Orgenesis completes acquisition of Koligo Therapeutics and announces additional acquisition of Icellator(R) Technology from Tissue Genesis in related…

Orgenesis completes acquisition of Koligo Therapeutics and announces additional acquisition of Icellator(R) Technology from Tissue Genesis in related transaction

Icellator(R) commercially available for lipotransfer in first two countries with more approvals expected

Germantown, MD, US October 19th, 2020 Orgenesis Inc. (NASDAQ: ORGS)(Orgenesis or the Company), a global biotech company working to unlock the full potential of celland gene therapies, today announced completion of thepreviously announcedacquisition ofKoligo Therapeutics, Inc.(Koligo), a regenerative medicine company. Additionally, the Company announced that it has acquired substantially all of the assets ofTissue Genesis, LLC(Tissue Genesis), adding to a growing list of POCare technology resources.

The acquisition of Tissue Genesis was initially undertaken via Koligo Therapeutics, Inc., and became part of the Koligo acquisition transaction. Orgenesis will now own the entire inventory of Tissue GenesisIcellator(R) devices, related kits and reagents, a broad patent portfolio to protect the technology, registered trademarks, clinical data, and existing business relationships for commercial and development stage use of the Icellator technology.

The Icellator device is a point-of-care cell isolation technology that rapidly recovers high yields of stromal and vascular cells (SVF) from adipose tissue (fat) to be used therapeutically. Adipose tissue is recognized as a superior source for adult stem cells found abundantly in the micro-vasculature and stroma of human fat. Further details include:

With the Koligo acquisition closed, we believe that we are making rapid progress on a number of fronts, said Vered Caplan, CEO of Orgenesis. Specifically, we plan to leverage the therapies and technologies from Koligo and Tissue Genesis across our POCare Platform. One of our first goals is to accelerate the commercial scaleup of KYSLECEL throughout the United States and, subject to regulatory and logistical considerations, in international markets as well. Subject to FDA review and clearance of our IND application, we also look forward to commencing patient recruitment for a phase 2 randomized clinical trial of KT-PC-301, an autologous clinical development stage cell therapy candidate for COVID-19-related Acute Respiratory Distress Syndrome, or ARDS. We plan to use the Icellator device to support scalable, cost-effective production of KT-PC-301. Additionally, Koligos development stage 3D-V bioprinting technology for the vascularization of autologous cells to create biodegradable and shelf-stable three-dimensional cell and tissue implants will be explored for diabetes and pancreatitis applications, with longer term applications for neural, liver, and other cell/tissue transplants also potentially explored.

The Icellator system is highly complementary to our POCare technology systems, as well as Koligos 3D-V bioprinting technology. Technologies such as these support our mission of improving the efficacy and lowering the costs of cell and gene therapies by delivering autologous cell therapies at the point of care through our global network of hospitals and healthcare institutions, concluded Caplan.

Under the terms of the Koligo merger agreement, Orgenesis acquired all of the outstanding stock of Koligo from its shareholders for approximately USD 14.5 million in shares of Orgenesis common stock valued at USD7.00 per share (with certain non-accredited investors paid approximately USD 20,000 solely in cash) and an assumption of USD 1.9 million in liabilities, estimated to be substantially all of Koligos liabilities. Orgenesis acquired substantially all the assets of Tissue Genesis for an additional consideration of USD 500,000 in closing cash and future royalties. Additional details of the transactions will be available in the Companys Form 8-K, which will be filed with the Securities and Exchange Commission, and will be available atwww.sec.gov.

Pearl Cohen Zedek Latzer Baratz LLP and KPMG advised Orgenesis on the Koligo Transaction. Maxim Group LLC acted as a finder and Nelson Mullins Riley & Scarborough, LLP advised Koligo on the Transaction.

About Orgenesis

Orgenesis is a global biotech company working to unlock the full potential of celland gene therapies (CGTs) in an affordable and accessible format at the point of care. The Orgenesis POCarePlatform is comprised of three enabling components: a pipeline of licensedPOCare Therapeuticsthat are processed and produced in closed, automatedPOCare Technologysystems across a collaborativePOCare Network. Orgenesisidentifies promising new therapies and leverages its POCare Platform to provide a rapid, globally harmonized pathway for these therapies to reach and treat large numbers of patients at lowered costs through efficient, scalable, and decentralized production. The Network brings together patients, doctors, industry partners, research institutes and hospitals worldwide to achieve harmonized, regulated clinical development and production of the therapies. Learn more about the work Orgenesis is doing atwww.orgenesis.com.

Notice Regarding Forward-Looking Statements

The information in this release is as of October 19, 2020. Orgenesis assumes no obligation to update forward-looking statements contained in this release as a result of new information or future events or developments. This release contains forward looking statements about Orgenesis, Koligo, Koligos technology, and potential development and business opportunities of Koligo and Orgenesis following the closing of the Transaction, each of which involve substantial risks and uncertainties that could cause actual results to differ materially from those expressed or implied by such statements. Risks and uncertainties include, among other things, uncertainties regarding the commercial success of the Companys products; the uncertainties inherent in research and development, including the ability to meet anticipated clinical endpoints, commencement and/or completion dates for our clinical trials, regulatory submission dates, regulatory approval dates and/or launch dates, as well as the possibility of unfavorable new clinical data and further analyses of existing clinical data; the risk that clinical trial data are subject to differing interpretations and assessments by regulatory authorities; whether regulatory authorities will be satisfied with the design of and results from our clinical studies; whether and when any such regulatory authorities may approved the Companys development products, and, if approved, whether such product candidates will be commercially successful; decisions by regulatory authorities impacting labeling, manufacturing processes, safety and/or other matters that could affect the availability or commercial potential of the Companys products; uncertainties regarding the impact of COVID-19 on the Companys business, operations and financial results and competitive developments.

A further description of risks and uncertainties can be found in the Companys Annual Report on Form 10-K for the fiscal year ended December 31, 2019 and in its subsequent reports on Form 10-Q, including in the sections thereof captioned Risk Factors and Forward-Looking Information, as well as in its subsequent reports on Form 8-K, all of which are filed with the U.S. Securities and Exchange Commission and available atwww.sec.gov.

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Orgenesis completes acquisition of Koligo Therapeutics and announces additional acquisition of Icellator(R) Technology from Tissue Genesis in related...

Stem Cell Therapy Market to Witness Steady Expansion During 2025 KYT24 – KYT24

Of late, there has been an increasing awareness regarding the therapeutic potential of stem cells for management of diseases which is boosting the growth of the stem cell therapy market. The development of advanced genome based cell analysis techniques, identification of new stem cell lines, increasing investments in research and development as well as infrastructure development for the processing and banking of stem cell are encouraging the growth of the global stem cell therapy market.

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One of the key factors boosting the growth of this market is the limitations of traditional organ transplantation such as the risk of infection, rejection, and immunosuppression risk. Another drawback of conventional organ transplantation is that doctors have to depend on organ donors completely. All these issues can be eliminated, by the application of stem cell therapy. Another factor which is helping the growth in this market is the growing pipeline and development of drugs for emerging applications. Increased research studies aiming to widen the scope of stem cell will also fuel the growth of the market. Scientists are constantly engaged in trying to find out novel methods for creating human stem cells in response to the growing demand for stem cell production to be used for disease management.

It is estimated that the dermatology application will contribute significantly the growth of the global stem cell therapy market. This is because stem cell therapy can help decrease the after effects of general treatments for burns such as infections, scars, and adhesion. The increasing number of patients suffering from diabetes and growing cases of trauma surgery will fuel the adoption of stem cell therapy in the dermatology segment.

Global Stem Cell Therapy Market: Overview

Also called regenerative medicine, stem cell therapy encourages the reparative response of damaged, diseased, or dysfunctional tissue via the use of stem cells and their derivatives. Replacing the practice of organ transplantations, stem cell therapies have eliminated the dependence on availability of donors. Bone marrow transplant is perhaps the most commonly employed stem cell therapy.

Osteoarthritis, cerebral palsy, heart failure, multiple sclerosis and even hearing loss could be treated using stem cell therapies. Doctors have successfully performed stem cell transplants that significantly aid patients fight cancers such as leukemia and other blood-related diseases.

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Global Stem Cell Therapy Market: Key Trends

The key factors influencing the growth of the global stem cell therapy market are increasing funds in the development of new stem lines, the advent of advanced genomic procedures used in stem cell analysis, and greater emphasis on human embryonic stem cells. As the traditional organ transplantations are associated with limitations such as infection, rejection, and immunosuppression along with high reliance on organ donors, the demand for stem cell therapy is likely to soar. The growing deployment of stem cells in the treatment of wounds and damaged skin, scarring, and grafts is another prominent catalyst of the market.

On the contrary, inadequate infrastructural facilities coupled with ethical issues related to embryonic stem cells might impede the growth of the market. However, the ongoing research for the manipulation of stem cells from cord blood cells, bone marrow, and skin for the treatment of ailments including cardiovascular and diabetes will open up new doors for the advancement of the market.

Global Stem Cell Therapy Market: Market Potential

A number of new studies, research projects, and development of novel therapies have come forth in the global market for stem cell therapy. Several of these treatments are in the pipeline, while many others have received approvals by regulatory bodies.

In March 2017, Belgian biotech company TiGenix announced that its cardiac stem cell therapy, AlloCSC-01 has successfully reached its phase I/II with positive results. Subsequently, it has been approved by the U.S. FDA. If this therapy is well- received by the market, nearly 1.9 million AMI patients could be treated through this stem cell therapy.

Another significant development is the granting of a patent to Israel-based Kadimastem Ltd. for its novel stem-cell based technology to be used in the treatment of multiple sclerosis (MS) and other similar conditions of the nervous system. The companys technology used for producing supporting cells in the central nervous system, taken from human stem cells such as myelin-producing cells is also covered in the patent.

Global Stem Cell Therapy Market: Regional Outlook

The global market for stem cell therapy can be segmented into Asia Pacific, North America, Latin America, Europe, and the Middle East and Africa. North America emerged as the leading regional market, triggered by the rising incidence of chronic health conditions and government support. Europe also displays significant growth potential, as the benefits of this therapy are increasingly acknowledged.

Asia Pacific is slated for maximum growth, thanks to the massive patient pool, bulk of investments in stem cell therapy projects, and the increasing recognition of growth opportunities in countries such as China, Japan, and India by the leading market players.

Global Stem Cell Therapy Market: Competitive Analysis

Several firms are adopting strategies such as mergers and acquisitions, collaborations, and partnerships, apart from product development with a view to attain a strong foothold in the global market for stem cell therapy.

Some of the major companies operating in the global market for stem cell therapy are RTI Surgical, Inc., MEDIPOST Co., Ltd., Osiris Therapeutics, Inc., NuVasive, Inc., Pharmicell Co., Ltd., Anterogen Co., Ltd., JCR Pharmaceuticals Co., Ltd., and Holostem Terapie Avanzate S.r.l.

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Stem Cell Therapy Market to Witness Steady Expansion During 2025 KYT24 - KYT24

Mohammed Hussain Alqahtani shares his insights about the evolution of plastic surgery – LA Progressive

Dr. Mohammed Hussain Alqahtani has a rich insight into the world of cosmetic developments. In his expansive career, he has dealt with several surgical as well as non-surgical procedures. Plastic Surgery, or at least the cosmetic kind, has always been quite the trend. However, it was not always absolutely safe or, to say, readily affordable. Dr. Alqahtani educates us on how there has been a monumental shift in the industry, while also enlightening us about how safe and approachable the procedures are currently.

Its not always about beautifying a certain part. In fact, it could also be a genuine necessity.

Dr. Alqahtani has shared his expertise on several forums and interviews. He champions the positivity cosmetic surgery brings in the life of a person. To begin with, he says, Its not always about beautifying a certain part. In fact, it could also be a genuine necessity. He says people falsely associate cosmetic procedures with being limited to getting a fuller lip or breast augmentation. The truth is cosmetic treatments arent gender-biased. They are safe procedures conducted by trained doctors adhering to the highest health and hygiene protocol.

The situation with plastic surgery earlier was different and has now undergone a sea change. The treatments and procedures have been standardized, ensuring patient safety. There is no longer fear of any contamination or hygiene issues. The surgery procedures are now assisted by highly efficient software and AI machines that bring in precision. The treatments are supervised by highly skilled doctors who recommend procedures only after considering your medical history.

Dr. Alqahtani says the most significant victory lies in the fact that plastic surgeries now can give burn patients, acid-attack victims, etc. a new lease of life. Victims can undergo a safe and secure treatment, which can help them forget their trauma. People should be able to opt for a cosmetic procedure if they wish to. The enhancement of facial features often adds to the self-confidence of a person.

The future will also have Integrated Stem Cell technology that will help regenerate new cells. Besides these, several ongoing medical experiments will bring about contributory changes in the future. For now, Dr. Alqahtani assures that plastic surgery is no longer a stigma but a new way of looking at your own life.

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Mohammed Hussain Alqahtani shares his insights about the evolution of plastic surgery - LA Progressive

Manya Saaraswat Makes Top 5 Finish in 2020 Miss World America Competition, Three Other Indian Americans in Top 10 – India West

Miss World America this month held its virtual competition for 2020, with a quartet of Indian Americans making the Top 10 and one, Manya Saaraswat, making it all the way to the Top 5.

Alissa Anderegg of New York was the grand prize winner and will hold the title of 2020 Miss World America.

In addition to Saaraswat of Pennsylvania, Indian Americans Serene Singh of Colorado; Manju Bangalore of Oregon; and Shree Saini of Washington were top 10 finishers.

The Top 10 were named from a group of 28 women that included six Indian Americans and a Bangladeshi American (see India-West article here: https://bit.ly/2H5dFFD).

Saaraswat immigrated to the United States when she was three years old. She has since moved around seven times and has attended over 10 different schools, according to her bio.

Because she was moving around a lot, her family became her best friends and remain so today. Both of her parents are physicians and from a young age, Saaraswat was encouraged to lead a service driven life. At 14, she began volunteering in the neonatal intensive care unit at a local hospital. It was here where she found her love for pediatrics and medicine, her bio said.

She entered Bucknell University on a presidential fellowship, which is the highest merit scholarship the university offers. Her academic endeavors led her to a stem cell internship at Harvard University, four publications in medical journals, and a life-changing trip to volunteer and intern at a local hospital in India, the bio notes.

Currently, she is pursuing a master of science of health policy and economics at Weill Cornell Medicine before she enters medical school.

Singh is a native Coloradan and a Rhodes Scholar, and is starting her doctorate degree in criminal justice at the University of Oxford, her bio notes.

A Truman Scholar and an alumnus of the University of Colorado, she graduated with summa cum laude honors in political science and journalism degrees with a minor in leadership studies, it said.

Singh, her bio notes, cares deeply about empowering girls and women worldwide. She is the founder of a The Serenity Project Brave Enough to Fly nonprofit, an organization that aims to give confidence tools to at-risk women. Her passion for paying forward her skills from pageantry and modeling have reached hundreds of women, has won Victoria Secrets GRL PWR campaign, and serve as a Dalai Lama Fellow and Global Changemaker, her bio adds.

Singh plans to advance her passion for public service to one day serve on the United States Supreme Court.

Bangalore is a physicist, actor and the founder of Operation Period, a youth-led nonprofit addressing menstrual inequity through art, advocacy, education, community engagement and aid.

She received her physics degree and math minor from the University of Oregon in 2018 and is now pursuing her M.S. in aerospace engineering with a concentration on propulsion systems, it said.

She has worked at two NASA centers, Marshall Space Flight Center and Johnson Space Center, on propulsion and the cockpit displays for the Orion spacecraft, as well as in the White House under President Obama on science policy.

Saini isa global speaker who has been invited to speak in over eight countries and 30 states, her bio touts.

She graduated from the University of Washington and has been a visiting student at Harvard, Stanford and Yale universities.

Saini has devoted her life to community service. At age 15, she started her nonprofit and since then, she has written thousands of articles and served hundreds of nonprofits, it said.

Herimpact has reached millions: earning her the Best Pageant Titleholder award and recognitions from the Secretary of State, Senate, Governor and American Heart Association CEO.

Sainis childhood dream to serve as Miss World inspired her to change her adversities to advocacy. She is a survivor of bullying, facial burns and heart defect.

At just age 12, she got a pacemaker surgery to keep her alive. Doctors said her physical activities would be forever limited but Saini persevered to regain her lost physical and emotional strength, the bio said.

In addition to Saaraswat and Anderegg, the top 5 included Alissa Musto of Massachusetts; Molly May of Mississippi; and Megan Gordan of South Carolina.

The Miss World America 2020 winner will be formally announced as the winner at a crowning ceremony is slated for Oct. 24.

Last years winner Emmy Rose Cuvelier will crown her successor who will represent the United States at the 70th Miss World edition to be held in the last quarter of next year.

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Manya Saaraswat Makes Top 5 Finish in 2020 Miss World America Competition, Three Other Indian Americans in Top 10 - India West

Microscopy Beyond the Resolution Limit – Lab Manager Magazine

Image of microtubules in a fixed cell sample. A 3 microns x 3 microns confocal scan of microtubules in a fixed 3T3 cell labeled with quantum dots analyzed in two ways. Upper left: image scanning microscopy (ISM), lower right: super-resolution optical fluctuation image scanning microscopy (SOFISM) after Fourier-reweighting.

UW Physics, A. Makowski

The Polish-Israeli team from the Faculty of Physics of the University of Warsaw and the Weizmann Institute of Science has made another significant achievement in fluorescent microscopy. In the pages of the Optica journal, the team presented a new method of microscopy which, in theory, has no resolution limit. In practice, the team managed to demonstrate a fourfold improvement over the diffraction limit.

The continued development of biological sciences and medicine requires the ability to examine smaller and smaller objects. Scientists need to see into the structure of, and the mutual relationships between, for example, proteins in cells. At the same time, the samples being observed should not differ from the structures naturally occurring in biological organisms, which rules out the use of aggressive procedures and reagents. Although it revolutionized the natural sciences, the classical optical microscope is clearly insufficient today. Due to the wavelike nature of light, an optical microscope does not allow imaging structures smaller than about 250 nanometers. As a result, objects closer to each other than half the wavelength of light (which is about 250 nm for green light) cannot be discerned. This phenomenon, known as the diffraction limit, is one of the main obstacles in observing the tiniest biological structures that scientists have long attempted to overcome. Electron microscopes provide orders of magnitude better resolution but only allow the examination of inanimate objects, which must be placed in a vacuum and bombarded by an electron beam. For this reason, electron microscopy cannot be used for studying living organisms and the natural processes occurring in them. This is where fluorescence microscopy steps in, hence the rapid development of super-resolution fluorescence microscopy as a field of physical sciences and the two Nobel Prizes already awarded for related researchin 2008 and 2014.

Nowadays several techniques of fluorescence microscopy are available, and some of them have become widespread in biological imaging. Some methods, such as PALM, STORM, or STED microscopy, are characterized by an ultra-high resolution and allow discerning objects located just a dozen or so nanometers from each other. However, these techniques require long exposure times and a complex procedure of biological specimen preparation. Other techniques, such as SIM or ISM microscopy, are easy to use, but offer a very limited resolution improvement, allowing researchers to identify structures only half the size of the diffraction limit.

Aleksandra Sroda, Adrian Makowski, and Dr. Radek Lapkiewicz from the Quantum Optics Lab at the Faculty of Physics of the University of Warsaw, in cooperation with professor Dan Oron's team from the Weizmann Institute of Science in Israel, have introduced a new technique of super-resolution microscopy, called super-resolution optical fluctuation image scanning microscopy (SOFISM). In SOFISM, the naturally occurring fluctuations in emission intensity of fluorescent markers are used to further enhance the spatial resolution of an image scanning microscope (ISM). ISM, an emerging super-resolution method, has already been implemented in commercial products and proven valuable for the bioimaging community. This implementation is largely because ISM achieves a modest improvement in lateral resolution (x2), with very few changes to the optical setup and without the common handicap of long exposure times. Thus, it enables a natural extension of the capabilities of a standard confocal microscope. ISM uses a confocal microscope in which a single detector is replaced with a detector array. In SOFISM, correlations of intensities detected by multiple detectors are computed. In principle, the measurement of the nth order correlation can lead to a factor of 2n resolution improvement with respect to the diffraction limit. In practice, the resolution achievable for higher-order correlations is limited by the signal-to-noise ratio of the measurements.

"SOFISM is a compromise between ease of use and resolution. We believe that our method will fill the niche between the complex, difficult-to-use techniques, providing very high resolution and the easy-to-use lower-resolution methods. SOFISM does not have a theoretical resolution limit, and in our article, we demonstrate results which are four times better than the diffraction limit. We also show that the SOFISM method has a high potential in the imaging of three-dimensional biological structures," Lapkiewicz said.

Crucially, SOFISM is, in its technical aspects, highly accessible, as it only requires introducing a small modification to the widely-used confocal microscopereplacing its photomultiplier tube with a SPAD array detector. In addition, it is necessary to slightly increase the measurement time and change the data processing procedure. "Until recently, SPAD array detectors were expensive and their specifications were not sufficient for correlation-based microscopy. This situation has recently changed. The new SPAD detectors introduced last year removed both the technological and price-related barriers. This makes us think that fluorescence microscopy techniques such as SOFISM might, in a few years' time, become widely used in the field of microscopic examination," stressed Lapkiewicz.

- This press release was originally published on theUniversity of Warsaw's Faculty of Physics website

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SFARI | New collaboration between SFARI and Nancy Lurie Marks Family Foundation will generate hundreds of iPSC lines for autism research – SFARI News

The Simons Foundation Autism Research Initiative (SFARI) and the Nancy Lurie Marks Family Foundation (NLMFF) are pleased to announce that they joined efforts to generate induced pluripotent stem cells (iPSCs) from blood samples of participants in Simons Searchlight.

With an investment of $450,000 from each organization, SFARI and NLMFF intend to generate iPSCs from 100 individuals over the next year. They plan to possibly generate another 100 iPSCs during a second year of the collaboration. iPSCs will be generated by the New York Stem Cell Foundation (NYSCF) and stored in the SFARI biorepository at Infinite Biologics. Samples will be available for request by researchers worldwide through SFARI Base for a nominal fee.

The first batch of about 30 iPSC lines is estimated to be available in early 2021. It will include lines from individuals with genetic variants in six high-confidence autism risk genes (DYRK1A, GRIN2B, HNRNPH2, SCN2A, SETBP1 and SYNGAP1). SFARI currently estimates that batches of ~ 3050 iPSC lines will become available every three months, following the first batch. These new iPSC lines will complement the existing SFARI collection of iPSCs that have been previously generated from Simons Simplex Collection and Simons Searchlight participants.

With the advent of high-throughput methods that enable well-controlled, quantitative analysis on a large number of samples in parallel1, iPSCs derived from individuals with genetic changes have become valuable tools for biomedical research. This is especially important for studying developmental brain conditions, where access to tissue of the affected organ, the brain, is only possible postmortem.

Due to the remarkable progress in technologies, iPSCs can be differentiated into many different cell types, including neurons and glia2-5, or grown into brain organoids6. By creating a centralized iPSC resource, SFARI and the NLMFF hope to reduce some of the experimental variability introduced when using iPSCs from different providers and often created by using different somatic source cell types or reprogramming methods.

Simons Searchlight provides researchers with clinical data and biospecimens of individuals who are carriers of rare recurrent genetic changes that greatly increase the risk of autism spectrum disorder (ASD) or related neurodevelopmental disorders. Given that the individual genetic events are rare, the data and biospecimens are difficult and costly for any individual laboratory to collect. Likewise, the generation of iPSCs is a highly specialized, lengthy and expensive process. By centralizing the generation of iPSCs derived from Simons Searchlight participants, SFARI and NLMFF will save researchers time and money and will create a technically homogenous resource intended to accelerate research progress. The extensive clinical and phenotypic data associated with the iPSCs lines will also be available through SFARI Base.

iPSCs are a powerful tool to advance our knowledge of autism biology, says SFARI senior scientist Julia Sommer. It is our hope that the generation of these lines will speed up researchon the many genetic changes associated with ASD and their impact on brain development and function.

The iPSCs will be derived from proband peripheral blood mononuclear cells (PBMCs)7 by Sendai virus delivery of reprogramming factors at the NYSCF. Detailed quality control (QC) data (including but not limited to karyotype and pluripotency analysis) will be available on each line. As the reprogramming is organized in batches and it takes six to nine months to generate a fully QCed iPSC line, iPSC lines for the different genetic conditions selected from Simons Searchlight will become available in batches during the next one to two years. At the moment, there are no plans to create iPSCs from the probands family members. However, we are considering the generation of isogenic controls for select samples, either by rescuing mutations in samples from individuals with genetic changes or by introducing common mutations in a well characterized control iPSC line.

To stay up-to-date on readily available iPSCs, please visit SFARI iPS cell models resource page. Requests to order cell lines can be made through SFARI Base.

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SFARI | New collaboration between SFARI and Nancy Lurie Marks Family Foundation will generate hundreds of iPSC lines for autism research - SFARI News

Five Indian American Researchers Named Among NIH 2020 New Innovator Awardees – India West

Five Indian American researchers and one Bangladeshi-American have been named among the 2020 Directors New Innovator Award recipients by the National Institutes of Health.

Among the recipients are Anindita Basu, Subhamoy Dasgupta, Deeptankar DeMazumder, Siddhartha Jaiswal, Shruti Naik, and Mekhail Anwar, according to the NIH website.

Basu, of the University of Chicago, was selected for the project, Profiling Transcriptional Heterogeneity in Microbial Cells at Single Cell Resolution and High-Throughput Using Droplet Microfluidics.

The Indian American is an assistant professor in genetic medicine at the University of Chicago and leads a multi-disciplinary research group that uses genomics, microfluidics, imaging and nano/bio-materials to develop new tools to aid in diagnosis and treatment of disease.

Basu obtained a B.S. in physics and computer engineering at the University of Arkansas, Ph.D. in soft matter physics at University of Pennsylvania, followed by post-doctoral studies in applied physics, molecular biology and bioinformatics at Harvard University and Broad Institute.

Her lab applies high-throughput single-cell and single-nucleus RNA-seq to map cell types and their function in different organs and organisms, using Drop-seq and DroNc-seq that Basu co-invented during her post-doctoral work.

Dasgupta is with the Roswell Park Comprehensive Cancer Center and was named for his project, Decoding the Nuclear Metabolic Processes Regulating Gene Transcription.

Dasgupta is an assistant professor in the Department of Cell Stress Biology at Roswell Park Comprehensive Cancer Center. He earned his B.S. from Bangalore University and M.S. in biochemistry from Banaras Hindu University, India before receiving his Ph.D. in biomedical sciences from University of North Texas Health Science Center at Fort Worth, where, as a Department of Defense predoctoral fellow, he characterized the functions of a novel gene MIEN1 in tumor progression and metastasis.

He then joined the laboratory of Bert W. O'Malley, M.D. at Baylor College of Medicine, where he studied the functions of transcriptional coregulators in tumor cell adaptation and survival, as a Susan G. Komen postdoctoral fellow.

DeMazumder, of the University of Cincinnati College of Medicine, was chosen for the project, Eavesdropping on Heart-Brain Conversations During Sleep for Early Detection and Prevention of Fatal Cardiovascular Disease.

DeMazumder joined the University of Cincinnati in 2017 as assistant professor of medicine, director of the Artificial Intelligence Center of Excellence and a Clinical Cardiac Electrophysiologist after completing his doctorate at SUNY Stony Brook in Synaptic Electrophysiology, a medical degree at Medical College of Virginia-Virginia Commonwealth University, internship at Mount Sinai and residency at University of Virginia in Internal Medicine, and clinical and research fellowships at Johns Hopkins University.

His longstanding goals are to transform clinical observations into testable research hypotheses, translate basic research findings into medical advances, and evaluate personalized treatment protocols in rigorous clinical trials, while caring for patients with heart rhythm disorders and improving their quality of life.

Jaiswal, of Stanford University, was named for his project, Clonal Hematopoiesis in Human Aging and Disease.

Jaiswal is an investigator at Stanford University in the Department of Pathology, where his lab focuses on understanding the biology of the aging hematopoietic system.

As a post-doctoral fellow, he identified a common, pre-malignant state for blood cancers by reanalysis of large sequencing datasets.

This condition, termed "clonal hematopoiesis, is characterized by the presence of stem cell clones harboring certain somatic mutations, primarily in genes involved in epigenetic regulation of hematopoiesis.

Clonal hematopoiesis is prevalent in the aging population and increases the risk of not only blood cancer, but also cardiovascular disease and overall mortality. Understanding the biology of these mutations and how they contribute to the development of cancer and other age-related diseases is the current focus of work in the lab.

Naik, of New York University School of Medicine, was named for her project, Decoding Microbe-Epithelial Stem Cell Interactions in Health and Disease.

Naik is an assistant professor at New York University School of Medicine. She received her doctorate in Immunology from the University of Pennsylvania-National Institutes of Health Graduate Partnership Program.

There she discovered that normal bacteria living on our skin, known as the commensal microbiota, educate the immune system and help protect us from harmful pathogens.

As a Damon Runyon Fellow at the Rockefeller University, Naik found that epithelial stem cells can harbor a memory of inflammation which boosts their regenerative abilities and established a new paradigm in inflammatory memory, her bio states.

The Naik lab studies the dynamic interactions between immune cells, epithelial stem cells, and microbes with a focus on 3 major areas of research: Tissue regeneration and cancer, host-microbe interactions, and early in life immunity.

Anwar, of U.C. San Francisco, was named for his project, Implantable Nanophotonic Sensors forIn VivoImmunoresponse.

Anwar, whose father is from Bangladesh, is a physician-scientist at UCSF, where he is an associate professor in the Department of Radiation Oncology. Driven by the challenges his patients face when fighting cancer specifically addressing the vast heterogeneity in treatment response by identifying the optimal treatment to pair with each patients unique biology he leads a laboratory focused on developing integrated circuits (or computer chips) forin vivocancer sensing.

After completing his bachelors in physics at U.C. Berkeley, where he was awarded the University Medal, he received his medical degree at UCSF, and doctorate in electrical engineering and computer science from the Massachusetts Institute of Technology where his research focused on using micro-fabricated devices for biological detection.

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Five Indian American Researchers Named Among NIH 2020 New Innovator Awardees - India West

Stem Cell Therapy Market 2020-2026 | XX% CAGR Projection Over the Next Five Years, Predicts Market Research Future with Market Size & Growth Key…

Stem Cell Therapy Market report would come handy to understand the competitors in the market and give an insight into sales, volumes, revenues in the Stem Cell Therapy Industry & will also assists in making strategic decisions. The report also helps to decide corporate product & marketing strategies. It reduces the risks involved in making decisions as well as strategies for companies and individuals interested in the Stem Cell Therapy industry. Both established and new players in Stem Cell Therapy industries can use the report to understand the Stem Cell Therapy market.

In Global Market, the Following Companies Are Covered:

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Analysis of the Market:

Stem-cell therapy is the use of stem cells to treat or prevent a disease or condition. Bone marrow transplant is the most widely used stem-cell therapy, but some therapies derived from umbilical cord blood are also in use.

In the last several years, global stem cell therapy market developed fast at a average growth rate of 46.81%.

Market Analysis and Insights: Global Stem Cell Therapy Market

In 2019, the global Stem Cell Therapy market size was USD 403.6 million and it is expected to reach USD 1439.9 million by the end of 2026, with a CAGR of 19.7% during 2021-2026.

Global Stem Cell Therapy Scope and Market Size

Stem Cell Therapy market is segmented by Type, and by Application. Players, stakeholders, and other participants in the global Stem Cell Therapy market will be able to gain the upper hand as they use the report as a powerful resource. The segmental analysis focuses on revenue and forecast by Type and by Application in terms of revenue and forecast for the period 2015-2026.

Segment by Type, the Stem Cell Therapy market is segmented into Autologous, Allogeneic, etc.

Segment by Application, the Stem Cell Therapy market is segmented into Musculoskeletal Disorder, Wounds & Injuries, Cornea, Cardiovascular Diseases, Others, etc.

Regional and Country-level Analysis

The Stem Cell Therapy market is analysed and market size information is provided by regions (countries).

The key regions covered in the Stem Cell Therapy market report are North America, Europe, China, Japan, Southeast Asia, India and Central & South America, etc.

The report includes country-wise and region-wise market size for the period 2015-2026. It also includes market size and forecast by Type, and by Application segment in terms of revenue for the period 2015-2026.

Competitive Landscape and Stem Cell Therapy Market Share Analysis

Stem Cell Therapy market competitive landscape provides details and data information by vendors. The report offers comprehensive analysis and accurate statistics on revenue by the player for the period 2015-2020. It also offers detailed analysis supported by reliable statistics on revenue (global and regional level) by player for the period 2015-2020. Details included are company description, major business, company total revenue and the revenue generated in Stem Cell Therapy business, the date to enter into the Stem Cell Therapy market, Stem Cell Therapy product introduction, recent developments, etc.

The major vendors include Osiris Therapeutics, NuVasive, Chiesi Pharmaceuticals, JCR Pharmaceutical, Pharmicell, Medi-post, Anterogen, Molmed, Takeda (TiGenix), etc.

This report focuses on the global Stem Cell Therapy status, future forecast, growth opportunity, key market and key players. The study objectives are to present the Stem Cell Therapy development in North America, Europe, China, Japan, Southeast Asia, India and Central & South America.

Stem Cell Therapy Market Breakdown by Types:

Stem Cell Therapy Market Breakdown by Application:

Critical highlights covered in the Global Stem Cell Therapy market include:

The information available in the Stem Cell Therapy Market report is segmented for proper understanding. The Table of contents contains Market outline, Market characteristics, Market segmentation analysis, Market sizing, customer landscape & Regional landscape. For further improving the understand ability various exhibits (Tabular Data & Pie Charts) has also been used in the Stem Cell Therapy Market report.

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SMAR1 repression by pluripotency factors and consequent chemoresistance in breast cancer stem-like cells is reversed by aspirin – Science

RESULTS SMAR1 expression declines with progression in breast cancers

When we evaluated the expression of SMAR1 in various cancers by screening in silico GEPIA (Gene Expression Profiling Interactive Analysis) database, SMAR1 was found to be reduced in the tumor tissues of several cancers compared to counterpart normal tissues (fig. S1A) and, in the Oncomine database, SMAR1 was substantially reduced in invasive breast carcinomas (fig. S1B). We then evaluated the correlation between SMAR1 mRNA levels with disease prognosis in breast cancer patients by Kaplan-Meier (Km) plots using the publicly available Km plotter database (https://kmplot.com/analysis). High SMAR1 expression correlated with longer RFS (Fig. 1A) and with overall survival (OS) and progression-free survival (PFS) (fig. S1C). However, the P values for OS and PFS were not as substantial as RFS, which could be due to the smaller sample sizes for both OS (397 subjects) and PFS (165 subjects) as compared to that of RFS (1764 subjects). Furthermore, immunofluorescence and Western blotting analyses also revealed reduced SMAR1 expression in stage III as compared to stage II breast tumor tissues (Fig. 1, B and C). These results indicate that SMAR1 expression decreases with advancement of breast cancer.

(A) Kaplan-Meier analysis plot (Km plot) representing correlation of SMAR1 expression with relapse-free survival (RFS) of patients with breast cancer. The intrinsic subtype has been kept as follows: all; the hazard ratios (HR) with 95% confidence intervals and P value are noted (n = 1764). (B) Tissue immunofluorescence (B) and Western blotting (C) for the expression of SMAR1 (red) in stage II versus stage III human tumor samples (n = 5 patients for each stage). Nuclei were stained with DAPI. Scale bars, 200 m; magnification, 10. The graph in (B) shows the corrected total cell fluorescence (CTCF) value of SMAR1 between stages II and III in samples, as calculated using ImageJ. (n = 5 for each stage). (D) Bar diagram depicting relative mRNA level of SMAR1 in mouse tumor tissues on days 7, 14, and 21 as calculated by real-time PCR (n = 3 mice in each group). (E) Bar diagram depicting percentage of SMAR1+ cells on days 7, 14, and 21 mouse tumor tissues as detected by flow cytometry (n = 3 in each group). (F and G) Representative tissue immunofluorescence (F) and immunohistochemistry (G) images staining for SMAR1 in mouse tumor tissues on days 7 and 21 (n = 3 in each group). Scale bars, (F) 200 m; magnification, 10; (G) 1 mm, magnification 20. (H) Bar diagram depicting the percentage of CSCs (% each of CD44+/CD24, Oct4+, and Sox2+ cells) in mouse tumor tissues on days 7, 14, and 21, respectively, as determined by flow cytometry (n = 3 in each group). (I) Correlation plot depicting the relationship between % CSCs (CD44+/CD24) and % SMAR1+ cells in mouse tumor tissues on days 7, 14, and 21. R is the correlation coefficient. (J) Correlation plot between SMAR1 and ALDH1 obtained from the R2 database, specifically the tumor breast invasive carcinoma-TCGA-1097 dataset. (K) t-SNE plot of SMAR1 and ALDH1 obtained from the R2 database (using tumor breast invasive carcinoma-TCGA-1097 dataset). (L) Scatter plot assessing relative SMAR1 mRNA expression in flow cytometrically sorted pure NSCCs and CSCs from human breast tumor samples (n = 4). (M) Representative Western blot assessing SMAR1 expression in adherent cells and primary spheres of MCF-7, MDA-MB-468, and MDA-MB-231 cell lines (n = 3). (N) Immunofluorescence images of SMAR1 expression in adherent cells and primary spheres of the MCF-7 and MDA-MB-468 lines. Scale bars, 100 m; magnification, 20 (n = 3). (O) From left: % SMAR1+ cells (left); mean fluorescence intensity (MFI) of Oct4, Sox2, and Nanog (center); and % cytokeratin 18 (CK18)+ cells (right) in adherent cells, secondary spheres, and differentiated (diff.) spheres of MCF-7 cell line (n = 3 to 5 experiments). Data in (A) to (O) are mean SD or representative of three independent experiments unless otherwise noted. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001 by unpaired t test (B), Mann-Whitney U test (C), Kruskal-Wallis test (D), two-way analysis of variance (ANOVA) (L), or ordinary one-way ANOVA (E, H, and O).

Next, we orthotopically inoculated 4T1 tumor cells in the mammary fat pad of female BALB/c mice, and tumor tissues were collected on the 7th, 14th, and 21st days thereafter. Examination of SMAR1 expression at these time points of progressive tumor growth revealed a stark decrease in SMAR1 expression with increased tumor burden in mice (Fig. 1, D to G). These results together indicate a negative association of SMAR1 with tumor progression and a positive connection with RFS.

Given our findings that SMAR1 expression negatively correlates with disease progression in breast cancer, and previous reports from others and our laboratory (3, 15) demonstrating positive correlation of CSCs with breast cancer progression and therapeutic resistance, we postulated a possible inverse relationship between SMAR1 and CSCs.

To validate our hypothesis, tumor tissues were collected from BALB/c mice at weekly time intervals (days 7, 14, and 21), and the cells were harvested and subjected to flow cytometry. Our flow cytometric analysis revealed gradual increase in the percentage of CD44+/24/low CSCs (16) in total tumor mass from days 7 to 21 (Fig. 1H) with significant decrease in SMAR1 expression level (Fig. 1D). In addition, when the percentage of SMAR1+ cells was plotted against the percentage of CD44+/24/low CSCs present in the total tumor mass of days 7, 14, and 21, respectively, a significant, negative correlation between SMAR1 and the CSC population was observed (Fig. 1I). An increase in the population of Oct4+ and Sox2+ cells were also marked by flow cytometry in the tumor mass from days 7 to 21 (Fig. 1H) that comes in line with our previous CD44+/24/low data. This negative correlation of SMAR1 with CSC content was further supported by in silico correlation plot from two databasesthe GEPIA database and the R2 Genomics Analysis and Visualization Platform database (fig. S1D and Fig. 1J) and t-SNE (t-distributed stochastic neighbor embedding) plots from the R2 database (Fig. 1K)where in breast cancer, SMAR1 had a significantly negative correlation with ALDH1, a CSC marker (17, 18). Next, flow cytometry gating of CSCs (CD44+/24/low) and nonstem cancer cells (NSCCs; CD44+/24+, CD44/24, and CD44/24+) from tumor tissues of BALB/c mice revealed a lower expression of SMAR1 in CSCs as compared to NSCCs (fig. S1E). Together, these findings support our hypothesis that SMAR1 may be attenuated in CSCs.

To further corroborate these results, CSCs and NSCCs were isolated from breast cancer patient tissues using flow cytometry, and the expression of SMAR1 was detected by semiquantitative polymerase chain reaction (PCR). The results indicated lower expression of SMAR1 in patient-derived CSCs than in their nonstem counterpart (Fig. 1L).

To confirm our hypothesis in vitro, breast cancer cell lines MCF-7, MDA-MB-468, and MDA-MB-231 were cultured in serum-free, growth factorsupplemented media on ultralow attachment surface for 6 to 7 days to obtain primary spheres, which was then cultured in serum-free conditions for an additional 7 to 8 days to acquire secondary spheres to further enrich the CSC population. When characterized for pluripotency markers in comparison to adherent cells, the primary spheres showed increased abundance of four core stemness markers: Oct4, Sox2, Nanog, and ALDH1 (fig. S1F). Secondary spheres, which displayed more CSCs (CD44+/24/low, Oct4+, and Sox2+) than did primary spheres (fig. S1G), had additionally greater expression of ALDH1 (fig. S1G). Pure CSCs, which were sorted out from secondary spheres as CD44+/24/low, also displayed significantly higher ALDH1 levels than did NSCCs (fig. S1H).

Western blot and immunofluorescence analyses showed a significant decrease in SMAR1 expression in primary spheres derived from the MCF-7, MDA-MB-468, and MDA-MB-231 cell lines compared to their respective cultures of adherent cells (Fig. 1, M and N). SMAR1 expression further declined in secondary spheres (fig. S1, I and J). This correlates with our hypothesis that SMAR1 decreases with increasing stemness. When these secondary spheres were redifferentiated by culturing them in 10% serum-containing complete media, an increase in the percentage of SMAR1+ cells was observed (Fig. 1O, left), coincident with significantly decreased expression of Oct4, Sox2, and Nanog (Fig. 1O, middle) and restored/augmented expression of the differentiation marker cytokeratin 18 (CK18) (Fig. 1O, right).

We also further characterized the CSCs by comparing different cell cycle stages of adherent cells with secondary spheres as a measure of cellular quiescence, a signature of CSCs. It is well established that CSCs are maintained in a poised, quiescent state characterized by slow cell cycling that confers them resistance to cytotoxic drugs (19, 20). Supporting our hypothesis, secondary spheres showed significantly higher percentages of G0-G1 population than the adherent cells (fig. S2A). When NSCCs were transfected with Oct4 and Sox2 complementary DNA (cDNA) plasmids, there was an enhancement of the G0-G1 population (fig. S2B), indicating enrichment of CSC-like properties in them and thus supporting the contribution of these two pluripotency markers in the maintenance of stemness.

We next transfected control or Oct4 and Sox2 cDNA into MDA-MB-468 cells and, 24 hours afterward, performed sphere formation assays. On the 10th day of sphere formation, the transfected set showed greater quiescence per measurement of the G0-G1 cell populations (fig. S2C). The G0-G1 population of the control set gradually increased over 12th to14th day, and the control set reached about the same level of quiescence as the transfected set on the 14th day (which was also the time required for secondary sphere formation) (fig. S2C), indicating that Oct4 and Sox2 transfection increased stemness character, thus expediting sphere formation.

Apart from these, to further validate the CSCs, we also evaluated the level of reactive oxygen species (ROS) in adherent cells versus secondary spheres by 2,7dichlorofluorescein diacetate (DCFDA) assay, as it is already well reported by various previous studies that CSCs display low ROS level (21, 22). Our results showed significantly lower expression of ROS in secondary spheres as compared to the adherent cells (fig. S2D).

Furthermore, we compared the tumor formation potential of MDA-MB-468 cells and secondary spheres in BALB/c athymic nude mice. In line with the reports that CSCs have higher ability than NSCCs in forming a tumor (23), after 30 days of tumor inoculation, mice inoculated with secondary spheres showed greater tumor volume and weight than the mice inoculated with cells (fig. S2E). Together, these results provide support of the stem-like nature of the cells used and further validate our hypothesis that SMAR1 is repressed in breast CSCs.

The above results showing the low expression of SMAR1 in CSCs raised the possibility of SMAR1 having an anti-CSC role. Previous findings from our group and others have established that the CSCs are resistant to conventional chemotherapy (3). Considering all these, we next aimed at exploring the role of SMAR1, if any, in drug resistance of CSCs.

Although the chemotherapeutic drug doxorubicin failed to induce apoptosis in breast cancer stem cellenriched secondary spheres derived from MCF-7 and MDA-MB-468 cell line, it could do so in SMAR1-overexpressed ones (Fig. 2A). This led us to hypothesize that SMAR1 might have the ability to sensitize CSCs by altering their chemo-resistance. To confirm our hypothesis, we transfected the secondary spheres derived from MCF-7, MDA-MB-468, and MDA-MB-231 cell lines, with SMAR1 overexpression plasmid (SMAR1 cDNA). Overexpression of SMAR1 in these spheres led to a significant decrease in both mRNA (Fig. 2B) and protein levels (Fig. 2C) of ATP-binding cassette super-family G member 2 (ABCG2), one of the most crucial drivers of breast CSC drug resistance. However, there was no significant change in the expression levels of multidrug resistance-associated protein 1 (MRP1) and multidrug resistance protein 1 (MDR1) (fig. S3A), two other important drug resistance pumps following SMAR1 overexpression. Likewise, augmentation of SMAR1 also led to a significant decrease in the ABCG2+ cell population in the secondary spheres (fig. S3B). In addition, when the pure CSCs (sorted as CD44+/24/low from secondary spheres) were transfected with SMAR1 cDNA, the ABCG2 expression within them was considerably declined (fig. S3C).

(A) Bar diagram depicting percentage of apoptosis after SMAR1 cDNA transfection and doxorubicin treatment in MCF-7 and MDA-MB-468 secondary spheres as analyzed by flow cytometry (n = 3 biological replicates). (B) RelativeABCG2 mRNA expression quantified by real-time PCR in MCF-7, MDA-MB-468, and MDA-MB-231 secondary spheres after SMAR1 cDNA transfection (n = 3 biological replicates). (C) Western blot displaying ABCG2 expression after SMAR1 cDNA transfection in MCF-7, MDA-MB-231, and MDA-MB-468 secondary spheres (n = 3 independent experiments). Transfection efficiency was determined also by Western blotting for SMAR1 and GFP. (D) The relative ABCG2 mRNA expression was determined after knock-down of SMAR1 using shRNA in MCF-7, MDA-MB-468, and MDA-MB-231 adherent cells by real-time PCR (n = 3 biological replicates). (E) Western blot depicting changes in ABCG2 level in MCF-7 and MDA-MB-468 adherent cells after SMAR1 shRNA transfection (n = 3 independent experiments). Knockdown efficiency of SMAR1 shRNA is shown. (F) t-SNE plot of SMAR1 and ABCG2 obtained from R2 database (using the tumor breast invasive carcinoma-TCGA-1097 dataset). (G) Correlation plot between SMAR1 and ABCG2 as obtained from R2 database using the same dataset; R = 0.252, P = 2.09 1017. (H) Bar diagram depicting the fold change of SMAR1 binding on ABCG2 promoter as determined by ChIP assay and real-time PCR in MCF-7, MDA-MB-468, and MDA-MB-231 adherent cells and secondary spheres (n = 3 biological replicates). (I) Semiquantitative PCR depicting the changes in binding of SMAR1 on ABCG2 promoter after SMAR1 cDNA transfection in MCF-7 secondary spheres, as determined by ChIP assay. (n = 3 biological replicates). (J) In silico docking of SMAR1 on the target region of ABCG2 promoter by HDOCK. Data are mean SD or representative of three independent experiments unless otherwise noted. ***P < 0.001 and ****P < 0.0001 by ordinary one-way ANOVA (A) or by Mann-Whitney U test (B, D, and H).

In contrast, knocking down SMAR1 expression in these cell lines using short hairpin RNA (shRNA) led to enhancement of ABCG2 expression to a heightened extent as determined by real-time PCR (Fig. 2D) and Western blot (Fig. 2E), but no change was observed for MRP1 and MDR1 (fig. S3D). This indicates that SMAR1 may be acting as an inhibitor of ABCG2 but not of MRP1 and MDR1. When we screened the secondary spheres of MCF-7 and MDA-MB-468 for the expression of these three drug resistance pumps, the secondary spheres derived from both these cell lines showed a significantly higher percentage of ABCG2+ cell population than MRP1 and MDR1 (fig. S3E), indicating that ABCG2 might serve as the most crucial contributor of drug resistance in breast cancer. When the expression of ABCG2 was knocked down in the secondary spheres, a significant rise in apoptosis was seen after doxorubicin treatment (fig. S3F), indicating the significance of ABCG2 in breast cancer stem cell chemoresistance and the hint that SMAR1 might serve as a repressor of ABCG2 fascinated us. Moreover, comparing the in silico R2 databasederived t-SNE plot for ABCG2 with the previously derived SMAR1 t-SNE plot (as shown in Fig. 1J) showed that the patients showing higher expression of SMAR1 displayed lower ABCG2 level, which further strengthened our hypothesis (Fig. 2F). In addition, in silico correlation plot of SMAR1 and ABCG2 displayed a significant negative correlation (R = 0.252; Fig. 2G).

Next, in an effort to identify a potential binding site of SMAR1 on ABCG2 promoter, we obtained 2000 to +100base pair (bp)long ABCG2 promoter sequence from the eukaryotic promoter database and scrutinized it using the Genomatix SMARTest (www.genomatix.de). A 405-bp spanning putative S/MAR was identified at 1149 to 745 upstream of the transcription start site on ABCG2 promoter. Overlapping primer pairs were designed against the predicted S/MAR, and chromatin immunoprecipitation (ChIP) assay was performed to validate the binding of SMAR1 on this putative S/MAR. The results revealed SMAR1 binding on the ABCG2 promoter (Fig. 2H) at the site of primer pair 2 in all the three cell lines MCF-7, MDA-MB-231, and MDA-MB-468. Moreover, the binding of SMAR1 was significantly lesser in the secondary spheres than their corresponding adherent cell lines (Fig. 2H). In addition, when these secondary spheres were transfected with the SMAR1 overexpression plasmid, a significant rise in the SMAR1 binding to the given region on ABCG2 promoter was recorded (Fig. 2I). These data come in line with our previous observation that rise in SMAR1 expression leads to significant attenuation of ABCG2 expression as described in Fig. 2 (B and C). We also performed in silico docking experiments to visualize the binding of SMAR1 on ABCG2 promoter using HDOCK server. The docking results showed that SMAR1 binds to the ABCG2 promoter using the interactions with DNA backbone, although it shows preference to the major groove of the DNA (Fig. 2J and fig. S3G). These results validated that SMAR1 represses drug efflux pump ABCG2, thus raising the possibility of sensitizing drug-resistant CSCs by augmenting SMAR1.

Reports indicate that SMAR1 recruits various histone deacetylases (HDACs) to the promoters of target genes to facilitate histone deacetylation and chromatin condensation which ultimately leads to the repression of the target gene (8, 24). To unveil the mechanism underlying SMAR1-induced repression of ABCG2, we subsequently aimed at identifying the type of HDAC, if any, recruited by SMAR1 on ABCG2 promoter. To that end, ChIP assays were performed using the major class I HDACs, among which HDAC2 was found to be binding along with SMAR1 on the given region of ABCG2 promoter. Furthermore, when these secondary spheres were transfected with SMAR1 overexpression construct, the binding of HDAC2 was significantly enhanced, suggesting that SMAR1 recruits HDAC2 to the promoter (Fig. 3A). Protein coimmunoprecipitation (CoIP) assay further proved physical interaction between SMAR1 and HDAC2 (Fig. 3B), and the association increased when SMAR1 was overexpressed in the secondary spheres, hence supporting the above findings (Fig. 3B). One of the major histone moieties deacetylated by HDACs is H3 lysine 9 (H3K9), which otherwise remains acetylated in active chromatins and deacetylation of which leads to chromatin condensation and repression of transcription (25). The S/MAR region of ABCG2 promoter showed a higher extent of H3K9 acetylation in secondary spheres derived from both MCF-7 and MDA-MB-468 cell lines than their adherent counterparts (Fig. 3C), indicating a more active chromatin signature of ABCG2 in CSCs that confer them high chemotherapy resistance. Transfection of SMAR1 cDNA in these secondary spheres led to a significant decline in H3K9 acetylation indicating possible deacetylation of the moiety by HDAC2 due to presence of SMAR1 (Fig. 3D). Treating the SMAR1 cDNAtransfected secondary spheres with potent class I HDAC inhibitors, either trichostatin A (TSA) (26) or sodium butyrate (NaBu) (27), rescued H3K9 from deacetylation, thereby resulting in an increase in the acetylation of H3K9 in these HDAC inhibitortreated SMAR-overexpressed secondary spheres than the untreated SMAR1-overexpressed ones (Fig. 3E).

(A) Bar diagram depicting the relative binding of HDAC2 on SMAR1 binding region of ABCG2 promoter after SMAR1 cDNA transfection in MCF-7 and MDA-MB-468 secondary spheres, as determined by ChIP assay and real-time PCR (left). Semiquantitative PCR data of HDAC2 binding on ABCG2 promoter in the same sample set (middle). The transfection efficiency of SMAR1 cDNA plasmid (right) (n = 3 biological replicates). (B) Coimmunoprecipitation assay showing physical association of SMAR1 with HDAC2. SMAR1 was immunoprecipitated from cell lysates of control and SMAR1 cDNA transfected MCF-7 and MDA-MB-468 secondary spheres. Western blot was done to detect both SMAR1 and HDAC2. Input represents whole cell lysates, (n = 3 independent experiments). (C) ChIP assay followed by real-time PCR was performed to determine the acetylation of H3K9 (AcH3K9) in the SMAR1 binding region of ABCG2 promoter in MCF-7 and MDA-MB-468 adherent cells and secondary spheres (n = 3 biological replicates). (D) ChIP assay followed by real-time PCR was performed to determine the change in AcH3K9 level on SMAR1 binding region of ABCG2 promoter after SMAR1 cDNA transfection in MCF-7 and MDA-MB-468 secondary spheres (n = 3 biological replicates). (E) Real-time PCR was performed to detect the fold change of AcH3K9 ChIP on ABCG2 promoter after SMAR1 cDNA transfection and trichostatin A (TSA)/sodium butyrate (NaBu) treatment in MCF-7 secondary spheres (n = 3 biological replicates). (F) Bar diagram depicting relative fold change of AcH3K9 ChIP on ABCG2 promoter after SMAR1 cDNA transfection, SMAR1 cDNA + HDAC2 siRNA transfection, and SMAR1 cDNA transfection + romidepsin treatment in MCF-7 secondary spheres as detected by real-time PCR (n = 3 biological replicates). (G) Western blot assessing the changes in expression of ABCG2 and AcH3K9 in control, SMAR1 cDNAtransfected, SMAR1 cDNA + HDAC2 siRNAtransfected, and SMAR1 cDNAtransfected + romidepsin-treated MCF-7 secondary spheres (n = 3 independent experiments). (H) Western blot data showing changes ABCG2 and AcH3K9 level in MCF-7 and MDA-MB-468 secondary spheres after SMAR1 cDNA transfection and TSA treatment (n = 3 independent experiments). (I) In silico docking of SMAR1-HDAC2 on target region of ABCG2 promoter. (J) Diagrammatic representation of ABCG2 promoter deacetylation via HDAC2 recruitment by SMAR1. Data are mean SD or representative of three independent experiments unless otherwise noted. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001 by Mann-Whitney U test (A, C, and D) or by Kruskal-Wallis test followed by Dunns multiple comparisons post hoc test (E and F).

Moreover, we used HDAC2 small interfering RNA (siRNA) to specifically knock down HDAC2 or used HDAC2 inhibitor romidepsin, which specifically inhibits HDAC2 (and also HDAC1) without affecting other class I HDACs (28, 29) and is reported to be more potent than both TSA and NaBu (30). In line with the data in Fig. 3E, the HDAC2 siRNAtransfected or romidepsin-treated SMAR1-overexpressed secondary spheres showed significantly higher acetylation of H3K9, reconfirming our hypothesis (Fig. 3F and fig. S4A). In HDAC2 siRNAtransfected or romidepsin-treated sets, SMAR1, although overexpressed, failed to repress ABCG2 expression, thus confirming the contribution of HDAC2 in SMAR1-mediated repression of ABCG2 (Fig. 3G and fig. S4A). TSA-treated SMAR1-overexpressed secondary spheres furnished similar result where inhibition of HDAC2 led to failure of ABCG2 repression by SMAR1 (Fig. 3H). Furthermore, the level of acetylated H3K9 (AcH3K9) was higher in HDAC2-inhibited SMAR1-overexpressed spheres than the untreated SMAR1-overexpressed ones (Fig. 3, G and H).

The in silico docking (Fig. 3I) of SMAR1 with HDAC2 revealed that HDAC2 docks onto SMAR1 majorly using its N-terminal domain. The major interaction with the ABCG2 promoter is caused by SMAR1 protein by its residues 327 to 333. Residues 282 to 286 and 292 to 293 are buried into the major groove of the promoter showing significant baseamino acid interactions. The results thus far support our hypothesis that SMAR1 uses HDAC2 to repress ABCG2 transcription (Fig. 3J) and suggests that augmenting SMAR1 expression in CSCs may prove to be a CSC-sensitizing approach.

To delineate the mechanism underlying SMAR1 repression in CSCs, we analyzed the SMAR1 promoter for predicted binding sites of various transcription factors. The SMAR1 promoter sequence (2000 to +100 bp) was obtained from the eukaryotic promoter database and scrutinized using the promoter analyzing tool JASPAR (http://jaspar.genereg.net/). The screening revealed a putative Oct4-Sox2 joint binding domain on SMAR1 promoter at 604 to 590 bp with a binding score of 11.785 and relative score 0.844, indicating a strong possibility of binding (Fig. 4A). Given that Oct4 and Sox2 are two of the most crucial drivers of stemness and pluripotency of embryonic stem cells and CSCs (31, 32), and our previous observation that overexpression of Oct4 and Sox2 led to enhanced stemness phenotype and expedited sphere formation of adherent breast cancer cells (fig. S2, B and C), abovementioned prediction indicates that they might be the master contributors toward the reduced expression of SMAR1 in breast CSCs.

(A) Diagrammatic representation of Oct4-Sox2 complex binding on SMAR1 promoter. (B) Bar diagram depicting relative SMAR1 mRNA expression after Oct4 cDNA or Sox2 cDNA transfection in MCF-7, MDA-MB-468, and MDA-MB-231 adherent cells (left). The transfection efficiency of Oct4 cDNA and Sox2 cDNA was checked by real time (n = 3 biological replicates) (middle and right). (C) Western blot assessing the change in expression of SMAR1 in Oct4 cDNA and Sox2 cDNAtransfected MCF-7 adherent cells. (n = 3 independent experiments). Transfection efficiency was determined by Western blot. (D) Western blot depicting the changes in SMAR1 level after Oct4 and Sox2 knockdown using shRNA in MCF-7 secondary spheres. (n = 3 independent experiments) Knockdown efficiency was confirmed also by Western blot. (E) Expression of SMAR1 was assessed by Western blot in control and different treatment conditions such as Oct4 cDNAtransfected, Sox2 cDNAtransfected, Oct4 shRNA + Sox2 cDNAtransfected, Sox2 shRNA + Oct4 cDNAtransfected MCF-7 adherent cells. (n = 3 independent experiments). (F) In silico docking of Oct4-Sox2 complex on target region of SMAR1 promoter. (G) ChIP assay followed by semiquantitative PCR displaying the binding of Oct4 and Sox2 on target region of SMAR1 promoter in MCF-7 secondary spheres (n = 3 biological replicates). (H) ChIP assay depicting the changes in binding of Oct4 and Sox2 on SMAR1 promoter after knockdown of either Oct4 or Sox2 in MCF-7 secondary spheres as determined by real-time PCR (n = 3 biological replicates). The knockdown efficiency of Oct4 and Sox2 shRNA was determined by Western blot (inset). (I) Representative semiquantitative PCR data of the same sample set (n = 3 biological replicates). (J) Diagrammatic representation of SMAR1 repression by Oct4-Sox2 complex. Data are mean SD or representative of three independent experiments unless otherwise mentioned. *P < 0.05, **P < 0.01, and ***P < 0.001 by Mann-Whitney U test [(B), middle, right] or by Kruskal-Wallis test followed by Dunns multiple comparisons post hoc test [(B), left; (H)].

To validate the above indications, first, we transfected MCF-7, MDA-MB-468, and MDA-MB-231 adherent cells with Oct4 and Sox2 cDNA plasmids and examined the expression of SMAR1 by real-time PCR. Overexpression of Oct4 and Sox2 in these cell lines led to significant reduction in SMAR1 mRNA expression, confirming Oct4- and Sox2-dependent repression of SMAR1 at the point of transcription (Fig. 4B). We confirmed a decrease at the protein level as well by Western blotting analysis (Fig. 4C). In contrast, knocking down Oct4 and Sox2 by shRNAs in the secondary spheres resulted in a considerable rise in SMAR1 expression (Fig. 4D). To determine whether Oct4 and Sox2 are individually capable of repressing SMAR1, we knocked down either Oct4 or Sox2 using shRNA while overexpressing the other. In both scenarios (Oct4 shRNA + Sox2 cDNA and Sox2 shRNA + Oct4 cDNA), the decrease in SMAR1 expression was hindered, indicating that both Oct4 and Sox2 are necessary for the inhibition of SMAR1 transcription in breast CSCs (Fig. 4E).

The results, so far, strengthened our hypothesis that CSCs inherently repress SMAR1 expression and that Oct4 and Sox2 serve as the critical inhibitors of SMAR1 expression in CSCs. We next performed in silico docking experiments to visualize the binding of the proposed Oct4-Sox2 complex on the SMAR1 promoter. Docking of Oct4-Sox2 complex with the SMAR1 promoter (Fig. 4F) revealed that Oct4 binds to the minor groove of DNA with residues from 337 to 341 and to major groove with residues from 302 to 307. Sox2 binds to the phosphate backbone of the SMAR1 promoter with its two Lys58 and Lys66 residues. To validate the promoter binding prediction from JASPAR, ChIP assay was performed in MCF-7 secondary spheres with primer pairs designed against the putative Oct4-Sox2 complex binding site on SMAR1 promoter. The result showed binding of both Oct4 and Sox2 on the predicted region of the SMAR1 promoter (Fig. 4G).

Next, to validate whether the formation of Oct4-Sox2 complex is crucial for the transcriptional inhibition of SMAR1, we knocked down Oct4 by shRNA in secondary spheres, which led to significantly reduced binding Sox2 to the predicted site on SMAR1 promoter. Likewise, knocking down Sox2 decreased Oct4 binding to the SMAR1 promoter to a significant extent (Fig. 4, H and I). As mentioned previously, the expression of SMAR1 was greatly enhanced in both the Oct4 shRNA and Sox2 shRNAtransfected sets (Fig. 4D). These results validated the requirement of Oct4-Sox2 complex formation to bind to SMAR1 promoter and repress its transcription. The findings so far support the hypothesis that Oct4 and Sox2, two crucial pluripotency factors, jointly attenuate the expression of SMAR1 in CSCs as an escape strategy against the chemosensitivity role of SMAR1 (Fig. 4J).

Oct4 and Sox2 are reported to recruit various coactivator or corepressor complexes to regulate the expression of their target genes (33, 34). Previous reports have already established the involvement of HDACs and polycomb repressor complexes (PRCs) in Oct4-, Sox2-, and Nanog-mediated gene repression (35, 36). To find the epigenetic modifiers used by Oct4-Sox2 complex to repress SMAR1, we performed ChIP assays using various HDACs and PRC proteins in secondary spheres derived from MCF-7 and MDA-MB-468 cells. Our results revealed the binding of HDAC1 along with Oct4 and Sox2 on the predicted region of the SMAR1 promoter (Fig. 5A). When Oct4 and Sox2 were knocked down, a significant decline in HDAC1 binding to the predicted promoter region was observed (Fig. 5B), indicating that Oct4 and Sox2 may serve as HDAC1 recruiters in the secondary spheres. Similarly, CoIP experiments showed a physical interaction between Oct4, Sox2, and HDAC1 in these secondary spheres (Fig. 5C). As described above, overexpression of Oct4 and Sox2 in the adherent cells leads to a decline in SMAR1 expression (Fig. 4B); however, when these Oct4 + Sox2overexpressed cells were treated with class I HDAC inhibitors TSA or NaBu, Oct4 and Sox2 failed to repress SMAR1 expression (Fig. 5D).

(A) Binding of HDAC1 along with Oct4 and Sox2 on SMAR1 promoter assessed by ChIP and ChIP-re-ChIP assays in MCF-7 and MDA-MB-468 secondary spheres. Primer pair specific for Oct4-Sox2 binding site on SMAR1 promoter was used (n = 3 independent experiments). (B) Bar diagrams depicting changes in binding of HDAC1 on SMAR1 promoter after Oct4 and Sox2 knockdown using shRNA, as determined by ChIP and real-time PCR in MCF-7 secondary spheres (n = 3 biological replicates). Knockdown efficiency of Oct4 and sox2 shRNA was determined using Western blot. Data are mean SD or representative of three independent experiments unless otherwise mentioned. **P < 0.01 and ***P < 0.001 by Kruskal-Wallis test followed by Dunns multiple comparisons post hoc test. (C) CoIP with Western blotting to assess physical association between Oct4, Sox2, and HDAC1 immunoprecipitated from cell lysates of MCF-7 secondary spheres (n = 3 independent experiments). (D) Western blotting to assess SMAR1 expression in MCF7 adherent cells after Oct4 cDNA + Sox2 cDNA transfection and TSA/NaBu treatment. The transfection efficiency of Oct4 cDNA and Sox2 cDNA was confirmed also by Western blot (right) (n = 3 independent experiments). (E) Western blotting to evaluate changes in SMAR1 and AcH3K9 levels in control and various conditions, including Oct4 cDNA + Sox2 cDNAtransfected, Oct4 cDNA + Sox2 cDNA + HDAC1 siRNAtransfected, and Oct4 cDNA + Sox2 cDNAtransfected + romidepsin-treated MCF-7 adherent cells. Knockdown efficiency of HDAC1 siRNA was confirmed also by Western blot (n = 3 independent experiments). (F) ChIP assay followed by semiquantitative PCR was performed to assess the changes in AcH3K9 ChIP on Oct4-Sox2 binding site of SMAR1 promoter after Oct4 or Sox2 knockdown in MCF7 secondary spheres (n = 3 independent experiments). (G) Changes in AcH3K9 ChIP on SMAR1 promoter after Oct4 cDNA + Sox2 cDNA transfection and TSA/NaBu treatment in MCF7 adherent cells (n =3 independent experiments). (H) Changes in AcH3K9 ChIP on Oct4-Sox2 binding site of SMAR1 promoter after Oct4 cDNA + Sox2 cDNA transfection and HDAC1 siRNA/romidepsin treatment in MCF-7 adherent cells (n = 3 independent experiments). (I) Protein complex of Oct4, Sox2, and HDAC1 alone (upper) and bound to the target region of the SMAR1 promoter (lower), as derived from in silico docking models. (J) Diagrammatic representation of SMAR1 repression by promoter deacetylation due to HDAC1 recruitment by Oct4 and Sox2. All blots are representative of three independent experiments unless otherwise noted.

Furthemore, we knocked down HDAC1 using siRNA or inhibited it with romidepsin (which inhibits HDAC1 and HDAC2 with greater potency than either TSA or NaBu, as mentioned above with Fig. 3F) (2830) in the Oct4 + Sox2overexpressed adherent cells. In both the HDAC1 siRNA and romidepsin-treated cells, Oct4 and Sox2 failed to repress SMAR1 expression (Fig. 5E), thus supporting the involvement of HDAC1 in Oct4-Sox2mediated repression of SMAR1.

One of the major histone moieties deacetylated by HDAC1 is H3K9 (37). Knocking down Oct4 and Sox2 in secondary spheres led to a significant rise in H3K9 acetylation on the predicted region of SMAR1 promoter (Fig. 5F and fig. S4B). This corresponds to the augmented expression of SMAR1 after Oct4 and Sox2 knockdown as shown in Fig. 4D. Similarly, overexpression of Oct4 + Sox2 in adherent cells led to a decline in H3K9 acetylation on SMAR1 promoter; however, treating the Oct4 + Sox2overexpressed cells with either TSA or NaBu rescued H3K9 from deacetylation (Fig. 5G). Similarly, knocking down HDAC1 using siRNA or inhibiting HDAC1 by romidepsin in Oct4 + Sox2overexpressed adherent cells led to significant rise in AcH3K9 level on SMAR1 promoter (Fig. 5H and fig. S4C), validating the involvement of HDAC1 in Oct4- and Sox2-mediated deacetylation of H3K9 on SMAR1 promoter and its repression. This corresponds to the heightened AcH3K9 levels in HDAC1 siRNAtransfected or romidepsin-treated Oct4 + Sox2overexpressing cells in comparison to the untreated counterparts (Fig. 5E).

Docking of Oct4-Sox2-HDAC1 complex on SMAR1 promoter revealed that Oct4 binds to the major groove of DNA composed of residues 1 to 5 and 25 to 30 and that HDAC1 interacts with both Sox2 and Oct4, wherein Sox2 lodges itself in the groove between the Oct4 and HDAC1 (Fig. 5I), indicating the deacetylation of H3K9 on SMAR1 promoter through HDAC1 by Oct4-Sox2 complex (Fig. 5J). Together, these results unveiled a hitherto unknown role of stemness factors in repressing SMAR1 to bestow drug resistance in CSCs.

The above findings bring us closer to our objective of targeting the therapy-resistant CSCs by augmentation of SMAR1. Because these results support the candidature of Oct4 and Sox2 in repressing SMAR1 in CSCs, they might be a suitable target for enhancing SMAR1 and, thus, sensitizing CSCs. Our search of the existing literature to find natural and synthetic compounds that might inhibit Oct4 and Sox2 to augment that of SMAR1 expression suggested the candidature of aspirin. Some studies have reported that aspirin is an inhibitor of stemness and pluripotency-related gene expression (3840), and this common, over-the-counter drug reportedly inhibits chemotherapy-induced increases in CSC numbers and sensitizes these typically drug-resistant cells (3). Therefore, we explored its effect on SMAR1. Real-time PCR analysis showed that treating CSC-enriched secondary spheres of human breast cancer cells with aspirin (3) led to a significant rise in SMAR1 mRNA levels (Fig. 6A) and a significant decline in those of Oct4 and Sox2 mRNA (Fig. 6B), whereas Western blotting showed a decline in ABCG2 and an increase in SMAR1 protein level after aspirin treatment (Fig. 6C). Flow cytometric analysis of control versus aspirin-treated secondary spheres depicted a significant rise in the number of SMAR1+ cells along with a decline in that of Oct4+ and Sox2+ cells (Fig. 6D). ChIP assays further revealed a significantly lower binding of Oct4 and Sox2 on the target region of the SMAR1 promoter in aspirin-treated secondary spheres (Fig. 6E, left). Alongside the rise in SMAR1 expression described above (Fig. 6A), aspirin-treated secondary spheres showed a greater binding of SMAR1 on the ABCG2 promoter (Fig. 6E, right).

(A) Bar diagram depicting real-time PCR data assessing relative SMAR1 mRNA expression in control and aspirin-treated MDA-MB-468 and MCF-7 secondary spheres (n = 3 biological replicates). (B) Real-time PCR data showing relative Oct4 and Sox2 mRNA expression in control and aspirin-treated MCF-7 secondary spheres (n = 3 biological replicates). (C) Western blot displaying SMAR1 and ABCG2 expression in control and aspirin-treated MDA-MB-468 and MCF-7 secondary spheres (n = 3 independent experiments). (D) Bar diagram showing flow cytometry data depicting % Oct4+, % Sox2+, and % SMAR1+ cells in MDA-MB-468 and MCF-7 secondary spheres after aspirin treatment (n = 3 biological replicates). (E) ChIP assay followed by real-time PCR depicting the alternation in binding of Oct4 and Sox2 on SMAR1 promoter (left) and SMAR1 on ABCG2 promoter (right) after aspirin treatment in MCF-7 secondary spheres (n = 3 biological replicates). (F) Western blot displaying SMAR1 level in control, Oct4 cDNA + Sox2 cDNAtransfected, aspirin-treated, and Oct4 cDNA + Sox2 cDNAtransfected + aspirin-treated MCF-7 secondary spheres (n = 3 independent experiments). (G) Western blot and densitometric quantification showing relative SMAR1 expression in control, aspirin-treated, HDAC1 cDNAtransfected, and HDAC1cDNAtransfected + aspirin-treated MCF-7 secondary spheres (n = 3 independent experiments). (H) Bar diagram displaying changes in HDAC2 ChIP on SMAR1 binding region of ABCG2 promoter after aspirin treatment in MCF-7 secondary spheres, as determined by real-time PCR. (n = 3 biological replicates). (I) Western blot displaying ABCG2 level in control, aspirin-treated, SMAR1 shRNAtransfected, and SMAR1 shRNAtransfected + aspirin-treated MCF-7 secondary spheres (n = 3 independent experiments). (J) Western blot displaying ABCG2 expression in control, aspirin-treated, HDAC2 siRNAtransfected, and HDAC2 siRNAtransfected + aspirin-treated MCF-7 secondary spheres (n = 3 independent experiments). (K) Bar diagram displaying the percentage of apoptosis in MDA-MB-468 and MCF-7 secondary spheres after doxorubicin (Dox), aspirin, and aspirin + Dox treatment (n = 3 independent experiments). (L) Bar diagram depicting the changes in percentage of apoptosis in control, aspirin + Doxtreated and Oct4 cDNA + Sox2 cDNAtransfected + aspirin + Doxtreated MDA-MB-468 and MCF-7 secondary spheres (n = 3 independent experiments). (M) Bar diagrams displaying changes in percentage of apoptosis in control, aspirin + Doxtreated, ABCG2 cDNAtransfected + aspirin + Doxtreated, HDAC2 siRNAtransfected + aspirin + Doxtreated MDA-MB-468 and MCF-7 secondary spheres (n = 3 independent experiments). Data are mean SD or representative of three independent experiments unless otherwise noted. N.S., P > 0.05; *P < 0.05; **P < 0.01; ***P < 0.001; and ****P < 0.0001 by Mann-Whitney U test (A, B, E, and H), by unpaired t test (D), by Kruskal-Wallis test along with Dunns multiple comparison post hoc test (G), or by ordinary one-way ANOVA alone (K) and with Dunnetts multiple comparison post hoc test (L and M).

In secondary spheres that were transfected to overexpress Oct4 and Sox2, aspirin failed to enhance SMAR1 expression (Fig. 6F and fig. S4D), suggesting that aspirin augments SMAR1 in CSCs by repressing the expression of its major transcriptional attenuators. Next, to validate the involvement of HDAC1 in this axis, we overexpressed HDAC1 then treated the secondary spheres with aspirin. Our results revealed that while aspirin alone could significantly enhance SMAR1 expression, it failed to do so in HDAC1-overexpressed secondary spheres (Fig. 6G and fig. S4E). These data corroborate the inhibition of Oct4-Sox2-HDAC1 axis during aspirin-mediated enhancement of SMAR1 expression.

Next, we proceeded to determine the effect of aspirin on SMAR1-HDAC2 axis, which ultimately may lead to ABCG2 repression. Our results have already furnished that aspirin increases the binding of SMAR1 on ABCG2 promoter (as shown in Fig. 6E, right). Next, our ChIP data revealed that aspirin treatment significantly increased HDAC2 binding to the ABCG2 promoter (Fig. 6H). Furthermore, while aspirin alone could repress ABCG2 expression, in the presence of SMAR1 shRNAmeaning less SMAR1 (fig. S4F)it did not (Fig. 6I), indicating the requirement of SMAR1 in aspirin-mediated ABCG2 repression. Similarly, when HDAC2 was knocked down (fig. S4G), aspirin did not reduce ABCG2 expression, confirming the requirement of HDAC2 in the aspirin-SMAR1 mechanism (Fig. 6J).

Furthermore, aspirin-treated secondary spheres underwent significant apoptosis upon treatment with doxorubicin, to which these cells were otherwise resistant (Fig. 6K). Here again, there was a significant reduction in the percentage of apoptotic cells after Oct4 + Sox2 overexpression before aspirin + doxorubicin treatment (Fig. 6L). When ABCG2 was overexpressed or HDAC2 was knocked down during aspirin + doxorubicin treatment (fig. S4H), the amount of apoptosis significantly declined (Fig. 6M). These results indicate that the effect of aspirin in hindering CSC survival is through repressing drug resistance pumps like ABCG2 through enhancement of a SMAR1-HDAC2 axis. Together, the results indicate the potential of aspirin as a two-pronged attack in sensitizing CSCs toward chemotherapeutic drug doxorubicin by attenuating the stemness factors Oct4 and Sox2 and augmenting SMAR1 to ultimately regress ABCG2.

Last, we validated the above in vitro results in vivo using BALB/c mice inoculated orthotopically with 4T1-derived spheres into the mammary fat pad. After 7 days of tumor inoculation, the mice were subjected to intraperitoneal injection of aspirin and doxorubicin, each alone or in combination, every alternate day up to 2 weeks (Fig. 7A). Our results depict that, when treated alone, aspirin failed to make much difference in tumor size when compared with control ones (Fig. 7, B and C). However, aspirin treatment resulted in a significant rise in SMAR1 expression, as determined by Western blot (Fig. 7D). Furthermore, in comparison to tumors from control mice, those from aspirin-treated mice had significantly lower Oct4, Sox2, and ABCG2 expression and greater SMAR1 expression (Fig. 7E), as determined by real-time PCR. The expression of SMAR1 was attenuated in tumors from mice treated with doxorubicin alone; however, combining doxorubicin with aspirin resulted in an increase in SMAR1 expression (Fig. 7, D and E). Likewise, the expression of Oct4, Sox2, and ABCG2, which were augmented upon treatment with doxorubicin alone, showed a stark decline in tumors from dual-treated mice (Fig. 7E), together suggesting that aspirin may counter the CSC-associated effects of doxorubicin. Moreover, the dual-treated mice displayed the greatest reduction in tumor size among the four groups (Fig. 7, B and C). These results are in line with a previous report (3) from our laboratory that aspirin enhances the magnitude of CSC apoptosis after treatment with doxorubicin. The present work has thus revealed the mechanism behind such sensitization.

(A) Flowchart depicting the scheme of protocol of the animal study. Female BALB/c mice were inoculated with 4T1 spheres. From the seventh day after tumor inoculation, aspirin (100 mg/kg), doxorubicin (Dox) (5 mg/kg), or aspirin (100 mg/kg) + Dox (5 mg/kg) was given intraperitoneally every alternate day up to 2 weeks (n = 5 for each group). After treatment, the mice were sacrificed, tumor volume was measured, and tumor tissue was collected. (B) Representative images of the tumors of each group. (C) Scatter plots depicting the tumor volume (cm3) in control, aspirin-treated, Dox-treated, and aspirin + Doxtreated mice. (D) Western blot data and densitometry showing SMAR1 expression in control, aspirin-treated, Dox-treated, and aspirin + Doxtreated mice tumor tissues. (E) Bar diagrams displaying real-time PCR data performed to assess the changes in expression of Oct4, Sox2, SMAR1, and ABCG2 in control, aspirin-treated, Dox-treated, and aspirin + Doxtreated mice tumor tissues. Data are mean SD or representative of five independent biological replicates. N.S., P > 0.05; *P < 0.05; **P < 0.01; ***P < 0.001; and ****P < 0.0001 by ordinary one-way ANOVA with Dunnetts multiple comparison post hoc test (C), by Kruskal-Wallis test alone (E), and with Dunns multiple comparison post hoc test (D).

Drug resistance and frequent occurrences of relapse are the major hurdles in anticancer therapies(41). CSCs not only play a pivotal role in drug-resistant phenotype of the tumors but also are practically nontargetable, leading to recurrence of the tumor and, in many cases, fatality of the patient (42, 43). Therefore, sensitizing CSCs may increase the success of cancer therapy. CSCs show high expression of a variety of oncogenes that drive the hallmarks of cancer. Oct4, Sox2, Nanog, and ALDH1the core regulators of stemness or pluripotencyare augmented in CSCs(44), so are the various drug efflux pumps like ABCG2, MRP1, and MDR1 (45). To specifically target CSCs, the intricate signaling networks that are essential for driving the CSC function and phenotype thus need to be unraveled.

SMAR1, previously known to function in chromatin remodeling, tissue-specific gene regulation, and tissue-specific metabolism (46), has been shown to induce tumor regression (47), and a diminished expression of SMAR1 is frequently associated with poor prognosis of various cancers (9). This protein not only serves as a attenuator of tumor proliferation and metastasis but also is an inducer of p53-mediated apoptosis (9). Its role as a repressor of cyclin D1, Slug, and the Wnt/-catenin pathway supports its antitumor role (8, 10). In more advance cancer stages, expression of SMAR1 is markedly reduced (9), suggesting that SMAR1 is negatively correlated with tumor aggression, a feature driven in part by CSCs. Given that CSCs are reportedly adept at escaping or repressing various tumor suppressor factors to ensure their survival, we thought it is highly plausible that CSCs might also hinder SMAR1 functions.

Thus, we aimed at unveiling its role in breast CSCs specifically in the context of drug resistance. CSCs isolated from tumors of multiple breast cancer patients and mice showed reduced expression of SMAR1 compared with isolated nonstem-like cancer cells. Nakka et al. (14) have also reported that SMAR1-depleted MCF-7 cells have increased CD44 variant exon inclusion and a greater metastatic propensity in mice. Considering that breast CSCs express CD44 as one of their major surface markers (48, 49), their report is not only aligned with our results but also strengthens the possibility of existence of an inverse relationship between SMAR1 and stemness and thus of SMAR1 having some anti-CSC role. Further to a previous report from our laboratory showing that CSC-enriched spheres were insensitive to doxorubicin due to their abundant expression of the drug efflux pumps ABCG2, MDR1, MRP1, and others (50), here we found that doxorubicin could induce apoptosis in CSCs when they overexpressed SMAR1. We also found that the promoter of one of the aforementioned drug resistance pumps, and a reportedly potent one in breast cancer (3, 51), ABCG2, harbors a MAR-binding domain, which mediates SMAR1 binding to its target genes (10). ABCG2 is also crucial for maintaining stem cell proliferation and stem cell phenotypes (52), and its expression is augmented with tumor progression (53). Multiple reports from our laboratory and others had previously established that SMAR1 exerts its inhibitory effect by chromatin condensation and deacetylation of histones through the recruitment of different HDACs (10, 12, 14). These and our results here together suggest that SMAR1 recruits HDAC2 to deacetylate H3K9 on ABCG2 promoter, thereby inhibiting ABCG2 transcription and chemoresistance.

Furthermore, SMAR1 was found to be transcriptionally attenuated in CSCs by co-operative action of stemness markers Oct4 and Sox2, indicating that possibly this mechanism maintains an augmented multidrug resistance feature of CSCs. Oct4 and Sox2 recruit various corepressor complexes, like HDACs and PRC proteins, as an aid of gene regulation. Our experiments also revealed the involvement of HDAC1 along with deacetylation of H3K9 in this case. HDAC1 has already been described as a regulator of embryonic stem cell differentiation that acts in aid with various pluripotency factors (54). Both Oct4 and Sox2 are reported to colocalize with HDAC1, which acts as a mediator of Oct4- and Sox2-derived gene repression that has been previously established (55, 56), further supporting our findings. These findings together indicate that SMAR1 is a modulatory target molecule, enhancing the expression of which sensitizes CSCs by restraining their drug resistance. The anticancer properties of aspirin, including that it inhibits the stemness factors Oct4, Sox2, and Nanog, have been highlighted for some years now (3840). Here, we found that aspirin treatment leads to reduction of Oct4 and Sox2 along with significant augmentation of SMAR1 expression, which epigenetically decreases ABCG2 expression, which may underlie the resulting drug sensitization of otherwise resistant CSCs to the common chemotherapeutic doxorubicin both in vitro and in vivo. Thus, aspirin here acts in two ways, inhibiting tumor stemness and repressing chemoresistance, both through enabling SMAR1 expression. Aspirin might therefore be explored as a way to improve the efficacy of chemotherapy in patients with CSC burdened tumors.

Breast cancer cell lines MCF-7, MDA-MB-468, and MDA-MB-231 were obtained from National Centre for Cell Science, Pune, India. All cell lines were passaged for fewer than 6 months after resuscitation. The cells were routinely maintained in complete RPMI medium at 37C in a humidified incubator containing 5% CO2 as previously described (57). Cells were allowed to reach confluence before use.

For sphere culture, the cells were seeded at 2.5 104 cells per well in six-well Ultra-Low Adherence plates (Corning) in Dulbeccos modified Eagles medium/F12 with bovine insulin (5 g/ml) (Sigma-Aldrich), recombinant epidermal growth factor (20 ng/ml), basic fibroblast growth factor (20 ng/ml), B27 supplement (BD Biosciences), and 0.4% bovine serum albumin (BSA) as previously described (50, 57). Primary spheres were subjected to secondary sphere formation by weekly trypsinization and dissociation followed by reseeding in serum-free media at 2.5 104 cells per well into Ultra-Low Adherence six-well plates.

Healthy secondary spheres were treated with 2.5 mM aspirin (3) (Merck Millipore) for specific experiments. Aspirin, being sparingly soluble in distilled water, 1 M stock solution was prepared in dimethyl sulfoxide (DMSO). For all in vitro assays with aspirin, DMSO was used as control. The secondary spheres were treated with chemotherapeutic agent doxorubicin (2.5 M) (MP Biomedicals) alone or in combination with aspirin for specific experiments (50). TSA (Sigma-Aldrich) and NaBu (Merck Millipore) were used as class I HDAC inhibitors at 2.5 nM and 0.4 mM, respectively (26, 27), for 24 hours. Romidepsin was used at 10 ng/ml for 24 hours as a specific inhibitor of HDAC1 and HDAC2 (29).

For whole cell lysates, cells were homogenized in lysis buffer [20 mM Hepes, (pH7.5), 10 mM KCl, 1.5 mM MgCl2, 1 mM Na-EDTA, and 1 mM dithiothreitol]. All buffers were supplemented with protease inhibitor mixtures (Thermo Fisher Scientific). Protein concentrations were estimated using Lowry method. The lysates containing 50 g of protein were mixed with an equal volume of 2 SDSpolyacrylamide gel electrophoresis (SDS-PAGE) sample buffer, heated at 90C for 2 min, and loaded onto 8 to 15% SDS-PAGE gel (depending on the molecular weight of the protein of interest). An equal amount of protein (50 g) was loaded in each well. For the experiments detecting SMAR1 in control and transfected/treated secondary spheres, in which SMAR1 expression was low, we loaded 80 g of protein in each well. The proteins were transferred to a polyvinylidenedifluoride membrane (Merck Millipore), which was then blocked with 5% nonfat milk in tris-buffered saline containing 0.05% Tween 20 before antibody treatments. The membranes were probed with specific primary antibodies followed by respective HRP-tagged secondary antibodies and visualized by chemiluminescence. The antibodies used are SMAR1 (Bethyl Laboratories), ABCG2 (Novus Biologicals/Santa Cruz Biotechnology), Sox2/ Ac-H3k9/HDAC2/HDAC1/GFP (green fluorescent protein) (Cell Signaling Technology), and Oct4/Sox2 (Santa Cruz Biotechnology). Equivalent protein loading was verified using -actin (Cell Signaling Technology) or -tubulin (Thermo Fisher Scientific). For densitometric analysis of Western blots, the intensity of the protein of interest was normalized to that of a loading control (-actin or -tubulin).

To determine the direct physical interaction between SMAR1 and HDAC2 or Oct4/Sox2 and HDAC1, CoIP experiments were performed. Immune complexes from whole cell lysates were purified using SMAR1 or Oct4/Sox2 antibody and Protein A Sepharose beads (Sigma-Aldrich). The immunopurified proteins were immunoblotted for both protein of interest that coprecipitated (HDAC2/HDAC1) and the protein being pulled down (SMAR1/Oct4/Sox2). The protein of interest was visualized by chemiluminescence.

One microgram of the total RNA, extracted from cells with TRIzol reagent (Ambion) was reverse transcribed using a Verso cDNA Synthesis kit (Thermo Fisher Scientific) and then subjected to either semiquantitative PCR with ExPrime Taq 2x Master Mix (GeNet Bio) using GeneAmp-PCR System 2720 (Applied Biosystems) or real-time PCR using SYBR Green Master mix (Roche) in Roche Light Cycler 96 system. The cDNAs were amplified with the following primers specific for SMAR1 human (forward: 5-GGCCATCCAGATTCAGTGAG-3; reverse: 5-AGCAGGACTCAAACGAAAGG-3), SMAR1 mouse (forward: 5GCATTGAGGCCAAGCTGCAAGCTC-3; reverse: 5-CGGAGTTCAGGG-TGATGAGTGTGAC-3), ABCG2 human (forward: 5-CTTACAGTTCTCAGCAGCTCTTCG-3; reverse: 5-CGAGGCTGATGAATGGAGAAG-3), MRP1 human (forward: 5-ACCATCCACGACCCTAAT-3; reverse: 5CCACCTTGGAACTCTCTTTC-3), MDR1 human (forward: 5-GGAGATAGGCTGG-TTTGATG-3; reverse: 5-GTCCAAGAACAGGACTGATG-3), Oct4 human (forward: 5-GGGCTCTCCCATGCATTCAAAC-3; reverse: 5-CACCTTCCCTCCAACCAGTTGC-3), Oct4 mouse (forward: 5-TCTTTCCACCAGGCCCCCGGCTC-3; reverse: 5-TGCGGGCGGACATGGGGAGATCC-3), Sox2 human (forward: 5-CCATGCAGGTTGACACCGTTG-3; reverse: 5-TCGGCAGACTGATTCAAATAATACAG-3), Sox2 mouse (forward: 5-CCGCGTCAAGAGGCCCATGAA-3; reverse: 5-CCCGCTTCTCGGTCTCGGACAA-3), ABCG2 mouse (forward: 5-TCGCAGAAGGAGATGTGTTGAG-3; reverse: 5-CCAGAATAGCATTAAGGCCAGG-3), -actin (forward: 5-AGGTCATCACCATTGGCAAT-3; reverse: 5-ACTCGTCATACTCCTGCTTG-3), glyceraldehyde-3-phosphate dehydrogenase (GAPDH) human (forward: 5-CCTGCACCACCAACTGCTTA-3reverse: 5-GGCCATCCACAGTCTTCTGGG3), and GAPDH mouse (forward: 5-CATCACTGCCACCCAGAAGACTG-3; reverse: 5-ATGCCAGTGAGCTTCCCGTTCAG-3).

The PCR products of semiquantitative PCR were analyzed by 2% agarose gel electrophoresis. For real-time PCR, relative expression was calculated using Ct method with 2Ct as fold change (58).

ChIP assays were performed using standard protocol of Millipore. PCR assay for identification of SMAR1 binding site on ABCG2 promoter and Oct4 and Sox2 binding on SMAR1 promoter was performed using the following different primer sets: SMAR1 on ABCG2 promoter: (for 5CCGTGCTGGCCTTAATTT-3/Rev. 5ATGATGCGC-CCAAACATT-3); Oct4-Sox2 on SMAR1 promoter: (For 5GGACGCTGACATTTGAGTT-3/Rev. 5GCTCTCCACCTGCTTCTA-3). Extracted DNA was used for either semiquantitative or real-time PCR. The products of semiquantitative PCR were analyzed by 2% agarose gel electrophoresis. The fold change of real-time PCR was calculated using ddCt method(58).

The overexpression constructs of Oct4 (pcDNA 3.3 OCT4, plasmid no. 26816), Sox2 (pSin-EF2-Sox2-Pur, plasmid no. 16577), HDAC1 (HDAC1 Flag, plasmid no. 13820), and the shRNAs against Oct4 (LL-HOCT4i, plasmid no. 12198), and Sox2 (pLKO.1 Sox2 3H b, plasmid no. 26352) were purchased from Addgene. The ABCG2 siRNA (NM_004827), HDAC1 siRNA (NM_004964), and HDAC2 siRNA (NM_001527) were purchased from Sigma-Aldrich. The SMAR1 overexpression plasmid (SMAR1 cDNA) and SMAR1 shRNA were gifts from S. Chattoadhyay (10, 14). The SMAR1 overexpression plasmid produces a GFP-tagged SMAR1 protein that gives a separate band of external SMAR1-GFP when visualized in Western blot (10).

The plasmids and control vectors were introduced into cells and spheres using Lipofectamine-2000 (Invitrogen) according to the protocol provided by the manufacturer. Stably expressing clones were isolated by limiting dilution and selection with puromycin dihydrochloride (1 g/ml; Sigma-Aldrich) or G418 Sulfate (1 mg/ml; Sigma-Aldrich), and the resistant cells were cloned and screened by Western blotting with specific antibodies. The siRNA were transfected using Lipofectamine-2000, and cells were harvested after 34 to 36 hours after which the knockdown efficiency was determined using Western blot.

The cells were fixed in 4% paraformaldehyde, permeabilized in 0.1% Triton X-100, and blocked in blocking buffer [5% BSA in phosphate-buffered saline (PBS)]. Cells were then incubated with 1% BSA containing SMAR1 antibody (Bethyl Laboratories) or ABCG2 antibody (Santa Cruz Biotechnology) overnight at 4C in a humid atmosphere. After washing in PBS, cells were incubated with secondary antibodies conjugated with either Alexa Fluor 546 (red) or Alexa Fluor 488 (green). The 4,6-diamidino-2-phenylindole (DAPI) was used as nuclear stain (blue). Images were acquired using a confocal microscope (Leica) (13).

Primary human breast cancer tissue samples were obtained with informed consents from all patients from the Department of Surgery, IPGMER and SSKM Hospital, Kolkata, India in accordance with the Research Oversight Committee of IPGMER and associated research and analyses were done in Bose Institute, Kolkata, India in accordance with the Institutional Human Ethics Committee (BIHEC/2017-18/5). These tumors were exclusively primary site cancers that had not been treated with either chemotherapy or radiotherapy. For comparison of SMAR1 expression between stage II and stage III tumor tissues, n = 5 samples for each group were collected. SMAR1 expression was detected in these tissues by either immunofluorescence or Western blot. For Western blot, the tissues were first mechanically disaggregated on ice, then homogenized in ice-cold radioimmunoprecipitation assay lysis buffer (Sigma-Aldrich) supplemented with protease inhibitor cocktail (Thermo Fisher Scientific) at 4C. After homogenization, the tissues were centrifuged at 10,000 rpm for 15 to 20 min at 4C, and the supernatant was collected for further Western blot analysis.

To obtain pure CSC and NSCC population, the tissues (n = 4) were subjected to flow cytometric sorting of NSCCs and CSCs. For sorting, the tissues were mechanically disaggregated, digested with collagenase, and filtered through a 30-m filter (42).The CSCs were sorted as CD44+/24 population after staining with allophycocyanin (APC)CD44 and phycoerythrin (PE)-CD24 antibodies (BD Biosciences). The rest of the quadrants (CD44/24, CD44+/24+, and CD44/24+) were sorted as NSCCs. The cells were sorted twice, and the purity of sorted populations was verified by flow cytometry. The sorted CSCs and NSCCs were subjected to further RNA isolation and PCR.

Human and mice tissue samples were dissected out, fixed in Bouins fixative overnight, and cryo-protected, and serial sections were cut on a cryostat (CM1850, Leica) at 4 to 5 m thickness.

For immunohistochemistry, the tissue sections were washed with PBS, antigen retrieval was done with enzymatic retrieval method using trypsin-CaCl2 solution. Sections were blocked with 1% BSA at 37C. Sections were incubated overnight at 4C in a humid atmosphere with primary antibodies against SMAR1 (1:1000; Bethyl Laboratories). The sections were and then incubated with biotinylated anti-rabbit immunoglobulin G followed by peroxidase conjugate ExtrAvidin (1:100; Sigma-Aldrich) for 60 min and 3,3-diaminobenzidine was used as chromogen (1:100; Sigma-Aldrich, AEC101-1KT) to visualize the reaction product and counterstained with hematoxylin (1:1; HiMedia, India). Last, sections were washed in distilled water and mounted in glycerol gelatin. Images were acquired with a bright-field microscope at 20 magnification.

For immunofluorescence, the tissue sections were washed with PBS, antigen retrieval was done using 10 mM sodium citrate buffer (pH 6.0) at a subboiling temperature for 10 to 15 min. The tissues were permeabilized using 0.4% Triton X-100 in PBS for 10 min followed by blocking in 5% BSA in PBS Tween 20. Sections were incubated overnight at 4C in a humid atmosphere with primary antibody against SMAR1 (1:1000; Bethyl Laboratories). After washing in PBS, the sections were incubated with secondary antibodies conjugated with Alexa Fluor 546 (red). The DAPI was used as nuclear stain (blue). Images were acquired using a confocal microscope (Leica). All immunohistochemistry and immunofluorescence experiments and their analysis were performed in a blinded manner.

Expression of breast cancer stem cell marker CD44 and CD24 was assessed by flow cytometric analysis of cells and spheres using CD44-APC and CD24-PE antibodies (BD Biosciences). CD44+/CD24 CSCs were gated from spheres on the basis of the cell surface phenotype by flow cytometry. To study the pluripotency markers Oct4, Sox2, Nanog, and ALDH1; differentiation marker CK18; and drug resistance marker ABCG2, the following antibodies were used: Oct4PerCP-Cy5.5 (BD Biosciences), Sox2Alexa Fluor 647 (BD Biosciences), Nanog-PE (BD Biosciences), CK18-PE (BD Biosciences), ALDH1fluorescein isothiocyanate (FITC) (Santa Cruz Biotechnology), and ABCG2-PE (BD Biosciences). Mean fluorescence intensities of Oct4PerCP-Cy5.5, Sox2Alexa Fluor 647, and Nanog-PE were quantified (3). To determine the expression of SMAR1, samples were incubated with SMAR1 antibody (Bethyl Laboratories) in 1% BSA in PBS solution, followed by tagging with FITC-conjugated secondary antibody. The percentage of cells expressing SMAR1 and the mean fluorescence intensity were recorded. To study the percentage of apoptosis by flow cytometry, the FITC-annexin V apoptosis detection kit (BD Biosciences) was used as per the manufacturers protocol.

For cell cycle analysis, the cells were harvested, washed with PBS, and fixed with chilled 70% ethanol. After fixation, the cells were washed and resuspended in PBS, treated with ribonuclease A, and, lastly, stained with propidium iodide (PI). The percentages of cells at different cell cycle stages (G0-G1, S, and G2-M) were determined on the basis of DNA content by flow cytometry using FACSVerse Flow Cytometer (BD Biosciences) using histogram plot of normalized count (y axis) versus PI (linear x axis)(59).

To study the role of aspirin in augmenting the expression of SMAR1 in vivo, female BALB/c mice bearing syngeneic breast cancer cells 4T1 were used. Female BALB/c mice weighing 20 to 25 g were maintained in a temperature-controlled room with light-dark cycle. All animal experiments were performed following principles of laboratory animal care (NIH publication no. 85-23, revised in 1985) and Indian laws on Protection of Animals under the provision of the ethics committee for the purpose of control and supervision of experiments on animals (reg. no. 95/99/CPCSEA; approval no: IAEC/BI/94/2018), Bose Institute. The following two experiments were performed using the BALB/c mice.

In the first, to evaluate the effect of aspirin, mice (n = 20) were inoculated within the mammary fat pad with 1 106 4T1 cells derived from secondary spheres. For that, the 4T1 secondary spheres were first trypsinized to form single cells, followed by a cell viability assay using trypan blue exclusion method, and a total number of 1 106 viable cells were inoculated in the mice. On the seventh day after tumor inoculation, tumor-bearing mice were divided into four groups (n = 5 in each group): control set, aspirin-treated set, doxorubicin-treated set, and aspirin + doxorubicintreated set. From that day onward, the mice were intraperitoneally treated with PBS (control set), aspirin (100 mg/kg), doxorubicin (5 mg/kg), or aspirin (100 mg/kg) + doxorubicin (5 mg/kg) every alternate day for 2 weeks (seven doses at 48-hour intervals) (60, 61). After 2 weeks of treatment, all four groups of mice were sacrificed, tumor volume was measured, the expression of SMAR1 was detected using Western blot, and the expression of SMAR1, ABCG2, Oct4, and Sox2 mRNAs was measured by real-time PCR.

In the second experiment, to evaluate the changes in CSC percentage and SMAR1 expression along different time points of progressive tumor growth, the female BALB/c mice were inoculated with 1 106 4T1 cells, as mentioned above. The mice were divided into three groups and one group each was sacrificed on the 7th, 14th, and 21st days, respectively, after the day of tumor inoculation. The percentage of CSCs within the tumors of each group was measured as CD44+/24/low (16), Oct4+, and Sox2+ cells. The percent of SMAR1+ cells was determined by flow cytometry, and expression of SMAR1 mRNA was determined by real-time PCR. All tagged antibodies for flow cytometry were purchased from BD Biosciences.

For the nude mouse xenograft model, to determine the tumor formation potential of grafted MDA-MB-468 cells and secondary spheres, female BALB/c athymic nude mice (4 to 5 weeks old, each weighing 18 to 22 g) were used. These mice were obtained from the Centre for Translational Animal Research, Bose Institute, and all experiments were performed following the guidelines of the Bose Institute animal ethics committee in accordance with CPCSEA guidelines (reg. no. 95/99/CPCSEA; approval no: IAEC/BI/94/2018). The mice were raised in pathogen-free temperature-controlled environment with light-dark cycle. Prior inoculation, the cell viability was assessed by trypan blue exclusion method. The mice were orthotopically inoculated in mammary fat pad with either 6 106 viable MDA-MB-468 cells or 6 106 viable cells from MDA-MB-468 secondary spheres (n = 3 for each group). The mice were regularly observed for tumor formation, and the tumor volume was measured every other day. Thirty days after the day of tumor inoculation, the mice were sacrificed, tumor tissues were collected, and the tumor volumes and weights were measured (6264).

The full-length structure of SMAR1 (NP_001167010.1) and Oct4 (NP_001167002.1) was modeled in I-TASSER web server (65). The predicted structure was prepared and minimized using Schrodinger PRIME module (66). X-ray crystallographic structures of Sox2 [Protein Data Bank (PDB) ID: 2LE4], HDAC2 (PDB ID: 3MAX), and HDAC1 (PDB ID: 4BKX) were already available, so the co-ordinate file was downloaded from The Research Collaboratory for Structural Bioinformatics (RCSB) PDB and further processed in PyMOL. To analyze the interaction of Oct4-Sox2, they were docked upon each other in ZDOCK (67). The same method was followed for docking SMAR1-HDAC2 proteins. To study the binding with the SMAR1 promoter, Oct4-Sox2 complex was docked on SMAR1 promoter (5-TTTTAAAATGTAAAACCCA-3) in HDOCK (68). The same method was followed to dock SMAR1-HDAC2 on ABCG2 promoter (5-CATTTTAAGACAAAATTAAGG-CCAGCACGG-3) and SMAR1 on ABCG2 promoter (5-CATTTTAAGACAAAATTAAGG-CCAGCACGG-3. The final predicted docked structures of all the complexes were viewed and analyzed with PyMOL (69, 70).

The normal versus tumor expression of SMAR1 in various cancers and the correlation plot between SMAR1 and ALDH1 in breast cancer were obtained from the GEPIA database using single gene analysis in The Cancer Genome Atlas (TCGA) tumors dataset (71). The t-SNE plots of SMAR1, ALDH1, and ABCG2 and the correlation plot between SMAR1, ALDH1 and SMAR1, and ABCG2 in invasive breast carcinomas (n = 1097 samples) were obtained from the R2 database (R2 Genomics Analysis and Visualization Platform) using tumor breast invasive carcinoma-TCGA-1097 dataset (72). Km analysis was performed using the publicly available database at http://kmplot.com/analysis/ with the following options: Affy id: 233186_s_at; splitting patients by Autoselect best cut off; survival: RFS (n = 1764), OS (n = 397), PFS (n = 165); probe set option: only Jetset best probe set; ER/PR/HER2 status: all; TP53 status: all; and intrinsic subtype: all. The normal versus tumor SMAR1 expression analysis in invasive breast carcinoma was also obtained from Oncomine database (Finak dataset of breast cancer) (73) using the following filters: cancer versus normal analysis; cancer type, breast cancer; and dataset, Finak breast.

The 2000- to +100-bp spanning promoter sequence of human ABCG2 and SMAR1 genes was obtained from the Eukaryotic Promoter Database (74). The S/MAR domain on the ABCG2 promoter was determined using Genomatix software suite using the SMARTest tool (www.genomatix.de/online_help/help_gems/SMARTest.html). The SMARTest identifies potential S/MARs by performing a density analysis based on the S/MAR matrix library (75). The Oct4 and Sox2 binding region on SMAR1 promoter was determined by JASPAR transcription factor binding profile database (http://jaspar.genereg.net/) (76).

Values are shown as mean and SD, unless otherwise indicated. All quantitative figures were constructed using GraphPad Prism version 7.00 with the alpha level set at 0.05 for all tests (GraphPad Prism 7.00). All experiments were independently repeated at least three times, data were analyzed, and significance (P < 0.05) of the differences between mean values was determined by statistician-confirmed, suitable statistical tests. Data with normal distribution were analyzed by either Students t test or analysis of variance (ANOVA) as appropriate. For multiple comparisons where applicable, one-way ANOVA with Dunnetts multiple comparison of post hoc test was performed for normal data. To analyze normalized data, like real-time PCR data that do not follow normal distribution, nonparametric tests are used. For nonnormal data with two unpaired groups, Mann-Whitney U test was performed; for nonnormal data with three or more groups, Kruskal-Wallis test was performed. For multiple comparisons of nonnormal data, Dunns multiple comparison post hoc test was used along with Kruskal-Wallis test.

Acknowledgments: We thank A. Adhikary at the Centre for Research in Nanoscience and Nanotechnology, University of Calcutta for thoughtful comments on this manuscript, D. Chakraborty for the help in the animal and IHC experiments, and U. K. Ghosh and R. Dutta for the technical assistance. Funding: This work was supported by research grants from Department of Science and TechnologyScience and Engineering Research Board (DST-SERB), Government of India (grant number EMR/2016/003607). The first author A.B. is under UGC-SRF fellowship, Government of India, the contingency grant of which has also supported the work. Author contributions: T.D. conceptualized the project, designed the experiments, and reviewed and edited the manuscript. A.B. carried out most of the experiments, analyzed data, wrote the manuscript, and prepared the figures. S.M., P.K., and S.B. reviewed the data and reviewed and edited the manuscript. Apratim Dutta carried out the CoIP experiments, performed the R2 and GEPIA database study, and prepared the figures. N.B. and S. Chatterjee performed in silico docking experiments. D.S. did the Km plotter and Oncomine database study. U.B. and S. Chakraborty performed cell culture. Abhishek Dutta carried out cell cycle experiments. S. Chattopadhyay provided the SMAR1 cDNA and SMAR1 shRNA plasmids and reviewed the manuscript. K.J. supervised the in vivo mice model experiments. D.K.S. provided the primary human tissue samples. Competing interest: The authors declare that they have no competing interests. Data and materials availability: All the data needed to evaluate the conclusions in the paper are present in the paper or the Supplementary Materials.

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SMAR1 repression by pluripotency factors and consequent chemoresistance in breast cancer stem-like cells is reversed by aspirin - Science

While Risky, Sorrento Therapeutics Has Many Options to Win – Investorplace.com

When I last did a write-upabout Sorrento (NASDAQ:SRNE), a biotech company that has a myriad of drug and diagnostic candidates for Covid-19, SRNE stock was trading at $9.48. The stock made some nice gains after that then gave it all back. The stock is now all the way back down to $8.

So now what? Is there still a bull thesis in place or should investors get cautious? Well, Im still bullish. But then again, this is still very much a high-risk company, with many drugs in the early phases. After all, SRNE has seen quite a bit of volatility this year and this will likely remain the case.

Recently, Sorrento had its Covid-19 update for its research and development efforts. The main announcement was an exclusive license agreement with Personalized Stem Cells, Inc., which involves global rights for a stem cell treatment. It is currently going into a Phase-1 clinical trial for 20 hospitalized patients with Covid-19 in California. A Phase-2 trial would include patients from other geographies.

As seen with the treatment of President Donald Trump, there has been much more attention paid to stem cells. Note that they were a key part of the testing for Regenerons (NASDAQ:REGN) antibody cocktail, REGN-COV2.

Heres what Dr. Henry Ji, the CEO of Sorrento, had to say about his companys announcement:

Stem cells were a missing piece in our comprehensive portfolio of potential solutions against COVID-19. We now cover multiple stages of the continuum of care from prevention to potential therapeutic solutions for the most advanced stages of the disease. With PSCs Phase 1 product candidate, we hope to move quickly through the next clinical trials, and, if successful, be able to provide a supportive therapy that may save the lives of the most advanced patients and may also ensure patients who have to undergo intensive care can benefit from a therapy with the potential to minimize the long-term effects of the disease due to the lung damage created by the virus early in the infection.

It has been remarkable how swiftly Ji has refocused his company on Covid-19. Here are just some of the treatments and diagnostics: COVI-TRACE (a diagnostic test), T-VIVA-19 (a vaccine) and a variety of neutralizing antibodies like COVI-GUARD, COVI-AMG and COVI-SHIELD.

Although, the COVI-TRACE may have the biggest impact on the bottom line for SRNE stock. This is a low-cost test that is based on a patients saliva. The test takes only eight minutes or so.

While it seems likely a vaccine will be available within the next couple months, it will take time for a full rollout. The logistics will certainly be daunting. In the meantime, there will be a need for better testing systems.

In terms of the risks, they are considerable. Except for abivertinib, which is in a Phase-2 program, there havent been human trials for the other Covid-19 candidates. This is certainly concerning since many other companies, such as Pfizer (NYSE:PFE), Johnson & Johnson (NYSE:JNJ) and Novavax (NASDAQ:NVAX), have drugs that are in Phase 3.

Something else: Sorrento is a relatively small company. So given its wide assortment of candidates, the company may be stretched. Does the organization really have the bandwidth?

Its a tough call. Yet SRNE stock has the benefit of optionality. Thus, only a couple candidates need to pan out to make a difference. It also helps that the FDA has been focused on accelerating the approval process because of the dangers of the pandemic.

So again, SRNE stock is no slam dunk. But the company still has a decent chance of being a big winner.

On the date of publication, Tom Taulli did not have (either directly or indirectly) any positions in any of the securities mentioned in this article.

Tom Taulli (@ttaulli) is an advisor/board member for startups and author of various books and online courses about technology, includingArtificial Intelligence Basics,The Robotic Process Automation HandbookandLearn Python Super Fast. He is also the founder of WebIPO, which was one of the first platforms for public offerings during the 1990s.

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While Risky, Sorrento Therapeutics Has Many Options to Win - Investorplace.com