of RING1B and ER in maintaining the cellular identity of luminal breast cancer cells (fig. S6B).

Standard ChIP experiments performed with cross-linking agents do not discriminate between direct and indirect binding of proteins to DNA. While TFs are typically recruited to chromatin through the recognition of cognate DNA motifs, they can also occupy sites devoid of these motifs via interaction with other factors. Moreover, most epigenetic machineries do not directly bind DNA and are recruited to specific genomic locations via interaction with TFs, RNA molecules, or histone modifications. Although we did not observe interaction of RING1B with ER or FOXA1, our ChIP-seq experiments revealed a high degree of chromatin colocalization of RING1B with ER, FOXA1, and GRHL2 in the presence of E2 (Figs. 3 to 5). To determine how these factors associate and network functionally at chromatin during E2 stimulation and to detect all their possible protein-protein-DNA and protein-DNA interaction events, we performed ChIP-exo experiments (39) and applied the ChExMix pipeline (40). ChIP-exo greatly improves the resolution of binding sites from hundreds of base pairs to a single-nucleotide resolution by including a 5-3 exonuclease that degrades the DNA protruding from the occupied binding site (41). We performed RING1B, ER, FOXA1, and GRHL2 ChIP-exo (to the best of our knowledge, RING1B and GRHL2 ChIP-exo are not yet reported) in two biological replicates (reads merged for downstream analysis). In agreement with our ChIP-seq experiments (Fig. 3), ChIP-exo tags for ER and RING1B were strongly enriched at chromatin upon E2 induction, while FOXA1 enrichment was similar between HD and E2 conditions (Fig. 6, A and B). Also, GRHL2 binding to chromatin was not dependent on E2 stimulation (Fig. 5B and Fig. 6, A to B). Genome browser screenshots of RING1B, FOXA1, and ER ChIP-seq and ChIP-exo assays showed a comparable enrichment following E2 administration (Fig. 6C).

(A) Number of ER, RING1B, FOXA1, and GRHL2 ChIP-exo tags identified in HD and after 45 of E2. (B) Genome browser screenshots of GRHL2, RING1B, ER, and FOXA1 ChIP-exo at CDC27 and MYC loci in HD and after 45 of E2. (C) Genome browser screenshots of RING1B, ER, and FOXA1 ChIP-seq and ChIP-exo at RARA and GREB1 enhancers in HD and after 45 of E2. (D) Heat maps and sequence color plots of binding subtypes identified in ER, FOXA1, GRHL2, and RING1B ChIP-exo after 45 of E2. On the right of each sequence color plot, see the distribution of the ChIP-exo tag patterns at each of the main subclass binding events identified in ER, RING1B, FOXA1, and GRHL2 ChIP-exo experiments and the number of events. (E) MEME analysis of known TF motifs identified within 100 bp from the summit of the RING1B tags. (F) Distribution of ESR1 (ER) and JUN cognate sequences respective to the submit of the RING1B tags. (G) Genome browser screenshots of RING1B and ER ChIP-seq and ChIP-exo in HD and after 45 of E2. Boxes represent distance between the submit of ChIP-exo tags. (H) Distribution of FOXA1, GRHL2, and RING1B ChIP-exo tags relative to stranded ER tags containing a full ERE motif [ER subtype 1 in (D)]. (I) Distribution of FOXA1, GRHL2, and RING1B ChIP-exo tags relative to stranded ER tags containing half ERE motif [ER subtype 3 in (D)].

We then identified binding event subtypes for each of the four factors upon E2 administration. ER ChIP-exo tags (~80%) contained EREs, of which 182 and 592 harbored full EREs and half EREs, respectively, suggesting that ER was recruited to chromatin as a homodimer in ~30% of the binding events (Fig. 6D, upper left). We found 128 events in which ERE was not detected, suggesting that ER may potentially bind a novel motif. In addition, most of the FOXA1 and GRHL2 were bound at their cognate sequences (both single and double motifs), albeit with subtle differences between the subtypes (Fig. 6D, upper right and bottom left). However, we were unable to determine the existence of a RING1B cognate DNA binding motif, although we identified four RING1B binding types based on the shape of the tags, suggesting that RING1B is not recruited to a specific DNA sequence but rather is recruited by RNA or by multiple TFs, or both (Fig. 6D, bottom right). Next, we determined the binding motifs located within 100 base pairs (bp) upstream and downstream of the RING1B ChIP-exo tags to identify potential TF corecruitment with RING1B. In agreement with our model, we found significant enrichment of ERE (ESR1) motifs, indicative of a potential ER binding as well as motifs of known ER cofactors such FOS/JUN, E2F, and AP-2 families (Fig. 6E). Notably, the JUN binding motif was only 3 bp from the RING1B binding sites, and ERE (ESR1) motifs were found approximately 10 bp around RING1B (Fig. 6F). We confirmed the binding prediction of ER ~10 bp next to RING1B (Fig. 6G), which was not possible to achieve with standard-resolution ChIP-seq. Last, we determined the tag distribution of RING1B, FOXA1, and GRHL2 relative to the main ER binding subtypes, as a homodimer or a monomer. Notably, the distribution of RING1B, FOXA1, and GRHL2 binding is influenced by the ER binding pattern. All three factors can be recruited up to 30 bp upstream and downstream of the palindromic ER homodimer motif (Fig. 6H). However, since the ER monomer motif is directional, we could determine the relative binding localization of these factors in a strand-specific manner, which reveals that most of the RING1B recruitment is downstream and GRHL2 upstream of ER monomers (Fig. 6I). FOXA1 binding does not appear to be influenced by ER as its distribution with respect to ER is relatively even compared to that of RING1B and GRHL2. This finding suggests that at half ERE sites, FOXA1 plays a crucial role in recruiting ER to the chromatin, which is in line with prior findings (42). However, when ER binds as a homodimer at full ERE sites, the binding distribution of all three factorsRING1B, GRHL2, and FOXA1seems to be heavily influenced by ER binding (Fig. 6H). This suggests that at full ERE sites, ER can influence FOXA1, GRHL2, and RING1B binding. Together, these results demonstrate a high-resolution view of the intimate binding profiles of RING1B with breast cancer TFs including ER, FOXA1, and GRHL2, further supporting our overall finding of functional cooperativity between these factors in the estrogen response of luminal breast cancer.

Despite knowing for over 80 years that estrogen drives breast cancer proliferation, the exact molecular mechanisms of liganded ER and its effects on gene regulation and chromatin organization are still not well understood. A deeper understanding is needed to uncover novel therapeutic strategies for treating ER-dependent breast cancers and other estrogen-regulated human diseases. Much effort has been dedicated toward characterizing the intricate network of functional interactions between ER, oncogenic TFs, and epigenetic machineries, with particular emphasis on how these factors are assembled upon acute E2 exposure (4, 43, 44). Nevertheless, there is a limited understanding of the hierarchical events that occur at the genomic and epigenomic level following hours of exposure to estrogens. Given the plasticity of the breast cancer genome during hormone-stimulated proliferation (22), it is crucial to uncover the changes in chromatin organization and epigenetic events that occur during prolonged periods of estrogen exposure. Our results reveal that the Polycomb protein RING1B is at the core of the epigenetic factory that positively regulates the transcriptional response to estrogen in ER+ breast cancer cells (see model, fig. S8).

The mechanisms that regulate the tethering of Polycomb proteins to chromatin are under constant investigation (13). Although we know much about PRC1 and PRC2 recruitment mechanisms in embryonic stem cells, very little is known in adult stem cells and cancer cells (14, 29). There is a significant gap in knowledge of how PRC1 complexes regulate genes during initiation and progression in cancer (45) and how different PRC1 variants are dynamically assembled and recruited to chromatin. In ESCs, PRC1 complexes are mainly involved in maintaining repression of developmental genes (46), but recent studies indicate that PRC1 acquires dual functions during early cell specification and in adult stem cells. While PRC1 complexes still repress lineage-specific genes, they also facilitate gene transcription. Examples are found during neuronal and mesodermal differentiation, in epidermal and intestinal stem cells, as well as in breast cancer and melanoma (17, 4751). At least two outstanding questions remain: (i) Why do differentiating cells and somatic stem cells require PRC1 complexes to regulate both gene expression and repression? (ii) What is driving this functional switch? It would be fascinating to determine whether PRC1 complexes acquire gene activating functions in premalignant cells as a by-product of tumor evolution or whether PRC1 drives cancer development by gaining novel activating functions. It is not yet known whether RING1B exhibits activating functions by regulating active genes and enhancers in differentiating adult mammary stem cells (MaSC) during mammary gland development and whether these functions differ during in MaSC self-renewal.

In ER+ breast cancer cells, ER is rapidly recruited to chromatin and ubiquitinated (52) after ligand binding. Ubiquitinated ER cycles on and off ERE sites to activate target gene transcription (30, 53). A large number of ER cofactors are recruited to chromatin in a tightly coordinated and dynamic manner within minutes after ligand administration (10, 54). Our results expand upon this knowledge and indicate that bursts of ER-driven transcriptional activity continue to occur many hours following estrogen stimulation. A large proportion of these transcriptional changes occur independently of chromatin accessibility. Instead, we propose that chromatin accessibility may be also required for recruitment of factors involved in gene repression (55, 56). Nevertheless, future analysis of both gene transcription and chromatin accessibility at the single-cell level will be instrumental to delineate in greater detail how hormone-induced transcriptional changes are coupled to changes in chromatin structure.

Previous study from our lab has shown that cPRC1 colocalizes with ER at active genes and enhancers to regulate their expression (15). However, the molecular mechanism by which RING1B regulates ER function is not known. Here, we propose that minutes after E2 administration, RING1B is recruited to chromatin by RNA molecules and/or ER cofactors in a cPRC1-independent context and that upon prolonged and constant E2 administration, a cPRC1 complex, containing CBX4 and PCGF2, is engaged to chromatin to maintain the transcriptional activity of enhancers and promoters required for proliferation of luminal breast cancer cells. Our efforts aimed to determine whether the RING1B enzymatic activity or interaction with the nucleosome is required for the regulation of estrogen-induced genes revealed a much more complex scenario than previously anticipated. Whether RING1B is an E3 ligase of nonhistone substrates in luminal breast cancer cells is not known. We hypothesize that in a subset of RING1B-ER cotarget genes and enhancers, RING1B binds to nucleosomes and ubiquitinates either a TF (e.g., ER, FOXA1, and GRHL2) or an epigenetic factor to stabilize their function (4, 30, 57). Ligand-bound ER is recruited to chromatin along with a number of E3 ligases (e.g., E6AP and BRCA1) that serve as coactivators not only to promote ER-driven gene expression but also to mediate ER ubiquitination and subsequent proteolysis through a mechanism known as activation-coupled ER degradation (4, 58, 59). RING1B might prove to be another E3 ligase of ER, although we did not detect RING1B-ER direct interaction in our previous study under stringent pull-down conditions (15), which may not capture transient interaction or indirect interaction through other cofactors. Mechanistically, our results suggest that the enzymatic activity of RING1B is required for its stable binding to chromatin, supporting a role of RING1B in monoubiquitinating cofactors recruited to RING1B/ER cotarget genes and enhancers. Further analyses are required to determine the exact role of RING1Bs activity in regulating specific sets of RING1B-ER cotargets during estrogen stimulation. Nonetheless, we propose that RING1B is required for maintaining the positive feedback loop of ER cycles in response to estrogen in luminal breast cancer.

We observed RING1B recruitment to EREs not occupied by ER. EREs can be occupied by ER and ER. ER has antiproliferative effects (60), is not expressed in T47D cells, and is not regulated by RING1B. These observations suggest that either RING1B is recruited to these sites after ER displacement or, in contrast, RING1B is a sensor that dictates future ER recruitment. We hypothesize the latter for two main reasons: (i) RING1B is recruited before the first on and off cycle of ER recruitment and displacement, which occurs at around 120 min after E2 addition (30), and (ii) after 24 hours of E2 administration, ER and RING1B are corecruited to sites that were previously only occupied by RING1B upon 45 min of estrogen exposure.

Last, our results establish the existence of relevant cooperative and functional interactions between RING1B, ER, and other key TFs central in regulating the estrogen-mediated transcriptional program. We propose that a defined binding arrangement of these factors dictates their interrelationships, resulting in a dynamic gene-regulatory network deployed during the early and late stimulation with estrogen to ensure rapid and constant transcriptional programs in luminal breast cancer.

MDA-MB-231, T47D, and MCF7 [American Type Culture Collection (ATCC) catalog #HTB-26, #HTB-133, and #HTB-22) were maintained at 37C with 5% CO2 and split every 2 to 3 days according to ATCC recommendations. Culture media was supplemented with 1 penicillin/streptomycin and 1 glutaMAX, and complete culture media for each cell line were as follows: MDA-MB-231, Dulbeccos modified Eagles medium with 10% fetal bovine serum (FBS); T47D, RPMI 1640 with 10% FBS and insulin (10 g/ml); MCF7, Eagles Minimum Essential Medium (EMEM) with 10% FBS and insulin (10 g/ml). When estrogen (10 nM E2, Sigma-Aldrich E2758-250MG) was added, cells were maintained in phenol-red free media and 5% charcoal-depleted FBS for 72 hours before treating with ethanol (vehicle) or E2. Cells were routinely tested to be free of mycoplasma infection.

For the 5-bromo-2-deoxyuridine (BrdU) incorporation analysis, cells (2 105/ml) were incubated for 30 min in culture medium containing 10 M BrdU. Then, cells were harvested, washed twice with 1 phosphate-buffered saline (PBS), and fixed in cold 70% ethanol overnight at 4C. After removal of ethanol, DNA was denatured with 2 N HCl supplemented with 0.5% Triton X-100 for 30 min at room temperature, then neutralized with two washes of 0.1 M sodium tetraborate (pH 9), and resuspended in 70% ethanol. Then, cells were recovered by centrifugation, washed once with 1 PBS, and resuspended in 100 l of blocking buffer [0.5% Tween 20 and 1% bovine serum albumin (BSA) in 1 PBS] containing 10 l of mouse anti-BrdU antibody (Becton Dickinson, #347580), and incubated at room temperature for 30 min. After a wash with 1 PBS, cells were incubated 15 min at room temperature with goat anti-mouse Alexa 647 antibody (Thermo Fisher Scientific, #A21236) diluted in blocking buffer. Last, cells were washed with 1 PBS once and resuspended in 1 PBS containing propidium iodide (5 g/ml) (Sigma) and analyzed using BD FACSCanto II (BD Biosciences) in the Flow Cytometry Shared Resource, Sylvester Comprehensive Cancer Center.

Cell proliferation was evaluated using the Cell Proliferation Dye eFluor 670 (Thermo Fisher Scientific) following the manufacturers specifications. Briefly, 5 million cells were incubated during 5 min at 37C with 10 M eFluor 670 in 1 PBS and 0.1% BSA. The reaction was stopped by adding complete media and incubated for 5 min at 37C. After washing the cells once with complete media, the cells were cultured under normal conditions. After 24 hours, cell populations were evaluated using BD FACSCanto II (BD Biosciences).

To produce shRNA lentiviruses, 2 106 human embryonic kidney 293T cells (ATCC #CRL-3216) were plated into a 10-cm2 plate and transfected 16 hours later with 8 g of pLKO-shRNAs (Addgene, #10879 for CTR; Sigma-Aldrich, #TRCN0000033697 for RING1B; and Sigma-Aldrich, #TRCN0000014881 for FOXA1), 2 g of pCMV-VSV-G, and 6 g of pCMV-dR8.91 plasmids using calcium phosphate. Seventy-two hours after transfection, the viral supernatant was collected, passed through a 0.45 M polyethersulfone filter, and used to transduce MDA-MB-231 and T47D cells. Specifically, 3 105 cells were plated into a six-well plate followed by the addition of viral media with polybrene (8 g/ml; Millipore-Sigma, #TR-1003-G). Cells were centrifuged for 1 hour at 1000g at 32C and then incubated overnight with fresh viral media. Viruses were removed and complete culture medium was added for cell recovery. Cells were selected 24 hours after recovery with puromycin (2 g/ml; Biogems, #5855822) and were maintained in selection. All experiments were performed within 2 weeks after transduction. The shRING1B oligos were cloned into the pLKO-tet-on plasmid, and LT3GEPIR-shRenilla luciferase was used as the doxycycline-inducible control. Lentiviruses were produced from the two plasmids as described above. Cells were treated with doxycycline (100 ng/ml) for 2 days before culturing them in HD media for 72 hours.

Doxycycline-inducible T47D shCTR and shRING1B cells were treated with doxycycline (100 ng/ml) for 3 days. After induction, 4000 shCTR and shRING1B cells were plated into individual wells in a 96-well plate. The medium was replaced 1 day after plating, and the cells were treated with 100 nM tamoxifen (4-hydroxytamoxifen; Sigma-Aldrich, H7904-5MG) or 30 nM fulvestrant (ICI 182780; Tocris, catalog #1047). The treatment medium was changed every 2 days, and the number of viable cells in culture was measured on days 0, 3, 5, and 7 using the CellTiter-Glo Luminescent Cell Viability Assay (Promega, G7572).

Stable T47D and MCF7 shCTR and shRING1B cells were first cultured in hormone-deprived media for 3 days. After hormone deprivation, 3000 T47D shCTR and shRING1B cells and 2000 MCF7 shCTR and shRING1B cells were each plated into three individual wells on a six- well plate. Cells were cultured in 2 ml of media containing either vehicle (ethanol) or vehicle plus 10 nM estrogen. Medium was refreshed every 3 days. After 2 weeks of culture (T47D) and 3 weeks of culture (MCF7), medium was removed, and colonies were stained with crystal violet (0.25 g of Crystal Violet; Sigma-Aldrich, C3886-25G; 13.5 ml of 37% Formaldehyde; Sigma-Aldrich, 252549-100; 5 ml of methanol; VWR, BDH20864.400; 1 PBS to 500 ml; Sigma-Aldrich, P3813-10PAK) for 20 min. After staining, the wells were gently washed by dipping the plates into a tub of running tap water to avoid disturbing the colonies on the plate surface. The plates were air-dried after thorough washing, and the colonies were imaged using an Epson V750 Pro photoscanner at 1200 dpi resolution. Colonies were quantified and analyzed using the ImageJ Plugin ColonyArea.

Cells were lysed in high-salt buffer [300 nM NaCl, 50 mM tris-HCl (pH 8), 10% glycerol, and 0.2% NP-40] supplemented with protease inhibitors (Sigma-Aldrich, #04693132001) and sonicated 5 min at 4C with a Bioruptor in 30 seconds ON-OFF cycles. After centrifugation at 16,000g for 15 min, soluble material was quantified by Bradford assay (Bio-Rad, #5000006). Western blotting was performed using standard protocols and imaged on an Odyssey CLx imaging system (Li-COR), and various exposures within the linear range were captured using Image Studio software. Images were rotated, resized, and cropped using Adobe Photoshop CC 2019 and imported into Adobe Illustrator CC 2019 to be assembled into figures.

MDA-MB-231 cells were grown to 50 to 60% confluency before dissociation with trypsin. A total of 5.6 106 cells were pelleted and washed with 1 PBS. Seven micrograms of HA-FOXA1-pCDNA3 and 8 g of HA-ER-pCDNA3 or 5 g of GFP-pCDNA3 were added to the cell pellet. Pellet was resuspended in Resuspension Buffer (Neon Transfection System 100 L Kit; Thermo Fisher Scientific, MPK10025) to a total volume of 100 l. Cells were electroporated with a Neon Transfection System (Thermo Fisher Scientific, MPK5000) at 1400 V, 10-ms pulse width, and a pulse number of 4. A total of 1.12 107 transfected cells were plated onto one P150 plate. Medium was replaced 24 hours later with growth media containing 10 nM E2, and the cells were collected for Western blotting, RT-qPCR, and ChIP assays 48 hours later.

A total of 6 105 freshly harvested cells were washed with cold 1 PBS and pelleted. Each pellet of cells was resuspended in 500 l of cold lysis buffer [10 mM tris-HCl (pH 8), 50 mM sodium bisulfite, 1% Triton X-100, 10 mM MgCl2, 8.6% sucrose, and 10 mM sodium butyrate, adjusted to pH 6.5] before centrifugation at 20,000g for 15 min at 4C. The supernatant was discarded and the pellet was kept on ice. Pellet was again resuspended in 500 l of cold lysis buffer before centrifugation at 20,000g for 15 min at 4C. The supernatant was also discarded. This step was repeated two more times. After a total of four rounds of lysis buffer treatment, the pellet was incubated for 1 hour at 4C in 100 l of 0.4 M H2SO4 and then centrifuged at 20,000g for 5 min. The supernatant was placed in a new microtube, and 900 l of acetone was added to the supernatant and stored at 20C overnight. The next day, samples were centrifuged at 20,000g for 10 min, and the supernatant was discarded. The pellet containing the histone was air-dried for 2 to 5 min and then resuspended in 30 to 50 l of water. Concentration of histones was measured by a Bradford assay.

ATAC-seq experiments were performed as we previously described (15). FASTQ data were processed using the ATAC-seq/ENCODE pipeline from the Kundaje lab (https://github.com/kundajelab/atac_dnase_pipelines) with default parameters and aligned to the hg19 genome. Homer annotatePeaks and findMotifsGenome were used for peak annotation and motif analysis, respectively. The TCseq Bioconductor package was used to visualize temporal patterns of ATAC-seq peaks. ATAC-seq heat maps and boxplots were created with R v.3.5.1 ComplexHeatmap and ggplot2 packages, respectively. Binary ATAC-seq heat maps were generated using Python v2.7.3 (https://gist.github.com/daler/07eb1a95f1e4639f22bd). Bedtools v2.26.0 was used to determine peak overlaps and NGS Plot v2.61 was used to generate density plots.

Cells were grown to 70 to 80% confluency on 150-cm2 plates, and typically six plates were used. Before and after treatment with 10 nM E2 for 45 min, 8 hours, and 24 hours, cells were washed once with 1 PBS. Cells were then cross-linked for 10 min in 10 ml of 1 PBS with 1 ml of 11% formaldehyde buffer [50 mM Hepes-KOH (pH 7.5), 100 mM NaCl, 1 mM EDTA, 0.5 mM EGTA, 11% formaldehyde; Thermo Fisher Scientific, #28908] before quenching with 0.5 ml of 2.5 M glycine for 5 min. Cells were then washed two times with 1 PBS. Cross-linked cells were harvested and washed once more with cold 1 PBS, and the pellet was flash-frozen in liquid nitrogen and stored at 80C. Magnetic beads were preblocked and antibody-bound before the addition of chromatin. For each ChIP, 50 l of Dynabeads Protein G (Invitrogen, #10004D) was washed three times with 1 ml of 0.5% BSA in 1 PBS (Sigma-Aldrich, A9418), using a magnetic stand to collect the magnetic beads in between washes. Beads were suspended in 250 l of the BSA solution, and 5 g (for nonhistone proteins) or 2 g (for histone modifications) of antibody was added (RING1B: Active Motif, #39664; ER: Diagenode, #15100066; FOXA1: Abcam, #ab23738; H3K27Ac: Abcam, #ab4729; GRHL2: Sigma, #HPA004820). For ChIP-seq experiments, 1 g of spike-in antibody was also added (Active Motif, #61686). Beads were incubated on a rotating platform overnight at 4C. The next day, the beads were washed three more times in the BSA solution before the chromatin was added. To prepare the chromatin, each pellet was resuspended in 2.5 ml of LB1 [50 mM Hepes-KOH (pH 7.5), 140 mM NaCl, 1 mM EDTA, 10% glycerol, 0.5% IGEPAL CA-630 (Sigma-Aldrich, I8896), and 10% Triton X-100] and rocked at 4C for 10 min. After spinning down at 1350g for 5 min at 4C, the pellets were resuspended in 2.5 ml of LB2 [10 mM tris-HCl (pH 8), 200 mM NaCl, 1 mM EDTA, and 0.5 mM EGTA] and rocked at room temperature for 10 min. Nuclei were pelleted at 1350g for 5 min at 4C before resuspension in 2 ml of LB3 [10 mM tris-HCl (pH 8), 100 mM NaCl, 1 mM EDTA, 0.5 mM EGTA, 0.1% Na-deoxycholate, and 0.5% N-lauroylsarcosine] and sonication using the Bioruptor Pico (Diagenode, #B01060010) at 4C in Bioruptor tubes with beads (Diagenode, #C01020031)10 cycles of 30 s on, 30s off, repeat with brief vortex in between. Two hundred microliters of 10% Triton X-100 was added to the sonicated lysate, which was spun at 20,000g for 15 min at 4C to pellet the debris. The chromatin (20 l) was decross-linked in 80 l of 1 PBS at 65C for 3 hours, purified using the QIAquick PCR Purification Kit (Qiagen, #28106), and quantified using Qubit. Chromatin (30 g) was added to the preblocked beads and gently mixed overnight on rotators at 4C. Spike-in chromatin (50 ng; Active Motif, #53083) was also added. The next day, the supernatant was discarded and the beads were washed 5 with radioimmunoprecipitation assay buffer [50 mM Hepes-KOH (pH 7.5), 500 mM LiCl, 1 mM EDTA, 1% IGEPAL, and 0.7% Na-deoxycholate], collecting the beads on the magnetic rack in between washes. Beads were washed once more with 1 ml of TE with 50 mM NaCl and spun down at 960g for 3 min at 4C to remove residual TE buffer. Beads were eluted in 210 l of elution buffer [50 mM tris-HCl (pH 8), 10 mM EDTA, and 1% SDS] at 65C for 15 min with brief vortexing every 2 min. Beads were spun down, and 200 l of supernatant was transferred to a new tube and decross-linked overnight at 65C with shaking at 1000 rpm. One percent of the chromatin input is also decross-linked in the same volume of elution buffer. The next day, 200 l of TE is added to the decross-linked samples, which were treated for 2 hours at 37C with ribonuclease A (0.2 g/ml) followed by 2 hours of proteinase K (0.2 g/ml; New England Biolabs, #P8107) at 55C. The immunoprecipitated DNA was purified using the QIAquick PCR Purification Kit and quantified via Qubit. Immunoprecipitated DNA was used to either perform ChIP-qPCR or generate libraries using the NEBNext Ultra DNA Library Prep Kit for Illumina (New England Biolabs, #E7370) following the manufacturers instructions. Libraries were visualized on a Tapestation 2200 using D1000 DNA ScreenTape (Agilent Technologies, #50675582) and quantified on a Qubit 3 fluorometer with Qubit double-stranded DNA high-sensitivity reagents (Thermo Fisher Scientific, #Q32851) following the manufacturers instructions, then pooled and sequenced (single-end, 75 bp) on a NextSeq 500. Processed data were viewed using the University of California, Santa Cruz (UCSC) genome browser. ChIP-qPCR was performed on a Bio-Rad CFX96 Real-Time System with iTaq Universal SYBR Green Supermix (Bio-Rad, #1725124) and analyzed with CFX Manager software (Bio-Rad).

All ChIP-seq data generated in this study were analyzed according to the following methodology: FASTQ data were processed with Trimmomatic v0.32 to remove low-quality reads and then aligned to the human genome hg19 using Burrows-Wheeler Aligner (BWA) v0.7.13 with the following parameters: aln -q 5 -l 32 -k 2. Duplicate reads were removed using Picard v1.126. Peaks were called using MACS2.1 with default parameters shiftsize 160 nomodel p 0.01 for all data. Whole-cell extract (input) from the corresponding cells was used as controls. Peaks with signal (fold enrichment over input generated from MACS2) > 4 and a q value < 0.05 were used for downstream analysis. BigWig file output from MACS v 2.1.0.20150731 was visualized in the UCSC genome browser. Homer annotatePeaks v4.8.3 was used for peak annotation. Bedtools v2.26.0 intersect was used to determine peak overlaps. NGS Plot v2.61 was used to generate heat maps and density plots.

ChIP-exo was performed using the ChIP-exo 5.0 protocol (39) with minor adaptations. Protein A Mag Sepharose (GE Healthcare) beads were preblocked and bound with antibody before the ChIP. Ten microliters of beads was washed three times with 500 l of 0.5% BSA in 1 PBS at 4C. Five micrograms of antibody was added to the washed beads, and the beads were resuspended in 250 l of the 0.5% BSA solution and allowed to incubate overnight on a rotating platform at 4C. The next day, the beads were washed three times in 500 l of 0.5% BSA solution. Sixty micrograms of chromatin was added to the beads, and the IP was performed in a total volume of 500 l of IP dilution buffer [20 mM tris-HCl (pH 8.0), 2 mM EDTA, 150 mM NaCl, and 1% Triton X-100] with protease inhibitors (Roche) at 4C overnight. A total of 120 g of chromatin (two samples with 60 g of chromatin) was used for each ChIP-exo experiment. In addition, NEBNext Multiplex Oligos for Illumina Index Primers and the Universal PCR Primer for Illumina were used instead of the ExA2_iNN and the ExA1-58 oligos. All other steps were identical to the original ChIP-exo 5.0 protocol.

FASTQ data were processed with cutadapt v1.15 (--nextseq-trim=20 -m 10) to remove low-quality reads and then aligned to the human genome hg19 using BWA v0.7.13 (aln -q 5 -l 32 -k 2). Peaks and motif subtypes were determined using ChExMix v0.41 and MEME v5.0.5 after filtering blacklisted regions and enabling a probability-based duplicate filter (--readfilter). Motif matching and motif distributions were determined using MEME-chip v5.0.2 with the JASPAR 2016 motif database. Peak distributions were determined using gaussian kernel function estimates of ChExMix motif aligned peaks.

SE and typical enhancers were defined using the ROSE pipeline with default parameters using H3K27ac ChIP-seq peaks as input.

FASTQ data were processed with cutadapt v1.15 (--nextseq-trim=20 -m 18) to remove low-quality reads. Expected gene counts were obtained using RSEM v1.3.0 and STAR v2.5.3a alignment to the human hg19 transcriptome (GENCODE V19 annotation). RUVseq v1.12.0 was used to adjust gene counts by removing unwanted variance using exogenous ERCC spike-in RNA. Differential expression was determined using DESeq2 v1.18.1 and R (version 3.4.1) with a q value < 0.05 and an FC > 2 (Wald test). Heat maps were generated using variance stabilized gene counts from DESeq2. For GSEAs, the Wald statistic of each time point compared to hormone-deprived conditions was used as input for the Preranked module of GSEA v3.0 on Hallmark gene sets (-scoring_scheme weighted nrom meandiv).

Acknowledgments: We are indebted to members of the Morey laboratory and Dr. Gloria Mas for discussions and the Oncogenomics Core Facility at the Sylvester Comprehensive Cancer Center for performing high-throughput sequencing. We also thank the Flow Cytometry Core Facility for assistance with cell sorting. We are grateful to F. Beckedorff for assisting with the ATAC-seq analysis and M. J. Rossi for providing technical help with the ChIP-exo experiments. Funding: This work was supported by Sylvester Comprehensive Cancer Center funds, AACR-Bayer Innovation and Discovery grant (18-80-44-MORE), Flight Attendant Medical Research Institute (FAMRI) Breast Cancer Developmental Grant, American Cancer Society (ACS; IRG-17-183-16), Stanley J. Glaser Foundation Research Award (UM-SJG-2020-3), Leukemia and Lymphoma Society Specialized Center of Research grant (LLS-SCOR), and the Lampert Breast Cancer Research Fund to L.M. Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under Award Number P30CA240139. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Author contributions: L.M. and Y.Z. designed the study and analyzed the experiments with input from J.M.S. and R.E.V. Y.Z. conducted all the experiments except histone extractions, growth curves, and expression profiles in MCF7 cells (L.G.-M.), ATAC-seq analysis and colony formation assays (H.L.C.), and cell cycle profiles and BrdU assays (N.W. in the laboratory of R.E.V.). Bioinformatics analyses were performed by Y.Z., H.L.C., and D.L.K. (Bioinformatics core, Sylvester Comprehensive Cancer Center). D.L.K. performed ChIP-exo analysis. L.M. supervised the experiments and provided intellectual support toward interpretation of the results. L.M. and H.L.C. wrote the manuscript. Competing interests: The authors declare that they have no competing interests. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. Additional data related to this paper may be requested from the authors. The genome-wide data of this study are deposited in the NCBI Gene Expression Omnibus (GEO) database: GSE137579.

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Estrogen induces dynamic ER and RING1B recruitment to control gene and enhancer activities in luminal breast cancer - Science Advances

Participation of Somatic Stem Cells, Labeled by a Unique …

A monoclonal antibody (A3) was generated by using rat malignant fibrous histiocytoma (MFH) cells as the antigen. Generally, MFH is considered to be a sarcoma derived from undifferentiated mesenchymal cells. Molecular biological analyses using the lysate of rat MFH cells revealed that A3 is a conformation specific antibody recognizing both N-glycan and peptide. A3-labeled cells in bone marrow were regarded as somatic stem cells, because the cells partly coexpressed CD90 and CD105 (both immature mesenchymal markers). In the hair follicle cycle, particularly the anagen, the immature epithelial cells (suprabasal cells) near the bulge and some immature mesenchymal cells in the disassembling dermal papilla and regenerating connective tissue sheath/hair papilla reacted to A3. In the cutaneous wound-healing process, A3-labeled epithelial cells participated in re-epithelialization in the wound bed, and apparently, the labeled cells were derived from the hair bulge; in addition, A3-labeled immature mesenchymal cells in the connective tissue sheath of hair follicles at the wound edge showed the expansion of the A3 immunolabeling. A3-labeled immature epithelial and mesenchymal cells contributed to morphogenesis in the hair cycle and tissue repair after a cutaneous wound. A3 could become a unique antibody to identify somatic stem cells capable of differentiating both epithelial and mesenchymal cells in rat tissues.

Keywords: N-glycan; antibody; cutaneous wound healing; hair follicle cycle; somatic stem cells.

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Participation of Somatic Stem Cells, Labeled by a Unique ...

COVID-19 Impact on Global Cell Therapy Industry 2020: Market Trends, Size, Share, Applications, SWOT Analysis by Top Key Players and Forecast Report…

TheGlobal Cell Therapy Marketwas estimated to be valued at USD XX million in 2018 and is projected to reach USD XX million by 2026, at a CAGR of XX% during 2019 to 2026. Growing aging patient population, the rise in cell therapy transplantations globally, and rising disease awareness drive the growth of the market.

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Cell therapyinvolves the administration of somatic cell preparations for the treatment of diseases or traumatic damages. The objective of this study is to provide long term treatment through a single injection of therapeutic cells.

However, stringent regulatory policies may restrain growth of the market in the forecast period.

The global Cell Therapy Market is primarily segmented based on different type, technique, cell source, technology, end users and region.

On the basis of type, the market is split into:* Allogenic Therapies* Autologous Therapies

On the basis of technique, the market is split into:* Stem Cell Therapy* Cell Vaccine* Adoptive Cell Transfer (ACT)* Fibroblast Cell Therapy* Chondrocyte Cell Therapy* Other Technique

On the basis of cell source, the market is split into:* Bone Marrow* Adipose Tissue* Umbilical Cord Blood-Derived Cells

On the basis of technology, the market is split into:* Viral Vector Technology* Cell Immortalization Technology* Genome Editing Technology

On the basis of end user, the market is split into:* Hospitals & Clinics* Regenerative Medicine Centers* Other End Users

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Moreover, the market is classified based on regions and countries as follows:* North America- U.S., Canada* Europe- U.K., France, Germany, Italy and Rest of Europe* Asia-Pacific- China, Japan, India and Rest of Asia Pacific* South America- Brazil, Mexico and Rest of South America* Middle East & Africa- South Africa, Saudi Arabia and Rest of Middle East & Africa

Key Market Players: The key players profiled in the market include:* Kolon TissueGene, Inc.* JCR Pharmaceuticals Co. Ltd.* Osiris Therapeutics, Inc.* Stemedica Cell Technologies, Inc.* Fibrocell Science, Inc.* Vericel Corporation* Pharmicell Co., Ltd* Anterogen.CO.,LTD.* Baxter Healthcare Corporation.* Arteriocyte Medical Systems

These enterprises are focusing on growth strategies, such as new product launches, expansions, acquisitions, and agreements & partnerships to expand their operations across the globe.

Key Benefits of the Report:* Global, regional, country, type, technique, cell source, technology, end users market size and their forecast from 2018-2026* Identification and detailed analysis on key market dynamics, such as, drivers, restraints, opportunities, and challenges influencing growth of the market* Detailed analysis on industry outlook with market specific PESTLE, and supply chain to better understand the market and build expansion strategies* Identification of key market players and comprehensively analyze their market share and core competencies, detailed financial positions, key product, and unique selling points* Analysis on key players strategic initiatives and competitive developments, such as joint ventures, mergers, and new product launches in the market* Expert interviews and their insights on market shift, current and future outlook, and factors impacting vendors short term and long term strategies* Detailed insights on emerging regions, type, technique, cell source, technology and end users with qualitative and quantitative information and facts

Target Audience:* Cell Therapy Manufactures* Traders, Importers, and Exporters* Raw Material Suppliers and Distributors* Research and Consulting Firms* Government and Research Organizations* Associations and Industry Bodies

Research Methodology:The market is derived through extensive use of secondary, primary, in-house research follows by expert validation and third party perspective, such as, analyst reports of investment banks. The secondary research is the primary base of our study wherein we conducted extensive data mining, referring to verified data products, such as, white papers, government and regulatory published articles, technical journals, trade magazines, and paid data products.

For forecasting, regional demand & supply factors, recent investments, market dynamics including technical growth scenario, consumer behavior, and end use trends and dynamics, and production capacity were taken into consideration. Different weightages have been assigned to these parameters and quantified their market impacts using the weighted average analysis to derive the market growth rate.

The market estimates and forecasts have been verified through exhaustive primary research with the Key Industry Participants (KIPs), which typically include:* Manufacturers* Suppliers* Distributors* Government Body & Associations* Research Institutes

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Table of Content1. Introduction2. Research Methodology3. Executive Summary4. Global Cell Therapy Market Overview4.1. Market Segmentation & Scope4.2. Market Trends4.2.1. Drivers4.2.2. Restraints4.2.3. Opportunities4.2.4. Supply Chain Analysis4.3. Global Cell Therapy Market Porters Five Forces Analysis4.4. Global Cell Therapy Market PESTEL Analysis5. Global Cell Therapy Market, by Type5.1. Global Cell Therapy Market, Size and Forecast, 2015-20265.2. Global Cell Therapy Market, by Allogenic Therapies, 2015-20265.2.1. Key driving factors, trends and opportunities5.2.2. Market size and forecast, 2015-20265.3. Global Cell Therapy Market, by Autologous Therapies, 2015-20265.3.1. Key driving factors, trends and opportunities5.3.2. Market size and forecast, 2015-20266. Global Cell Therapy Market, by Technique6.1. Global Cell Therapy Market, Size and Forecast, 2015-20266.2. Global Cell Therapy Market, by Stem Cell Therapy, 2015-20266.2.1. Key driving factors, trends and opportunities6.2.2. Market size and forecast, 2015-20266.3. Global Cell Therapy Market, by Cell Vaccine, 2015-20266.3.1. Key driving factors, trends and opportunities6.3.2. Market size and forecast, 2015-2026

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COVID-19 Impact on Global Cell Therapy Industry 2020: Market Trends, Size, Share, Applications, SWOT Analysis by Top Key Players and Forecast Report...

A caveolin binding motif in Na/K-ATPase is required for stem cell differentiation and organogenesis in mammals and C. elegans – Science Advances

INTRODUCTION

Embryonic development is characterized by the temporal and spatial regulation of cell proliferation, migration, differentiation, and tissue formation. Although these processes are genetically determined, several signaling mechanisms including Wnt have been recognized as essential in regulating cell lineage specification and organogenesis (13).

The Na/Kadenosine triphosphatase (ATPase) (NKA), discovered in crab nerve fibers by Skou (4), belongs to the P-type ATPase superfamily. It has an enzymatic function that couples adenosine 5-triphosphate (ATP) hydrolysis to the transmembrane movement of Na+ and K+ in a cell lineagedependent manner. For example, while the NKA is involved in the formation of action potentials in excitable cells, its polarized distribution is key to the functionality of the epithelium.

In addition to its canonical enzymatic function, we and others have shown that the NKA has an enzymatic activityindependent signaling function through its interactions with membrane cholesterol and proteins such as Src, epidermal growth factor (EGF) receptor, and caveolin-1 (58). We use the term signaling with liberty here, referring to the ability of NKA to work as a receptor, a scaffold, and a signal integrator by regulating the functions of its interacting proteins. This newly appreciated signaling function of the NKA has been implicated in several cellular processes (912). However, direct genetic evidence supporting a role for NKA signaling in animal physiology and disease progression is still lacking. This is due, in part, to the technical difficulties in studying its signaling separately from its ATPase-mediated pumping function because the latter is required for the survival of animal cells (13). Fundamentally, it is unknown whether the signaling function is an intrinsic property of the protein NKA, as its Na+- and K+-driven enzymatic activity has been recognized as. Therefore, we were prompted to address two important questions: (i) Were the signaling and Na+/K+ transport functions of the NKA coevolved? (ii) If so, does the signaling function of NKA represent a primordial yet common mechanism for the regulation of a fundamental process in animal biology?

Structurally, the NKA is composed of both and subunits. The subunit contains the binding sites for Na+/K+ as well as ouabain, which are distinct from that of other P-type ATPases (14). It also has an N-terminal caveolin binding motif (CBM) proximal to the first transmembrane helix (fig. S1A). To assess the functionality of this motif, we made F97A and F100A mutations that map to the rat 1 NKA sequence. This strategy has been used by others to study the function of CBM in proteins other than the NKA (15). We used a knockdown and rescue protocol to generate a stable cell line (LW-mCBM) that essentially expresses just the CBM mutant 1, which was confirmed using [3H]ouabain binding assays (fig. S1B). Western blot and confocal imaging analyses showed that the expression of mutant 1 NKA in LW-mCBM was comparable to that in the control cell line, named AAC-19 cells (fig. S1, B and C). The expression of CBM mutant 1 was sufficient to restore the expression of the 1 subunit of the NKA, allowing normal plasma membrane targeting of the CBM mutant NKA in LW-mCBM cells (fig. S1, C and D). The successful generation of a stable CBM mutant 1 cell line suggests that the CBM is not essential for the enzymatic activity of the NKA because the ion-transporting function is necessary for animal cell survival (13). In further support, we conducted kinetic studies of the CBM mutant NKA. As shown in Fig. 1A, the overall enzymatic activity per unit of 1 NKA expression was identical between the control AAC-19 and LW-mCBM cells. The Km values of Na+, K+, and ouabain were comparable between the CBM mutant NKA and control (Fig. 1, B to D) (16). Together, these data indicate that the N-terminal CBM is not directly involved in the regulation of the enzymatic properties of the NKA.

(A) Crude membrane preparations were made from AAC-19 and LW-mCBM cells and measured for ouabain-sensitive ATPase activity as described in Material and Methods. (B) Ouabain concentration curve. Crude membrane from LW-mCBM cells was prepared and measured for ATPase activity in the presence of different concentrations of ouabain. Data are shown as percentage of control, and each point represents three independent experiments. Curve fit analysis and IC50 (median inhibitory concentration) were calculated by GraphPad. (C and D) Measurements of Na+ and K+ Km. Assays were done as in (B). The combined data were collected from at least three repeats, and Km value (means SEM) was calculated using GraphPad.

On the basis of the above, we next turned our attention to determining the effects of the CBM mutation on signaling capabilities of the 1 NKA. Specifically, we first conducted immunoprecipitation experiments. As we reported previously in many types of cells (8), immunoprecipitation of caveolin-1 coprecipitated 1 in AAC-19 cells. In contrast, mutation of the CBM resulted in an over 80% decrease in coprecipitated 1 in LW-mCBM cells (Fig. 2A).

(A) Cell lysates from AAC-19 and LW-mCBM were immunoprecipitated (IP) with polyclonal anticaveolin-1 antibody. Immunoprecipitated complex was analyzed by Western blot for 1 and caveolin-1 (n = 4). **P < 0.01 compared to AAC-19. (B) Cell lysates from AAC-19 and LW-mCBM cells were subjected to sucrose gradient fractionation as described in Materials and Methods. A representative Western blot of three independent experiments was shown. **P < 0.01 in comparison to AAC-19. (C) AAC-19 and LW-mCBM cells were treated with different concentrations of ouabain for 10 min and analyzed by Western blot. A representative Western blot was shown (n = 4). *P < 0.05 versus 0 mM ouabain. (D) Cell growth curves of AAC-19 and LW-mCBM. *P < 0.05 versus AAC-19 cells. (E) BrdU assay of AAC-19 and LW-mCBM. The values are means SEM from at least three independent experiments. Photo credit: Xiaoliang Wang, Marshall Institute for Interdisciplinary Research at Marshall University.

To substantiate these observations, we next conducted a detergent-free and carbonate-based density gradient fractionation procedure and found that 1 NKA and its main signaling partners (Src and caveolin-1) were co-enriched in the low-density caveolar fractions, as previously reported in epithelial cells (8, 17). In sharp contrast, the expression of the CBM mutant 1 caused the redistribution of these proteins from low-density to high-density fractions (Fig. 2B). Quantitatively, when the ratios of fraction 4/5 of each protein versus total were calculated, we found that the low-density fraction 4/5 prepared from the control AAC-19 cells contained ~60, ~70, and 80% of caveolin-1, Src, and 1 NKA, respectively. However, in LW-mCBM cells, only ~20% of caveolin-1, Src, and 1 NKA were detected in fraction 4/5 (Fig. 2B).

To address the functional consequences of the dissociation of the 1 NKA from its signaling partners in LW-mCBM cells, we exposed these cells to ouabain, a specific agonist of the receptor NKA/Src complex. As shown in Fig. 2C, while ouabain stimulated phosphorylation of extracellular signalregulated kinase (ERK), a downstream effector of the NKA/Src signaling pathway in AAC-19 cells (5, 8), it failed to do so in LW-mCBM cells.

We have previously shown that 1 NKA signaling is key to the dynamic regulation of cell growth (16, 18). As shown in Fig. 2D, LW-mCBM cells grew much slower than AAC-19 cells. 5-Bromo-2-deoxyuridine (BrdU) incorporation assays further verified that the expression of CBM mutant 1 resulted in an inhibition of cellular proliferation (Fig. 2E). In short, the above in vitro experiments indicate that the gain of CBM enables the NKA to perform the enzymatic activityindependent signaling functions.

With the preceding in vitro data suggesting that the CBM is critically important to the signaling function of the NKA, we next set forth to test the physiological significance of this finding. Thus, we generated a knock-in mouse line expressing the aforementioned CBM mutant 1. The CBM mutant (mCBM) mouse was generated using the Cre/LoxP gene targeting strategy (19), as depicted in fig. S2A. The chimeric offspring were crossed to C57BL6 females to yield mCBM heterozygous mice, and the desired F97A and F100A substitutions were verified (fig. S2B). mCBM heterozygous mice were born fertile and survived to adulthood. Our attempts to generate mCBM homozygous mice yielded no viable homozygous pups (Fig. 3A) in nearly 400 young mice genotyped by polymerase chain reaction (PCR). These results document for the first time that the CBM in the 1 subunit of the NKA represents a fundamental signaling mechanism essential for mouse embryonic development and survival.

(A) Early embryonic lethality of mCBM homozygous embryos. (B) Morphological comparison and body size of wild-type (WT) (top), heterozygous (middle), and homozygous (bottom) mCBM embryos at E9.5. Black bars, 0.3 mm. The arrows show the abnormal head morphology. Body size was measured from at least 12 embryos in different genotypes by ImageJ. Data are presented as means SEM. ***P < 0.01 versus the average of WT. (C) Sagittal sections of WT and homozygous (Homo) and heterozygous (Het) embryos at E9.5 with hematoxylin and eosin (H&E) staining. Homozygous embryos that had defective brain development indicated by open arrows. (D) Brain cross section of WT, homozygous, and heterozygous embryos at E9.5 with H&E staining. Homozygous embryos that had unclosed neural tube in forebrain, midbrain, and hindbrain were indicated by arrows; WT and heterozygous E9.5 embryos with closed neural tube were indicated by arrowhead. (E) Morphological comparison of WT and Na/K-ATPase 1 (+/) embryos at E9.5. White bars, 0.3 mm (n = 5 to 7). Photo credit: Xiaoliang Wang, Marshall Institute for Interdisciplinary Research at Marshall University.

There is evidence that endogenous ouabain is important in animal physiology because of its role in stimulating the signaling function of the NKA (10, 19, 20). Because the loss of the CBM abolishes ouabain-induced signal transduction in vitro, we tested whether administration of pNaKtide, a specific inhibitor of the receptor NKA/Src complex (21), would cause the same embryonic lethality as we observed in mCBM mice. As depicted in fig. S3, we observed no change in fetal survival after administration of pNaKtide to female mice before mating and continued until the end of pregnancy. It is important to mention that pNaKtide has been proven to be specific and effective in blocking the NKA/Src receptor signaling in vivo (2226), and our control experiments showed that pNaKtide could cross the placental barrier. Moreover, this lack of pNaKtide effect on mouse embryogenesis appears to be consistent with a previous report demonstrating that neutralization of endogenous ouabain by injection of an anti-ouabain antibody did affect the kidney development of neonatal mice but did not affect their overall survival (20). On the basis of these, we concluded that the NKA/Src receptor function in the CBM mutant embryo was not the direct cause of lethality and set out to identify a hitherto unrecognized NKA CBM-dependent yet NKA-Srcindependent underlying mechanism.

Embryo implantation within mice occurs around embryonic day 4.5 (E4.5) (27), followed by gastrulation around E5.5 to E7.5 (28), when the simple embryo develops into an organized and patterned structure with three germ layers (29). Subsequently, organogenesis takes place at E8.0 and onward; the patterned embryo starts to develop its organ systems including the brain, heart, limbs, and spinal cord.

To further analyze and explore the molecular mechanisms of the CBM mutation in the embryonic development of mice, we harvested the fertilized eggs at E1.5, and cultured them in vitro. It has previously been demonstrated that 1 knockout results in the failure of blastocyst formation (13). In contrast, we found that eggs from mCBM heterozygous parents developed into morphologically normal blastocysts. These findings indicate that loss of the CBM does not affect the molecular mechanisms necessary for blastocyst formation. Thus, a loss of functional 1 CBM and complete knockout of 1 NKA both result in embryonic lethality but differ by their specific mechanisms. Knockout of 1 NKA inevitably causes the loss of NKA enzymatic function, which is incompatible with life (13), and results in the failure of blastocyst formation in mice. In contrast, our in vitro data indicate that a loss of the CBM does not cause any notable alteration in NKA enzymatic activity, which is supported by the observation that mCBM mice are still capable of producing morphologically normal blastocysts. Consequently, CBM role in development appears to be critical at a developmental stage beyond blastocyst stage, and we further set out to identify this stage.

To this end, we collected and genotyped embryos or yolk sacs from mCBM heterozygous mice at different days of gestation. We first dissected 31 embryos at E12.5 from three different mice (Fig. 3A). Reabsorption and empty deciduae were observed in six implantation sites with only the mothers genotype detectable. At E9.5, we were able to dissect a total of 303 embryos. Sixty-four of them were mCBM homozygous (21%), 71 were wild-type (23%), and 168 were mCBM heterozygous (55%) (Fig. 3A).

To further analyze the embryonic developmental defects, we examined mCBM embryos at E7.5, E8.5, and E9.5. The embryos looked similar between wild-type and mCBM homozygous mice at E7.5 and E8.5 under dissection microscopy. However, we found several severe morphological defects in homozygous embryos at E9.5 (Fig. 3, C and D). First, the overall size of embryos was considerably reduced in mCBM homozygous embryos (about 35% the size of the wild-type embryos). In addition, the observed effect of the CBM mutant on embryonic size was gene dose dependent, as the mCBM heterozygous embryos were significantly smaller than those of wild-type embryos but much bigger than the homozygous embryos. Second, most homozygous embryos did not turn, a process normally initiated at E8.5, suggesting that the loss of a functional CBM was responsible for a developmental arrest at an early stage of organogenesis. Last, the most severe morphological defects were observed in the heads of the mCBM homozygous embryos. In addition to the reduced size (about 25% of the size of wild-type embryos), we observed that mCBM homozygous embryos failed to close their cephalic neural folds (anterior neuropore) as indicated by the arrow in Fig. 3B. This phenotype more closely resembled wild-type embryos at E8.0 to E8.5, suggesting again that the loss of CBM arrested organogenesis in its early stages. On the other hand, all heterozygous embryos, although smaller than wild-type embryos, showed normal head morphology (Fig. 3B).

To follow up on the above observations, we collected and made histological sections of wild-type, heterozygous, and homozygous embryos at E9.5 (Fig. 3, C and D). Normally, formation and closure of the anterior neuropore occurs at E9.5 (Fig. 3D). In sharp contrast, mCBM homozygous embryos developed defects in neural closure. Specifically, failure of neural tube closure at the level of forebrain, midbrain, and hindbrain was prominent in homozygous embryos (Fig. 3D).

To further explore the molecular mechanism by which the loss of the CBM led to defects in organogenesis, we next conducted RNA sequencing analyses (RNAseq) in wild-type and mCBM homozygous embryos. More than 17,000 genes were read out in either mCBM homozygous or wild-type samples. Data analyses indicated that 214 and 208 genes from mCBM homozygous embryos were significantly down- and up-regulated, respectively (fig. S4). Among them, the expression of a cluster of transcriptional factors important for neurogenesis was significantly reduced. As depicted in Fig. 4A, the expression of neurogenin 1 and 2 (Ngn1/2), two basic helix-loop-helix (bHLH) transcriptional factors (30), was significantly down-regulated in homozygous embryos. Ngn1/2 are considered to be determination factors for neurogenesis, while members of the NeuroD family of bHLH work downstream to promote neuronal differentiation (31). We found that the expression of NeuroD1/4 was further reduced in mCBM homozygous embryos. As expected from these findings, the marker of neural stem cells nestin (Nes) and other genes related to neurogenesis including huntington-associated protein 1 (Hap1), nuclear receptor subfamily 2 group E members 1 (Nr2e1), and adhesion G protein (heterotrimeric guanine nucleotidebinding protein)coupled receptor (Adgrb1) were all down-regulated in mCBM homozygous embryos (Fig. 4A). To verify these data, we performed reverse transcription quantitative PCR (RT-qPCR) analyses of both wild-type and mCBM homozygous embryos collected at E9.5. As depicted in Fig. 4 (B to D), the aforementioned transcriptional factors were all down-regulated in a cascade fashion. While a modest reduction was found with Ngn1/2, the expression of NeuroD1/4 was almost completely inhibited. To test whether the effects of the CBM mutation on the expression levels of these transcriptional factors were gene dose dependent, we also examined mRNA levels of Ngn1/2 and NeuroD1/4 in mCBM heterozygous embryos. As depicted in Fig. 4 (B and C), the expression of these genes followed the pattern found in homozygous embryos. The expression level in heterozygous embryos was significantly reduced compared to wild-type embryos but was much higher than that of mCBM homozygous embryos. These gene dosingdependent cascade effects suggest that the 1 NKA is an important upstream regulator but not a determinant of neurogenesis like Ngn1/2 (32) or a key receptor mechanism like Wnt is.

(A) RNAseq results of several neurogenesis and neural stem cell markers. Log2 ratio = 1 means twofold of change. *P < 0.05 compared to WT. (B and C) RT-qPCR analysis of selected gene expression in WT, heterozygous, and homozygous mCBM embryos at E9.5. (D) RT-qPCR analysis of neural stem cell marker gene expression in WT and homozygous mCBM E9.5 embryos. (E) RT-qPCR analysis of neurogenesis marker genes in WT and NKA 1+/ mouse E9.5 embryos. Quantitative data are presented as means SEM from at least six independent experiments. *P < 0.05, **P < 0.01 versus WT control.

As a control, we also assessed the expression of different isoforms of NKA and caveolin-1. As depicted in fig. S5, no changes were detected in the expression of the 1 isoform of the NKA. This is expected, as the mutations were only expressed on exon 4. Previous reports have demonstrated that, in addition to the 1 isoform, neurons also express the 3 isoform, while muscle and glial cells express the 2 isoform of the NKA (9). No difference was observed in the expression of 3, while the expression of 2 was too low to be measured. We were also unable to detect any change in the expression of caveolin-1.

The total amount of protein recognized by the anti-NKA 1 antibody is unchanged in mCBM heterozygous mouse tissues compared to that of the wild type, albeit with changes in distribution in caveolar versus noncaveolar fractions. This indicates that the CBM mutant protein is fully expressed, as observed in cells (fig. S1), and further demonstrates that a reduction of enzymatic activity is not responsible for the observed phenotype in mCBM homozygous embryos. However, because the expression of wild-type 1 in mCBM heterozygous animals is most likely reduced, the phenotypic changes we observed in these mice could be due to the reduction of wild-type 1 expression rather than the expression of CBM mutant 1. To address this important issue, we collected embryos from 1 NKA heterozygous (1+/) mice and their littermate controls (33). In contrast to mCBM heterozygotes, reduction of 1 expression alone did not change the size of embryos (Fig. 3D), head morphology, or the expression of neuronal transcriptional factors (Fig. 4E). Because NKA 1 haploinsufficiency did not phenocopy mCBM heterozygosity, it was concluded that the mCBM allele was responsible for the observed changes.

The CBM in NKA has a consensus sequence of FCxxxFGGF (fig. S6). To assess the generality of CBM-mediated regulation, we first turned to the conserveness of the CBM in animal NKA. A database search reveals that, like Wnt, the mature form of NKA (i.e., containing CBM, Na+/K+ binding sites, and subunit) is absent in unicellular organisms but present in all multicellular organisms within animal kingdom (fig. S6). Further analysis of published data confirms the coevolutionary nature of the CBM and the binding sites for Na+ and K+ in the NKA. The first indication is from the analysis of single-cell organisms. No mature form of NKA is found in these organisms (fig. S6A). However, Salpingoeca rosetta, a marine eukaryote belonging to the Choanoflagellates class, undergoes a very primitive level of cell differentiation and specialization in their life cycle and expresses a putative NKA with several conserved motifs involved in the binding of Na+/K+. On the other hand, it contains no CBM (fig. S6) and there is also no evidence that it expresses a subunit.

Second, as depicted in figs. S6 and S7, Caenorhabditis elegans, an example of a metazoan organism, expresses a mature form of NKA (eat-6) that contains binding sites for Na+ and K+ as well as the N-terminal CBM. It also expresses a couple of putative NKA such as catp-2 (34). However, they contain neither the CBM nor Na+ and K+ binding sites.

Third, although the X amino acids in the NKA CBM in invertebrates vary, only conserved substitutions occurred in this motif. This is in sharp contrast to many other membrane receptors/transducers such as Patched and G that also contain a consensus CBM (figs. S6 and S7). Within vertebrates, the CBM sequence FCRQLFGGF in NKA remains completely conserved across all species. Moreover, this sequence remains conserved in all isoforms of the subunit except for the 4 isoform, which is exclusively expressed in sperm. The 4 isoform in some species still adapts the CBM sequence found in invertebrates (fig. S6). Moreover, of a total of nine subunits found in zebrafish (35), five appear to be 1 homologs that, like the 4 isoform, contain both vertebrate and invertebrate CBM sequences.

Last, turning to the evolutionary aspect of the receptor NKA/Src complex, we found that the Src-binding NaKtide and Y260 sequences, in sharp contrast to the CBM, are only conserved in mammalian ATP1A1 (fig. S7). Therefore, the NKA/Src receptor may have evolved after the acquisition of the CBM, and hence is not a part of the fundamental regulation of animal organogenesis (fig. S3).

In short, the N-terminal CBM, like the binding sites for Na+ and K+, is conserved in all subunits of NKA in animals, even after taking into consideration gene duplications and the generation of different isoforms or homologs. Thus, we postulate that this CBM must be evolutionally conserved to enable the NKA, in parallel with its enzymatic function, to serve an important role in the origination of multicellular organisms within the animal kingdom.

Organogenesis represents a unique feature of multicellular organisms. In considering the preceding findings, we reasoned that the loss of NKA CBM would also affect embryonic development in invertebrates such as C. elegans. To test our hypothesis, we used CRISPR-Cas9 to knock in the equivalent CBM double mutations of F75A and F78A in C. elegans NKA gene eat-6 (named as syb575) (fig. S8). Similar to the impact of the expression of CBM mutant 1 NKA in mice, no homozygous worms were produced, whereas the heterozygous worms hatched normally. Moreover, by using the gene balancer nT1, we confirmed that the F75A and F78A double mutations induced embryonic lethality in syb575 homozygotes secondary to L1 arrest (Fig. 5A). Furthermore, the observed larval arrest due to the loss of the eat-6 CBM was rescued by a transgene expressing a wild-type eat-6 complementary DNA (cDNA) through an extrachromosomal array (Fig. 5B). The lethality phenotype in syb575 mutants was different from those of the eat-6 mutants defective in enzymatic (transport) activity, because while the eat-6 mutants had growth defects, they were able to grow past the L1 stage (36). An exception to this was a cold-sensitive eat-6 (ad792) mutant with severely reduced transport activity, which exhibited L1 arrest at lower temperatures similarly to the syb575 mutant worms (36). Overall, those data suggest that both CBM-mediated signaling and ion transport activity by the NKA are essential to full-scale organogenesis in C. elegans.

(A) Heterozygous CBM mutant (mCBM) worms syb575/nT1 have GFP signals in pharynx (pointed with the arrowhead), while mCBM homozygous worms are GFP negative and arrested at larval stage (pointed with an arrow). (B) Rescue with a WT eat-6 gene showing a mCBM homozygous worm with a transgenic marker sur-5::GFP. Arrow points the somatic GFP signals. (C) Mutation of CBM1 NKA (F97A; F100A) results in reduced colony formation in human iPSC (mCBM iPSC). (D) RT-qPCR analysis of stem cell markers and primary germ layer markers in WT and mCBM iPSC. *P < 0.05 compared to WT. n = 7. Photo credit: Liquan Cai, Marshall Institute for Interdisciplinary Research at Marshall University.

In short, our data indicate that loss of the NKA CBM results in defective organogenesis in both mice and C. elegans. This, together with our finding that the NKA CBM is conserved in all NKA regardless of isoform or homolog, indicates that the NKA was originally evolved as a dual functional protein in multicellular organisms, and that it represents a primordial and common mechanism for regulating stem cell differentiation and early stage of organogenesis in animals.

Turning now to even more general features of the CBM in organogenesis, we searched for the plant plasma membrane H-ATPase that functions equivalently to the animal NKA. Like the NKA, the plant plasma membrane H-ATPase also contains a sequence motif at the first transmembrane segment that is in accordance with the consensus CBM. This motif is completely conserved from blue algae to land plants but does not exist within yeast and bacteria (fig. S6).

To assess the human relevance of our findings, we used CRISPR-Cas9 gene editing to generate the same mutations in human induced pluripotent stem cells (iPSCs) (fig. S9). As depicted in Fig. 5C, the expression of mutant CBM 1 reduced the colony formation ability of human iPSCs. Concomitantly, this was accompanied by a significant reduction in the expression of stemness markers (both Nanog and Oct4), and transcriptional factors controlling germ layer differentiation (gene MIXL and T for mesoderm, OTX2 and SOX1 for ectoderm, and GATA4 and SOX17 for endoderm) (Fig. 5D). These findings confirm an essential role of the NKA CBM in the regulation of stem cell differentiation and suggest the potential utility of targeting the NKA for improving tissue regeneration.

The canonical Wnt pathway is made of multiple components localized in the plasma membrane and cytosol (2, 3). Functionally, this pathway is critically important in animal organogenesis (2, 37). For example, it plays an essential role in the establishment of neurogenic niches and regulates the differentiation of neural stem cells into neuroblasts during organogenesis by regulating the expression of transcriptional factors Ngn and NeuroD (37, 38). Thus, we were prompted by the observed neural defects in mice to test whether the expression of the CBM mutant 1 NKA affects Wnt/-catenin signaling.

In the first set of studies, we examined the cellular distribution of -catenin in LW-mCBM cells. As depicted in Fig. 6A, confocal imaging analysis showed that -catenin was distributed away from the plasma membrane in a vesicle-like form in LW-mCBM cells. To verify this finding, we fractionated the cell lysates as performed in Fig. 3B and observed that -catenin, like Src and caveolin-1, moved from the low-density fractions to high-density fractions when compared to control cells (Fig. 6B). Control experiments showed no changes in the expression of E-cadherin, glycogen synthase kinase3 (GSK-3), LRP5/6 (Low-density lipoprotein receptor-related protein 5 and 6), and -catenin in LW-mCBM cells (Fig. 6C).

(A) -Catenin staining of AAC-19 and LW-mCBM at basal level (n = 5). Blue arrow indicated -catenin signal in the cytoplasm of cells. (B) Sucrose gradient fractionation of -catenin in AAC-19 and LW-mCBM cells (n = 3). **P < 0.01. (C) Western blot analysis of Wnt/-catenin signaling proteins in AAC-19, LX-2, and LW-mCBM cells from at least six independent experiments. Two samples from each cell lines are presented. (D) Wnt3a induced TOPFlash luciferase report assay in AAC-19 and LW-mCBM (n = 8). ***P < 0.01. (E) Wnt3a induced expression of Wnt/-catenin targeting genes (n = 8). **P < 0.01. (F) Wnt3a induced TOPFlash luciferase report assay in AAC-19, LX-2, and LW-mCBM cells (n = 4). ***P < 0.01.

To test whether these changes in -catenin distribution alter the function of canonical Wnt signaling, we conducted a TOPFlash luciferase activity assay (39). Cells were transiently transfected with the reporter plasmid, exposed to Wnt3a conditional medium, and then subjected to TOPFlash luciferase assays. As shown in Fig. 6D, while Wnt3a induced a greater than 35-fold increase in luciferase activity in AAC-19 cells, it only produced a fourfold increase in LW-mCBM cells, which equates to an approximate 90% reduction in the dynamics of Wnt activation. To further test the impact of the CBM mutation on Wnt signaling, we examined the effects of Wnt3a on the expression of Wnt target genes. Cells were exposed to Wnt3a for 6 hours and subjected to RT-qPCR analysis. As depicted in Fig. 6E, while Wnt3a increased the expression of c-Myc, Lef, and NKD1 expression in AAC-19 cells, it failed to do so in LW-mCBM cells.

On the basis of the above observations, we reasoned that the NKA CBM might play an essential role in the dynamic regulation of Wnt signaling. We therefore analyzed Wnt signaling in our LX-2 cell line. This cell line was made by the same strategy used for the generation of LW-mCBM cells, and it expresses essentially just the 2 isoform (40). We have observed that 2 NKA, like CBM mutant 1, maintains cellular pumping capacity but is unable to signal via Src like a wild-type 1 NKA (40). However, unlike CBM mutant 1, 2 does contain the same CBM at the N terminus (fig. S6). As depicted in Fig. 6F, expression of the 2 isoform produced a rescue of Wnt signaling dynamics when compared to that in LW-mCBM cells, which reinforces the idea that the NKA CBM is key to the dynamics of Wnt signaling. Like in LW-mCBM cells, no change in -catenin expression was noted in LX-2 cells. However, compared to LW-mCBM cells, caveolin-1 expression was decreased in LX-2 cells, while ERK activity was increased (Fig. 6C). Together, these findings suggest that the conserved NKA CBM is essential for regulating Wnt signaling, which is independent of the pumping or CTS (ardiotonic steroid)activated Src-dependent signaling transduction.

To see whether there is evidence of Wnt signaling defects in mCBM homozygous embryos, we examined the RNAseq data using a tool kit of pathway analysis. As depicted in fig. S10, Wnt signaling appears to be defective at the transcriptional level. First, the expression of one of the Wnt receptors [Frizzled homolog 5 (Fzd5)] and one of the Wnt ligands (Wnt7b) was down-regulated (fig. S10A). Second, the Wnt/-catenin signaling inhibitor, secreted frizzled-related protein 5 (Sfrp5), was up-regulated in mCBM homozygous embryos. Third, the -catenin destruction complex component adenomatosis polyposis coli (APC) was down-regulated in mCBM homozygous embryos. All these defects in Wnt signaling were confirmed by RT-qPCR analysis of both wild-type and mCBM homozygous embryos at E9.5 (fig. S10B). In addition, APC down-regulation was also observed at the protein level in mCBM iPSCs (fig. S10C). Last, the defect in Wnt signaling was further substantiated by the altered expression of Wnt downstream target genes. As shown in fig. S10B, the expression of Lef and NKD1 was significantly reduced in mCBM homozygous embryos. The expression of c-Myc was too low to be detected.

Together, these data provide strong support to the notion that the CBM is a key to the regulation of Wnt by the NKA. We hypothesize that this critical function of the NKA CBM may explain why the CBM is conserved in all four subunit isoforms of the NKA. It is important to mention that the specific molecular defects in Wnt signaling that we have identified were tested in epithelial cells, a model we have previously used to characterize 1-specific signaling functions (16, 41). In view of the cell/tissue specificity of both NKA expression and subunit assemble (42) and Wnt signaling (13, 37), it is likely that this mechanism does not fully explain the Wnt signalingrelated defects in embryogenesis.

The enzymatic function of NKA coordinates the transmembrane movement of Na+/K+, which is essential for the survival of individual animal cells. At the tissue/organ level, the ATP-powered transport of Na+/K+ by the NKA is required for neuronal firing, muscle contraction, and the formation and functionality of epithelia and endothelia. The NKA was found to be essential for forming septate junction in Drosophila melanogaster (43, 44) via a regulatory mechanism independent of its ion-pumping activity. Here, we reveal an additional fundamentally important role of NKA in the regulation of signal transduction through a separate functional domain (CBM) unrelated to its enzymatic activity.

Our findings raise the question of why NKA acquired the CBM in addition to its binding sites for Na+ and K+. One possible explanation for this is that the additional functionality in NKA (fulfilled by the CBM) evolved for the purpose of regulating stem cell differentiation and organogenesis in multicellular organisms. Two observations support this hypothesis. First, both Wnt and NKA are present in the first multicellular organisms within the animal kingdom and are evolutionally conserved ever since. Thus, it is likely that the NKA and Wnt work in concert to enable stem cell differentiation and organogenesis in animals. Second, while Wnt is key to the cellular programs of stemness and cell lineage specification (2), it does not directly participate in cell lineagespecific activities of newly differentiated cells. Instead, this particular function might be fulfilled by the NKA. Conceivably, the NKA could have been evolved, as exemplified by the mitochondrial cytochrome c in ATP generation, to bring together two seemingly unrelated processes (i.e., Wnt signaling regulation via the CBM and ion transport through Na+ and K+ binding) into one signaling circuitry, which is critical to the dynamic regulation of transcriptional factors that are required for organogenesis in a temporally and spatially organized manner. Needless to say, this hypothesis remains to be tested. In addition, other important signaling pathways such as Notch and Sonic Hedgehog may also be regulated by NKA.

It is also of interest to note the evolutionary conserveness of the CBM in the plant plasma membrane H-ATPase. Like its counterpart within the animal kingdom, the plasma membrane H-ATPase is essential for plant organogenesis (45). Unlike the NKA, the plasma membrane H-ATPase exists in single-celled organisms such as yeast, and their ion-pumping function is regulated by similar mechanisms (46). However, yeast, with no use for cellular machinery needed for organogenesis, does not contain the H-ATPase with conserved CBM. Moreover, we also observed that no CBM exists in the plasma membrane Ca-ATPase (fig. S6), both of which belong to the same type II P-type ATPase family as the NKA. While the Ca-ATPase is a more ancient protein than the NKA, as its expression can be found in unicellular organisms, the H/K-ATPase appeared later than the NKA, at some point during the development of vertebrates. Thus, we suggest that the NKA may have evolved from a P-ATPase of unicellular organisms via the gain of both the CBM and Na+/K+ binding sites. In contrast, the H/K-ATPase may have evolved from the NKA, losing not only the Na+ binding site but also the CBM.

We have shown a direct interaction between the NKA and caveolin-1 (8, 17), which has been independently confirmed (47). The loss of the CBM significantly reduced the interaction between NKA and caveolin-1 as revealed by multiple assays. In addition to caveolin-1, we and others have reported several signal transductionrelated interactions (48). Of these, the potential interaction between 1 NKA and Src has attracted the most attention, especially in the past 10 years (7). While most studies indicated an important role of Src in CTS-activated signal transduction via 1 NKA, several publications have questioned whether 1 NKA interacts with Src directly to regulate Src functionality (49, 50). While this important difference remains to be experimentally addressed, we would like to point out the following facts. First, while we recognize the merit of using purified protein preparation to study protein interaction, it is important to recognize the limitation of using purified Src from bacterial expression system because they are heterogeneously phosphorylated. Second, we have reported multiple lines of evidence that support a direct interaction between 1 NKA and Src, including the identification of isoform-specific Src interaction, the mapping of potential Src-interacting sites in the 1 isoform, and the development of pNaKtide as Src inhibitor and receptor antagonist. These findings have substantially increased our understanding of 1 NKA/Src interaction in cell biology and animal physiology. It is important to mention that several groups not associated with us have successfully used pNaKtide to block ouabain and NKA signaling in vitro and in vivo (2326, 51). While our group and others continue to characterize the molecular basis and biological function of the NKA/Src receptor complex, we propound that the question of NKA/caveolin-1 interaction is a more pressing one in the context of this study. The role of CBM in caveolin-protein interaction and caveolae-related signaling is still debated (41, 52, 53).

Last, we conclude from these interesting findings that the NKA is not just an ion pump or a CBM-directed regulator but a critical multifunctional protein. This whole functionality underlies a hitherto unrecognized common mechanism essential for stem cell differentiation and organogenesis in multicellular organisms within the animal kingdom. Moreover, many recent studies also support the concept that the 1 NKA has acquired more functional motifs (e.g., Src-binding sites for the formation of NKA/Src receptor complex) during evolution. In addition, we have demonstrated that either knockdown of 1 NKA or the expression of an N-terminal fragment containing the CBM of the 1 subunit was sufficient to attenuate purinergic calcium signaling in renal epithelial cells (54). The 1 NKA is also found to be essential for CD36 and CD40 signaling in macrophages and renal epithelial cells (55, 56). Aside from the profound biological and fundamental implications, the previously unidentified NKA-mediated regulation of Wnt signaling through its N-terminal CBM may have substantial implications in our understanding of disease progression. The rapidly increasing appreciation of Wnt signaling in the pathogenesis of cancer and cardiovascular diseases (2, 3, 38) underlies the potential utility of NKA as a multidrug target (12, 22, 57, 58).

Acknowledgments: Funding: This work was supported by grants from: National Institutes of Health (NIH) Research Enhancement Award (R15) (R15 HL 145666); American Heart Association (AHA) Scientist Development Grant (#17SDG33661117); Brickstreet Foundation and the Huntington Foundation, which provide discretionary funds to the Joan C. Edwards School of Medicine. (These funds are both in the form of endowments that are held by Marshall University). Author contributions: Conceptualization: Z.X., X.W., J.X.X., L.C., G.-Z.Z., S.V.P., and J.I.S.; methodology: X.W., L.C., I.L., D.W., and G.-Z.Z.; investigation: X.W., L.C., X.C., J.W., Y.C., and J.Z.; writing (original draft): X.W., J.X.X., and Z.X.; writing (review and editing): Z.X., J.X.X., L.C., J.I.S., S.V.P., D.W., G.-Z.Z., and X.W.; funding acquisition: Z.X.; visualization: X.W. and Z.X. Competing interests: The authors declare that they have no competing interests. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. Additional data related to this paper may be requested from the authors.

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