A real life Superman celebrates 5 years of survival from one of the deadliest cancers – Newswise

Newswise CLEVELAND Three college graduations. Three family weddings. The births of two grandchildren.

Andy Superman Simon has cherished each of these milestones since he was diagnosed five years ago with a glioblastoma multiforme (GBM grade 4), one of the deadliest and most challenging cancers to treat. GBM patients typically survive an average of 12-15 months. Only 6.8 percent of GBM patients survive five years, according to the National Brain Tumor Society.

But the Superman of University Hospitals Seidman Cancer Center who memorably donned a full costume for his final treatment in September 2016 and is free of cancer today with no recurrence is anything but typical.

I feel incredible, says Simon, now 56. I flew through treatment with ease, because I had the best team and the best surgeon. The way I see it, I had cancer, I dont have it.

The crushing headache, similar to a migraine yet inexplicably and mysteriously different, struck early one morning in November 2015. Pulling out of his driveway to head to the ER, Simon was equidistant from two different hospital systems. He and his wife believe that fateful turn to come to UH Ahuja Medical Center, and then UH Seidman Cancer Center, has made all the difference.

If we hadnt gone to UH, I honestly believe in my heart that Andy wouldnt be here today, said Amy, Simons wife.

Neurosurgeon Andrew Sloan, MD, Director of UHs Brain Tumor & Neuro-Oncology Center and the UH Seidman Center for Translational Neuro-Oncology, diagnosed the large mass in Simons brain as a GBM. He performed a craniotomy on Simon using 5-Aminolevulinic Acid (5-ALA), an experimental agent that improves the surgeons ability to identify the tumor. Dr. Sloans own surgical trial assessing this agent was one of only a handful of studies in the United States at the time, though it is now approved for use throughout the US by the FDA. Simon took the 5-ALA prior to surgery, which causes the cancer cells to glow hot pink, for more complete removal of these aggressive, invasive tumors.

Radiation and chemotherapy are the standard of care following a craniotomy for GBM.

Simon also took advantage of a novel phase I clinical trial that involved genetically engineering his own blood cells to express a mutant protein that made them more resistant to chemotherapy enabling him to safely withstand steadily higher doses of toxic chemotherapy through six rounds. While this phase I trial was designed only to show safety and feasibility, the median survival of the participants was 3.3-fold higher than anticipated based on case-matched historical controls with GBM undergoing standard treatment.

A new clinical trial, funded by a $2.3 million grant from the National Cancer Institute and based on the gene therapy Simon participated in, will open at UH Seidman Cancer Center in the next few months.

Andy has been a champion, Dr. Sloan says of the poster-boy for this trial, noting that five-year GBM survivors commonly experience recurrence. Hes a real fighter.

This treatment is really a game-changer. This could be the new standard of care. Its really exciting and very promising.

For the last several years, Simon has celebrated with a big party complete with a photo display of his milestones. He was planning a blowout celebration this year until the pandemic struck.

There is hope, says Simon. I have too many things to fight for, and to live for. Ive gotten too far. Im going to be a statistic for the other side. Every day is a milestone really.

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About University Hospitals / Cleveland, Ohio

Founded in 1866, University Hospitals serves the needs of patients through an integrated network of 19 hospitals, more than 50 health centers and outpatient facilities, and 200 physician offices in 16 counties throughout northern Ohio.The systems flagship academic medical center, University Hospitals Cleveland Medical Center, located in Clevelands University Circle, is affiliated with Case Western Reserve University School of Medicine. The main campus also includes University Hospitals Rainbow Babies & Children's Hospital, ranked among the top childrens hospitals in the nation; University Hospitals MacDonald Women's Hospital, Ohio's only hospital for women; University Hospitals Harrington Heart & Vascular Institute, a high-volume national referral center for complex cardiovascular procedures; and University Hospitals Seidman Cancer Center, part of the NCI-designated Case Comprehensive Cancer Center. UH is home to some of the most prestigious clinical and research programs in the nation, including cancer, pediatrics, women's health, orthopedics, radiology, neuroscience, cardiology and cardiovascular surgery, digestive health, transplantation and urology. UH Cleveland Medical Center is perennially among the highest performers in national ranking surveys, including Americas Best Hospitals from U.S. News & World Report. UH is also home to Harrington Discovery Institute at University Hospitals part of The Harrington Project for Discovery & Development. UH isone of the largest employers in Northeast Ohio with 28,000 physicians and employees.Advancing the Science of Health and the Art of Compassion is UHs vision for benefitting its patients into the future and To Heal. To Teach. To Discover.is the organizations unwavering mission. Follow UH on Facebook @UniversityHospitalsand Twitter @UHhospitals. For more information, visitUHhospitals.org.

About University Hospitals Seidman Cancer Center

UH Seidman Cancer Center is the only freestanding cancer hospital in Northeast Ohio, where all clinicians and staff are dedicated to the prevention, diagnosis and treatment of cancer while researching new and innovative treatment options through clinical trials. Nationally ranked cancer care is also available to patients through the 11-country region at 18 community-based locations. Our UH Seidman specialists make up 14 cancer-specific teams focused on determining integrated care plans tailored to patients needs. UH Seidman Cancer Center is part of the National Cancer Institute (NCI)-designated Case Comprehensive Cancer Center at Case Western Reserve University, one of 50 comprehensive cancer centers in the country. Patients have access to advanced treatment options, ranging from a pioneering stem cell transplant program founded more than 40 years ago and a wide range of immunotherapy to the first and only proton therapy center in northern Ohio for adults and children. Go to UHhospitals.org/Seidman for more information.

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A real life Superman celebrates 5 years of survival from one of the deadliest cancers - Newswise

Global Cell Harvesting Market to Reach US$381,4 Million by the Year 2027 – Salamanca Press

NEW YORK, Nov. 25, 2020 /PRNewswire/ --Amid the COVID-19 crisis, the global market for Cell Harvesting estimated at US$233.2 Million in the year 2020, is projected to reach a revised size of US$381.4 Million by 2027, growing at a CAGR of 7.3% over the period 2020-2027.Manual, one of the segments analyzed in the report, is projected to grow at a 7.9% CAGR to reach US$284.4 Million by the end of the analysis period. After an early analysis of the business implications of the pandemic and its induced economic crisis, growth in the Automated segment is readjusted to a revised 5.6% CAGR for the next 7-year period. This segment currently accounts for a 28.3% share of the global Cell Harvesting market.

Read the full report: https://www.reportlinker.com/p05798117/?utm_source=PRN

The U.S. Accounts for Over 30.9% of Global Market Size in 2020, While China is Forecast to Grow at a 10.4% CAGR for the Period of 2020-2027

The Cell Harvesting market in the U.S. is estimated at US$72 Million in the year 2020. The country currently accounts for a 30.86% share in the global market. China, the world second largest economy, is forecast to reach an estimated market size of US$34.9 Million in the year 2027 trailing a CAGR of 10.4% through 2027. Among the other noteworthy geographic markets are Japan and Canada, each forecast to grow at 6.1% and 7% respectively over the 2020-2027 period. Within Europe, Germany is forecast to grow at approximately 6.6% CAGR while Rest of European market (as defined in the study) will reach US$34.9 Million by the year 2027.We bring years of research experience to this 5th edition of our report. The 226-page report presents concise insights into how the pandemic has impacted production and the buy side for 2020 and 2021. A short-term phased recovery by key geography is also addressed.

Competitors identified in this market include, among others,

Read the full report: https://www.reportlinker.com/p05798117/?utm_source=PRN

I. INTRODUCTION, METHODOLOGY & REPORT SCOPE I-1

II. EXECUTIVE SUMMARY II-1

1. MARKET OVERVIEW II-1 Cell Harvesting - A Prelude II-1 Impact of Covid-19 and a Looming Global Recession II-1 With Stem Cells Holding Potential to Emerge as Savior for Healthcare System Struggling with COVID-19 Crisis, Demand for Cell Harvesting to Grow II-1 Select Clinical Trials in Progress for MSCs in the Treatment of COVID-19 II-2 Lack of Antiviral Therapy Brings Spotlight on MSCs as Potential Option to Treat Severe Cases of COVID-19 II-3 Stem Cells Garner Significant Attention amid COVID-19 Crisis II-3 Growing R&D Investments & Rising Incidence of Chronic Diseases to Drive the Global Cell Harvesting Market over the Long-term II-3 US Dominates the Global Market, Asia-Pacific to Experience Lucrative Growth Rate II-4 Biopharmaceutical & Biotechnology Firms to Remain Key End-User II-4 Remarkable Progress in Stem Cell Research Unleashes Unlimited Avenues for Regenerative Medicine and Drug Development II-4 Drug Development II-5 Therapeutic Potential II-5

2. FOCUS ON SELECT PLAYERS II-6 Recent Market Activity II-7 Innovations and Advancements II-7

3. MARKET TRENDS & DRIVERS II-8 Development of Regenerative Medicine Accelerates Demand for Cell Harvesting II-8 The Use of Mesenchymal Stem Cells in Regenerative Medicine to Drive the Cell Harvesting Market II-8 Rise in Volume of Orthopedic Procedures Boosts Prospects for Stem Cell, Driving the Cell Harvesting II-9 Exhibit 1: Global Orthopedic Surgical Procedure Volume (2010- 2020) (in Million) II-11 Increasing Demand for Stem Cell Based Bone Grafts: Promising Growth Ahead for Cell Harvesting II-11 Spectacular Advances in Stem Cell R&D Open New Horizons for Regenerative Medicine II-12 Exhibit 2: Global Regenerative Medicines Market by Category (2019): Percentage Breakdown for Biomaterials, Stem Cell Therapies and Tissue Engineering II-13 Stem Cell Transplants Drive the Demand for Cell Harvesting II-13 Rise in Number of Hematopoietic Stem Cell Transplantation Procedures Propels Market Expansion II-15 Growing Incidence of Chronic Diseases to Boost the Demand for Cell Harvesting II-16 Exhibit 3: Global Cancer Incidence: Number of New Cancer Cases in Million for the Years 2018, 2020, 2025, 2030, 2035 and 2040 II-17 Exhibit 4: Global Number of New Cancer Cases and Cancer-related Deaths by Cancer Site for 2018 II-18 Exhibit 5: Number of New Cancer Cases and Deaths (in Million) by Region for 2018 II-19 Exhibit 6: Fatalities by Heart Conditions: Estimated Percentage Breakdown for Cardiovascular Disease, Ischemic Heart Disease, Stroke, and Others II-19 Exhibit 7: Rising Diabetes Prevalence Presents Opportunity for Cell Harvesting: Number of Adults (20-79) with Diabetes (in Millions) by Region for 2017 and 2045 II-20 Ageing Demographics to Drive Demand for Stem Cell Banking II-20 Global Aging Population Statistics - Opportunity Indicators II-21 Exhibit 8: Expanding Elderly Population Worldwide: Breakdown of Number of People Aged 65+ Years in Million by Geographic Region for the Years 2019 and 2030 II-21 Exhibit 9: Life Expectancy for Select Countries in Number of Years: 2019 II-22 High Cell Density as Major Bottleneck Leads to Innovative Cell Harvesting Methods II-22 Advanced Harvesting Systems to Overcome Centrifugation Issues II-23 Sophisticated Filters for Filtration Challenges II-23 Innovations in Closed Systems Boost Efficiency & Productivity of Cell Harvesting II-23 Enhanced Harvesting and Separation of Micro-Carrier Beads II-24

4. GLOBAL MARKET PERSPECTIVE II-25 Table 1: World Current & Future Analysis for Cell Harvesting by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2020 through 2027 II-25

Table 2: World Historic Review for Cell Harvesting by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2012 through 2019 II-26

Table 3: World 15-Year Perspective for Cell Harvesting by Geographic Region - Percentage Breakdown of Value Sales for USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets for Years 2012, 2020 & 2027 II-27

Table 4: World Current & Future Analysis for Manual by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2020 through 2027 II-28

Table 5: World Historic Review for Manual by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2012 through 2019 II-29

Table 6: World 15-Year Perspective for Manual by Geographic Region - Percentage Breakdown of Value Sales for USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World for Years 2012, 2020 & 2027 II-30

Table 7: World Current & Future Analysis for Automated by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2020 through 2027 II-31

Table 8: World Historic Review for Automated by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2012 through 2019 II-32

Table 9: World 15-Year Perspective for Automated by Geographic Region - Percentage Breakdown of Value Sales for USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World for Years 2012, 2020 & 2027 II-33

Table 10: World Current & Future Analysis for Peripheral Blood by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2020 through 2027 II-34

Table 11: World Historic Review for Peripheral Blood by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2012 through 2019 II-35

Table 12: World 15-Year Perspective for Peripheral Blood by Geographic Region - Percentage Breakdown of Value Sales for USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World for Years 2012, 2020 & 2027 II-36

Table 13: World Current & Future Analysis for Bone Marrow by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2020 through 2027 II-37

Table 14: World Historic Review for Bone Marrow by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2012 through 2019 II-38

Table 15: World 15-Year Perspective for Bone Marrow by Geographic Region - Percentage Breakdown of Value Sales for USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World for Years 2012, 2020 & 2027 II-39

Table 16: World Current & Future Analysis for Umbilical Cord by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2020 through 2027 II-40

Table 17: World Historic Review for Umbilical Cord by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2012 through 2019 II-41

Table 18: World 15-Year Perspective for Umbilical Cord by Geographic Region - Percentage Breakdown of Value Sales for USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World for Years 2012, 2020 & 2027 II-42

Table 19: World Current & Future Analysis for Adipose Tissue by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2020 through 2027 II-43

Table 20: World Historic Review for Adipose Tissue by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2012 through 2019 II-44

Table 21: World 15-Year Perspective for Adipose Tissue by Geographic Region - Percentage Breakdown of Value Sales for USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World for Years 2012, 2020 & 2027 II-45

Table 22: World Current & Future Analysis for Other Applications by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2020 through 2027 II-46

Table 23: World Historic Review for Other Applications by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2012 through 2019 II-47

Table 24: World 15-Year Perspective for Other Applications by Geographic Region - Percentage Breakdown of Value Sales for USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World for Years 2012, 2020 & 2027 II-48

Table 25: World Current & Future Analysis for Biotech & Biopharma Companies by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2020 through 2027 II-49

Table 26: World Historic Review for Biotech & Biopharma Companies by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2012 through 2019 II-50

Table 27: World 15-Year Perspective for Biotech & Biopharma Companies by Geographic Region - Percentage Breakdown of Value Sales for USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World for Years 2012, 2020 & 2027 II-51

Table 28: World Current & Future Analysis for Research Institutes by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2020 through 2027 II-52

Table 29: World Historic Review for Research Institutes by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2012 through 2019 II-53

Table 30: World 15-Year Perspective for Research Institutes by Geographic Region - Percentage Breakdown of Value Sales for USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World for Years 2012, 2020 & 2027 II-54

Table 31: World Current & Future Analysis for Other End-Uses by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2020 through 2027 II-55

Table 32: World Historic Review for Other End-Uses by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2012 through 2019 II-56

Table 33: World 15-Year Perspective for Other End-Uses by Geographic Region - Percentage Breakdown of Value Sales for USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World for Years 2012, 2020 & 2027 II-57

III. MARKET ANALYSIS III-1

GEOGRAPHIC MARKET ANALYSIS III-1

UNITED STATES III-1 Increasing Research on Stem Cells for Treating COVID-19 to drive the Cell Harvesting Market III-1 Rising Investments in Stem Cell-based Research Favors Cell Harvesting Market III-1 Exhibit 10: Stem Cell Research Funding in the US (in US$ Million) for the Years 2011 through 2017 III-2 A Strong Regenerative Medicine Market Drives Cell Harvesting Demand III-2 Arthritis III-3 Exhibit 11: Percentage of Population Diagnosed with Arthritis by Age Group III-3 Rapidly Ageing Population: A Major Driving Demand for Cell Harvesting Market III-4 Exhibit 12: North American Elderly Population by Age Group (1975-2050) III-4 Increasing Incidence of Chronic Diseases Drives Focus onto Cell Harvesting III-5 Exhibit 13: CVD in the US: Cardiovascular Disease* Prevalence in Adults by Gender & Age Group III-5 Rising Cancer Cases Spur Growth in Cell Harvesting Market III-5 Exhibit 14: Estimated Number of New Cancer Cases and Deaths in the US (2019) III-6 Exhibit 15: Estimated New Cases of Blood Cancers in the US (2020) - Lymphoma, Leukemia, Myeloma III-7 Exhibit 16: Estimated New Cases of Leukemia in the US: 2020 III-7 Market Analytics III-8 Table 34: USA Current & Future Analysis for Cell Harvesting by Type - Manual and Automated - Independent Analysis of Annual Sales in US$ Thousand for the Years 2020 through 2027 III-8

Table 35: USA Historic Review for Cell Harvesting by Type - Manual and Automated Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2012 through 2019 III-9

Table 36: USA 15-Year Perspective for Cell Harvesting by Type - Percentage Breakdown of Value Sales for Manual and Automated for the Years 2012, 2020 & 2027 III-10

Table 37: USA Current & Future Analysis for Cell Harvesting by Application - Peripheral Blood, Bone Marrow, Umbilical Cord, Adipose Tissue and Other Applications - Independent Analysis of Annual Sales in US$ Thousand for the Years 2020 through 2027 III-11

Table 38: USA Historic Review for Cell Harvesting by Application - Peripheral Blood, Bone Marrow, Umbilical Cord, Adipose Tissue and Other Applications Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2012 through 2019 III-12

Table 39: USA 15-Year Perspective for Cell Harvesting by Application - Percentage Breakdown of Value Sales for Peripheral Blood, Bone Marrow, Umbilical Cord, Adipose Tissue and Other Applications for the Years 2012, 2020 & 2027 III-13

Table 40: USA Current & Future Analysis for Cell Harvesting by End-Use - Biotech & Biopharma Companies, Research Institutes and Other End-Uses - Independent Analysis of Annual Sales in US$ Thousand for the Years 2020 through 2027 III-14

Table 41: USA Historic Review for Cell Harvesting by End-Use - Biotech & Biopharma Companies, Research Institutes and Other End-Uses Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2012 through 2019 III-15

Table 42: USA 15-Year Perspective for Cell Harvesting by End-Use - Percentage Breakdown of Value Sales for Biotech & Biopharma Companies, Research Institutes and Other End-Uses for the Years 2012, 2020 & 2027 III-16

CANADA III-17 Market Overview III-17 Exhibit 17: Number of New Cancer Cases in Canada: 2019 III-17 Market Analytics III-18 Table 43: Canada Current & Future Analysis for Cell Harvesting by Type - Manual and Automated - Independent Analysis of Annual Sales in US$ Thousand for the Years 2020 through 2027 III-18

Table 44: Canada Historic Review for Cell Harvesting by Type - Manual and Automated Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2012 through 2019 III-19

Table 45: Canada 15-Year Perspective for Cell Harvesting by Type - Percentage Breakdown of Value Sales for Manual and Automated for the Years 2012, 2020 & 2027 III-20

Table 46: Canada Current & Future Analysis for Cell Harvesting by Application - Peripheral Blood, Bone Marrow, Umbilical Cord, Adipose Tissue and Other Applications - Independent Analysis of Annual Sales in US$ Thousand for the Years 2020 through 2027 III-21

Table 47: Canada Historic Review for Cell Harvesting by Application - Peripheral Blood, Bone Marrow, Umbilical Cord, Adipose Tissue and Other Applications Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2012 through 2019 III-22

Table 48: Canada 15-Year Perspective for Cell Harvesting by Application - Percentage Breakdown of Value Sales for Peripheral Blood, Bone Marrow, Umbilical Cord, Adipose Tissue and Other Applications for the Years 2012, 2020 & 2027 III-23

Table 49: Canada Current & Future Analysis for Cell Harvesting by End-Use - Biotech & Biopharma Companies, Research Institutes and Other End-Uses - Independent Analysis of Annual Sales in US$ Thousand for the Years 2020 through 2027 III-24

Table 50: Canada Historic Review for Cell Harvesting by End-Use - Biotech & Biopharma Companies, Research Institutes and Other End-Uses Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2012 through 2019 III-25

Table 51: Canada 15-Year Perspective for Cell Harvesting by End-Use - Percentage Breakdown of Value Sales for Biotech & Biopharma Companies, Research Institutes and Other End-Uses for the Years 2012, 2020 & 2027 III-26

JAPAN III-27 Increasing Demand for Regenerative Medicine in Geriatric Healthcare and Cancer Care to Drive Demand for Cell Harvesting III-27 Exhibit 18: Japanese Population by Age Group (2015 & 2040): Percentage Share Breakdown of Population for 0-14, 15-64 and 65 & Above Age Groups III-27 Exhibit 19: Cancer Related Incidence and Deaths by Site in Japan: 2018 III-28 Market Analytics III-29 Table 52: Japan Current & Future Analysis for Cell Harvesting by Type - Manual and Automated - Independent Analysis of Annual Sales in US$ Thousand for the Years 2020 through 2027 III-29

Table 53: Japan Historic Review for Cell Harvesting by Type - Manual and Automated Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2012 through 2019 III-30

Table 54: Japan 15-Year Perspective for Cell Harvesting by Type - Percentage Breakdown of Value Sales for Manual and Automated for the Years 2012, 2020 & 2027 III-31

Table 55: Japan Current & Future Analysis for Cell Harvesting by Application - Peripheral Blood, Bone Marrow, Umbilical Cord, Adipose Tissue and Other Applications - Independent Analysis of Annual Sales in US$ Thousand for the Years 2020 through 2027 III-32

Table 56: Japan Historic Review for Cell Harvesting by Application - Peripheral Blood, Bone Marrow, Umbilical Cord, Adipose Tissue and Other Applications Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2012 through 2019 III-33

Table 57: Japan 15-Year Perspective for Cell Harvesting by Application - Percentage Breakdown of Value Sales for Peripheral Blood, Bone Marrow, Umbilical Cord, Adipose Tissue and Other Applications for the Years 2012, 2020 & 2027 III-34

Table 58: Japan Current & Future Analysis for Cell Harvesting by End-Use - Biotech & Biopharma Companies, Research Institutes and Other End-Uses - Independent Analysis of Annual Sales in US$ Thousand for the Years 2020 through 2027 III-35

Table 59: Japan Historic Review for Cell Harvesting by End-Use - Biotech & Biopharma Companies, Research Institutes and Other End-Uses Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2012 through 2019 III-36

Table 60: Japan 15-Year Perspective for Cell Harvesting by End-Use - Percentage Breakdown of Value Sales for Biotech & Biopharma Companies, Research Institutes and Other End-Uses for the Years 2012, 2020 & 2027 III-37

CHINA III-38 Rising Incidence of Cancer Drives Cell Harvesting Market III-38 Exhibit 20: Number of New Cancer Cases Diagnosed (in Thousands) in China: 2018 III-38 Market Analytics III-39 Table 61: China Current & Future Analysis for Cell Harvesting by Type - Manual and Automated - Independent Analysis of Annual Sales in US$ Thousand for the Years 2020 through 2027 III-39

Table 62: China Historic Review for Cell Harvesting by Type - Manual and Automated Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2012 through 2019 III-40

Table 63: China 15-Year Perspective for Cell Harvesting by Type - Percentage Breakdown of Value Sales for Manual and Automated for the Years 2012, 2020 & 2027 III-41

Table 64: China Current & Future Analysis for Cell Harvesting by Application - Peripheral Blood, Bone Marrow, Umbilical Cord, Adipose Tissue and Other Applications - Independent Analysis of Annual Sales in US$ Thousand for the Years 2020 through 2027 III-42

Table 65: China Historic Review for Cell Harvesting by Application - Peripheral Blood, Bone Marrow, Umbilical Cord, Adipose Tissue and Other Applications Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2012 through 2019 III-43

Table 66: China 15-Year Perspective for Cell Harvesting by Application - Percentage Breakdown of Value Sales for Peripheral Blood, Bone Marrow, Umbilical Cord, Adipose Tissue and Other Applications for the Years 2012, 2020 & 2027 III-44

Table 67: China Current & Future Analysis for Cell Harvesting by End-Use - Biotech & Biopharma Companies, Research Institutes and Other End-Uses - Independent Analysis of Annual Sales in US$ Thousand for the Years 2020 through 2027 III-45

Table 68: China Historic Review for Cell Harvesting by End-Use - Biotech & Biopharma Companies, Research Institutes and Other End-Uses Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2012 through 2019 III-46

Table 69: China 15-Year Perspective for Cell Harvesting by End-Use - Percentage Breakdown of Value Sales for Biotech & Biopharma Companies, Research Institutes and Other End-Uses for the Years 2012, 2020 & 2027 III-47

EUROPE III-48 Cancer in Europe: Key Statistics III-48 Exhibit 21: Cancer Incidence in Europe: Number of New Cancer Cases (in Thousands) by Site for 2018 III-48 Ageing Population to Drive Demand for Cell Harvesting Market III-49 Exhibit 22: European Population by Age Group (2016, 2030 & 2050): Percentage Share Breakdown by Age Group for 0-14, 15- 64, and 65 & Above III-49 Market Analytics III-50 Table 70: Europe Current & Future Analysis for Cell Harvesting by Geographic Region - France, Germany, Italy, UK and Rest of Europe Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2020 through 2027 III-50

Table 71: Europe Historic Review for Cell Harvesting by Geographic Region - France, Germany, Italy, UK and Rest of Europe Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2012 through 2019 III-51

Table 72: Europe 15-Year Perspective for Cell Harvesting by Geographic Region - Percentage Breakdown of Value Sales for France, Germany, Italy, UK and Rest of Europe Markets for Years 2012, 2020 & 2027 III-52

Table 73: Europe Current & Future Analysis for Cell Harvesting by Type - Manual and Automated - Independent Analysis of Annual Sales in US$ Thousand for the Years 2020 through 2027 III-53

Table 74: Europe Historic Review for Cell Harvesting by Type - Manual and Automated Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2012 through 2019 III-54

Table 75: Europe 15-Year Perspective for Cell Harvesting by Type - Percentage Breakdown of Value Sales for Manual and Automated for the Years 2012, 2020 & 2027 III-55

Table 76: Europe Current & Future Analysis for Cell Harvesting by Application - Peripheral Blood, Bone Marrow, Umbilical Cord, Adipose Tissue and Other Applications - Independent Analysis of Annual Sales in US$ Thousand for the Years 2020 through 2027 III-56

Table 77: Europe Historic Review for Cell Harvesting by Application - Peripheral Blood, Bone Marrow, Umbilical Cord, Adipose Tissue and Other Applications Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2012 through 2019 III-57

Table 78: Europe 15-Year Perspective for Cell Harvesting by Application - Percentage Breakdown of Value Sales for Peripheral Blood, Bone Marrow, Umbilical Cord, Adipose Tissue and Other Applications for the Years 2012, 2020 & 2027 III-58

Table 79: Europe Current & Future Analysis for Cell Harvesting by End-Use - Biotech & Biopharma Companies, Research Institutes and Other End-Uses - Independent Analysis of Annual Sales in US$ Thousand for the Years 2020 through 2027 III-59

Table 80: Europe Historic Review for Cell Harvesting by End-Use - Biotech & Biopharma Companies, Research Institutes and Other End-Uses Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2012 through 2019 III-60

Table 81: Europe 15-Year Perspective for Cell Harvesting by End-Use - Percentage Breakdown of Value Sales for Biotech & Biopharma Companies, Research Institutes and Other End-Uses for the Years 2012, 2020 & 2027 III-61

FRANCE III-62 Table 82: France Current & Future Analysis for Cell Harvesting by Type - Manual and Automated - Independent Analysis of Annual Sales in US$ Thousand for the Years 2020 through 2027 III-62

Table 83: France Historic Review for Cell Harvesting by Type - Manual and Automated Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2012 through 2019 III-63

Table 84: France 15-Year Perspective for Cell Harvesting by Type - Percentage Breakdown of Value Sales for Manual and Automated for the Years 2012, 2020 & 2027 III-64

Table 85: France Current & Future Analysis for Cell Harvesting by Application - Peripheral Blood, Bone Marrow, Umbilical Cord, Adipose Tissue and Other Applications - Independent Analysis of Annual Sales in US$ Thousand for the Years 2020 through 2027 III-65

Table 86: France Historic Review for Cell Harvesting by Application - Peripheral Blood, Bone Marrow, Umbilical Cord, Adipose Tissue and Other Applications Markets - Independent Analysis of Annual Sales in US$ Thousand for Years 2012 through 2019 III-66

Table 87: France 15-Year Perspective for Cell Harvesting by Application - Percentage Breakdown of Value Sales for Peripheral Blood, Bone Marrow, Umbilical Cord, Adipose Tissue and Other Applications for the Years 2012, 2020 & 2027 III-67

Excerpt from:
Global Cell Harvesting Market to Reach US$381,4 Million by the Year 2027 - Salamanca Press

Tanya Siddiqi, MD, Discusses the Promise of Reduced Toxicity With Liso-Cel – AJMC.com Managed Markets Network

In addition, liso-cels distinct manufacturing process creates a defined composition of CD8+ and CD4+ T-cells, which may reduce product variability; however, the manufacturer states, the clinical significance of defined composition is unknown.

For insights on what the arrival of liso-cel could mean in the treatment landscape, The American Journal of Managed Care (AJMC) turned to Tanya Siddiqi, MD, director of the Chronic Lymphocytic Leukemia Program at Toni Stephenson Lymphoma Center and associate clinical professor, Department of Hematology & Hematopoietic Cell Transplantation at City of Hope, Duarte, California.

Siddiqi was an investigator for ZUMA-1, which led to the approval of axicabtagene ciloleucel(axi-cel), sold as Yescarta, and the TRANSCEND NHL trial for liso-cel.She has addressed major scientific meetings on the challenge of managing the toxicities associated with CAR T-cell therapyand discussed how liso-cel represents a step forward over its predecessors.

This interview, conducted before the BMS announcement, has been edited for clarity and length.

AJMC: We're anticipating an FDA decision on liso-cel before the end of the year. Can you discuss the need of the patients who would take this new CAR T-cell therapy?

Siddiqi: So, for CAR T-cell therapy targeting CD19-positive B-cell lymphomasspecifically aggressive B-cell lymphomaswe already have a couple of FDA-approved options. The question is: what is liso-cel? How is it different? Why would people pick this over other things? In the trials that we've conducted, we found that liso-cel seems to have lesser toxicity in terms of the specific CAR T-cell side effects of cytokine release syndrome or hyper-inflammation, as well as neurotoxicity. We've just seen fewer severe adverse events so much so that at some [cancer] centers across the country, weve been able to give liso-cel CAR T-cells to patients in the clinic or outpatient setting rather than having to admit them to the hospital , depending on the patient's situation.

Those are the strengths of liso-celless toxicity and thus, a better chance of giving it in the outpatient setting with hospital admission available to anyone who develops a fever or other side effects. This means fewer days of inpatient hospitalization for these patients, so it may be less costly overall. I dont think the efficacy is necessarily differentmeaning that it seems to work as well as the other FDA-approved products already commercially available. But for the reasons that I've listed, I think it might be a very good option for older patients, maybe patients who are bit more frail, or younger patients who just don't want to be admitted to the hospitalthey just want to try to do it in the outpatient setting.

AJMC:You touched on this already, but can you discuss how Iiso-cel differs from earlier CAR T-cell therapiesboth in the way it's manufactured and how it works, and what that reduced variability means for patients?

Siddiqi: Liso-celis manufactured in a way that it gives very precise, equal numbers of CAR cells that are labeled CD4 and CD8, in a 1:1 ratio. All of us have T cells to fight infections with, and these T cells are what we take from patients. Then, we modify them in the lab by genetic engineering in order to produce CAR T-cells so that now instead of looking for infections, these CAR T cells are going to look for B-cell lymphoma cells and fight lymphoma.

The other products are given back to patients as a bag of CAR T cells mixed with potentially varying ratios of different types of T cellsCD4+, CD8+, etc. With liso-cel the manufacturing process actually separates out the CD4+ and CD8+ types of T cells first, and then manufactures CAR-T cells out of them separately. So, when we give the cells back to patients, we give it in a 1:1 ratio of CD4+ and CD8+ cells. We know exactly how many CD4+ and how many CD8+ T-cells these patients receive. And the thought is, the researchers and the drug manufacturer feel that this helps to have an expectation of what expansion you will have of these cells in the body.

Therefore, we potentially have an idea of what type of side effects or how severe the side effects might be. It may limit some of those side effects, or at least make them a little bit more predictable or controlled.

AJMC:Thats a great way to shift to your own work on length of stay due to CRS. What do we know about the key variables in determining whether a patient will experience a side effect that requires an extended stay in the hospital, and can more be done to avoid lengthy hospital stays?

Siddiqi: That's a very important question. Because lengthy hospital stays, especially in the [intensive care unit], really adds to the bill and the financial burden of these treatments. We know that people who have a big burden of disease going into CAR T-cell therapy, meaning they have a lot of lymphoma in their bodies, they tend to be at higher risk for more side effects like cytokine release syndrome and neurotoxicity. Probably because there's so much inflammation thats generated while these CAR T-cells are trying to fight the lymphoma. What we know is that people who come to us for CAR T-cells with lesser disease might have fewer side effects potentially and a better overall outcome.

So, we always try to advise our referring physicians, and educate patients, at conferences, to try to send these patients to us before they are at the end of the linebefore theyve tried and failed everything, and now theres just rampant disease. [At that point,] you're dealing with a situation where the patient is going to have more side effects and will not be able to tolerate the CAR T cells as well. Instead, if they fail two lines of therapy and the disease is still small in volume, but it's starting to progress, we can treat them more effectively with CAR T cells and with fewer side effects potentially.

AJMC:That brings up the next topicthere have been discussions that CAR T-cell therapy should be given earlier during treatment. As you said, if its not given as the last resort, patients might respond better. Where do you see those patterns heading in the future? And would that be truer for some patients than others?

Siddiqi: With aggressive diffuse large B-cell lymphoma, there's about a 60% to 70% chance of curing that in the frontline setting. With the line of chemo-immunotherapy, you can cure 60% to 70% of patients so that it never comes back. But the rest of themwhen it just relentlessly keeps coming back and it's hard to cureonce those patients relapse they tend to keep relapsing. So, our mainstay in the relapse setting is to give them salvage chemo-immunotherapy, collect stem cells, and take them to autologous stem cell transplantation if they've achieved a remission with the salvage chemotherapy. If they haven't achieved remission with that salvage chemotherapy, then they should go on to CAR T cells directly instead of waiting and trying more and more chemotherapies. After failing second line therapy, the FDA approval allows us to try CAR T cells. There are studies that are now ongoing that are comparing CAR T cells to autologous stem cell transplantation after failing first line therapy. So, once patients relapse the first time, these studies are comparing giving them salvage chemotherapy and transplant, versus taking them straight to CAR T cells. Once we have that data, we'll know better whether we can do CAR T cells even earlier in the lines of therapy.

AJMC:Weve been hearing for some time more about allogeneic or off-the-shelf therapies. What progress has been made on in that technology?

Siddiqi: I'm not too involved with these trials myself, but I know we have trials at City of Hope that are ongoing with off-the-shelf therapy. What I can tell you is that it's very attractive in that you don't have to collect T cells from patients, keeping their lymphoma under control while these T cells then go to the lab and CAR T cells are manufactured in 2-4 weeks depending on which product it is, and then they come back and get infused. With off-the-shelf products, you can just grab it and go as soon as you know the patient needs it.

The initial concerns were because the cells are not from the patient themselvesthe cells are from donors. Across the board there might be concerns of rejection and what's called graft-versus-host disease and things like that. So far, I don't think in the trial they've come up with such side effects to any significant extent. What I don't know is whether they've come up with a good result yet. Is it looking like the benefits of taking off-the-shelf CAR T cells are as good as autologous CAR T cells, meaning patients own CAR T cells? I think that remains to be seen. If they are, then it's much easier to use off-the-shelf CAR T cells. Maybe at the American Society of Hematology annual meeting in December we will see more data.

AJMC: How is COVID-19 affecting the clinical trial process for CAR T cell therapy?

Siddiqi: When the pandemic kind of started surging early in the year, and when we went into lockdown mode from March onward, we and other centers across the country took a lot of steps to slow down our clinical trial enrollment. Our staff started staggering who would come into work which day of the week and who could work from home. For those in the clinical trials office, there was a lot of need for safety and logistical reasons for us to slow down enrollment onto clinical trials. And there were other questions, such as, who would take care of patients at home once we discharged them after they received CAR T cells? What if their caregivers were exposed and got sick? Logistically, it was difficult to safely do many trials, especially CAR T cell trials and transplants earlier in the year.

Since the end of summer, we ramped up again, and we're now doing as many transplants and CAR T cells as we were probably doing last year. So, we're pretty much all the way up again, but I don't know how this winter will go because COVID is surging again.

As far as just CAR T cells themselves, we had to also think about travel for the cells because Juno Therapeutics is in Seattle, and Kite Pharma is here in Los Angeles, but Novartis is elsewhere. Just the movement of these cells was a concern because of travel restrictions during COVID-19. But as far as I know, the companies did not lose that commitmentthey told us, well get the cells to you, we will find a way to do it. I don't think any patients went without cells who should have received cells.

AJMC: What advice do you have for community oncologists interested in CAR T cell therapy for their patients?

Siddiqi: Theres good news for community physicians. We may soon have a therapeutic option of liso-cel CAR T cell therapy which seems to have lesser side effects. So, this might make things cheaper due to less need for hospitalization potentially without compromising the chance of cure. We want these patients to try CAR T cell therapy sooner rather than later in their relapses. You can always try multiple cycles of chemotherapy at some other time if you relapse again, but if you can be cured with CAR T cells such that you never need treatment again, why not try that first? For the patients who respond well to CAR T cells, the treatment works extremely well. And that's the Holy Grail to find the cure for all patients.

Maybe only half the patients will currently have a very good and durable responsebut those patients may never relapse again. So why not try it sooner rather than later? And of course, we're always looking for trial patients, because now we need to improve these results even further. So, community oncologists should also refer for trials, because I think that its very important to have trials with different combinationsCAR T cells plus another immunotherapy agentto see if we can improve upon the response rates even more.

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Tanya Siddiqi, MD, Discusses the Promise of Reduced Toxicity With Liso-Cel - AJMC.com Managed Markets Network

Tetracycline-based Antibiotics Show Promise for Combating Zika Infections – Global Biodefense

A widely used antibiotic methacycline was shown effective at preventing brain infections and reducing neurological problems associated with Zika virus in mice models.

National Institutes of Health (NIH) researchers used advanced drug screening techniques to test out more than 10,000 compounds in search of Zika virus therapeutics. The scientists discovered that the widely used antibiotic methacycline was effective at preventing brain infections and reducing neurological problems associated with the virus in mice. Additionally, they found that drugs originally designed to combat Alzheimers disease and inflammation may also help fight infections.

In this study, the researchers looked for drugs that prevent the virus from reproducing by blocking the activity of a protein called NS2B-NS3 Zika virus protease. The Zika virus is a protein capsule that carries long strings of RNA-encoded instructions for manufacturing more viral proteins. During an infection, the virus injects the RNA into a cell, resulting in the production of these proteins, which are strung together, side-by-side, like the parts in a plastic model airplane kit. The NS2B-NS3 protease then snaps off each protein, all of which are critical for assembling new viral particles.

The study was a collaboration between scientists on Dr. Naths team and researchers in laboratories led by Anton Simeonov, Ph.D., scientific director at the NIHs National Center for Advancing Translational Sciences (NCATS) and Radhakrishnan Padmanabhan, Ph.D., Professor of Microbiology & Immunology, Georgetown University Medical Center, Washington, D.C.

The Zika virus is primarily spread by the Aedes aegypti mosquito. In 2015 and 2016, at least 60 countries reported infections. Some of these countries also reported a high incidence of infected mothers giving birth to babies born with abnormally small heads resulting from a developmental brain disorder called fetal microcephaly. In some adults, infections were the cause of several neurological disorders including Guillain-Barr syndrome, encephalitis, and myelitis. Although many scientists have tried, they have yet to discover an effective treatment or vaccination against the virus.

Proteases act like scissors. Blocking protease activity is an effective strategy for counteracting many viruses, said Rachel Abrams, Ph.D., an organic chemist in Dr. Naths lab and the study leader. We wanted to look as far and wide as possible for drugs that could prevent the protease from snipping the Zika virus polyprotein into its active pieces.

To find candidates, Dr. Abrams worked with scientists on Dr. Simeonovs and Dr. Padmanabhans teams to create assays, or tests, for assessing the ability of drugs to block NS2B-NS3 Zika virus protease activity in plates containing hundreds of tiny test tubes. Each assay was tailored to a different screening, or sifting, technique. They then used these assays to simultaneously try out thousands of candidates stored in three separate libraries.

One preliminary screen of 2,000 compounds suggested that commonly used, tetracycline-based antibiotic drugs, like methacycline, may be effective at blocking the protease.

Meanwhile, a large-scale screen of more than 10,000 compounds helped identify an investigational anti-inflammatory medicine, called MK-591, and a failed anti-Alzheimers disease drug, called JNJ-404 as potential candidates. A virtual screen of over 130,000 compounds was also used to help spot candidates. For this, the researchers fed the other screening results into a computer and then used artificial intelligence-based programs to learn what makes a compound good at blocking NS2B-NS3 Zika virus protease activity.

These results show that taking advantage of the latest technological advances can help researchers find treatments that can be repurposed to fight other diseases, said Dr. Simeonov.

The Zika virus is known to preferentially infect stem cells in the brain. Scientists suspect this is the reason why infections cause more harm to newborn babies than to adults. Experiments on neural stem cells grown in petri dishes indicated that all three drugs identified in this study may counteract these problems. Treating the cells with methacycline, MK-591, or JNJ-404 reduced Zika virus infections.

Because tetracyclines are U.S. Food and Drug Administration-approved drugs that are known to cross the placenta of pregnant women, the researchers focused on methacycline and found that it may reduce some neurodevelopmental problems caused by the Zika virus. For instance, Zika-infected newborn mice that were treated with methacycline had better balance and could turn over more easily than ones that were given a placebo. Brain examinations suggested this was because the antibiotic reduced infections and neural damage. Nevertheless, the antibiotics did not completely counteract harm caused by the Zika virus. The weight of mice infected with the virus was lower than control mice regardless of whether the mice were treated with methacycline.

These results suggest that tetracycline-based antibiotics may at least be effective at preventing the neurological problems associated with Zika virus infections, said Dr. Abrams. Given that they are widely used, we hope that we can rapidly test their potential in clinical trials.

Therapeutic Candidates for the Zika Virus Identified by a High Throughput Screen for Zika Protease Inhibitors.PNAS, November 23, 2020

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Study Suggests AYAs Treated for AML Have High Risk of Developing Long-Term Complications – Cancer Network

Study results published in the International Journal of Epidemiology suggested that adolescent and young adult (AYA) patients treated for acute myeloid leukemia (AML) have a high risk of developing long-term health complications.1

The most common complications, or late effects as they are referred to in the study, observed among AYA survivors in this study were cardiovascular, endocrine, and respiratory diseases. Moreover, these complications were found to be more prevalent among non-white AYA patients and those living in more impoverished communities.

Our study shed light on the high burden of late effects among young survivors of AML, lead author Renata Abraho, MD, MSc, PhD, a postdoctoral fellow at theUC Davis Comprehensive Cancer Centerand the Center for Healthcare Policy and Research, said in a press release.2

To estimate the cumulative incidence and investigate the main predictors of late effects among this patient population, researchers identified 1168 eligible AYAs with AML who survived at least 2years after diagnosis from 1996 to 2012 in the California Cancer Registry. Importantly, late effects were reported from State hospital discharge data, and patients were followed through 2014.

Ultimately, the most common late effects reported at 10years after diagnosis were endocrine (26.1%), cardiovascular (18.6%), and respiratory (6.6%), followed by neurologic (4.9%), liver/pancreatic (4.3%), renal (3.1%), avascular necrosis (2.7%), and second primary malignancies (2.4%). Moreover, of the total study cohort, 547 (46.8%) received a hematopoietic stem cell transplant (HSCT).

Following multivariable adjustments, the investigators found that AYAs who underwent HSCT or had non-favorable risk AML experienced an approximately 2-fold or higher increased likelihood of all late effects. Additionally, AYAs of Hispanic, Black, or Asian/Pacific Islander race or ethnicity and those who resided in lower socio-economic neighborhoods were shown to be at higher risk of numerous late effects when compared with non-Hispanic White patients.

This higher risk may relate to the financial hardship that patients with cancer often experience, senior author Theresa Keegan, PhD, MS, associate professor at the UC Davis Comprehensive Cancer Center, said in a press release. As a result of cancer, AYA survivors and their families may miss work, experience income loss, and incur substantial out-of-pocket expenses.

According to the researchers, many factors may have led to the observed disparities in disease burden. These include differences in therapeutic management, patients response to treatment, AML with high-risk mutations, coexisting diseases, and socioeconomic factors.

Further, compared to younger or older cancer survivors, the investigators indicated AYA patients suffer a higher financial burden. They may go without treatment and long-term follow-up visits that could mitigate the impact of late effects. Moreover, their risk of late effects may be exacerbated by unhealthy lifestyle habits such as smoking, excessive alcohol consumption, lack of exercise, non-protected sun exposure, and poor diet.

Our findings underscore the need for long-term surveillance for the prevention, early detection and treatment of late effects, and can inform the development of AYA-focused consensus-based guidelines that will ultimately improve the quality of life and survival of these young vulnerable patients, the study authors wrote.

References:

1. Abraho R, Huynh JC, Benjamin DJ, et al. Chronic medical conditions and late effects after acute myeloid leukaemia in adolescents and young adults: a population-based study. International Journal of Epidemiology. doi: 10.1093/ije/dyaa184

2. Young survivors of acute myeloid leukemia have long-term complications from treatment [news release]. Published November 9, 2020. Accessed November 17, 2020. https://www.newswise.com/articles/young-survivors-of-acute-myeloid-leukemia-have-long-term-complications-from-treatment?sc=sphr&xy=10019792

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Mustang Bio Announces Positive Opinion from the European Medicines Agency on Orphan Drug Designation for Its Lentiviral Gene Therapy for the Treatment…

November 24, 2020 08:00 ET | Source: Mustang Bio, Inc.

WORCESTER, Mass., Nov. 24, 2020 (GLOBE NEWSWIRE) -- Mustang Bio, Inc. (Mustang) (NASDAQ: MBIO), a clinical-stage biopharmaceutical company focused on translating todays medical breakthroughs in cell and gene therapies into potential cures for hematologic cancers, solid tumors and rare genetic diseases, today announced that the European Commission (EC) issued a positive opinion on its application for Orphan Drug Designation for Mustangs lentiviral gene therapy for the treatment of X-linked severe combined immunodeficiency (XSCID), also known as bubble boy disease. The Designation applies both to MB-107 for the treatment of newly diagnosed infants between two months and two years of age and to MB-207 for the treatment of patients who have been previously treated with hematopoietic stem cell transplantation (HSCT) and for whom re-treatment is indicated. The European Medicines Agency (EMA) previously granted Advanced Therapy Medicinal Product classification to MB-107 in April 2020. The U.S. Food and Drug Administration (FDA) also previously granted Rare Pediatric Disease and Orphan Drug Designations to MB-107 and MB-207, as well as Regenerative Medicine Advanced Therapy Designation to MB-107.

Orphan Drug Designation in the European Union (EU) is granted by the European Commission based on a positive opinion issued by the European Medicines Agency Committee for Orphan Medicinal Products (EMA COMP). To qualify, an investigational medicine must be intended to treat a seriously debilitating or life-threatening condition that affects fewer than five in 10,000 people in the EU, and there must be sufficient non-clinical or clinical data to suggest the investigational medicine may produce clinically relevant outcomes. EMA Orphan Drug Designation provides companies with certain benefits and incentives, including protocol assistance, differentiated evaluation procedures for Health Technology Assessments in certain countries, access to a centralized marketing authorization procedure valid in all EU member states, reduced regulatory fees and 10 years of market exclusivity.

Manuel Litchman, M.D., President and Chief Executive Officer of Mustang, said, We are very pleased to receive a positive opinion from the EC on Orphan Drug Designation for our lentiviral gene therapy for XSCID. It is an important milestone for Mustang as we approach the initiation of our pivotal MB-107 and MB-207 clinical trials, which we anticipate will support regulatory filings in both the U.S. and EU. We look forward to working closely with the EMA as we continue our progress to make MB-107 and MB-207 available for patients suffering with XSCID.

MB-107 is currently being assessed in a Phase 1/2 clinical trial for XSCID in newly diagnosed infants under the age of two at St. Jude Childrens Research Hospital (St. Jude), UCSF Benioff Childrens Hospital in San Francisco and Seattle Childrens Hospital. Mustang submitted an investigational new drug application (IND) to the FDA to initiate a pivotal multi-center Phase 2 clinical trial of MB-107 in this same patient population. The trial is expected to enroll 10 patients who, together with 15 patients enrolled in the current multi-center trial led by St. Jude, will be compared with 25 matched historical control patients who have undergone HSCT. The primary efficacy endpoint will be event-free survival. The initiation of this trial is expected soon. Mustang is targeting topline data from this trial in the second half of 2022.

Earlier this month, Mustang signed an agreement with Minaris Regenerative Medicine GmbH (Minaris), a leading contract development and manufacturing service provider for the cell and gene therapy industry, to enable technology transfer and GMP clinical manufacturing of Mustangs MB-107 lentiviral gene therapy program for the treatment of XSCID in newly diagnosed infants in Europe. Under the terms of the agreement, Minaris will perform technology transfer of the manufacturing and analytical processes, as well as their adoption to the European regulatory environment, for the GMP-compliant manufacturing of the drug product at its site in Ottobrunn, Germany, with the goal of supplying clinical trials in Europe.

MB-207 is currently being assessed in a Phase 1/2 clinical trial at the National Institute of Allergy and Infectious Diseases for XSCID patients who have been previously treated with HSCT and for whom re-treatment is indicated. Mustang expects to file an IND with the FDA to initiate a pivotal multi-center pivotal Phase 2 clinical trial of MB-207 in this same patient population in the first quarter of 2021 and is targeting topline data from this trial in the second half of 2022.

About X-linked Severe Combined Immunodeficiency (XSCID) X-linked severe combined immunodeficiency is a rare genetic disorder that occurs in approximately 1 per 225,000 births. It is characterized by the absence or lack of function of key immune cells, resulting in a severely compromised immune system and death by one year of age if untreated. Patients with XSCID have no T-cells or natural killer cells. Although their B-cells are normal in number, they are not functional. As a result, XSCID patients are usually affected by severe bacterial, viral or fungal infections early in life and often present with interstitial lung disease, chronic diarrhea and failure to thrive.

The specific genetic disorder that causes XSCID is a mutation in the gene coding for the common gamma chain (c), a protein that is shared by the receptors for at least six interleukins. These interleukins and their receptors are critical for the development and differentiation of immune cells. The gene coding for c is known as IL-2 receptor gamma, or IL2RG. Because IL2RG is located on the X-chromosome, XSCID is inherited in an X-linked recessive pattern, resulting in almost all patients being male.

About Mustang Bio Mustang Bio, Inc. is a clinical-stage biopharmaceutical company focused on translating todays medical breakthroughs in cell and gene therapies into potential cures for hematologic cancers, solid tumors and rare genetic diseases. Mustang aims to acquire rights to these technologies by licensing or otherwise acquiring an ownership interest, to fund research and development, and to outlicense or bring the technologies to market. Mustang has partnered with top medical institutions to advance the development of CAR T therapies across multiple cancers, as well as a lentiviral gene therapy for XSCID. Mustang is registered under the Securities Exchange Act of 1934, as amended, and files periodic reports with the U.S. Securities and Exchange Commission (SEC). Mustang was founded by Fortress Biotech, Inc. (NASDAQ: FBIO). For more information, visit http://www.mustangbio.com.

ForwardLooking StatementsThis press release may contain forward-looking statements within the meaning of Section 27A of the Securities Act of 1933 and Section 21E of the Securities Exchange Act of 1934, each as amended. Such statements include, but are not limited to, any statements relating to our growth strategy and product development programs and any other statements that are not historical facts. Forward-looking statements are based on managements current expectations and are subject to risks and uncertainties that could negatively affect our business, operating results, financial condition and stock value. Factors that could cause actual results to differ materially from those currently anticipated include: risks relating to our growth strategy; our ability to obtain, perform under, and maintain financing and strategic agreements and relationships; risks relating to the results of research and development activities; risks relating to the timing of starting and completing clinical trials; uncertainties relating to preclinical and clinical testing; our dependence on third-party suppliers; our ability to attract, integrate and retain key personnel; the early stage of products under development; our need for substantial additional funds; government regulation; patent and intellectual property matters; competition; as well as other risks described in our SEC filings. We expressly disclaim any obligation or undertaking to release publicly any updates or revisions to any forward-looking statements contained herein to reflect any change in our expectations or any changes in events, conditions or circumstances on which any such statement is based, except as required by law, and we claim the protection of the safe harbor for forward-looking statements contained in the Private Securities Litigation Reform Act of 1995.

Company Contacts: Jaclyn Jaffe and William Begien Mustang Bio, Inc. (781) 652-4500 ir@mustangbio.com

Investor Relations Contact: Daniel Ferry LifeSci Advisors, LLC (617) 430-7576 daniel@lifesciadvisors.com

Media Relations Contact: Tony Plohoros 6 Degrees (908) 591-2839 tplohoros@6degreespr.com

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Mapping out the mystery of blood stem cells – Science Codex

Princess Margaret scientists have revealed how stem cells are able to generate new blood cells throughout our life by looking at vast, uncharted regions of our genetic material that hold important clues to subtle biological changes in these cells.

The finding, obtained from studying normal blood, can be used to enhance methods for stem cell transplantation, and may also shed light into processes that occur in cancer cells that allow them to survive chemotherapy and relapse into cancer growth many years after treatment.

Using state-of-the art sequencing technology to perform genome-wide profiling of the epigenetic landscape of human stem cells, the research revealed important information about how genes are regulated through the three-dimensional folding of chromatin.

Chromatin is composed of DNA and proteins, the latter which package DNA into compact structures, and is found in the nucleus of cells. Changes in chromatin structure are linked to DNA replication, repair and gene expression (turning genes on or off).

The research by Princess Margaret Cancer Centre Senior Scientists Drs. Mathieu Lupien and John Dick is published in Cell Stem Cell, Wednesday, November 25, 2020.

"We don't have a comprehensive view of what makes a stem cell function in a specific way or what makes it tick," says Dr. Dick, who is also a Professor in the Department of Molecular Genetics, University of Toronto.

"Stem cells are normally dormant but they need to occasionally become activated to keep the blood system going. Understanding this transition into activation is key to be able to harness the power of stem cells for therapy, but also to understand how malignant cells change this balance.

"Stem cells are powerful, potent and rare. But it's a knife's edge as to whether they get activated to replenish new blood cells on demand, or go rogue to divide rapidly and develop mutations, or lie dormant quietly, in a pristine state."

Understanding what turns that knife's edge into these various stem cell states has perplexed scientists for decades. Now, with this research, we have a better understanding of what defines a stem cell and makes it function in a particular way.

"We are exploring uncharted territory," says Dr. Mathieu Lupien, who is also an Associate Professor in the Department of Medical Biophysics, University of Toronto. "We had to look into the origami of the genome of cells to understand why some can self-renew throughout our life while others lose that ability. We had to look beyond what genetics alone can tell us."

In this research, scientists focused on the often overlooked noncoding regions of the genome: vast stretches of DNA that are free of genes (i.e. that do not code for proteins), but nonetheless harbour important regulatory elements that determine if genes are turned on or off.

Hidden amongst this noncoding DNA - which comprise about 98% of the genome - are crucial elements that not only control the activity of thousands of genes, but also play a role in many diseases.

The researchers examined two distinct human hematopoietic stem cells or immature cells that go through several steps in order to develop into different types of blood cells, such as white or red blood cells, or platelets.

They looked at long-term hematopoietic stem cells (HSCs) and short-term HSCs found in the bone marrow of humans. The researchers wanted to map out the cellular machinery involved in the "dormancy" state of long-term cells, with their continuous self-renewing ability, as compared to the more primed, activated and "ready-to-go" short-term cells which can transition quickly into various blood cells.

The researchers found differences in the three-dimensional chromatin structures between the two stem cell types, which is significant since the ways in which chromatin is arranged or folded and looped impacts how genes and other parts of our genome are expressed and regulated.

Using state-of-the-art 3D mapping techniques, the scientists were able to analyze and link the long-term stem cell types with the activity of the chromatin folding protein CTCF and its ability to regulate the expression of 300 genes to control long-term, self-renewal.

"Until now, we have not had a comprehensive view of what makes a stem cell function in a particular way," says Dr. Dick, adding that the 300 genes represent what scientists now think is the "essence" of a long-term stem cell.

He adds that long-term dormant cells are a "protection" against malignancy, because they can survive for long periods and evade treatment, potentially causing relapse many years later.

However, a short-term stem cell that is poised to become active, dividing and reproducing more quickly than a long-term one, can gather up many more mutations, and sometimes these can progress to blood cancers, he adds.

"This research gives us insight into aspects of how cancer starts and how some cancer cells can retain stem-cell like properties that allow them to survive long-term," says Dr. Dick.

He adds that a deeper understanding of stem cells can also help with stem cells transplants for the treatment of blood cancers in the future, by potentially stimulating and growing these cells ex vivo (out of the body) for improved transplantation.

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Scientists Reveal a New Drug That Directs Stem Cells To Desired Sites – Science Times

Researchers at Stanford Burnham Prebys Medical Discovery Institute recently developed a drug that can lure stem cells to impaired tissue and enhance the efficacy of treatment.

This is considered a "scientific first," not to mention a major advance for the field of regenerative drugs. Such a discovery, which theProceedings of the National Academy of Sciences or PNASpublished could enhance the present stem cell treatments developed to cure such neurological disorders like stroke, spinal cord injury, ALS or other amyotrophic lateral sclerosis, as well as other neurodegenerative diseases -- and have their use expanded to new conditions such as arthritis or heart disease.

In the study, toxic or green cells disappeared when mice with a neurodegenerative condition were given both therapeutic or red cells and the drug SDV1a, which matched with delayed onset of symptoms and longer lives.

(Photo : Stem Cell Research via Getty Images) In this undated handout photo released by the Institute for Stem Cell Research in 2005, neurons (red) and astrocytes (green), which can be made from neural stem cells, are seen.

Results Suggesting Efficacy of the Drug

The study results proposed that SDV1a can be used to enhance the stem cell treatments' efficacy. According to Evan Snyder, MD, PhD, theCenter for Stem Cells & Regenerative Medicine at Stanford Burnham Prebysprofessor and director, "the ability to instruct a stem cell where to go in the body, or to a particular region of a given organ is the 'Holy Grail' for regenerative medicine.

Snyder, who's also the senior author of the study, added, now, for the first time, stem cells can be directed to a desired area and focus its therapeutic effect.

Almost a decade-and-a-half back, the senior author, together with his team, found that stem cells are drawn to infection, a biological 'fire alarm' indicating that damage has taken place.

Nevertheless, using inflammation as a healing appeal is not possible since an inflammation environment can be dangerous to the body. Hence, researchers have been searching for mechanisms to help in the migration of stem cells or 'home' to the body's desired areas.

Such a mechanism or tool, according to reports on this new finding, would be a great contributor for disorders in which preliminary inflammatory indicators disappear over time, like chronic spinal cord injury or stroke, and conditions where the inflammation's role is not clearly understood, like heart disease, for one.

Fortunately, after decades of investing in stem cell science, scientists are now making "tremendous progress," saidCalifornia Institute for Regenerative Medicine or CIRMpresident and CEO Maria Millan, MD said, in their understanding of the manner such cells work and the manner they can be attached to help reverse disease or an injury.

The CIRM partially funded this new study. Millan also said, Snyder's group has identified a medicine that could enhance "the ability of neural stem cells to home to sites of injury and initiate repair."

More so, the president and CEO also explained, the drug candidate could help fast-track the stem cell treatments' development, specifically for conditions including Alzheimer's disease and spinal cord injury.

In the research, study investigators modified an inflammatory molecule called CXCL12, which the Snyder's group discovered previously, could guide healing stem cells to areas that need repair to develop the SDV1a.

As such, this new medicine works by improving stem cell binding and minimizing inflammatory indicating and can be injected anywhere to attract stem cells to a particular site without causing any inflammation.

Since such inflammation can be dangerous, Snyder explained, they modified CXL12 by "tripping away the risky beat and maximizing the good bit."

Now, he added, they have a drug, drawing stem cells to an area of pathology, but not creating or worsening the unwanted infection.

"Now, we have a drug that draws stem cells to a region of pathology, but without creating or worsening unwanted inflammation."

Furthermore, to present that the new medication can improve the effectiveness of stem cell therapy, the scientists implanted SDV1a and human neural stem cells into the brains of mice thatSandhoff disease, a neurodegenerative disease.

The scientists have already started testing the ability of SDV1a to enhance stem cell therapy in a mouse model of Lou Gehrig's disease, also known as ALS, which results from progressive loss of motor neurons in the brain.

Snyder said they are optimistic that the mechanism of action of this new drug may potentially benefit various neurodegenerative disorders and non-neurological conditions like arthritis, heart disease, and even brain cancer.

Interestingly, he also explained, since CXL12 and its receptor is said to be implicated in cytokine storm that exemplifies severeCOVID-19, some of their understandings of how to constrain infection without controlling other normal procedures selectively may be helpful in that field, as well.

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Scientists Reveal a New Drug That Directs Stem Cells To Desired Sites - Science Times

Celularity Announces Dosing of First Patient in Phase I Study of Human Placental Hematopoietic Stem Cell-Derived Natural Killer Cells (CYNK-001) in…

Details Category: DNA RNA and Cells Published on Wednesday, 25 November 2020 12:03 Hits: 420

FLORHAM PARK, NJ, USA I November 24, 2020 I Celularity, Inc., a clinical-stage cell therapeutics company focused on the development of innovative allogeneic placenta-derived cellular therapies, announced today that the first patient was dosed in its Phase 1 clinical study of human placental hematopoietic stem cell-derived natural killer cells (CYNK-001) in adults with recurrent glioblastoma multiforme.

"Celularity is committed to the development of innovative therapeutic tools to treat serious diseases, particularly targeting diseases with unmet medical needs that have a devastating impact on patients and families.As testimony to this commitment, we are extremely excited to announce the dosing of our first patient in our first clinical trial for, glioblastoma multiforme (GBM). Through the study team's diligent efforts, we were able to rapidly complete the start-up activities and to accelerate the commencement of patient screening, enrollment, and first dosing in this important study," said Robert J. Hariri, M.D., Ph.D., Celularity's Founder, Chairman and Chief Executive Officer.

This study (ClinicalTrials.gov Identifier:NCT04489420) will determine the maximum safe dose (MSD) of CYNK-001 which are culture-expanded NK cells derived from human placental CD34+ cells. The intravenous (IV) cohort will receive repeat administration of CYNK-001 cells after lymphodepleting chemotherapy. The intratumoral (IT) cohort will not receive lymphodepletion. The safety of this treatment will be evaluated, as researchers investigate the role of NK cells in the treatment of recurrent glioblastoma.

"Glioblastoma patients have poor survival and novel treatments are urgently needed for this patient population," said Nazanin Majd, M.D., Ph.D., assistant professor of Neuro-Oncology at The University of Texas MD Anderson Cancer Center and principal investigator of the study. "Placental-derived NK cells are a promising approach in treatment of GBM patients as these cells have been shown to kill GBM tumor cells in pre-clinical animal studies. This trial offers an innovative immunotherapy approach where exogenously manufactured NK cells will be administered to GBM patients with the goal of shrinking the tumor and improving outcomes."

In a related development, the Company also announced that its abstract highlighting the details of this Phase 1 study was accepted for a poster presentation at the 25thAnnual Meeting and Education Day of the Society for Neuro-Oncology (SNO) which will occur November 19-21, 2020.

About CYNK-001 CYNK-001 is an investigational cryopreserved allogeneic, off-the-shelf NK cell therapy developed from placental hematopoietic stem cells. CYNK-001 is being investigated as a potential treatment option in adults with COVID-19, as well as for various hematologic cancers and solid tumors. NK cells are a unique class of immune cells, innately capable of targeting cancer cells and interacting with adaptive immunity. CYNK-001 cells derived from the placenta are currently being investigated as a treatment for acute myeloid leukemia (AML), multiple myeloma (MM), and glioblastoma multiforme (GBM).

About Celularity Celularity, headquartered in Florham Park, N.J., is a next-generation Biotechnology company leading the next evolution in cellular medicine by developing off-the-shelf allogeneic cellular therapies. Celularity's innovative approach to cell therapy harnesses the unique therapeutic potential locked within the cells of the postpartum placenta. Through nature's immunotherapy engine the placenta Celularity is leading the next evolution of cellular medicine with placenta-derived T cells, NK cells, and pluripotent stem cells to target unmet and underserved clinical needs in cancer, infectious and degenerative diseases. To learn more visit celularity.com.

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Celularity Announces Dosing of First Patient in Phase I Study of Human Placental Hematopoietic Stem Cell-Derived Natural Killer Cells (CYNK-001) in...

The stem/progenitor landscape is reshaped in a mouse model of essential thrombocythemia and causes excess megakaryocyte production – Science Advances

INTRODUCTION

The myeloproliferative neoplasms are a family of clonal blood disorders characterized by overproduction of platelets [essential thrombocythemia (ET)], overproduction of red blood cells [polycythemia vera (PV)], or bone marrow fibrosis [myelofibrosis (MF)]. The genetic bases for these diseases have largely been described: Mutations in JAK2 are found in 99% of PV and 50 to 60% of ET and MF cases, while frameshift mutations in CALR are responsible for 25 to 40% of cases of ET and MF (13). Frameshift mutants of calreticulin (CALR) have a novel C terminus that acts as a rogue ligand for the thrombopoietin receptor, MPL, and activates Janus kinasesignal transducer and activator of transcription (JAK-STAT) signaling (4, 5). We recently described the generation of a mouse model of mutant CALR-driven ET that faithfully recapitulates the key phenotypes of the human disease, namely, increased numbers of cells throughout the megakaryocytic (MK) lineage, particularly platelets (6).

Hematopoiesis is classically modeled as a stepwise process beginning with a multipotent hematopoietic stem cell (HSC), which is functionally defined by its capability to reconstitute multilineage hematopoiesis when transplanted into a myeloablated recipient (7). This HSC then transits through a series of intermediate stages with increasing lineage restriction to terminally differentiated blood cells (8, 9). However, newly popularized single-cell technologies such as single-cell RNA sequencing (scRNAseq) have reshaped our understanding of hematopoiesis and suggest that cells travel through a continuum of differentiation rather than a series of rigidly defined stages (10, 11). In a recent demonstration of the power of scRNAseq to untangle complex differentiation processes, it was used to interrogate the transcriptomes of hematopoietic stem and progenitor cells (HSPCs) to identify novel intermediate populations within erythropoiesis, which could then be isolated and characterized via fluorescence-activated cell sorting (FACS) strategies (12).

While HSCs are traditionally defined to be capable of reconstituting all blood lineages in transplantation experiments, there is an increasing body of evidence that some cells within the immunophenotypic HSC compartment already exhibit some lineage bias or restriction (1315). Studies in mice have shown that MK and erythroid lineages may branch off before other myeloid and lymphoid lineages (1618), and lineage tracing studies have shown the MK lineage to be the earliest generated from HSCs (1923). A transposon-based lineage tracing strategy showed some tags to be shared between long-term HSCs (LT-HSCs) and megakaryocyte progenitors (MkPs) but not multipotent progenitors (MPPs), indicative of a direct pathway linking HSCs and MK bypassing MPP (19). We therefore asked whether our mouse model of mutant CALR-driven ET could allow us to interrogate the differences in the hematopoietic landscapes between wild-type (WT) and disease model mice, with a particular focus on MK trajectories.

We generated scRNAseq data from FACS-sorted HSPCs [Lin Sca1+ cKit+ (LSK) and Lin Sca1 cKit+ (LK) populations] from a pair of WT and CALR DEL (knock-in of del52 allele) homozygous (HOM) littermate mice. After quality control, we retained 11,098 WT (5959 LSK and 5139 LK) and 15,547 HOM (7732 LSK and 7815 LK) cells for downstream analysis. We began by defining highly variable genes, which we used to perform principal component analysis (PCA) and generate a k = 7 nearest-neighbor graph. Cells were then assigned to clusters by mapping onto a previously published dataset of 44,082 LK cells (24), with manual annotation of clusters (fig. S1A). Cells from all major blood lineages can be seen and separate into distinct trajectories. To determine which cells were over- or underrepresented in the CALR DEL HOM mouse, we compared relative numbers of cells from each genotype. The most notable changes in relative cell abundance were increased numbers of cells in the HSC and MK clusters (fig. S1B), consistent with the increased platelet phenotype of our ET mouse model (6). We repeated the analysis on a second pair of WT and CALR DEL HOM littermate mice, in this case retaining 3451 WT (972 LSK and 2479 LK) and 12,372 HOM (4548 LSK and 7824 LK) cells for downstream analysis after quality control, and again observed an increase in cells in the HSC and MK clusters (fig. S1C).

To better understand the subgroups of cells within stem/progenitor cells, we chose to use partition-based graph abstraction (PAGA) (25) to visualize our data. This method generates a graph in which each node represents a group of closely related cells and edge weights correspond to the strength of connection between two nodes. We again compared relative abundances between WT and CALR DEL HOM mice and colored the nodes so red nodes are enriched in CALR mice, while blue nodes are underrepresented. We observed that the fine cluster that was most overrepresented in CALR DEL HOM mice (marked with an arrow) fell between the HSC and MK clusters in both repeats (Fig. 1A and fig. S1D). We plotted the expression of the MK markers Cd9, Itga2b (CD41), Mpl, Pf4, and VWF in our PAGA and hypothesized two MK trajectories, as indicated by the green and blue arrows (fig. S1E). As the fine cluster most overrepresented in CALR DEL HOM mice would be an intermediate on one of these trajectories (green arrow), we further hypothesized that these cells would be of particular relevance in the disease setting of mutant CALR-driven ET and thus aimed to further study them.

(A) PAGA of scRNAseq data from WT and CALR DEL HOM mice. Red nodes represent those present at increased abundance in CALR DEL HOM mice, while blue nodes represent those at reduced abundance. The most highly enriched node is noted with an arrow. (B) RNA expression of the flow cytometry markers CD48, EPCR (Procr), and CD150 (Slamf1) plotted on PAGA graphs from (A). Cells within our node of interest (marked with an arrow) are CD48, EPCR, and CD150+. (C) Representative plots of SLAM cells from WT and CALR DEL HOM mice. CALR DEL HOM mice show higher numbers of both ESLAMs (Lin CD48 CD150+ CD45+ EPCR+) and pMKPs (Lin CD48 CD150+ CD45+ EPCR). FITC, fluorescein isothiocyanate; PE, phycoerythrin. (D) Quantification of bone marrow frequency of pMKPs in WT and CALR DEL HOM mice. The frequency of pMKPs within live bone marrow mononuclear cells (BMMNCs) is significantly increased in CALR DEL HOM mice (WT, n = 3, 0.00029 0.00008; HOM, n = 3, 0.0025 0.0008; *P = 0.042).

We examined the expression of a series of genes typically used to FACS isolate different hematopoietic populations and found this fine cluster to be CD48, EPCR (Procr), and CD150+ (Slamf1) (Fig. 1B). We designed an immunophenotypic scheme to identify and isolate cells from this fine cluster, defining them to be Lin, CD150+, CD48, EPCR, and CD45+. On the basis of our subsequent characterization of these cells, we eventually termed them proliferative MkPs or pMKPs. Consistent with our transcriptomic data, when comparing WT mice to CALR mutant mice, we found an increase in the frequency of pMKPs in CALR DEL HOM mice as assayed by flow cytometry (Fig. 1, C and D). We also found that pMKPs were expanded in CALR DEL HET mice, albeit to a lesser extent than observed in CALR DEL HOM mice (fig. S1F).

To characterize pMKPs, we FACS-sorted single ESLAM (EPCR+ SLAM) HSCs (Lin CD45+ CD48 CD150+ EPCR+) (26), pMKPs (Lin CD45+ CD48 CD150+ EPCR), and MkPs (Lin Sca1 cKit+ CD41+ CD150+) (27) (fig. S2A) from WT mice into individual wells of a 96-well plate and observed them every day for 4 days. We analyzed our sort data and observed that in pMKPs, markers traditionally used to define MkPs were Sca1/lo/mid, cKit+, and CD41mid/+ (fig. S2B). pMKPs were additionally CD9+ and MPL+ (fig. S2C). On each day, we classified each well with surviving cell(s) into one of four categories, using cell size as a proxy for megakaryopoiesis (2830): (i) exactly one large cell, presumed to be a megakaryocyte; (ii) multiple large cells; (iii) mixed expansion, with both large and small cells; and (iv) expansion with only small cells (Fig. 2A). To verify that larger cells represented MK cells, using cells from day 4 ESLAM, pMKP, and MkP colonies, we quantified average CD41 intensity via immunofluorescence and classified cells as small or large via bright-field microscopy, using a small/large dichotomy assessed via bright-field microscopy to match the classification scheme used in Fig. 2A. Here, we confirmed that large cells have significantly higher CD41 staining, supporting their identification as MK (fig. S2D). In some cases, particularly large cells within mixed colonies showed very high CD41 staining and membrane extensions that resembled proplatelets (representative picture is shown in fig. S2E). Furthermore, we sorted pMKPs from VWF (von Willebrand factor)green fluorescent proteinpositive (GFP+) mice and found that large cells had a very bright VWF-GFP signal, supporting their identification as MK. Smaller cells in these clones had a much dimmer VWF-GFP signal, suggesting that they likely represent more immature cells that have not progressed as far through megakaryopoiesis (fig. S2F).

(A) Representative pictures of in vitro culture output of single ESLAMs, pMKPs, and MkPs into four categories: 1 MK, >1 MK, mixed, or proliferation only. (B) Classification of in vitro culture output of single ESLAMs, pMKPs, and MkPs at day 4 after FACS isolation. ESLAMs almost exclusively proliferated without producing megakaryocytes, while MkPs almost exclusively produced MKs, usually producing only a single MK. pMKPs showed a strong MK bias but were more likely to proliferate than were MkPs. ESLAMs, n = 306 wells from five experiments; pMKPs, n = 291 wells from six experiments; MkPs, n = 235 wells from five experiments. Chi-square test, ****P < 0.0001. (C) Timing of megakaryopoiesis in ESLAMs, pMKPs, and MkPs. Individual cells were observed for 4 days after sort, and the first date on which cell(s) showed signs of megakaryopoiesis was noted. MkPs were faster to begin megakaryopoiesis than were pMKPs (at day 2, MkPs: 89.5 0.7%; pMKPs: 50 6%; *P = 0.02). ESLAMs, n = 5; pMKPs, n = 6; MkPs, n = 5. (D) Log2-transformed cell counts of megakaryocytes from pMKPs and MkPs after 4 days of culture. Each point represents the average value from one of four separate experiments. Average of four experiments: pMKP, 1.12; MkP, 0.412, *P = 0.0295. (E) Histogram of the minimum number of cell divisions for 103 pMKPs and 158 MkPs that produced only megakaryocytes after 4 days of culture across four experiments. Chi-square test, ***P = 0.0001.

The vast majority of ESLAMs showed expansion with only small cells at day 4, consistent with being highly primitive HSCs with considerable proliferative potential, but not yet producing megakaryocytes. Similarly, as predicted for MkPs, more than 95% of wells showed exclusively production of MKs at day 4, with the majority producing only one MK. This lack of in vitro proliferation for single MkPs is consistent with previously published results, where 75% of MkPs did not divide and none produced more than 10 MKs (31). pMKPs exhibited an intermediate phenotype: While approximately 90% of wells showed production of some MKs, they were much more likely to produce multiple MK than were MkPs. In particular, pMKPs frequently proliferated into mixed colonies with both large and small cells, a behavior that was rarely seen for either ESLAMs or MkPs (Fig. 2B). Kinetic analysis showed that MkPs were faster to begin megakaryopoiesis than were pMKPs (Fig. 2C), and when considering only wells that produced only MKs, pMKPs produced more MKs than did MkPs (Fig. 2, D and E). pMKPs maintained their MK bias even when incubated under pro-erythroid or pro-myeloid conditions (fig. S3A). Culturing cells with thrombopoietin (THPO) increased the proportion of pMKPs that formed colonies with multiple MKs while reducing the number of mixed colonies (fig. S3B). To verify that our observed MK bias is not simply due to culture conditions supporting only megakaryopoiesis, we cultured ESLAMs under the same conditions for 10 days followed by flow cytometric analysis and observed multilineage differentiation (fig. S3C).

To examine the extent of overlap between our pMKPs and traditionally defined MkPs, we stained bone marrow with a panel incorporating all necessary markers and index sorted single pMKPs and MkPs. On the basis of index sort values, 97% of MkPs were CD45+, 50% were EPCR, and only 2% were CD48; when taken together, fewer than 1% of immunophenotypic MkPs also fell within the pMKP gate (fig. S3D); thus, pMKPs and MkPs can be FACS-separated on the basis of CD48 and EPCR. In contrast, we found that an average of 51% of pMKPs were also immunophenotypically MkPs (CD41+ Sca1 cKit+) (fig. S3E). As we observed a partial overlap between pMKPs and MkPs, we used our index sort data to assign each pMKP an overlap score based on the levels of CD41, Sca1, and cKit: 1/3 if only one marker overlapped, 2/3 if two overlapped, and 3/3 for pMKPs that also fall within the MkP immunophenotypic gate. No pMKPs had an overlap score of 0/3. We used the same classification scheme as in Fig. 2B and found that lower overlap scores correlated to a more proliferative, less MK-restricted phenotype: The pMKPs that are least similar to MkPs are the most proliferative and the least restricted to the MK lineage, although they still display a strong preference for MK production (fig. S3F). pMKPs with the lowest overlap score took the longest to enter megakaryopoiesis (fig. S3G). Together, our data indicate that pMKPs represent a group of cells with an MK bias and an increased proliferative potential as compared to traditionally defined MkPs.

We next determined whether pMKPs were capable of producing platelets in vivo. We made use of CD45.2 VWF-GFP donor mice and cKit W41/W41 CD45.1 recipient mice, which allowed us to track platelets (via VWF-GFP) and nucleated cells (by CD45.1/CD45.2 staining) (Fig. 3A). We FACS-sorted ESLAMs, pMKPs, and MkPs from VWF-GFP donor mice and transplanted 30, 60, or 120 cells per recipient into sublethally irradiated W41 mice along with 250,000 spleen MNCs (mononuclear cells) (SPMNCs) as helper cells and assayed peripheral blood chimerism every week for 4 weeks and at 16 weeks. We did not sort on VWF-GFP+ at this stage, but flow cytometry analysis showed that ESLAMs, pMKPs, and MkPs were all highly enriched for VWF-GFP expression when compared to total bone marrow (fig. S4A). We also transplanted one mouse per cohort with 250,000 SPMNCs alone to serve as a negative control to help with gating to avoid false positives. Representative gating strategies are shown in fig. S4 (B and C). As expected, ESLAMs were able to generate relatively high levels of platelets at all three cell doses, starting with a very low level at week 1 and increasing over the course of 4 weeks and continuing up to 16 weeks (although one recipient of 30 ESLAMs was lost to follow-up before the 16-week time point). pMKPs and MkPs were only able to reconstitute platelets at a very low level (1/105 to 1/104), even at the highest cell dose (Fig. 3, B to D and summarized in E). Low levels of donor-derived platelets were detected in 10 of 12 pMKP recipients and 8 of 13 MkP recipients within the first 4 weeks; extended observation up to 16 weeks showed that few recipients continued to produce VWF-GFP+ platelets, although all 3 pMKP recipients at the highest dose still showed VWF-GFP+ platelets. ESLAMs successfully produced CD11b+ myeloid cells in 10 of 10 recipients across varying cell doses, while pMKPs and MkPs only produced CD11b+ cells at a low level in 3 of 12 and 2 of 10 recipients, respectively (fig. S4, D to F and summarized in G). Therefore, we concluded that while pMKPs and MkPs have limited capabilities in a transplantation experiment, they both show an MK bias, in agreement with their in vitro behaviors. These low levels of reconstitution suggest that pMKPs and MkPs do not divide considerably in vivo, again similar to in vitro data.

(A) Schematic of VWF-GFP+ transplantation strategy. ESLAMs, pMKPs, and MkPs were sorted from VWF-GFP+, CD45.2 donor mice and transplanted into sublethally irradiated cKit W41/W41 CD45.1 recipients. PB, peripheral blood. (B) Platelet reconstitution from 30 donor cells. (C) Platelet reconstitution from 60 donor cells. (D) Platelet reconstitution from 120 donor cells. (E) Table summarizing numbers of mice with successful platelet production from ESLAMs, pMKPs, and MkPs. Here, transplanted cells were defined to have produced platelets if platelets were observed at a level of at least 1 in 105 at one or more time points within the first 4 weeks after transplantation.

Our single-cell transcriptomic analysis showed pMKPs to be an intermediate stage on an MK trajectory maintaining CD48 negativity (Fig. 1B and green arrow in fig. S1E), which suggests that they bypass the traditional MPP2 pathway (blue arrow in fig. S1E). We therefore asked whether we could show production of pMKPs from HSCs in an MPP2-independent manner by making use of a mouse model allowing inducible depletion of HSPCs. In this model, Tal1-Cre/ERT mice are crossed with R26DTA mice, wherein treatment with tamoxifen leads to specific expression of diphtheria toxin in HSCs and primitive progenitors and hence suicidal depletion of these early populations (Fig. 4A) (32). Within 6 weeks after HSC depletion, very few LT-HSCs remain, but levels of MPPs, committed progenitors, and mature blood cells are only slightly lower than in control animals (32). We reasoned that if pMKPs arise directly from HSCs, they should be depleted to a similar extent as HSCs, while if they arise from an MPP pathway, they should be depleted to a similar extent as MPPs (i.e., to a lesser extent than HSCs).

(A) Schematic of DTA (diphtheria toxin fragment A) HSC depletion model experiment. Tal1-CreERT/R26DTA mice were treated with four doses of tamoxifen at 0.1 mg/g to induce suicidal depletion of HSCs and then euthanized after 6 weeks for bone marrow (BM) analysis. (B) Frequencies of stem and progenitor cells with or without stem cell depletion. Cell populations that were significantly diminished by suicidal depletion of HSCs include ESLAMs (Cre, 17.1 10.8/105 BMMNC; Cre+, 4.3 2.0/105 BMMNC; *P = 0.012), LTHSCs (LSK CD48 CD150+) (Cre, 15 12/105 BMMNC; Cre+, 3.6 1.7/105 BMMNC; *P = 0.031), pMKPs (Cre, 13.0 7.6/105 BMMNC; Cre+, 4.1/105 BMMNC; *P = 0.013), and MkPs (Cre, 44.2 26.4/105 BMMNC; Cre+, 21.4 6.1/105 BMMNC; *P = 0.046); Cre, n = 8 and Cre+, n = 10. MPP2 (Cre, 25.1 29.1/105 BMMNC; Cre+, 13.3 3.6/105 BMMNC; P = 0.48) and preMegE (Cre, 90.0 62.9/105 BMMNC; Cre+, 73.9 29.6/105 BMMNC; P = 0.66) populations were depleted to lesser extents that did not reach statistical significance; Cren = 4 and Cre+n = 6. ns, not significant.

We compared mice carrying either no Cre or Tal1-Cre/ERT after treatment with tamoxifen to induce specific depletion of HSCs. We observed a depletion of approximately 75% in the numbers of HSCs [whether using ESLAM markers or LT-HSC (LSK CD48 CD150+) markers] and a 68% reduction in the numbers of pMKPs in HSC-depleted mice. By contrast, there was no significant reduction in MPP2 or preMegE populations, while MkPs were reduced by approximately 51% (Fig. 4B). Consistent with previously published results, we observed no statistically significant reduction in other multipotent populations, including MPP3 and MPP4 (33), and committed progenitor populations, including CFU-E (erythroid colony-forming units), pCFU-E, pGM (pre-granulocyte/macrophage), and GMP (granulocyte/monocyte progenitors) (fig. S5) (27). We noted that one Cre mouse was an outlier, with noticeably higher frequencies of almost all progenitor populations, and tested removing this outlier to ensure our conclusions were not unduly relying on this mouse. With the outlier removed, we calculated reductions of 68% in ESLAMs (P = 0.0001), 60% in pMKPs (P = 1.5 105), and an increase of 24% in MPP2 (P = 0.50). Our analysis is therefore robust to the removal of this outlier and demonstrates that the reduction in pMKP levels correlates more closely to that of ESLAMs than that of MPP2. Together, these data support a model in which pMKPs are produced from HSCs in an MPP2-independent manner and MkPs can be generated from pMKPs or via MPP2, accounting for their intermediate level of reduction.

After characterizing the pMKP population in WT mice, we next asked whether there were qualitative differences between WT and CALR DEL HOM cells along the MK trajectory and not solely a quantitative difference. To do so, we sorted single ESLAMs, pMKPs, and MkPs from WT and CALR DEL HOM mice and monitored their in vitro behavior over 4 days. While very few WT ESLAMs showed any MKs within the first 4 days after sort, a higher proportion of CALR DEL HOM ESLAMs showed MKs within mixed colonies (Fig. 5A). CALR DEL HOM pMKPs showed similar proportions of wells in each category (Fig. 5B), while CALR DEL HOM MkPs were more likely to form multiple MKs and less likely to form a single MK (Fig. 5C). To assess the statistical significance of these differences, using a Fishers exact or chi-square test required consolidation of our data into fewer categories, as some categories contained values that were too low (for example, for day 4 ESLAMs, the categories 1 MK and >1 MK were 0 in both WT and HOM). We thus consolidated ESLAM data into two categoriesno MK and MK (Fig. 5D)and pMKP and MkP data into three categories1 MK, >1 MK, and mixed + prolif only (Fig. 5, E and F). This showed that CALR DEL HOM ESLAMs were significantly more likely to form MKs (Fig. 5D). CALR DEL HOM pMKPs showed no statistically significant difference, suggesting no change in their MK bias or proliferative behavior compared to WT pMKPs (Fig. 5E). CALR DEL HOM MkPs were significantly more proliferative than were WT MkPs (Fig. 5F). We also extended our observation of ESLAM clones to day 7 and observed an even stronger increase in the production of megakaryocytes from CALR DEL HOM ESLAMs, an increase noted both in wells producing mixed clones and in those producing MK-only clones (Fig. 5, G and H).

(A) Classification of in vitro culture output of single ESLAMs from WT and CALR DEL HOM mice at day 4, using the classification scheme as in Fig. 2A. WT, n = 223; HOM, n = 225. (B) Classification of in vitro culture output of single pMKPs from WT and CALR DEL HOM mice at day 4; WT, n = 117; HOM, n = 161. Chi-square test P = 0.9201. (C) Classification of in vitro culture output of single MkPs from WT and CALR DEL HOM mice at day 4; WT, n = 136; HOM, n = 152. (D) Reclassification of data from (A) into two categories (MK or no MK) for a Fishers exact test, *P = 0.0191. (E) Reclassification of data from (B) into three categories (1 MK, >1 MK, and mixed + prolif only) for a chi-square test, P = 0.8183. (F) Reclassification of data from (C) into three categories (1 MK, >1 MK, and mixed + prolif only) for a chi-square test, **P = 0.0069. (G) Classification of in vitro culture output of single ESLAMs at day 7; WT, n = 136; HOM, n = 152. (H) Reclassification of data from (G) into two categories (MK or no MK) for a Fishers exact test, **P = 0.0014. (I) pMKPs as a proportion of live cells generated from in vitro culture of WT and CALR DEL HOM ESLAMs, assessed at day 3. WT, 0.062 0.015; HOM, 0.193 0.036, *P = 0.0135, n = 3 independent mice.

We also considered log2-transformed cell counts from those wells with exclusively megakaryocytes (i.e., 1 MK and >1 MK). In some cases, we observed the death of a cell or cells over our 4-day observation period; to account for cell death, we used the maximum number of cells observed over these 4 days. Mann-Whitney U tests showed no significant difference for pMKPs but a significant increase in MK production from CALR DEL HOM MkPs (fig. S6, A and B). Similarly, calculations of the minimum number of divisions required to produce the observed number of MKs found no difference for pMKPs but a significant shift to more divisions from CALR DEL HOM MkPs (fig. S6, C and D). We also cultured ESLAMs in vitro and assayed for the production of pMKPs, finding that CALR DEL HOM ESLAMs gave rise to significantly more pMKPs than did their WT counterparts (Fig. 5I). Together, we conclude that CALR DEL is acting at multiple stages of megakaryopoiesis, promoting an MK bias from the earliest HSC compartments and increased proliferation at both HSC and MkP levels. While pMKPs are increased in number in CALR DEL HOM mice, these cells do not show altered proliferation or MK bias in vitro.

Last, we made use of our scRNAseq data to compare gene expression between WT and CALR DEL HOM cells along the MK trajectory. We considered cells within 2 of the 13 clusters defined by our transcriptomic data (HSC and MK; fig. S1A) and 1 fine cluster (pMKP; arrow in Fig. 1A) (Fig. 6, A to C). As the pMKP fine cluster had fewer cells (24 in WT and 247 in CALR DEL HOM) than the larger HSC and MK clusters, we were only able to confidently call a small number of differentially expressed genes (DEGs) within this cluster. We performed Ingenuity Pathway Analysis (IPA) to determine which biological pathways and upstream regulators were most affected in the HSC and MK clusters; the small numbers of DEGs in pMKPs resulted in no statistically significant hits via IPA. The most affected canonical pathways fell into three broad groups: cell cycle (in blue), unfolded protein response (gold), and cholesterol biosynthesis (green) (Fig. 6, D and E). Full lists of canonical pathways, P values, and z scores are available in tables S1 (HSC) and S2 (MK). Genes contributing to these three pathways are highlighted in the same colors in Fig. 6, A to C; we note that pMKPs also show up-regulation of several UPR (unfolded protein response)associated genessuch as Hspa5, Pdia3, and Pdia6in addition to two known STAT targets (Ifitm2 and Socs2).

(A to C) Volcano plots showing DEGs between WT and CALR DEL HOM cluster 3 (HSC) (A), pMKP fine cluster (B), and cluster 11 (MK) (C). Genes within certain representative Gene Ontology (GO) terms are colored: regulation of cholesterol biosynthetic process (GO:0045540) (green), response to ER stress (GO:0034976) (gold), and regulation of mitotic cell cycle (GO:0007346) (blue). Other DEGs are colored in red. (D and E) Bar graphs showing z scores for up-regulated canonical pathways in cluster 3 (HSC) (C) and cluster 11 (MK) (D), filtered by P < 0.01 and z score of >1 or <1. Bars are highlighted in green for cholesterol biosynthesis, gold for ER stress/unfolded protein response, or blue for cell cycle. (F) Upstream regulator analysis. Hits were filtered by P < 0.01. Bar graph showing the 10 most up-regulated and 10 most down-regulated predicted upstream regulators, when comparing WT and CALR DEL HOM cluster 3 (HSC) (blue) and cluster 11 (MK) (red), as measured by combining the z scores from WT and MK analyses.

While cell cycle and UPR have previously been described as up-regulated in human CD34+ cells with CALR mutation (34), the discovery of cholesterol biosynthesis was somewhat unexpected. However, this aligned with the predicted significant activation of the lipid and cholesterol biosynthetic transcriptional machinery controlled by the sterol regulatory elementbinding proteins (SREBPs; SREBF1 and SREBF2) and the SREBF chaperone (SCAP) and their inhibitor insulin-induced gene 1 (INSIG1) (Fig. 6F). Moreover, as discussed further below, a role for cholesterol biosynthesis in a proliferative, platelet-biased blood disorder is biologically plausible. Upstream regulator analysis also pointed to activation of ERN1 (Ire1) and Xbp1, two constituents of UPR, as well as STAT5 (table S3), which is consistent with previous demonstrations that mutant CALR acts via STAT signaling (4, 3537). We additionally observed other previously undescribed signaling processes to be predicted to be activated, including drivers of proliferation such as CSF2 [granulocyte-macrophage colony-stimulating factor (GM-CSF)] and hepatocyte growth factor (HGF), or repressed, like the known tumor suppressors TP53 and let-7.

Single-cell transcriptomic approaches have allowed detailed examinations of differentiation landscapes in both normal and perturbed hematopoiesis without a requirement to initially define populations based on a set of cell surface markers. We therefore used single-cell transcriptomics to investigate our recently generated mutant CALR-driven mouse model of ET and found an expected increase in both HSCs and MK lineage cells. We also found an increase in a previously unknown group of cells, here termed pMKPs, linking HSCs with the MK lineage. In vitro, pMKPs displayed behaviors intermediate to those of HSCs and MkPs: Similarly to HSCs, they had some proliferative potential, but similarly to MkPs, they were almost exclusively restricted to the MK lineage. In transplantations, pMKPs and MkPs showed similar behavior: They both transiently produced platelets at a low level. We hypothesize that while pMKPs are more proliferative than MkPs in vitro, neither population is capable of sufficient proliferation to significantly contribute to platelet production in the transplant setting. While this manuscript was in preparation, another group described separating SLAM (Lin CD48 CD150+) cells based on EPCR and CD34, finding that EPCR SLAM cells performed poorly in transplants and showed gene expression profiles (high Gata1, Vwf, and Itga2b) indicative of MK bias (38), results that are broadly consistent with our own.

Our characterization of pMKPs accords well with an increasing understanding that at least a portion of megakaryopoiesis occurs via an early branch point directly from HSCs. While the standard model of hematopoiesis shows megakaryocytes subsequent to MPP2, lineage tracing experiments have shown that some MkPs are generated in an MPP2-independent way (19). Furthermore, in vivo labeling of the most primitive HSCs showed that within 1 week of label induction in LT-HSCs, label can be seen in MK lineages but no other, indicating that the HSC-to-MK pathway can be noticeably faster than pathways producing other lineages (22). Our results suggest that pMKPs are likely to arise independently of the MPP2 stage, as suicidal depletion of the earliest HSPCs reduces pMKPs to a much greater extent than MPP2s. It is therefore tempting to speculate that our pMKP sort scheme may isolate intermediate cells on this shorter, faster bypass trajectory. A recent study of JAK2 V617F-driven MF in humans attributed increased megakaryopoiesis to the expansion of both traditional MkPs and a novel MkP-like population, suggesting that cells that may be analogous to our pMKPs are relevant in human disease (30).

We also investigated an outstanding question about at which stages mutant CALR acts to drive a platelet phenotype. Mutant CALR has been demonstrated to increase the number of immunophenotypic HSCs and MkPs (6), and we also saw an expansion in the number of pMKPs. When considering the behavior of cells individually, it is clear that mutant CALR acts from the stem cell compartment: CALR DEL HOM HSCs were more proliferative and faster to produce megakaryocytes than were their WT counterparts. Mutant CALR did not show a strong effect on the proliferation or MK bias of pMKPs at the level of a single cell but drove an increase in proliferation of MkPs and thus the number of megakaryocytes produced. We therefore concluded that mutant CALR drives platelet bias and proliferation at multiple stages of megakaryopoiesis, although this effect is strongest within HSCs.

Last, we used our single-cell transcriptomic data to ask which biological pathways were most differentially regulated in our CALR DEL HOM mice. Mutant CALR was associated with an up-regulation of the unfolded protein response, as would be expected for cells with impaired chaperone activity and as has been seen in human patient cells (34). In addition, mutant CALR cells showed an increase in cell cycle genes, again consistent with observations from human patient cells (34) and in agreement with our in vitro data, which showed that mutant CALR HSCs and MkPs were more proliferative. We also found up-regulation of cholesterol biosynthesis pathway genes in mutant CALR hematopoietic cells. While cholesterol biosynthesis is broadly increased across numerous cancers (39), including hematological cancers (40), CALR has also been directly linked to cholesterol biosynthesis. CALR/ mouse embryonic fibroblasts show impaired endoplasmic reticulum (ER) Ca2+ levels, leading to overactivation of SREBPs, which then up-regulate cholesterol and triacylglycerol biosynthesis genes (41). As mutant CALR lacks its Ca2+-binding domain, it is possible that CALR DEL HOM cells phenocopy knockout cells with respect to ER Ca2+ stores, thus leading to the observed overactive transcription of cholesterol biosynthesis genes. While megakaryocytes derived from human patient samples have been shown to have increased store-operated Ca2+ entry due to the perturbation of a complex between STIM1, ERp57, and CALR (42), none of our differentially activated pathways from IPA pointed to altered cytoplasmic Ca2+ signaling in the stem and progenitor populations tested. This may reflect differences between progenitor and mature cells. Mice with impaired cholesterol efflux have more proliferative HSCs (43) and an increase in MkP proliferation and an ET-like phenotype (44), suggesting that there may be a previously unknown link between the CALR DEL mutation, cholesterol metabolism, proliferation of MkPs, and thus the overproduction of platelets. While cholesterol biosynthesis was the most prominent novel target found in our transcriptomic analysis, it was by no means alone. IPA upstream regulator analysis predicted an up-regulation of interleukin-5 (IL-5), GM-CSF, and HGFall with known roles in hematopoiesisin addition to several unexpected results, such as TBX2, a transcription factor that has not been studied in hematopoiesis. Upstream regulators predicted to be decreased include the tumor suppressor TP53; let-7, a microRNA with a role in the self-renewal of fetal HSCs (45); and KDM5B (Jarid1b), a histone methylase required for HSC self-renewal (46).

Overall, our study has characterized a previously undescribed MK trajectory implicated in the progression of ET. We find that pMKPs are an intermediate stage within one pathway of megakaryopoiesis and hypothesize that they may be situated within the MPP2-independent MK shortcut. Last, our analysis confirmed that JAK-STAT signaling, unfolded protein response, and cell cycle are all increased by the presence of mutant CALR and found up-regulation of cholesterol biosynthesis, in addition to numerous other potential upstream regulators. Functional validation of these biological pathways and upstream regulators may represent promising avenues of future research to better understand mutant CALR-driven disease and in the development of therapeutic strategies.

The objectives of the study were to generate transcriptomic data from our CALR mouse model of ET and to use these data to determine how the hematopoietic landscape is affected by the CALR DEL mutation. All mouse procedures were performed in strict accordance with the U.K. Home Office regulations for animal research under project license 70/8406.

Bone marrow cells were harvested from the femurs, tibia, and iliac crests of mice. Bones were crushed in a mortar and pestle in phosphate-buffered saline (PBS) and 2% fetal bovine serum (FBS) and 5 mM EDTA and then filtered through a 70-m filter to obtain a suspension of bone marrow cells. The suspension was incubated with an equal volume of ammonium chloride solution (STEMCELL Technologies, Vancouver, Canada) for 10 min on ice to lyse erythrocytes, followed by centrifugation for 5 min at 350g. The cell pellet was resuspended in PBS and 2% FBS and 5 mM EDTA, filtered again through a 70-m filter, and centrifuged again for 5 min at 350g. For cell sorting experiments, bone marrow mononuclear cell suspensions were immunomagnetically depleted of lineage (Lin)positive cells (EasySep Mouse Hematopoietic Progenitor Cell Isolation Kit, catalog no. 19856, STEMCELL Technologies). For staining, cells were incubated with the indicated antibodies for 40 min on ice; see attached tables for catalog information and concentrations used (table S4). Flow cytometry was performed on BD LSRFortessa analyzers, and flow cytometric sorting was performed on BD Influx 4 and 5 cell sorters (BD Biosciences, San Jose, USA). Flow data were analyzed using FlowJo software (Tree Star, Ashland, USA).

For 10x Chromium (10x Genomics, Pleasanton, CA) experiments, Lin c-Kit+ (LK) and Lin Sca1+ cKit+ (LSK) cells were sort purified as described above and processed according to the manufacturers protocol. Sample demultiplexing, barcodes processing, and gene counting were performed using the count commands from the Cell Ranger v1.3 pipeline (https://support.10xgenomics.com/single-cell-gene-expression/software/overview/welcome). After Cell Ranger processing, each sample (LK and LSK for WT and CALR HOM DEL) was filtered for potential doublets by simulating synthetic doublets from pairs of scRNAseq profiles and assigning scores based on a k nearest-neighbor classifier on PCA-transformed data. The 1 and 4.5% of cells with the highest doublets scores from each LSK or LK sample were removed from further analysis, respectively. Cells with >10% of unique molecular identifier (UMI) counts mapping to mitochondrial genes, expressing fewer than 500 genes, or with a total number of UMI counts further than 3 SDs from the mean were excluded. After quality control, 11,098 WT (5139 LK and 5959 LSK) and 15,547 HOM (7815 LK and 7732 LSK) cells were retained for downstream analysis from our first repeat. For our second repeat, 3451 WT (2479 LK and 972 LSK) and 12,372 HOM (7824 LK and 4548 LSK) cells were retained for downstream analysis. These cells were then normalized to the same total count. All scRNAseq data were analyzed using the Scanpy Python Module (47).

To assign cell type identities to WT and CALR samples, a previously published landscape of 45,000 WT LK and LSK hematopoietic progenitors (24) was used as a reference for cell type annotation. This reference was clustered using Louvain clustering, resulting in 13 clusters. LK + LSK samples were joined for each genotype (WT and CALR DEL HOM) and projected into the PCA space of this reference dataset. Nearest neighbors were calculated between the two datasets based on Euclidean distance in the top 50 PCA components. Cells were assigned to the same cluster to which the majority of their 15 nearest neighbors in the reference belonged.

A force-directed graph visualization of the 45,000 cell reference dataset was calculated by first constructing a k = 7 nearest-neighbor graph from the data, which was then used as input for the ForceAtlas2 algorithm as implemented in Gephi 0.9.1 (https://gephi.org). In the ForceAtlas2 algorithm, all cells are pushed away from each other, with the nearest-neighbor connections pulling them back together to segregate separate trajectories.

A fine-resolution clustering of the reference dataset was calculated using the Louvain algorithm, resulting in 63 clusters. These were used as input for a PAGA analysis of the reference dataset using the Scanpy Python Module with default parameters. The results of the PAGA analysis were visualized by using the nodes and their edge weights as input into the ForceAtlas2 algorithm for calculating force-directed graphs as implemented in Gephi 0.9.1. For visualization, only connections with edge weights of >0.3 were shown.

To visualize gene expression of the PAGA graph, the mean normalized expression of all cells belonging to each node was calculated and displayed on a per-node basis.

To calculate differential abundances, votes were given out from each WT LK and CALR LK cell to their k-nearest neighbors in the reference dataset, with k chosen such that the total number of votes given out by each sample was the same. For each cell in the reference dataset, the difference between the number of votes received from the WT and CALR HOM samples was calculated. This difference acts as a proxy for the differential abundance of WT and CALR HOM cells for the region of the LK landscape in which the reference cell is located. This differential abundance proxy could then be visualized either on the reference landscape itself or on the PAGA graph calculated using the reference landscape. In the latter case, each node of the PAGA graph was colored by the mean differential abundance of all cells belonging to that node.

After flow sorting, cells were cultured in StemSpan SFEM (serum-free expansion medium) (STEMCELL Technologies) supplemented with 10% FBS (STEMCELL Technologies), 1% penicillin/streptomycin (Sigma-Aldrich), 1% l-glutamine (Sigma-Aldrich), stem cell factor (SCF; 250 ng/ml), IL-3 (10 ng/ml), and IL-6 (10 ng/ml; STEMCELL Technologies), with or without thrombopoietin (100 ng/ml; STEMCELL Technologies), in round-bottom 96-well plates (Corning, Corning, USA). For pro-erythroid conditions, cells were cultured as above but with the following cytokines: SCF (250 ng/ml), THPO (thrombopoietin) (50 ng/ml), EPO (erythropoietin) (5 U/ml), IL-3 (20 ng/ml), and Flt3L (50 ng/ml). For pro-myeloid conditions, cells were cultured as above but with the following cytokines: SCF (250 ng/ml), THPO (50 ng/ml), granulocyte colony-stimulating factor (50 ng/ml), IL-3 (20 ng/ml), Flt3L (50 ng/ml), and GM-CSF (50 ng/ml).

At 1, 2, 3, 4, and, in some cases, 7 days after flow sorting, single cellderived clones were visually inspected. Wells with surviving cells were classified into one of four categories: (i) exactly one enlarged cell, presumed to be a megakaryocyte; (ii) multiple enlarged cells; (iii) mixed expansion, with both small and enlarged cells; and (iv) expansion with only small cells. In some cases, the experimenter was blinded to the identity of the cell population initially sorted into the well he/she was inspecting and the genotype of the mouse.

For immunofluorescence, cells were allowed to adhere to the surface of poly-l-lysinecoated slides for 30 min at 37C (Poly-Prep Slides, Sigma-Aldrich). Cells were then fixed with 4% paraformaldehyde (Sigma-Aldrich) in PBS overnight at 4C, permeabilized with 0.25% Triton X-100 (Sigma-Aldrich) in PBS for 10 min at room temperature, and blocked with 1% bovine serum albumin (Sigma-Aldrich) for 1 hour at room temperature. Cells were stained with CD41 Alexa Fluor 488 (BioLegend, catalog no. 133908) overnight and mounted with 4,6-diamidino-2-phenylindole (DAPI) (VECTASHIELD Mounting Medium with DAPI, Vector Laboratories Inc., Burlingame, USA; catalog no. H-1500). Pictures were acquired on LSM-710 and LSM-780 confocal microscopes (Zeiss) and analyzed using ZEN software (Zeiss). For quantification of immunofluorescence, cells were cultured on CD44-coated glass-bottom plates for immobilization (48), followed by fixation and staining as above. Pictures were acquired on a Leica DMI4000 microscope (Leica), and CD41 intensity and cell size were quantified using Fiji software.

FACS-sorted cells from VWF-GFP+ donors were injected into the tail veins of W41/W41 (CD45.1) recipient that had been sublethally irradiated with 1 400 centigrays with 250,000 spleen cells as helpers. Peripheral blood was analyzed 1, 2, 3, 4, and 16 weeks after transplant for all cohorts.

Differential expression analysis was performed between WT (LK + LSK) and CALR DEL HOM (LK + LSK) clusters using the Wilcoxon rank sum test on all genes that passed initial quality control (typically approximately 15,000). A Benjamini-Hochberg correction was applied to correct for multiple testing. Genes with an adjusted P value of <0.05 and a fold change of >1.5 between genotypes were marked as differentially expressed. The original normalized counts were used in all cases.

DEGs were studied using IPA (Qiagen). We imputed the whole transcriptome in IPA and then filtered for analysis only statistically significant (adjusted P < 0.01) items with a log2FC > 0.3785 or log2FC < 0.3785. Pathways and upstream regulator networks showing relationships and interactions experimentally confirmed between DEGs and others that functionally interact with them were generated and ranked in terms of significance of participating genes (P < 0.05) and activation status (z score).

Data were analyzed, and graphs were generated in Microsoft Excel (Microsoft) and GraphPad PRISM (GraphPad, La Jolla, USA). Data are presented as means SD. Unless otherwise stated, statistical tests were unpaired Students t tests. P values are as follows: *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001.

Acknowledgments: We would like to acknowledge J. Aungier, T. Hamilton, D. Pask, and R. Sneade for invaluable technical assistance; R. Schulte, C. Cossetti, and G. Grondys-Kotarba at the CIMR Flow Cytometry Core Facility for assistance with cell sorting; and S. Loughran, T. Klampfl, and E. Laurenti for valuable discussions. Funding: Work in the Gttgens laboratory is supported by the Medical Research Council (MR/M008975/1), Wellcome (206328/Z/17/Z), Blood Cancer UK (18002), and Cancer Research UK (RG83389, jointly with A.R.G.). Work in the Green laboratory is supported by Wellcome (RG74909), WBH Foundation (RG91681), and Cancer Research UK (RG83389, jointly with B.G.). Author contributions: D.P. and H.J.P. designed and conducted experiments with assistance from J.L. S.W. and H.P.B. performed bioinformatic analyses. M.V. performed IPA with supervision from A.V.-P. A.G. provided DTA mice. D.P. analyzed data and wrote the manuscript with input from H.J.P. and J.L. and supervision from B.G. and A.R.G. Competing interests: The authors declare that they have no competing interests. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. We have deposited scRNAseq data in the NCBI Gene Expression Omnibus (GEO) database with accession number GSE160466. Additional data related to this paper may be requested from the authors.

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The stem/progenitor landscape is reshaped in a mouse model of essential thrombocythemia and causes excess megakaryocyte production - Science Advances