Feeds:
Posts
Comments

Archive for the ‘Synergistic Innate and Adaptive Immunotherapy’ Category

CAR T-Cell Therapy Market: 2020 – 2027 – Global Market Analysis and Industry Forecast

Posted in Cancer and Current Therapeutics, Cancer Vaccines: Targeting Cancer Genes for Immunotherapy, CAR-T, combination immunotherapies., Immune Engineering, Immune Modulatory, Immunotherapy, Modulating Macrophages in Cancer Immunotherapy, Pharmaceutical Industry Competitive Intelligence, Pharmacogenomics, Synergistic Innate and Adaptive Immunotherapy on October 12, 2020| Leave a Comment »

CAR T-CELL THERAPY MARKET: 2020 – 2027

G L O B A L  M A R K E T  A N A L Y S I S  A N D

I N D U S T R Y  F O R E C A S T

 

DISCLAIMER

LPBI Group’s decision to publish the Table of Contents of this Report does not imply endorsement of the Report

Aviva Lev-Ari, PhD, RN, Founder 1.0 & 2.0 LPBI Group

Guest Reporter: MIKE WOOD

Marketing Executive
BIOTECH FORECASTS

 

ABOUT BIOTECH FORECASTS

BIOTECH FORECASTS is a full-service market research and business- consulting firm primarily focusing on healthcare, pharmaceutical, and biotechnology industries. BIOTECH FORECASTS provides global as well as medium and small Pharmaceutical and Biotechnology businesses with unmatched quality of “Market Research Reports” and “Business Intelligence Solutions”. BIOTECH FORECASTS has a targeted view to provide business insights and consulting to assist its clients to make strategic business decisions, and achieve sustainable growth in their respective market domain.

UPDATED on 10/13/2020

CAR T-CELL THERAPY MARKET

Mike Wood

Mike Wood

Marketing Executive at Biotech Forecasts
1 article 

CAR T-cell therapy as a part of adoptive cell therapy (ACT), has become one of the most rapidly growing and promising fields in the Immuno-oncology. As compared to the conventional cancer therapies, CAR T-cell therapy is the single-dose solution for the treatment of various cancers, significantly for some lethal forms of hematological malignancies.

CAR T-cell therapy mainly involves the use of engineered T-cells, the process starts with the extraction of T-cells through leukapheresis, either from the patient (autologous) or a healthy donor (allogeneic). After the expression of a synthetic receptor (Chimeric Antigen Receptor) in the lab, the altered T-cells are expanded to the right dose and administered into the patient’s body. where they target and attach to a specific antigen on the tumor surface, to kill the cancerous cells by igniting the apoptosis.

The global CAR T-cell therapy market was valued at $734 million in 2019 and is estimated to reach $4,078 million by 2027, registering a CAGR of 23.91% from 2020 to 2027.

Factors that drive the market growth involve, (1) Increased in funding for R&D activities pertaining to cell and gene therapy. By H1 2020 cell and gene therapy companies set new records in the fundraising despite the pandemic crisis. For Instance, by June 2020 totaled $1,452 Million raised in Five IPOs including, Legend Biotech ($487M), Passage Bio ($284M), Akouos ($244M), Generation Bio ($230M), and Beam Therapeutics ($207M), which is 2.5 times the total IPO of 2019.

Moreover, in 2019 cell therapy companies specifically have raised $560 million of venture capital, including Century Therapeutics ($250M), Achilles Therapeutics Ltd. ($121M in series B), NKarta Therapeutics Inc. ($114M), and Tmunity Therapeutics ($75M in Series B).

(2) Increased in No. of Approved Products, By July 2020, there are a total of 03 approved CAR T-cell therapy products, including KYMRIAH®, YESCARTA®, and the most recently approved TECARTUS™ (formerly KTE-X19). Furthermore, two CAR T-cell therapies BB2121, and JCAR017 are expected to get the market approval by the end of 2020 or in early 2021.

Other factors that boost the market growth involves; (3) increase in government support, (4) ethical acceptance of Cell and Gene therapy for cancer treatment, (5) rise in the prevalence of cancer, and (6) an increase in awareness regarding the CAR T-cell therapy.

However, high costs associated with the treatment (KYMRIAH® cost around $475,000, and YESCARTA® costs $373,000 per infusion), long production hours, obstacles in treating solid tumors, and unwanted immune responses & potential side effects might hamper the market growth.

The report also presents a detailed quantitative analysis of the current market trends and future estimations from 2020 to 2027.

The forecasts cover 2 Approach Types, 5 Antigen Types, 5 Application Types, 4 Regions, and 14 Countries.

The report comes with an associated file covering quantitative data from all numeric forecasts presented in the report, as well as with a Clinical Trials Data File.

KEY FINDINGS

The report has the following key findings:

  • The global CAR T-cell therapy market accounted for $734 million in 2019 and is estimated to reach $4,078 million by 2027, registering a CAGR of 23.91% from 2020 to 2027.
  • By approach type the autologous segment was valued at $655.26 million in 2019 and is estimated to reach $ 3,324.52 million by 2027, registering a CAGR of 22.51% from 2020 to 2027.
  • By approach type, the allogeneic segment exhibits the highest CAGR of 32.63%.
  • Based on the Antigen segment CD19 was the largest contributor among the other segments in 2019.
  • The Acute lymphocytic leukemia (ALL) segment generated the highest revenue and is expected to continue its dominance in the future, followed by the Diffuse large B-cell lymphoma (DLBCL) segment.
  • North America dominated the global CAR T-cell therapy market in 2019 and is projected to continue its dominance in the future.
  • China is expected to grow the highest in the Asia-Pacific region during the forecast period.

TOPICS COVERED

The report covers the following topics:

  • Market Drivers, Restraints, and Opportunities
  • Porters Five Forces Analysis
  • CAR T-Cell Structure, Generations, Manufacturing, and Pricing Models
  • Top Winning Strategies, Top Investment Pockets
  • Analysis of by Approach Type, Antigen Type, Application, and Region
  • 51 Company Profiles, Product Portfolio, and Key Strategies
  • Approved Products Profiles, and list of Expected Approvals
  • COVID-19 Impact on the Cell and Gene Therapy Industry
  • CAR T-cell therapy clinical trials analysis from 1997 to 2019
  • Market analysis and forecasts from 2020 to 2027

FORECAST SEGMENTATION

By Approach Type

  • Autologous
  • Allogeneic

By Antigen Type

  • CD19
  • CD20
  • BCMA
  • MSLN
  • Others

By Application

  • Acute lymphoblastic leukemia (ALL)
  • Diffuse large B-Cell lymphoma (DLBCL)
  • Multiple Myeloma (MM)
  • Acute Myeloid Leukemia (AML)
  • Other Cancer Indications

By Region

  • North America: USA, Canada, Mexico
  • Europe: UK, Germany, France, Spain, Italy, Rest of Europe
  • Asia-Pacific: China, Japan, India, South Korea, Rest of Asia-Pacific
  • LAMEA: Brazil, South Africa, Rest of LAMEA

Contact at info@biotechforecasts.com for any Queries or Free Report Sample

Report this

Published by

Mike Wood
Mike Wood
Marketing Executive at Biotech Forecasts
Published • 10h
1 article
The global CAR T-cell therapy market was valued at $734 million in 2019 and is estimated to reach $4,078 million by 2027, registering a CAGR of 23.91% from 2020 to 2027. celltherapy genetherapy immunotherapy cancertreatment cartcell regenerativemedicine biotech cancer

 

Table of Contents

 

CHAPTER 1: INTRODUCTION

1.1 REPORT DESCRIPTION 17
1.2 TOPICS COVERED 19
1.3 KEY MARKET SEGMENTS 20
1.4 KEY BENEFITS 21
1.5 RESEARCH METHODOLOGY 21
1.6 TARGET AUDIENCE 22
1.7 COMPANIES MENTIONED 23

CHAPTER 2: EXECUTIVE SUMMARY

2.1 EXECUTIVE SUMMARY 26
2.2 CXO PROSPECTIVE 29

CHAPTER 3: MARKET OVERVIEW

3.1 MARKET DEFINITION AND SCOPE 30
3.2 KEY FINDINGS 31
3.3 TOP INVESTMENT POCKETS 32
3.4 TOP WINNING STRATEGIES 33
3.4.1.Top winning strategies, by year, 2017-2019* 34
3.4.2.Top winning strategies, by development, 2017-2019*(%) 34
3.4.3.Top winning strategies, by company, 2017-2019* 35
3.5 TOP PLAYER POSITIONING, BY PIPELINE VOLUME, 2019 38
3.6 PORTERS FIVE FORCES ANALYSIS 39
3.7 COVID19 IMPACT ON CELL AND GENE THERAPY (CGT) INDUSTRY 41
3.8 MARKET DYNAMICS 46
3.8.1    Drivers 46
3.8.1.1   Increase in funding for R&D activities of CAR T-cell therapy 46
3.8.1.2   The rise in the prevalence of cancer 47
3.8.1.3   Increase in awareness regarding CAR T-cell therapy 47

 

3.8.2    Restrains 48
3.8.2.1   The high cost of CAR T-cell therapy treatment 48
3.8.2.2   Unwanted immune responses and side effects 48
3.8.2.3   Long production time 48
3.8.2.4   Obstacles in treating solid tumors 49
3.8.3    Opportunities 49
3.8.3.1   Untapped potential for emerging markets 49

CHAPTER 4: CAR T-CELL THERAPY, A BRIEF INTRODUCTION

4.1 OVERVIEW 50
4.2 SIXTY YEARS HISTORY OF CAR T-CELL THERAPY 51
4.3 CAR T-CELL STRUCTURE AND GENERATIONS 53
4.4 CAR T-CELL MANUFACTURING PROCESSES 56
4.5 PRICING AND PAYMENT MODELS FOR CAR T-CELL THERAPIES 59

CHAPTER 5: CAR T-CELL THERAPY MARKET, BY APPROACH TYPE

5.1 OVERVIEW 61
5.1.1    Market size and forecast 62
5.2 AUTOLOGOUS 63
5.2.1    Key market trends 63
5.2.2    Key growth factors and opportunities 64
5.2.3    Market size and forecast 64
5.2.4    Market size and forecast by country 65
5.3 ALLOGENEIC 66
5.3.1    Key market trends 67
5.3.2    Key growth factors and opportunities 68
5.3.3    Market size and forecast 68
5.3.4    Market size and forecast by country 69

CHAPTER 6: CAR T-CELL THERAPY MARKET, BY ANTIGEN TYPE

6.1 OVERVIEW 70
6.1.1         Market size and forecast 71
6.2 CD19 72
6.2.1         Market size and forecast 73
6.2.2         Market size and forecast by country 74

 

6.3 CD20 75
6.3.1 Market size and forecast 76
6.3.2 Market size and forecast by country 77
6.4 BCMA 78
6.4.1 Market size and forecast 79
6.4.2 Market size and forecast by country 80
6.5 MSLN 81
6.5.1 Market size and forecast 82
6.5.2 Market size and forecast by country 83
6.6 OTHERS 84
6.6.1 Market size and forecast 85
6.6.2 Market size and forecast by country 86

CHAPTER 7: CAR T-CELL THERAPY MARKET, BY APPLICATION

7.1 OVERVIEW 87
7.1.1       Market size and forecast 88
7.2 ACUTE LYMPHOBLASTIC LEUKEMIA (ALL) 89
7.2.1       Market size and forecast 90
7.2.2       Market size and forecast by country 91
7.3 DIFFUSE LARGE B-CELL LYMPHOMA (DLBCL) 92
7.3.1       Market size and forecast 93
7.3.2       Market size and forecast by country 94
7.4 MULTIPLE MYELOMA (MM) 95
7.4.1       Market size and forecast 96
7.4.2       Market size and forecast by country 97
7.5 ACUTE MYELOID LEUKEMIA (AML) 98
7.5.1       Market size and forecast 99
7.5.2       Market size and forecast by country 100
7.6 OTHERS 101
7.6.1       Market size and forecast 102
7.6.2       Market size and forecast by country 103

CHAPTER 8: CAR T-CELL THERAPY MARKET, BY REGION

8.1 OVERVIEW 104
8.1.1       Market size and forecast 104
8.2 NORTH AMERICA 105
8.2.1       Key market trends 105
8.2.2       Key growth factors and opportunities 105

 

8.2.3       Market size and forecast, by country 106
8.2.4       Market size and forecast, by approach type 106
8.2.5       Market size and forecast, by antigen type 107
8.2.6 Market size and forecast, by application 107
8.2.6.1 U.S. market size and forecast, by approach type 108
8.2.6.2 U.S. market size and forecast, by antigen type 108
8.2.6.3 U.S. market size and forecast, by application 109
8.2.6.4 Canada market size and forecast, by approach type 110
8.2.6.5 Canada market size and forecast, by antigen type 110
8.2.6.6 Canada market size and forecast, by application 111
8.2.6.7 Mexico market size and forecast, by approach type 112
8.2.6.8 Mexico market size and forecast, by antigen type 112
8.2.6.9 Mexico market size and forecast, by application 113
8.3 EUROPE 114
8.4.1 Key market trends 114
8.4.2 Key growth factors and opportunities 114
8.4.3 Market size and forecast, by country 115
8.4.4 Market size and forecast, by approach type 115
8.4.5 Market size and forecast, by antigen type 116
8.4.6 Market size and forecast, by application 116
8.3.6.1 UK market size and forecast, by approach type 117
8.3.6.2 UK market size and forecast, by antigen type 117
8.3.6.3 UK market size and forecast, by application 118
8.3.6.4 Germany market size and forecast, by approach type 119
8.3.6.5 Germany market size and forecast, by antigen type 119
8.3.6.6 Germany market size and forecast, by application 120
8.3.6.7 France market size and forecast, by approach type 121
8.3.6.8 France market size and forecast, by antigen type 121
8.3.6.9 France market size and forecast, by application 122
8.3.6.10 Spain market size and forecast, by approach type 123
8.3.6.11 Spain market size and forecast, by antigen type 123
8.3.6.12 Spain market size and forecast, by application 124
8.3.6.13 Italy market size and forecast, by approach type 125
8.3.6.14 Italy market size and forecast, by antigen type 125
8.3.6.15 Italy market size and forecast, by application 126
8.3.6.16 Rest of Europe market size and forecast, by approach type 127
8.3.6.17 Rest of Europe market size and forecast, by antigen type 127
8.3.6.18 Rest of Europe market size and forecast, by application 128
8.4 ASIA-PACIFIC 129
8.4.1 Key market trends 129
8.4.2 Key growth factors and opportunities 129
8.4.3 Market size and forecast, by country 130
8.4.4 Market size and forecast, by approach type 130

 

8.4.5       Market size and forecast, by antigen type 131
8.4.6 Market size and forecast, by application 131
8.4.6.1 China market size and forecast, by approach type 132
8.4.6.2 China market size and forecast, by antigen type 132
8.4.6.3 China market size and forecast, by application 133
8.4.6.4 Japan market size and forecast, by approach type 134
8.4.6.5 Japan market size and forecast by antigen type 134
8.4.6.6 Japan market size and forecast, by application 135
8.4.6.7 India market size and forecast, by approach type 136
8.4.6.8 India market size and forecast, by antigen type 136
8.4.6.9 India market size and forecast, by application 137
8.4.6.10 South Korea market size and forecast, by approach type 138
8.4.6.11 South Korea market size and forecast, by antigen type 138
8.4.6.12 South Korea market size and forecast, by application 139
8.4.6.13 Rest of Asia-Pacific market size and forecast, by approach type 140
8.4.6.14 Rest of Asia-Pacific market size and forecast, by antigen type 140
8.4.6.15 Rest of Asia-Pacific market size and forecast, by application 141
8.5 LAMEA 142
8.5.1 Key market trends 142
8.5.2 Key growth factors and opportunities 142
8.5.3 Market size and forecast, by country 143
8.5.4 Market size and forecast, by approach type 143
8.5.5 Market size and forecast, by antigen type 144
8.5.6 Market size and forecast, by application 144
8.5.6.1 Brazil market size and forecast by approach type 145
8.5.6.2 Brazil market size and forecast, by antigen type 145
8.5.6.3 Brazil market size and forecast, by application 146
8.5.6.4 South Africa market size and forecast, by approach type 147
8.5.6.5 South Africa market size and forecast, by antigen type 147
8.5.6.6 South Africa market size and forecast, by application 148
8.5.6.7 Rest of LAMEA market size and forecast by approach type 149
8.5.6.8 Rest of LAMEA market size and forecast, by antigen type 149
8.5.6.9 Rest of LAMEA market size and forecast, by application 150

CHAPTER 9: CLINICAL TRIALS ANALYSIS & PRODUCT PROFILES

9.1 OVERVIEW 151
9.1.1      No. of Clinical Trials from 1997 to 2019 151
9.1.2      Clinical Trials from 1997 to 2019: Based on Approach Type 152
9.1.3      Clinical Trials from 1997 to 2019: Based on Antigen Type 153
9.1.4      Clinical Trials from 1997 to 2019: Based on Application 154
9.1.5      Clinical Trials from 1997 to 2019: Based on Region 155

 

9.2 EXPECTED APPROVALS 156
9.3 APPROVED PRODUCTS PROFILES 157
9.3.1      KYMRIAH® 157
9.3.2      YESCARTA® 159
9.3.3      TECARTUS™ 161

CHAPTER 10: COMPANY PROFILES

10.1       Abbvie Inc. 162
10.2       Adaptimmune Therapeutics Plc 164
10.3 Allogene Therapeutics, Inc. 166
10.4 Amgen, Inc 168
10.5 Anixa Biosciences, Inc. 170
10.6 Arcellx, Inc. 172
10.7 Atara Biotherapeutics, Inc. 173
10.8 Autolus Therapeutics Plc. 175
10.9 Beam Therapeutics, Inc. 177
10.10 Bellicum Pharmaceuticals, Inc. 179
10.11 BioNtech SE 181
10.12 Bluebird Bio, Inc. 183
10.13 Carsgen Therapeutics, Ltd 185
10.14 Cartesian Therapeutics, Inc. 187
10.15 Cartherics Pty Ltd. 188
10.16 Celgene Corporation 189
10.17 Cellectis SA 191
10.18 Cellular Biomedicine Group, Inc. 193
10.19 Celularity, Inc. 195
10.20 Celyad SA 196
10.21 CRISPR Therapeutics AG 198
10.22 Eureka Therapeutics, Inc. 200
10.23 Fate Therapeutics, Inc. 201
10.24 Fortress Biotech, Inc 203
10.25 Gilead Sciences, Inc. 205
10.26 Gracell Biotechnology Ltd 207
10.27 icell Gene Therapeutics 208
10.28 Johnson & Johnson 209
10.29 Juventas Cell Therapy Ltd. 211
10.30 Kuur Therapeutics 212
10.31 Legend Biotech Corp. 213
10.32 Leucid Bio Ltd. 214
10.33 Minerva Biotechnologies Corp. 215

 

10.34     Molecular Medicine SPA (Molmed) 216
10.35     Nanjing Bioheng Biotech Co., Ltd. 218
10.36     Noile-Immune Biotech Inc. 219
10.37     Novartis AG 220
10.38     Oxford Biomedica PLC 222
10.39     Persongen Biotherapeutics (Suzhou) Co., Ltd. 224
10.40     Poseida Therapeutics, Inc. 226
10.41     Precigen, Inc. 227
10.42     Precision Biosciences, Inc. 229
10.43     Sorrento Therapeutics, Inc. 231
10.44     Takara Bio Inc. 233
10.45     Takeda Pharmaceutical Company Ltd. 235
10.46     TC Biopharm Ltd. 237
10.47     Tessa Therapeutics Pte Ltd. 238
10.48     Tmunity Therapeutics, Inc. 239
10.49     Unum Therapeutics Inc. 240
10.50     Xyphos Inc. 242
10.51     Ziopharm Oncology, Inc. 243

CHAPTER 11: CONCLUSION & STRATEGIC RECOMMENTATIONS

11.1     STRATEGIC RECOMMENDATIONS 245
11.2     CONCLUSION 247

 

CONTACT

info@biotechforecasts.com

MIKE WOOD

Marketing Executive

BIOTECH FORECASTS

Read Full Post »

Impaired antibody development is promoted by chronic viral infection

Posted in Adaptive Immune Response to Biomaterials and Tissue Repair, Allergy and Infectious Diseases, Antibody Responses Predict Antigen Exposure, Autoimmune Inflammatory DIseases, “Antibody–enzyme conjugates”, Biotechnology, Cell Biology, Cell Biology, Signaling & Cell Circuits, Cell Processing System in Cell Therapy Process Development, combination immunotherapies., Diagnostic Immunology, Human Antibody Response, Human Circulating Antibody Repertoire, Human Immune System in Health and in Disease, Human Naive B Cell Repertoire, Immune Engineering, Immune Modulatory, Immuno-Oncology & Genomics, Immunodiagnostics, Immunology, Immunotherapy, Infectious Disease & New Antibiotic Targets, Infectious Disease Immunodiagnostics, Innovation in Immunology Diagnostics, Monoclonal antibody therapy, Monoclonal Immunotherapy, Protection Against Autoimmune Disease, Signaling & Cell Circuits, Synergistic Innate and Adaptive Immunotherapy, Synthetic Immunology: Hacking Immune Cells, Universal Immune Cell Therapies (uICT), Viral diseases, tagged , , , , on December 1, 2019| Leave a Comment »

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

Effective humoral immune responses to infection and immunization are defined by high-affinity antibodies generated as a result of B cell differentiation and selection that occurs within germinal centers (GC). Within the GC, B cells undergo affinity maturation, an iterative and competitive process wherein B cells mutate their immunoglobulin genes (somatic hypermutation) and undergo clonal selection by competing for T cell help. Balancing the decision to remain within the GC and continue participating in affinity maturation or to exit the GC as a plasma cell (PC) or memory B cell (MBC) is critical for achieving optimal antibody avidity, antibody quantity, and establishing immunological memory in response to immunization or infection. Humoral immune responses during chronic infections are often dysregulated and characterized by hypergammaglobulinemia, decreased affinity maturation, and delayed development of neutralizing antibodies. Previous studies have suggested that poor antibody quality is in part due to deletion of B cells prior to establishment of the GC response.

 

In fact the impact of chronic infections on B cell fate decisions in the GC remains poorly understood. To address this question, researchers used single-cell transcriptional profiling of virus-specific GC B cells to test the hypothesis that chronic viral infection disrupted GC B cell fate decisions leading to suboptimal humoral immunity. These studies revealed a critical GC differentiation checkpoint that is disrupted by chronic infection, specifically at the point of dark zone re-entry. During chronic viral infection, virus-specific GC B cells were shunted towards terminal plasma cell (PC) or memory B cell (MBC) fates at the expense of continued participation in the GC. Early GC exit was associated with decreased B cell mutational burden and antibody quality. Persisting antigen and inflammation independently drove facets of dysregulation, with a key role for inflammation in directing premature terminal GC B cell differentiation and GC exit. Thus, the present research defines GC defects during chronic viral infection and identify a critical GC checkpoint that is short-circuited, preventing optimal maturation of humoral immunity.

 

Together, these studies identify a key GC B cell differentiation checkpoint that is dysregulated during chronic infection. Further, it was found that the chronic inflammatory environment, rather than persistent antigen, is sufficient to drive altered GC B cell differentiation during chronic infection even against unrelated antigens. However, the data also indicate that inflammatory circuits are likely linked to perception of antigen stimulation. Nevertheless, this study reveals a B cell-intrinsic program of transcriptional skewing in chronic viral infection that results in shunting out of the cyclic GC B cell process and early GC exit with consequences for antibody quality and hypergammaglobulinemia. These findings have implications for vaccination in individuals with pre-existing chronic infections where antibody responses are often ineffective and suggest that modulation of inflammatory pathways may be therapeutically useful to overcome impaired humoral immunity and foster affinity maturation during chronic viral infections.

 

References:

 

https://www.biorxiv.org/content/10.1101/849844v1

 

https://www.ncbi.nlm.nih.gov/pubmed/25656706

 

https://www.ncbi.nlm.nih.gov/pubmed/27653600

 

https://www.ncbi.nlm.nih.gov/pubmed/26912368

 

https://www.ncbi.nlm.nih.gov/pubmed/26799208

 

https://www.ncbi.nlm.nih.gov/pubmed/23001146

 

Read Full Post »

Obesity related insulin resistance is regulated by gut associated immune cells

Posted in Artificial Pancreas for Type1 Diabetes, Diabetes Mellitus, Diagnostic Immunology, Gestational diabetes, Glycobiology: Biopharmaceutical Production, Glycobiology: Biopharmaceutical Production, Pharmacodynamics and Pharmacokinetics, Gut Microbiome and Obesity, Human Immune System in Health and in Disease, Immunology, Immunotherapy, Inflammatory Pathophysiology, Nutrition Disorders, Obesity, Population Health Management, Population Health Management, Nutrition and Phytochemistry, Signaling & Cell Circuits, Synergistic Innate and Adaptive Immunotherapy, tagged , , , , on September 20, 2019| Leave a Comment »

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

Obesity is a global concern that is associated with many chronic complications such as type 2 diabetes, insulin resistance (IR), cardiovascular diseases, and cancer. Growing evidence has implicated the digestive system, including its microbiota, gut-derived incretin hormones, and gut-associated lymphoid tissue in obesity and IR. During high fat diet (HFD) feeding and obesity, a significant shift occurs in the microbial populations within the gut, known as dysbiosis, which interacts with the intestinal immune system. Similar to other metabolic organs, including visceral adipose tissue (VAT) and liver, altered immune homeostasis has also been observed in the small and large intestines during obesity.

 

A link between the gut microbiota and the intestinal immune system is the immune-derived molecule immunoglobulin A (IgA). IgA is a B cell antibody primarily produced in dimeric form by plasma cells residing in the gut lamina propria (LP). Given the importance of IgA on intestinal–gut microbe immunoregulation, which is directly influenced by dietary changes, scientists hypothesized that IgA may be a key player in the pathogenesis of obesity and IR. Here, in this study it was demonstrate that IgA levels are reduced during obesity and the loss of IgA in mice worsens IR and increases intestinal permeability, microbiota encroachment, and downstream inflammation in metabolic tissues, including inside the VAT.

 

IgA deficiency alters the obese gut microbiota and its metabolic phenotype can be recapitulated into microbiota-depleted mice upon fecal matter transplantation. In addition, the researchers also demonstrated that commonly used therapies for diabetes such as metformin and bariatric surgery can alter cellular and stool IgA levels, respectively. These findings suggested a critical function for IgA in regulating metabolic disease and support the emerging role for intestinal immunity as an important modulator of systemic glucose metabolism.

 

Overall, the researchers demonstrated a critical role for IgA in regulating intestinal homeostasis, metabolic inflammation, and obesity-related IR. These findings identify intestinal IgA+ immune cells as mucosal mediators of whole-body glucose regulation in diet-induced metabolic disease. This research further emphasized the importance of the intestinal adaptive immune system and its interactions with the gut microbiota and innate immune system within the larger network of organs involved in the manifestation of metabolic disease.

 

Future investigation is required to determine the impact of IgA deficiency during obesity in humans and the role of metabolic disease in human populations with selective IgA deficiency, especially since human IgA deficiency is associated with an altered gut microbiota that cannot be fully compensated with IgM. However, the research identified IgA as a critical immunological molecule in the intestine that impacts systemic glucose homeostasis, and treatments targeting IgA-producing immune populations and SIgA may have therapeutic potential for metabolic disease.

 

References:

 

https://www.nature.com/articles/s41467-019-11370-y?elqTrackId=dc86e0c60f574542b033227afd0fdc8e

 

https://www.jci.org/articles/view/88879

 

https://www.nature.com/articles/nm.2353

 

https://diabetes.diabetesjournals.org/content/57/6/1470

 

https://www.sciencedirect.com/science/article/pii/S1550413115001047?via%3Dihub

 

https://www.sciencedirect.com/science/article/pii/S1550413115002326?via%3Dihub

 

https://www.sciencedirect.com/science/article/pii/S1931312814004636?via%3Dihub

 

https://www.nature.com/articles/nature15766

 

https://www.sciencedirect.com/science/article/pii/S1550413116000371?via%3Dihub

 

https://www.nature.com/articles/nm.2001

 

https://www.sciencedirect.com/science/article/abs/pii/S1550413118305047?via%3Dihub

 

Read Full Post »

Newly Found Functions of B Cell

Posted in Adaptive Immune Response to Biomaterials and Tissue Repair, Allergy and Infectious Diseases, Autoimmune Inflammatory DIseases, CANCER BIOLOGY & Innovations in Cancer Therapy, Cancer Vaccines: Targeting Cancer Genes for Immunotherapy, Cancer-Immune Interactions, CNS-Immune Interface, combination immunotherapies., Cytokine Receptor Structure, Cytokines, Diagnostic Immunology, Human Immune System in Health and in Disease, Human Naive B Cell Repertoire, Immune Engineering, Immune Modulatory, Immuno-Oncology & Genomics, Immunodiagnostics, Immunology, Immunotherapy, Infectious Disease Immunodiagnostics, Innovation in Immunology Diagnostics, Integrin-targeted Combination Immunotherapy, Metabolic Immuno-Oncology, Modulating Macrophages in Cancer Immunotherapy, Monoclonal Immunotherapy, NK Cell-Based Cancer Immunotherapy, Protection Against Autoimmune Disease, Synergistic Innate and Adaptive Immunotherapy, Synthetic Immunology: Hacking Immune Cells, Tolerance-inducing Autoimmune Disease Therapeutics, Universal Immune Cell Therapies (uICT), tagged , , , , , , on May 23, 2019| Leave a Comment »

Newly Found Functions of B Cell

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

4.1.8

4.1.8   Newly Found Functions of B Cell, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 4: Single Cell Genomics

The importance of B cells to human health is more than what is already known. Vaccines capable of eradicating disease activate B cells, cancer checkpoint blockade therapies are produced using B cells, and B cell deficiencies have devastating impacts. B cells have been a subject of fascination since at least the 1800s. The notion of a humoral branch to immunity emerged from the work of and contemporaries studying B cells in the early 1900s.

Efforts to understand how we could make antibodies from B cells against almost any foreign surface while usually avoiding making them against self, led to Burnet’s clonal selection theory. This was followed by the molecular definition of how a diversity of immunoglobulins can arise by gene rearrangement in developing B cells. Recombination activating gene (RAG)-dependent processes of V-(D)-J rearrangement of immunoglobulin (Ig) gene segments in developing B cells are now known to be able to generate an enormous amount of antibody diversity (theoretically at least 1016 possible variants).

With so much already known, B cell biology might be considered ‘‘done’’ with only incremental advances still to be made, but instead, there is great activity in the field today with numerous major challenges that remain. For example, efforts are underway to develop vaccines that induce broadly neutralizing antibody responses, to understand how autoantigen- and allergen-reactive antibodies arise, and to harness B cell-depletion therapies to correct non-autoantibody-mediated diseases, making it evident that there is still an enormous amount we do not know about B cells and much work to be done.

Multiple self-tolerance checkpoints exist to remove autoreactive specificities from the B cell repertoire or to limit the ability of such cells to secrete autoantigen-binding antibody. These include receptor editing and deletion in immature B cells, competitive elimination of chronically autoantigen binding B cells in the periphery, and a state of anergy that disfavors PC (plasma cell) differentiation. Autoantibody production can occur due to failures in these checkpoints or in T cell self-tolerance mechanisms. Variants in multiple genes are implicated in increasing the likelihood of checkpoint failure and of autoantibody production occurring.

Autoantibodies are pathogenic in a number of human diseases including SLE (Systemic lupus erythematosus), pemphigus vulgaris, Grave’s disease, and myasthenia gravis. B cell depletion therapy using anti-CD20 antibody has been protective in some of these diseases such as pemphigus vulgaris, but not others such as SLE and this appears to reflect the contribution of SLPC (Short lived plasma cells) versus LLPC (Long lived plasma cells) to autoantibody production and the inability of even prolonged anti-CD20 treatment to eliminate the later. These clinical findings have added to the importance of understanding what factors drive SLPC versus LLPC development and what the requirements are to support LLPCs.

B cell depletion therapy has also been efficacious in several other autoimmune diseases, including multiple sclerosis (MS), type 1 diabetes, and rheumatoid arthritis (RA). While the potential contributions of autoantibodies to the pathology of these diseases are still being explored, autoantigen presentation has been posited as another mechanism for B cell disease-promoting activity.

In addition to autoimmunity, B cells play an important role in allergic diseases. IgE antibodies specific for allergen components sensitize mast cells and basophils for rapid degranulation in response to allergen exposures at various sites, such as in the intestine (food allergy), nose (allergic rhinitis), and lung (allergic asthma). IgE production may thus be favored under conditions that induce weak B cell responses and minimal GC (Germinal center) activity, thereby enabling IgE+ B cells and/or PCs to avoid being outcompeted by IgG+ cells. Aside from IgE antibodies, B cells may also contribute to allergic inflammation through their interactions with T cells.

B cells have also emerged as an important source of the immunosuppressive cytokine IL-10. Mouse studies revealed that B cell-derived IL-10 can promote recovery from EAE (Experimental autoimmune encephalomyelitis) and can be protective in models of RA and type 1 diabetes. Moreover, IL-10 production from B cells restrains T cell responses during some viral and bacterial infections. These findings indicate that the influence of B cells on the cytokine milieu will be context dependent.

The presence of B cells in a variety of solid tumor types, including breast cancer, ovarian cancer, and melanoma, has been associated in some studies with a positive prognosis. The mechanism involved is unclear but could include antigen presentation to CD4 and CD8 T cells, antibody production and subsequent enhancement of presentation, or by promoting tertiary lymphoid tissue formation and local T cell accumulation. It is also noteworthy that B cells frequently make antibody responses to cancer antigens and this has led to efforts to use antibodies from cancer patients as biomarkers of disease and to identify immunotherapy targets.

Malignancies of B cells themselves are a common form of hematopoietic cancer. This predilection arises because the gene modifications that B cells undergo during development and in immune responses are not perfect in their fidelity, and antibody responses require extensive B cell proliferation. The study of B cell lymphomas and their associated genetic derangements continues to be illuminating about requirements for normal B cell differentiation and signaling while also leading to the development of targeted therapies.

Overall this study attempted to capture some of the advances in the understanding of B cell biology that have occurred since the turn of the century. These include important steps forward in understanding how B cells encounter antigens, the co-stimulatory and cytokine requirements for their proliferation and differentiation, and how properties of the B cell receptor, the antigen, and helper T cells influence B cell responses. Many advances continue to transform the field including the impact of deep sequencing technologies on understanding B cell repertoires, the IgA-inducing microbiome, and the genetic defects in humans that compromise or exaggerate B cell responses or give rise to B cell malignancies.

Other advances that are providing insight include:

  • single-cell approaches to define B cell heterogeneity,
  • glycomic approaches to study effector sugars on antibodies,
  • new methods to study human B cell responses including CRISPR-based manipulation, and
  • the use of systems biology to study changes at the whole organism level.

With the recognition that B cells and antibodies are involved in most types of immune response and the realization that inflammatory processes contribute to a wider range of diseases than previously believed, including, for example, metabolic syndrome and neurodegeneration, it is expected that further

  • basic research-driven discovery about B cell biology will lead to more and improved approaches to maintain health and fight disease in the future.

References:

https://www.cell.com/cell/fulltext/S0092-8674(19)30278-8

https://onlinelibrary.wiley.com/doi/full/10.1002/hon.2405

https://www.pnas.org/content/115/18/4743

https://onlinelibrary.wiley.com/doi/full/10.1111/all.12911

https://cshperspectives.cshlp.org/content/10/5/a028795

https://www.sciencedirect.com/science/article/abs/pii/S0049017218304955

Read Full Post »

CytoReason is re-defining the Context of the Immune System for Drug Discovery

Posted in Adaptive Immune Response to Biomaterials and Tissue Repair, BioTechnology - Venture Creation, Engineering Better T Cells, Immune Engineering, Immune Modulatory, Immunodiagnostics, Immunotherapy, NK Cell-Based Cancer Immunotherapy, Protection Against Autoimmune Disease, Synergistic Innate and Adaptive Immunotherapy on May 21, 2019| Leave a Comment »

CytoReason is re-defining the Context of the Immune System for Drug Discovery

Reporter: Aviva Lev-Ari, PhD, RN

 

CytoReason is re-defining the context of the immune system at a cellular level in order to better understand disease and support more effective drug discovery and development.

Our leading-edge machine-learning driven approach identifies “cause and effect” of the gene/cell/cytokine relationships that lie at the heart of treating disease.

Faster and more accurately than ever before.

CytoReason’s mission is to simulate the cells that can stimulate discovery of:​

  • New targets for treating disease
  • New insights to mechanism of actions (both of disease and drugs)
  • Differences in responses to both disease and treatment
  • Which diseases a drug can impact

We have developed a unique machine-learning driven approach to “seeing” the cells that can make the difference in patients seeing a better life.

The insights our approach generates, enable pharmaceutical and biotech companies to make the right decisions, at the right time, in the drug discovery and development programs that bring better therapies.

Based on cutting edge technologies, trained on data that would normally be impossible to access, and steered by leading biological and data science researchers, our approach is underpinned by three core principles:​

SOURCE

https://www.cytoreason.com/

Press Release

https://docs.wixstatic.com/ugd/216dd2_b715f2c29a8c496eb65315d332a7077e.pdf

Case Studies

Click one of the buttons below to view a short case study presention:

Collaboration & Results

Working with leading global pharma and biotech companies and key research institutions, our results help guide R&D decision making.

​

​

​

​

​

​

Results

Our platform is tried and tested, producing real results with validation

•    Discovered: New cellular players in melanoma microenvironment

•    Discovered: New IL4 mechanism of action in atopic dermatitis

•    Discovered: Novel pre-treatment biomarkers in IBD anti-TNFα therapy

•    Discovered: 355 previously unreported cell/cytokine interactions (view infographic)

Publications

Science is the backbone of our methodologies and applications, and must stand the test of scientific scrutiny.  To date we have 16 research papers published in top quality peer-reviewed scientific journals, including four in 2018 alone – 3 of which were published in journals from the Nature group

SOURCE

 

Shen-Orr told Forbes in an article published late last month that CytoReason’s tech is able to calculate immune age in one of two ways: “Via cell-subset composition nearest neighbor approach or based on a gene expression signature where the genes are predictive of the cell-subsets composition, and they test for their enrichment in the gene expression pattern of the sample. The immune profiles of individuals are used to predict immune changes based on a machine learning methodology deployed on data on a range of cell-subsets. ”

“The immune age is a biological clock that will help to identify, the decline and progress in immunity that occurs in old age, to determine preventive measures and develop new treatment modalities to minimize chronic disease and death,” he added.

CytoReason’s tech has so far yielded two pending patents, 10 commercial and scientific collaborations, and 16 peer-reviewed publications.

Harel says it was a combination of forces that made CytoReason’s immune-focused methodology work: Big Data, machine learning, and biology. He describes it as “the intersection of computer science and biology.”

SEE ALSO: The Future Of Medicine: Israeli Scientists Unveil New Tech To 3D-Print Personalized Drugs

 

Professor Magdassi tells NoCamels that with 3D printing of hydrogels, molecules that are soluble in water, scientists can improve the performance of the drug through its delivery. For example, “the hydrogel once ingested can be designed to swell, releasing two, or three, or four drugs at a time [or with a delay] or it can be designed not to swell, depending on what we are trying to achieve.”

“The drug can be tailored to the patient because of the unique shape or structure of the hydrogel and/or its release behavior,” Professor Magdassi explains.

Currently, there is one 3D-printed drug on the market. In 2015, the US Food and Drug Administration (FDA) approved Spritam, a 3D-printed powdered drug in pill form for the treatment of epileptic seizures, designed to dissolve faster than other pills.

SOURCE

http://nocamels.com/2018/11/future-medicine-israel-3d-print-personalized-drugs/

 

Quantifying The Age Of Our Immune System Could Bring Us Some Steps Closer To Precision Medicine

Yiannis Mouratidis

Contributor

Science

Last January, CytoReason announced an agreement with Pfizer, in which the latter will leverage the former’s technology to create cell-based models of the immune system. According to the agreement, CytoReason will receive an undisclosed amount in the low double-digit millions of U.S. dollars from Pfizer in access fees, research support and success-based payments. Prof. Shen-Orr concluded, “The immune age is a biological clock that will help to identify, the decline and progress in immunity that occurs in old age, to determine preventive measures and develop new treatment modalities to minimize chronic disease and death.”
SOURCE

Read Full Post »

Immunoediting can be a constant defense in the cancer landscape

Posted in Anticancer Resistance, Apoptosis, BioIT: BioInformatics, NGS, Clinical & Translational, Pharmaceutical R&D Informatics, Clinical Genomics, Cancer Informatics, Breast Cancer - impalpable breast lesions, Cancer - General, Cancer and Current Therapeutics, CANCER BIOLOGY & Innovations in Cancer Therapy, Cancer Genomics, Cancer Informatics, cancer metabolism, Cancer Prevention: Research & Programs, Cancer Screening, Cancer Surgery of the Heart, Cancer Vaccines: Targeting Cancer Genes for Immunotherapy, Cancer-Immune Interactions, Cell Biology, Cell Biology, Signaling & Cell Circuits, Cell death pathways, Cell Processing System in Cell Therapy Process Development, cell-based therapy, Childhood cancer, Circulating Tumor Cells (CTC), combination immunotherapies., Efficacy of Anti-Tumor T Cells, Engineering Better T Cells, Engineering Enhanced Cancer Vaccines, Funding Opportunities for Cancer Research, Human Immune System in Health and in Disease, Imaging-based Cancer Patient Management, Immune Modulatory, Immuno-Oncology & Genomics, Immunology, Immunotherapy, Infectious Disease Immunodiagnostics, Innovation in Immunology Diagnostics, Integrin-targeted Combination Immunotherapy, Liquid Biopsy Chip detects an array of metastatic cancer cell markers in blood, Liquid Biopsy: Circulating Tumor Cells in Urine and Blood, Metabolic Immuno-Oncology, Microbiome and Responses to Cancer Therapy, MicroEngineering Cell-Tissue & Systems, Modulating Macrophages in Cancer Immunotherapy, Monoclonal Immunotherapy, NK Cell-Based Cancer Immunotherapy, Pancreatic cancer, Pharmacotherapy and Cell Activity, Population Health Management, Population Health Management, Genetics & Pharmaceutical, Population Health Management, Nutrition and Phytochemistry, Precision Cancer Medicine, Prostate Cancer: Monitoring vs Treatment, RNA Biology, Cancer and Therapeutics, Signaling & Cell Circuits, Single Cell Genomics, stem cell biology and patient-specific, Stem Cells for Regenerative Medicine, Synergistic Innate and Adaptive Immunotherapy, Synthetic Immunology: Hacking Immune Cells, Universal Immune Cell Therapies (uICT), Voices of Patients and Healthcare Providers, tagged , , , , on March 16, 2019| Leave a Comment »

Immuno-editing can be a constant defense in the cancer landscape, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 1: Next Generation Sequencing (NGS)

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

There are many considerations in the cancer immunoediting landscape of defense and regulation in the cancer hallmark biology. The cancer hallmark biology in concert with key controls of the HLA compatibility affinity mechanisms are pivotal in architecting a unique patient-centric therapeutic application. Selection of random immune products including neoantigens, antigens, antibodies and other vital immune elements creates a high level of uncertainty and risk of undesirable immune reactions. Immunoediting is a constant process. The human innate and adaptive forces can either trigger favorable or unfavorable immunoediting features. Cancer is a multi-disease entity. There are multi-factorial initiators in a certain disease process. Namely, environmental exposures, viral and / or microbiome exposure disequilibrium, direct harm to DNA, poor immune adaptability, inherent risk and an individual’s own vibration rhythm in life.

 

When a human single cell is crippled (Deranged DNA) with mixed up molecular behavior that is the initiator of the problem. A once normal cell now transitioned into full threatening molecular time bomb. In the modeling and creation of a tumor it all begins with the singular molecular crisis and crippling of a normal human cell. At this point it is either chop suey (mixed bit responses) or a productive defensive and regulation response and posture of the immune system. Mixed bits of normal DNA, cancer-laden DNA, circulating tumor DNA, circulating normal cells, circulating tumor cells, circulating immune defense cells, circulating immune inflammatory cells forming a moiety of normal and a moiety of mess. The challenge is to scavenge the mess and amplify the normal.

 

Immunoediting is a primary push-button feature that is definitely required to be hit when it comes to initiating immune defenses against cancer and an adaptation in favor of regression. As mentioned before that the tumor microenvironment is a “mixed bit” moiety, which includes elements of the immune system that can defend against circulating cancer cells and tumor growth. Personalized (Precision-Based) cancer vaccines must become the primary form of treatment in this case. Current treatment regimens in conventional therapy destroy immune defenses and regulation and create more serious complications observed in tumor progression, metastasis and survival. Commonly resistance to chemotherapeutic agents is observed. These personalized treatments will be developed in concert with cancer hallmark analytics and immunocentrics affinity and selection mapping. This mapping will demonstrate molecular pathway interface and HLA compatibility and adaptation with patientcentricity.

References:

 

https://www.linkedin.com/pulse/immunoediting-cancer-landscape-john-catanzaro/

 

https://www.cell.com/cell/fulltext/S0092-8674(16)31609-9

 

https://www.researchgate.net/publication/309432057_Circulating_tumor_cell_clusters_What_we_know_and_what_we_expect_Review

 

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4190561/

 

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5840207/

 

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5593672/

 

https://www.frontiersin.org/articles/10.3389/fimmu.2018.00414/full

 

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5593672/

 

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4190561/

 

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4388310/

 

https://www.linkedin.com/pulse/cancer-hallmark-analytics-omics-data-pathway-studio-review-catanzaro/

 

Read Full Post »

Immunotherapy may help in glioblastoma survival

Posted in Anticancer Resistance, BioIT: BioInformatics, NGS, Clinical & Translational, Pharmaceutical R&D Informatics, Clinical Genomics, Cancer Informatics, Breast Cancer - impalpable breast lesions, Cancer - General, Cancer and Current Therapeutics, CANCER BIOLOGY & Innovations in Cancer Therapy, Cancer Genomics, Cancer Informatics, cancer metabolism, Cancer Prevention: Research & Programs, Cancer Screening, Cancer Vaccines: Targeting Cancer Genes for Immunotherapy, Cancer-Immune Interactions, Cell Biology, Childhood cancer, CNS-Immune Interface, combination immunotherapies., Efficacy of Anti-Tumor T Cells, Engineering Better T Cells, Glioblastoma, Imaging-based Cancer Patient Management, Immune Engineering, Immune Modulatory, Immuno-Oncology & Genomics, Immunodiagnostics, Immunology, Immunotherapy, Inflammasome, Innovation in Immunology Diagnostics, Integrin-targeted Combination Immunotherapy, Liquid Biopsy Chip detects an array of metastatic cancer cell markers in blood, Metabolic Immuno-Oncology, Metastasis Process, Modulating Macrophages in Cancer Immunotherapy, Monoclonal Immunotherapy, Neuronal Circuits, NK Cell-Based Cancer Immunotherapy, Pancreatic cancer, Population genetics, Population Health Management, Population Health Management, Genetics & Pharmaceutical, Precision Cancer Medicine, Prostate Cancer: Monitoring vs Treatment, RNA Biology, Cancer and Therapeutics, Synergistic Innate and Adaptive Immunotherapy, Synthetic Immunology: Hacking Immune Cells, Universal Immune Cell Therapies (uICT), tagged , , , , , on March 16, 2019| Leave a Comment »

Immunotherapy may help in glioblastoma survival, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 1: Next Generation Sequencing (NGS)

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

Glioblastoma is the most common primary malignant brain tumor in adults and is associated with poor survival. But, in a glimmer of hope, a recent study found that a drug designed to unleash the immune system helped some patients live longer. Glioblastoma powerfully suppresses the immune system, both at the site of the cancer and throughout the body, which has made it difficult to find effective treatments. Such tumors are complex and differ widely in their behavior and characteristics.

 

A small randomized, multi-institution clinical trial was conducted and led by researchers at the University of California at Los Angeles involved patients who had a recurrence of glioblastoma, the most common central nervous system cancer. The aim was to evaluate immune responses and survival following neoadjuvant and/or adjuvant therapy with pembrolizumab (checkpoint inhibitor) in 35 patients with recurrent, surgically resectable glioblastoma. Patients who were randomized to receive neoadjuvant pembrolizumab, with continued adjuvant therapy following surgery, had significantly extended overall survival compared to patients that were randomized to receive adjuvant, post-surgical programmed cell death protein 1 (PD-1) blockade alone.

 

Neoadjuvant PD-1 blockade was associated with upregulation of T cell– and interferon-γ-related gene expression, but downregulation of cell-cycle-related gene expression within the tumor, which was not seen in patients that received adjuvant therapy alone. Focal induction of programmed death-ligand 1 in the tumor microenvironment, enhanced clonal expansion of T cells, decreased PD-1 expression on peripheral blood T cells and a decreasing monocytic population was observed more frequently in the neoadjuvant group than in patients treated only in the adjuvant setting. These findings suggest that the neoadjuvant administration of PD-1 blockade enhanced both the local and systemic antitumor immune response and may represent a more efficacious approach to the treatment of this uniformly lethal brain tumor.

 

Immunotherapy has not proved to be effective against glioblastoma. This small clinical trial explored the effect of PD-1 blockade on recurrent glioblastoma in relation to the timing of administration. A total of 35 patients undergoing resection of recurrent disease were randomized to either neoadjuvant or adjuvant pembrolizumab, and surgical specimens were compared between the two groups. Interestingly, the tumoral gene expression signature varied between the two groups, such that those who received neoadjuvant pembrolizumab displayed an INF-γ gene signature suggestive of T-cell activation as well as suppression of cell-cycle signaling, possibly consistent with growth arrest. Although the study was not powered for efficacy, the group found an increase in overall survival in patients receiving neoadjuvant pembrolizumab compared with adjuvant pembrolizumab of 13.7 months versus 7.5 months, respectively.

 

In this small pilot study, neoadjuvant PD-1 blockade followed by surgical resection was associated with intratumoral T-cell activation and inhibition of tumor growth as well as longer survival. How the drug works in glioblastoma has not been totally established. The researchers speculated that giving the drug before surgery prompted T-cells within the tumor, which had been impaired, to attack the cancer and extend lives. The drug didn’t spur such anti-cancer activity after the surgery because those T-cells were removed along with the tumor. The results are very important and very promising but would need to be validated in much larger trials.

 

References:

 

https://www.washingtonpost.com/health/2019/02/11/immunotherapy-may-help-patients-with-kind-cancer-that-killed-john-mccain/?noredirect=on&utm_term=.e1b2e6fffccc

 

https://www.ncbi.nlm.nih.gov/pubmed/30742122

 

https://www.practiceupdate.com/content/neoadjuvant-anti-pd-1-immunotherapy-promotes-immune-responses-in-recurrent-gbm/79742/37/12/1

 

https://www.esmo.org/Oncology-News/Neoadjuvant-PD-1-Blockade-in-Glioblastoma

 

https://neurosciencenews.com/immunotherapy-glioblastoma-cancer-10722/

 

Read Full Post »

TWEETS by @pharma_BI and @AVIVA1950 at #IESYMPOSIUM – @kochinstitute 2019 #Immune #Engineering #Symposium, 1/28/2019 – 1/29/2019

Posted in Adaptive Immune Response to Biomaterials and Tissue Repair, Antibody Responses Predict Antigen Exposure, CANCER BIOLOGY & Innovations in Cancer Therapy, Cancer-Immune Interactions, CAR-T, combination immunotherapies., Conference Coverage with Social Media, CRISPR/Cas9 & Gene Editing, Cytokine Receptor Structure, Efficacy of Anti-Tumor T Cells, Engineering Better T Cells, Human Antibody Response, Human Circulating Antibody Repertoire, Human Naive B Cell Repertoire, Immune Engineering, Immune Modulatory, Immuno-Oncology & Genomics, Immunodiagnostics, Immunology, Immunotherapy, Integrin-targeted Combination Immunotherapy, MHC Repertoires for Antigen Prediction, Modulating Macrophages in Cancer Immunotherapy, mRNA platform in Drug DIscovery, NK Cell-Based Cancer Immunotherapy, Protection Against Autoimmune Disease, Synergistic Innate and Adaptive Immunotherapy, Synthetic Immunology: Hacking Immune Cells on January 31, 2019| Leave a Comment »

TWEETS by @pharma_BI and @AVIVA1950 at #IESYMPOSIUM – @kochinstitute 2019 #Immune #Engineering #Symposium, 1/28/2019 – 1/29/2019

Real Time Press Coverage: Aviva Lev-Ari, PhD, RN

2.1.3.4

2.1.3.4   TWEETS by @pharma_BI and @AVIVA1950 at #IESYMPOSIUM – @kochinstitute 2019 #Immune #Engineering #Symposium, 1/28/2019 – 1/29/2019, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 2: CRISPR for Gene Editing and DNA Repair

eProceedings for Day 1 and Day 2

LIVE Day One – Koch Institute 2019 Immune Engineering Symposium, January 28, 2019, Kresge Auditorium, MIT

https://pharmaceuticalintelligence.com/2019/01/28/live-day-one-koch-institute-2019-immune-engineering-symposium-january-28-2019-kresge-auditorium-mit/

LIVE Day Two – Koch Institute 2019 Immune Engineering Symposium, January 29, 2019, Kresge Auditorium, MIT

https://pharmaceuticalintelligence.com/2019/01/29/live-day-two-koch-institute-2019-immune-engineering-symposium-january-29-2019-kresge-auditorium-mit/

  1.  32 minutes ago

    More

    AMAZING Conference I covered in Real Time

  2.  33 minutes ago

    More

    AMAZING Conference I covered in Real Time

    https://twitter.com/i/cards/tfw/v1/1090458269901115392?cardname=summary&autoplay_disabled=true&forward=true&earned=true&edge=true&lang=en&card_height=130&scribe_context=%7B%22client%22%3A%22web%22%2C%22page%22%3A%22profile%22%2C%22section%22%3A%22profile%22%2C%22component%22%3A%22tweet%22%7D&bearer_token=AAAAAAAAAAAAAAAAAAAAAPYXBAAAAAAACLXUNDekMxqa8h%252F40K4moUkGsoc%253DTYfbDKbT3jJPCEVnMYqilB28NHfOPqkca3qaAxGfsyKCs0wRbw#xdm_e=https%3A%2F%2Ftwitter.com&xdm_c=default2444&xdm_p=1
  3.  2 hours ago

     1 minute ago

    More

    LIVE Day One – e-Proceedings 2019 , January 28, 2019, Kresge Auditorium, MIT via

    https://twitter.com/i/cards/tfw/v1/1090467426557399040?cardname=summary&autoplay_disabled=true&forward=true&earned=true&edge=true&lang=en&card_height=130&scribe_context=%7B%22client%22%3A%22web%22%2C%22page%22%3A%22me%22%2C%22section%22%3A%22profile%22%2C%22component%22%3A%22tweet%22%7D&bearer_token=AAAAAAAAAAAAAAAAAAAAAPYXBAAAAAAACLXUNDekMxqa8h%252F40K4moUkGsoc%253DTYfbDKbT3jJPCEVnMYqilB28NHfOPqkca3qaAxGfsyKCs0wRbw#xdm_e=https%3A%2F%2Ftwitter.com&xdm_c=default9831&xdm_p=1

    LIVE Day Two – Koch Institute 2019 Immune Engineering Symposium, January 29, 2019, Kresge Auditorium, MIT

    1 like
    Reply
    Retweet

    Like

    Direct message

  4.  7 hours ago

    More

    Aviv Regev Melanoma: malignant cells with resistance in cold niches in situ cells express the resistance program pre-treatment: resistance UP – cold Predict checkpoint immunotherapy outcomes CDK4/6 abemaciclib in cell lines

  5.  7 hours ago

    Aviv Regev, a cell-cell interactions from variations across individuals Most UC-risk genes are cell type specificVariation – epithelial cell signature – organize US GWAS into cell type spec

  6.  8 hours ago

    More

    Diane Mathis Age-dependent Treg and mSC changes – Linear with increase in age Sex-dependent Treg and mSC changes – Female Treg loss in cases of Obesity leading to fibrosis Treg keep IL-33-Producing mSCs under rein Lean tissue/Obese tissue

  7.  9 hours ago

    More

    Martin LaFleur Loss of Ptpn2 enhances CD8+ T cell responses to LCMV and Tumors PTpn2 deletion in the immune system enhanced tumor immunity CHIME enables in vivo screening

  8.  9 hours ago

    More

    Alex Shalek Identifying and rationally modulating cellular drivers of enhanced immunity T Cells, Clusters Expression of Peak and Memory Immunotherapy- Identifying Dendritic cells enhanced in HIV-1 Elite Controllers

  10.   Retweeted

     12 hours ago

    More

    Onward: our own Michael Birnbaum, who assures us that if you feel like you’re an immunoengineer, then you ARE one!

    4 replies2 retweets2 likes
    Reply

    Retweeted

    Liked

    Direct message
    Show this thread

  11.  11 hours ago

    More

    Glenn Dranoff Adenosine level in blood or tissue very difficult to measure in blood even more than in tissue – NIR178 + PDR 001 Monotherapy (NIR178) combine with PD receptor blockage (PDR) show benefit A alone vs A+B in Clinical trial

  12.  11 hours ago

    More

    Glenn Dranoff PD-L1 blockade elicits responses in some patients: soft part sarcoma LAG-3 combined with PD-1 – human peripheral blood tumor TIM-3 key regulator of T cell and Myeloid cell function: correlates in the TCGA DB myeloid

  13.  11 hours ago

    More

    Glenn Dranoff Institute for Biomedical Research of Neurologic toxicities of CART t IL-6 activation AML – complete response – weekly dose of XmAb CD123X CD3 bispecific antibody anti tumor effect

  14.  12 hours ago

    More

    of protective HLA-DR4 effects outside of “peptide anchor” residues Class I MHC – HLA-E down regulate T and NK cells Receptor Binding: Positional preferences noted for NKG2A

  15.  12 hours ago

    More

    Yvonne Chen Activation of t Cell use CAR t Engineer CAR-T to respond to soluble form of antigens: CD19 CAR Responds to soluble CD19 GFP MCAR responds to Dimeric GFP “Tumor microenvironment is a scary place”

  16.  12 hours ago

    More

    Yvonne Chen Do we need a ligand to be a dimers? Co-expressed second-generation TGF-beta signaling

  17.  12 hours ago

    More

    Yvonne Chen “Engineering smarter and stronger T cells for cancer immunotherapy” OR-Gate cause no relapse – Probing limits of modularity in CAR Design Bispecific CARs are superior to DualCAR: One vs DualCAR (some remained single CAR)

  18.   Retweeted

     Jan 28

    More

    Ending the 1st session is Cathy Wu of detailing some amazing work on vaccination strategies for melanoma and glioblastoma patients. They use long peptides engineered from tumor sequencing data.

    3 replies1 retweet3 likes
    Reply

    Retweeted

    Liked

    Direct message
    Show this thread
  19.   Retweeted

     Jan 28

    More

    Some fancy imaging: Duggan gives a nice demo of how dSTORM imaging works using a micropatterend image of Kennedy Institute for Rheumatology! yay!

    1 retweet2 likes
    Reply
    Retweeted

    Liked

    Direct message
    Show this thread
  20.   Retweeted

     Jan 28

    More

    Lots of interesting talks in the second session of the – effects of lymphoangiogenesis on anti-tumor immune responses, nanoparticle based strategies to improve bNAbs titers/affinity for HIV therapy, and IAPi cancer immunotherapy

    1 retweet1 like
    Reply
    Retweeted

    Liked

    Direct message
  21.   Retweeted

     15 hours ago

    More

    Looking forward to another day of the . One more highlight from yesterday – from our own lab showcased her work developing cytokine fusions that bind to collagen, boosting efficacy while drastically reducing toxicities

    1 retweet2 likes
    Reply
    Retweeted

    Liked

    Direct message
  22.   Retweeted

     Jan 28

    More

    Members of our cell therapy team were down the street today at neighboring for the presented by .

    2 retweets6 likes
    Reply
    Retweeted

    Liked

    Direct message
  23.   Retweeted

     Jan 28

    More
    Replying to  

    He could have fooled me that he is, in fact, an immunologist!

    1 reply1 retweet3 likes
    Reply

    Retweeted

    Liked

    Direct message
  24.  
  25.   Retweeted

     Jan 22

    More

    I absolutely LOVE this essay. “Why geneticists stole cancer research even though cancer is primarily a signaling disease”

    https://twitter.com/i/cards/tfw/v1/1087802072144273408?cardname=summary&autoplay_disabled=true&forward=true&earned=true&edge=true&lang=en&card_height=130&scribe_context=%7B%22client%22%3A%22web%22%2C%22page%22%3A%22me%22%2C%22section%22%3A%22profile%22%2C%22component%22%3A%22tweet%22%7D&bearer_token=AAAAAAAAAAAAAAAAAAAAAPYXBAAAAAAACLXUNDekMxqa8h%252F40K4moUkGsoc%253DTYfbDKbT3jJPCEVnMYqilB28NHfOPqkca3qaAxGfsyKCs0wRbw#xdm_e=https%3A%2F%2Ftwitter.com&xdm_c=default1249&xdm_p=1
    8 replies36 retweets116 likes
    Reply

    Retweeted

    Liked

    Direct message
  26.   Retweeted

     Jan 28

    More

    Come and say Hi! ACIR will be back tomorrow at the Immune Engineering Symposium at MIT. Learn more at . . And stay tuned to read our summary of the talks on Feb 6.

    2 retweets1 like
    Reply
    Retweeted

    Liked

    Direct message

  27.  14 hours ago

    More

    Facundo Batista @MGH # in BG18 Germline Heavy CHain (BG18-gH) High-mannose patch – mice exhibit normal B cell development B cells from naive human germline BG18-gH bind to GT2 immunogen

  28.  14 hours ago

    More

    Preeti Sharma, U Illinois T cell receptor and CAR-T engineering TCR engineering for Targeting glycosylated cancer antigens Nornal glycosylation vs Aberrant Engineering 237-CARs libraries with conjugated (Tn-OTS8) against Tn-antigend In vitro

  29.  14 hours ago

    More

    Bryan Bryson Loss of polarization potential: scRNAseq reveals transcriptional differences Thioredoxin facilitates immune response to Mtb is a marker of an inflammatory macrophage state functional spectrum of human microphages

  30.  14 hours ago

    More

    Bryan Bryson macrophage axis in Mycobacterium tuberculosis Building “libraries” – surface marker analysis of Microphages Polarized macrophages are functionally different quant and qual differences History of GM-CSF suppresses IL-10

  31.  15 hours ago

    More

    Jamie Spangler John Hopkins University “Reprogramming anti-cancer immunity RESPONSE through molecular engineering” De novo IL-2 potetiator in therapeutic superior to the natural cytokine by molecular engineering mimicking other cytokines

  32.  15 hours ago

    More

    Jamie Spangler JES6-1 Immunocytokine – inhibiting melanoma Engineering a Treg cell-biased immunocytokine double mutant immunocytokine shows enhanced IL-2Ralpha exchange Affinity De Novo design of a hyper-stable, effector biased IL-2

  33.  1 day ago

    More

    , Volume Six: for and for . On com since 12/24/2018

    1 retweet1 like
    Reply
    Retweet

    Like

    View Tweet activity

  34.  1 day ago

    More

    , Volume Five: in of Cardiovascular Diseases. On com since 12/23/2018

    1 retweet1 like
    Reply
    Retweet

    Like

    View Tweet activity

  35.  1 day ago

    More

    , Volume Four: and : The for Cardiovascular Diseases. On com since 12/26/2015

    https://twitter.com/i/cards/tfw/v1/1090048203850952704?cardname=summary_large_image&autoplay_disabled=true&forward=true&earned=true&edge=true&lang=en&card_height=343.991455078125&scribe_context=%7B%22client%22%3A%22web%22%2C%22page%22%3A%22me%22%2C%22section%22%3A%22profile%22%2C%22component%22%3A%22tweet%22%7D&bearer_token=AAAAAAAAAAAAAAAAAAAAAPYXBAAAAAAACLXUNDekMxqa8h%252F40K4moUkGsoc%253DTYfbDKbT3jJPCEVnMYqilB28NHfOPqkca3qaAxGfsyKCs0wRbw#xdm_e=https%3A%2F%2Ftwitter.com&xdm_c=default1250&xdm_p=1
    1 retweet2 likes
    Reply
    Retweet

    Like

    View Tweet activity

  36.  1 day ago

    More

    , Volume Three: of Diseases: , and . On com since 11/29/2015

    https://twitter.com/i/cards/tfw/v1/1090047868537397248?cardname=summary_large_image&autoplay_disabled=true&forward=true&earned=true&edge=true&lang=en&card_height=343.991455078125&scribe_context=%7B%22client%22%3A%22web%22%2C%22page%22%3A%22me%22%2C%22section%22%3A%22profile%22%2C%22component%22%3A%22tweet%22%7D&bearer_token=AAAAAAAAAAAAAAAAAAAAAPYXBAAAAAAACLXUNDekMxqa8h%252F40K4moUkGsoc%253DTYfbDKbT3jJPCEVnMYqilB28NHfOPqkca3qaAxGfsyKCs0wRbw#xdm_e=https%3A%2F%2Ftwitter.com&xdm_c=default1251&xdm_p=1
    1 retweet1 like
    Reply
    Retweet

    Like

    View Tweet activity

  37.  1 day ago

    More

    , Volume Two: Cardiovascular : Cases in Design for Co-Curation. On com since 11/30/2015

    https://twitter.com/i/cards/tfw/v1/1090047458409922567?cardname=summary_large_image&autoplay_disabled=true&forward=true&earned=true&edge=true&lang=en&card_height=343.991455078125&scribe_context=%7B%22client%22%3A%22web%22%2C%22page%22%3A%22me%22%2C%22section%22%3A%22profile%22%2C%22component%22%3A%22tweet%22%7D&bearer_token=AAAAAAAAAAAAAAAAAAAAAPYXBAAAAAAACLXUNDekMxqa8h%252F40K4moUkGsoc%253DTYfbDKbT3jJPCEVnMYqilB28NHfOPqkca3qaAxGfsyKCs0wRbw#xdm_e=https%3A%2F%2Ftwitter.com&xdm_c=default1252&xdm_p=1
    1 retweet2 likes
    Reply
    Retweet

    Like

    View Tweet activity

  38.  1 day ago

    More

    , Volume One: on in . On com since 6/21/2013

    https://twitter.com/i/cards/tfw/v1/1090046947002667013?cardname=summary_large_image&autoplay_disabled=true&forward=true&earned=true&edge=true&lang=en&card_height=343.991455078125&scribe_context=%7B%22client%22%3A%22web%22%2C%22page%22%3A%22me%22%2C%22section%22%3A%22profile%22%2C%22component%22%3A%22tweet%22%7D&bearer_token=AAAAAAAAAAAAAAAAAAAAAPYXBAAAAAAACLXUNDekMxqa8h%252F40K4moUkGsoc%253DTYfbDKbT3jJPCEVnMYqilB28NHfOPqkca3qaAxGfsyKCs0wRbw#xdm_e=https%3A%2F%2Ftwitter.com&xdm_c=default1253&xdm_p=1
    1 retweet1 like
    Reply
    Retweet

    Like

    View Tweet activity

  39.  1 day ago

    More

    eProceeding LIVE Day One 2019 , January 28, 2019, Kresge Auditorium, MIT via

    https://twitter.com/i/cards/tfw/v1/1090039440536264704?cardname=summary&autoplay_disabled=true&forward=true&earned=true&edge=true&lang=en&card_height=130&scribe_context=%7B%22client%22%3A%22web%22%2C%22page%22%3A%22me%22%2C%22section%22%3A%22profile%22%2C%22component%22%3A%22tweet%22%7D&bearer_token=AAAAAAAAAAAAAAAAAAAAAPYXBAAAAAAACLXUNDekMxqa8h%252F40K4moUkGsoc%253DTYfbDKbT3jJPCEVnMYqilB28NHfOPqkca3qaAxGfsyKCs0wRbw#xdm_e=https%3A%2F%2Ftwitter.com&xdm_c=default1254&xdm_p=1
    1 retweet1 like
    Reply
    Retweet

    Like

    View Tweet activity

  40.  Jan 28

    More

    Michael Dustin ESCRT pathway associated with synaptic ectosomes Locatization, Microscopy Cytotoxic T cell granules CTLs release extracellular vescicles similar to T Helper with perforin and granzyme – CTL vesicles kill targets

    1 retweet
    Reply
    Retweet

    Like

    View Tweet activity

  41.  Jan 28

    More

    Michael Dustin Delivery of T cell Effector function through extracellular vesicles Synaptic ectosome biogenisis Model: T cells: DOpamine cascade in germinal cell delivered to synaptic cleft – Effector CD40 – Transfer is cooperative

  42.  Jan 28

    More

    Michael Dustin Delivery of T cell Effector function through extracellular vesicles Laterally mobile ligands track receptor interaction ICAM-1 Signaling of synapse – Sustain signaling by transient in microclusters TCR related Invadipodia

  43.  Jan 28

    More

    Mikael Pittet @MGH Myeloid Cells in Cancer Indirect mechanism AFTER a-PD-1 Treatment IFN-gamma Sensing Fosters IL-12 & therapeutic Responses aPD-1-Mediated Activation of Tumor Immunity – Direct activation and the ‘Licensing’ Model

    1 retweet2 likes
    Reply
    Retweet

    Like

    View Tweet activity

  44.  Jan 28

    More

    Stefani Spranger KI Response to checkpoint blockade Non-T cell-inflamed – is LACK OF T CELL INFILTRATION Tumor CD103 dendritic cells – Tumor-residing Batf3-drivenCD103 Tumor-intrinsic Beta-catenin mediates lack of T cell infiltration

    1 retweet2 likes
    Reply
    Retweet

    Like

    View Tweet activity

  45.  Jan 28

    More

    Max Krummel Gene expression association between two genes: and numbers are tightly linked to response to checkpoint blockage IMMUNE “ACCOMODATION” ARCHYTYPES: MYELOID TUNING OF ARCHITYPES Myeloid function and composition

  46.  Jan 28

    More

    Noor Momin, MIT Lumican-cytokines improve control of distant lesions – Lumican-fusion potentiates systemic anti-tumor immunity

    Translate Tweet

    1 retweet2 likes
    Reply
    Retweet

    Like

    View Tweet activity

  47.  Jan 28

    More

    Noor Momin, MIT Lumican fusion to IL-2 improves treatment efficacy reduce toxicity – Anti-TAA mAb – TA99 vs IL-2 Best efficacy and least toxicity in Lumican-MSA-IL-2 vs MSA-IL2 Lumican synergy with CAR-T

    1 retweet2 likes
    Reply
    Retweet

    Like

    View Tweet activity
  48.   Retweeted

     Jan 27

    More

    excited to attend the immune engineering symposium this week! find me there to chat about and whether your paper could be a good fit for us! 🦠🧬🔬🧫📖

    Join leading immunology researchers at our Immune Engineering Symposium on Jan. 28 & 29. Register now:
    5 retweets13 likes
    Reply
    Retweeted

    Liked

    Direct message
  49.   Retweeted

     Jan 28

    More

    Bob Schreiber and Tyler Jacks kicked off the with 2 great talks on the role of Class I and Class II neo-Ag in tumor immunogenicity and how the tumor microenvironment alters T cell responsiveness to tumors in vivo

    2 retweets4 likes
    Reply
    Retweeted

    Liked

    Direct message
  50.   Retweeted

     Jan 28

    More

    Scott Wilson from gave a fantastic talk on glycopolymer conjugation to antigens to improve trafficking to HAPCs and enhanced tolerization in autoimmunity models. Excited to learn more about his work at his faculty talk!

    1 reply2 retweets3 likes
    Reply

    Retweeted

    Liked

    Direct message
    Show this thread

  51.  Jan 28

    More

    AMAZING Symposinm

    Spending the (literal) first day of my fellowship at the ! Cathy Wu talking about the use of neoantigen targeting cancer vaccines for the treatment of ‘cold’ glioblastoma tumors in pts
    1 like
    Reply
    Retweet

    Like

    View Tweet activity
  52.   Retweeted

     Jan 28

    More

    Immune Engineering Symposium at MIT is underway!

    3 retweets7 likes
    Reply
    Retweeted

    Liked

    Direct message
  53.   Retweeted

     Jan 25

    More

    ACIR is excited to be covering the Immune Engineering Symposium at MIT on January 28-29. Learn more at .

    6 retweets8 likes
    Reply
    Retweeted

    Liked

    Direct message

  54.  Jan 28

    More

    Tyler Jacks talk was outstanding, Needs be delivered A@TED TALKs, needs become contents in the curriculum of Cell Biology graduate seminar as an Online class. BRAVO

    My boss, director Tyler Jacks, presenting beautiful, unpublished work at our 3rd .
    Reply
    Retweet

    Like

    View Tweet activity
  55.   Retweeted

     Jan 28

    More

    Here we go!! Today and tomorrow the tippity top immunologists converge at

    1 reply5 retweets7 likes
    Reply

    Retweeted

    Liked

    Direct message
    Show this thread
  56.   Retweeted

     Jan 28

    More

    Exciting start to this year’s Immune Engineering Symposium put on by at . A few highlights from the first section…

    1 reply5 retweets6 likes
    Reply

    Retweeted

    Liked

    Direct message
    Show this thread

  57.  Jan 28

    More

    Stephanie Dougan (Dana-Farber Cancer Institute) Dept. Virology IAPi outperforms checkpoint blockade in T cell cold tumors reduction of tumor burden gencitabine cross-presenting DCs and CD8 T cells – T cell low 6694c2

    1 retweet2 likes
    Reply
    Retweet

    Like

    View Tweet activity

  58.  Jan 28

    More

    Darrell Irvine (MIT, Koch Institute; HHMI) Engineering follicle delivery through synthetic glycans: eOD-60mer nanoparticles vs Ferritin-trimer 8-mer (density dependent)

  59.  Jan 28

    More

    Darrell Irvine (MIT, Koch Institute; HHMI) GC targeting is dependent on complement component CIQ – activation: Mannose-binding lectins recognize eOD-60mer but not eOD monomer or trimers

    1 retweet2 likes
    Reply
    Retweet

    Like

    View Tweet activity

  60.  Jan 28

    More

    Melody Swartz (University of Chicago) Lymphangiogenesis attractive to Native T cells, in VEGF-C tumors T cell homing inhibitors vs block T cell egress inhibitors – Immunotherapy induces T cell killing

  61.  Jan 28

    More

    Paradigm shift vs

    2 retweets4 likes
    Reply
    Retweet

    Like

    View Tweet activity

  62.  Jan 28

    More

    Cathy Wu @MGH breakthrough for Brain Tumor based neoantigen-specific T cell at intracranial site Single cells brain tissue vs single cells from neoantigen specific T cells – intratumoral neoantigen-specific T cells: mutARGAP35-spacific

    1 retweet2 likes
    Reply
    Retweet

    Like

    View Tweet activity

  63.  Jan 28

    More

    Cathy Wu (Massachusetts General Hospital) – CoFounder of NEON Enduring complete radiographic responses after + alpha-PD-1 treatment (anti-PD-1) NeoVax vs IVAC Mutanome for melanoma and Glioblastoma clinical trials

    1 retweet2 likes
    Reply
    Retweet

    Like

    View Tweet activity

  64.  Jan 28

    More

    , U of Chicago IV INJECTION: OVAALBUMIN OVA-P(GALINAC), P(GLCNAC), SUPRESS T CELL RESPONSE Abate T cells response – Reduced cytokine production & increased -regs

  65.  Jan 28

    More

    Interrogating markers of T cell dysfunction – chance biology of cells by CRISPR – EGR2 at 2 weeks dysfuntioning is reduced presence of EDR2 mutant class plays role in cell metabolism cell becomes functional regulator CD8 T cell

  66.  Jan 28

    More

    Bob Schreiber (Wash University of St. Louis) Optimal CD8+ T cells mediated to T3 require CD4+ T help

Read Full Post »

LIVE Day Two – Koch Institute 2019 Immune Engineering Symposium, January 29, 2019, Kresge Auditorium, MIT

Posted in Adaptive Immune Response to Biomaterials and Tissue Repair, Antibody Responses Predict Antigen Exposure, CANCER BIOLOGY & Innovations in Cancer Therapy, Cancer-Immune Interactions, Conference Coverage with Social Media, Cytokine Receptor Structure, Efficacy of Anti-Tumor T Cells, Engineering Better T Cells, Human Antibody Response, Human Circulating Antibody Repertoire, Human Naive B Cell Repertoire, Immune Engineering, Immune Modulatory, Immuno-Oncology & Genomics, Immunodiagnostics, Immunology, Immunotherapy, MHC Repertoires for Antigen Prediction, Modulating Macrophages in Cancer Immunotherapy, NK Cell-Based Cancer Immunotherapy, Protection Against Autoimmune Disease, Synergistic Innate and Adaptive Immunotherapy, Synthetic Immunology: Hacking Immune Cells on January 29, 2019| Leave a Comment »

LIVE Day Two – Koch Institute 2019 Immune Engineering Symposium, January 29, 2019, Kresge Auditorium, MIT

Reporter: Aviva Lev-Ari, PhD, RN

 

Real Time Press Coverage: Aviva Lev-Ari, PhD, RN

#IESYMPOSIUM @pharma_BI @AVIVA1950

 

MISSION The mission of the Koch Institute (KI) is to apply the tools of science and technology to improve the way cancer is detected, monitored, treated and prevented.

APPROACH We bring together scientists and engineers – in collaboration with clinicians and industry partners – to solve the most intractable problems in cancer. Leveraging MIT’s strengths in technology, the life sciences and interdisciplinary research, the KI is pursuing scientific excellence while also directly promoting innovative ways to diagnose, monitor, and treat cancer through advanced technology.

HISTORY The Koch Institute facility was made possible through a $100 million gift from MIT alumnus David H. Koch. Our new building opened in March 2011, coinciding with MIT’s 150th anniversary. Our community has grown out of the MIT Center for Cancer Research (CCR), which was founded in 1974 by Nobel Laureate and MIT Professor Salvador Luria, and is one of seven National Cancer Institute-designated basic (non-clinical) research centers in the U.S.

https://ki.mit.edu/files/ki/cfile/news/presskit/KI_Fact_Sheet_-_February_2018.pdf

January 28-29, 2019
Kresge Auditorium, MIT

Biological, chemical, and materials engineers are engaged at the forefront of immunology research. At their disposal is an analytical toolkit honed to solve problems in the petrochemical and materials industries, which share the presence of complex reaction networks, and convective and diffusive molecular transport. Powerful synthetic capabilities have also been crafted: binding proteins can be engineered with effectively arbitrary specificity and affinity, and multifunctional nanoparticles and gels have been designed to interact in highly specific fashions with cells and tissues. Fearless pursuit of knowledge and solutions across disciplinary boundaries characterizes this nascent discipline of immune engineering, synergizing with immunologists and clinicians to put immunotherapy into practice.

The 2019 symposium will include two poster sessions and four abstract-selected talks. Abstracts should be uploaded on the registration page. Abstract submission deadline is November 15, 2018. Registration closes December 14.

Featuring on Day 2, 1/29, 2019:

Session IV

Moderator: Michael Birnbaum, Koch Institute, MIT

 

Jamie Spangler (John Hopkins University)

“Reprogramming anti-cancer immunity through molecular engineering”

  • Reprogramming anti-cancer immunity response through molecular engineering”
  • Cytokines induce receptor dimerization
  • Clinical Use of cytokines: Pleiotropy, expression and stability isssues
  • poor pharmacological properties
  • cytokine therapy: New de novo protein using computational methods
  • IL-2 signals through a dimeric nad a trimeric receptor complex
  • IL-2 pleiotropy hinders its therapeutic efficacy
  • IL-2 activate immunosuppression
  • potentiation of cytokine activity by anti-IL-2 antibody selectivity
  • Cytokine binding – Antibodies compete with IL-2 receptor subunits
  • IL-2Ralpha, IL-2 Rbeta: S4B6 mimickry of alpha allosterically enhances beta
  • stimulates both Effectors and T-regs
  • JES6-1 immunocomplex selectively stimulates IL-2Ralpha cells
  • Engineering translational single-chain cytokine/antibody fusion
  • Engineering an EFFECTOR cell-based immunocytokine (602)
  • JES6-1 Immunocytokine – inhibiting melanoma
  • Engineering a Treg cell-biased immunocytokine
  • double mutant immunocytokine shows enhanced IL-2Ralpha exchange
  • Affinity  – molecular eng De Novo design of a hyper-stable, effector biased IL-2
  • De novo IL-2 poteniator in therapeutic superior to the natural cytokine by molecular engineering

 

Bryan Bryson (MIT, Department of Biological Engineering)

“Exploiting the macrophage axis in Mycobacterium tuberculosis (Mtb) infection”

  • TB  – who develop Active and why?
  • Immunological life cycle of Mtb
  • Global disease Mtb infection outcome varies within individual host
  • lesion are found by single bacteria
  • What are the cellular players in immune success
  • MACROPHAGES – molecular signals enhancing Mtb control of macrophages
  • modeling the host- macrophages are plastic and polarize
  • Building “libraries” – surface marker analysis of Microphages
  • Polarized macrophages are functionally different
  • quant and qual differences
  • History of GM-CSF suppresses IL-10
  • Loss of polarization potential: scRNAseq reveals transcriptional differences Thioredoxin facilitates immune response to Mtb is a marker of an inflammatory macrophage state
  • functional spectrum of human microphages

 

Facundo Batista (Ragon Institute (HIV Research) @MGH, MIT and Harvard)

“Vaccine evaluation in rapidly produced custom humanized mouse models”

  • Effective B cell activation requires 2 signals Antigen and binding to T cell
  • VDJ UCA (Unmutated common Ancestor)
  • B Cell Receptor (BCR) co-receptors and cytoskeleton
  • 44% in Women age 24-44
  • Prototype HIV broadly neutralizing Antibodies (bnAb) do not bind to Env protein – Immunogen design and validation
  • Target Identification –>> Immunogen Design –>>> Immunogen Validation
  • Human Ig Knock-ins [Light variable 5′ chain length vs 7′ length] decisive to inform immunogenicity – One-Step CRISPR approach does not require ES cell work
  • Proof of principle with BG18 Germline Heavy Chain (BG18-gH) High-mannose patch – mice exhibit normal B cell development
  • B cells from naive human germline BG18-gH bind to GT2 immunogen
  • GT2-nanoparticle 9NP) induces robust BG18-gH-500 cells: CD45.2 GL7 IgD
  • Interrogate immune response for HIV, Malaria, Zika, Flu

 

Session V

Moderator: Dane Wittrup, Koch Institute, MIT

 

Yvonne Chen (University of California, Los Angeles)

“Engineering smarter and stronger T cells for cancer immunotherapy”

  • Adoptive T-Cell Therapy
  • Tx for Leukemia – Tumor Antigen escape fro CAR T-cell therapy, CD19/CD20 OR-Gate CARs for prevention of antigen escape – 15 month of development
  • reduce probability of antigen escape due to two antigen CD19/CD20: Probing limits of modularity in CAR design
  • In vivo model: 75% wild type & 25% CD19 – relapse occur in the long term, early vs late vs no relapse: Tx with CAR t had no relapse
  • OR-Gate cause no relapse – Probing limits of modularity in CAR Design
  • Bispecific CARs are superior to DualCAR: One vs DualCAR (some remained single CAR)
  • Bispecific CARs exhibit superior antigen-stimulation capacity – OR-Gate CAR Outperforms Single-Input CARs
  • Lymphoma and Leukemia are 10% of all Cancers
  • TGF-gamma Rewiring T Cell Response
  • Activation of t Cell use CAR t
  • Engineer CAR-T to respond to soluble form of antigens: CD19 CAR Responds to soluble CD19
  • GFP MCAR responds to Dimeric GFP
  • “Tumor microenvironment is a scary place”

 

Michael Birnbaum, MIT, Koch Institute

“A repertoire of protective tumor immunity”

  • Decoding T and NK cell recognition – understanding immune recognition and signaling function for reprogramming the Immune system – Neoantigen vaccine pipeline
  • Personal neoantigen vax improve immunotherapy
  • CLASS I and CLASS II epitomes: MHC prediction performance – more accurate for CLASS I HLA polymorphisms
  • Immune Epitope DB and Analysis Resources 448,630 Peptide Epitomes
  • B cell assay: 413,000
  • T cell assays: 313,000
  • peptide sequence relationships – naturally occurring antigen predictions
  • Cleavable pMHC yeast display to determine peptide loading
  • HLA-DR4 libraries enrich a large collection of peptides: 96000 1/5 of entire peptide DB: Enriched motif, prediction algorithms
  • Algorithmic false negatives vs peptide concentration(nM)
  • HLA-DR4 effects outside of “peptide anchor” residues
  • Class I MHC – HLA-E down regulate T and NK cells
  • Receptor Binding: Positional preferences noted for NKG2A
  • Training data vs Algorithmic approach
  • Globally oriented –
  • TCR sequencing – TCR pairings – Multicell-per-well sequencing
  • MAD-HYPE algorithm

 

Glenn Dranoff, Novartis Institute for Biomedical Research

“Mechnism of protective tumor immunity”

  • Immune checkpoint blockade elicit 10 years survival in melanoma
  • PD-1 blockage esophageal carcinoma effective showing survival
  • renal cells, bladder
  • 20% benefit from Immuno therapy – CTLA-4 toxicity is high small % patient benefit
  • PD-1/PD-L1 anti CLTA-4 mAbs
  • solid tumors challenging
  • Requirement for effective IO – Tumor receptivity to immune infiltration
  • modulation
  • Novartis IO in the clinic: multiple tumor immune escape – complexity
  • Approach: focus trials aimed to learn immune response complementation groups manipulate into response
  • work with Engineering for delivery nimble to generate new data
  • Translational research in the clinic
  • CAR T cells
  • B cell malignancies are ideal targets for CAR T cells
  • Relapsed/Refractory – pediatric ALL refractory advanced to no relapse – complete response 80% – 6 years response
  • Antigen loss CD19 – targeting with combinatorial approach to avoid relapse
  • Large B cell lymphoma
  • Neurologic toxicities of CART t IL-6 activation
  • AML – complete response – weekly dose of XmAb CD123X CD3 bispecific antibody – protein engineering – anti tumor effect in refractory Leukemia
  • anaplastic thyroid carcinoma
  • PD-L1 blockade elicits responses in some patients: soft part sarcoma
  • LAG-3 combined with PD-1 – human peripheral blood tumor
  • TIM-3 key regulator of T cell and Myeloid cell function: correlates in the TCGA DB with myeloid
  • Adenosine level in blood or tissue very difficult to measure in blood even more than in tissue – NIR178 + PDR 001 Mono-therapy (NIR178) combine with PD receptor blockage (PDR) – shows benefit
  • A alone vs A+B in Clinical trial

 

Session VI

Moderator: Stefani Spranger, Koch Institute, MIT

 

Tim Springer, Boston Children’s Hospital, HMS

The Milieu Model for TGF-Betta Activation”

  • Protein Science – Genomics with Protein
  • Antibody Initiative – new type of antibodies not a monoclonal antibody – a different type
  • Pro TGF-beta
  • TGF-beta – not a typical cytokine it is a prodamine for Mature growth factor — 33 genes mono and heterogeneous dimers
  • Latent TGF-Beta1 crystal structure: prodomaine shields the Growth Factor
  • Mechanism od activation of pro-TGF-beta – integrin alphaVBeta 6: pro-beta1:2
  • Simulation in vivo: actin cytoskeleton cytoplasmic domain
  • LIFE CYCLE OF PROTGF-BETA
  • LRRC33 – GARP class relative
  • microglia and macrophage – link TGF-beta phenotype knock outs
  • TGF compartments of microglia separated myelination loss
  • Inhibition of TGF-beta enhances immune checkpoint
  • Loss of LRRC33-dependent TGF-beta signaling would counteract immune suppression in tumor and in slow tumor growth
  • lung metastasis of B16 in melanoma
  • immuno-histo-chemistry: LRRC33 tumor-associated myeloid cell lack cell surface proTGF-beta1
  • blocking antibodies LRRC33 mitigate toxicity on PD-L1 treatment

 

Alex Shalek, MIT, Department of Chemistry, Koch Institute

“Identifying and rationally modulating cellular drivers of enhanced immunity”

  • Balance in the Immune system
  • Profiling Granulomas  using Seq-Well 2.0
  • lung tissue in South Africa of TB patients
  • Granulomas, linking cell type abundance with burden
  • Exploring T cells Phenotypes
  • Cytotoxic & Effector ST@+ Regulatory
  • Vaccine against TB – 19% effective, only 0 IV BCG vaccination can elicit sterilizing Immunity
  • Profiling cellular response to vaccination
  • T cell gene modules across vaccine routes
  • T Cells, Clusters
  • Expression of Peak and Memory
  • Immunotherapy- Identifying Dendritic cells enhanced in HIV-1 Elite Controllers
  • moving from Observing to Engineering
  • Cellular signature: NK-kB Signaling
  • Identifying and testing Cellular Correlates of TB Protection
  • Beyond Biology: Translation research: Data sets: dosen

 

Session VII

Moderator: Stefani Spranger, Koch Institute, MIT

 

Diane Mathis, Harvard Medical School

“Tissue T-regs”

  • T reg populations in Lymphoid Non–lymphoid Tissues
  • 2009 – Treg tissue homeostasis status – sensitivity to insulin, 5-15% CD4+ T compartment
  •  transcriptome
  • expanded repertoires TCRs
  • viceral adipose tissue (VAT) –  Insulin
  • Dependencies: Taget IL-33 its I/1r/1 – encoded Receptor ST2
  • VAT up-regulate I/1r/1:ST2 Signaling
  • IL-33 – CD45 negative CD31 negative
  • mSC Production of IL-33 is Important to Treg
  • The mesenchyme develops into the tissues of the lymphatic and circulatory systems, as well as the musculoskeletal system. This latter system is characterized as connective tissues throughout the body, such as bone, muscle and cartilage. A malignant cancer of mesenchymal cells is a type of sarcoma.
  • mesenchymal Stromal Cells – mSC – some not all, VAT mSCs express IL-33
  • development of a mAb Panel for sorting the mSC Subtypes
  • Deeper transcriptome for Phenotyping of VAT mSCs
  • physiologic & pathologic perturbation
  1. Age-dependent Treg and mSC changes – Linear with increase in age
  2. Sex-dependent Treg and mSC changes – Female
  • Treg loss in cases of Obesity leading to fibrosis
  • Treg keep IL-33-Producing mSCs under rein
  • Lean tissue vs Obese tissue
  • Aged mice show poor skeletal muscle repair – it is reverses by IL-33 Injection
  • Immuno-response: target tissues systemic T reg
  • Treg and mSC

 

Aviv Regev, Broad Institute; Koch Institute

“Cell atlases as roadmaps to understand Cancer”

  • Colon disease UC – genetic underlining risk, – A single cell atlas of healthy and UC colonic mucosa inflammed and non-inflammed: Epithelial, stromal, Immune – fibroblast not observed in UC colon IAFs; IL13RA2 + IL11
  • Anti TNF responders – epithelial cells
  • Anti TNF non-responders – inflammatory monocytes fibroblasts
  • RESISTANCE to anti-cancer therapy: OSM (Inflammatory monocytes-OSMR (IAF)
  • cell-cell interactions from variations across individuals
  • Most UC-risk genes are cell type specific
  • Variation within a cell type helps predict GWAS gene functions – epithelial cell signature – organize US GWAS into cell type specific – genes in associated regions: UC and IBD

 

  • Melanoma
  • malignant cells with resistance in cold niches in situ
  • cells express the resistance program pre-treatment: resistance UP – cold
  • Predict checkpoint immunotherapy outcomes
  • CDK4/6 – computational search predict as program regulators: abemaciclib in cell lines

 

 

 

Poster Presenters

Preeti Sharma, University of Illinois

T cell receptor and CAR-T engineering – T cell therapy

  • TCR Complex: Vbeta Cbeta P2A Valpha Calpha
  • CAR-T Aga2 HA scTCR/scFv c-myc
  • Directed elovution to isolate optimal TCR or CAR
  • Eng TCR and CARt cell therapy
  • Use of TCRs against pep/MHC allows targeting a n array of cancer antigens
  • TCRs are isolated from T cell clones
  • Conventional TCR identification method vs In Vitro TCR Eng directed evolution
  • T1 and RD1 TCRs drive activity against MART-1 in CD4+ T cells
  • CD8+
  • TCR engineering for Targeting glycosylated cancer antigens
  • Normal glycosylation vs Aberrant glycosylation
  • Engineering 237-CARs  libraries with conjugated (Tn-OTS8) against multiple human Tn-antigend
  • In vitro engineering: broaden specificity to multiple peptide backbone
  • CAR engineering collaborations with U Chicago, U Wash, UPenn, Copenhagen, Germany

 

Martin LaFleur, HMS

CRISPR- Cas9 Bone marrow stem cells for Cancer Immunotherapy

  • CHIME: CHimeric IMmune Editing system
  • sgRNA-Vex
  • CHIME can be used to KO genes in multiple immune lineages
  • identify T cell intrinsic effects in the LCMV model Spleen-depleted, Spleen enhanced
  • Loss of Ptpn2 enhances CD8+ T cell responses to LCMV and Tumors
  • Ptpn2 deletion in the immune system enhanced tumor immunity
  • CHIME enables in vivo screening

 

 

Read Full Post »

LIVE Day One – Koch Institute 2019 Immune Engineering Symposium, January 28, 2019, Kresge Auditorium, MIT

Posted in Adaptive Immune Response to Biomaterials and Tissue Repair, Antibody Responses Predict Antigen Exposure, Cancer-Immune Interactions, Conference Coverage with Social Media, Human Antibody Response, Human Circulating Antibody Repertoire, Human Naive B Cell Repertoire, Immune Engineering, Immuno-Oncology & Genomics, Immunodiagnostics, Immunology, Immunotherapy, MHC Repertoires for Antigen Prediction, Synergistic Innate and Adaptive Immunotherapy, Synthetic Immunology: Hacking Immune Cells on January 28, 2019| Leave a Comment »

LIVE Day One – Koch Institute 2019 Immune Engineering Symposium, January 28, 2019, Kresge Auditorium, MIT

Reporter: Aviva Lev-Ari, PhD, RN

 

Real Time Press Coverage: Aviva Lev-Ari, PhD, RN

#IESYMPOSIUM @pharma_BI @AVIVA1950

MISSION The mission of the Koch Institute (KI) is to apply the tools of science and technology to improve the way cancer is detected, monitored, treated and prevented.

APPROACH We bring together scientists and engineers – in collaboration with clinicians and industry partners – to solve the most intractable problems in cancer. Leveraging MIT’s strengths in technology, the life sciences and interdisciplinary research, the KI is pursuing scientific excellence while also directly promoting innovative ways to diagnose, monitor, and treat cancer through advanced technology.

HISTORY The Koch Institute facility was made possible through a $100 million gift from MIT alumnus David H. Koch. Our new building opened in March 2011, coinciding with MIT’s 150th anniversary. Our community has grown out of the MIT Center for Cancer Research (CCR), which was founded in 1974 by Nobel Laureate and MIT Professor Salvador Luria, and is one of seven National Cancer Institute-designated basic (non-clinical) research centers in the U.S.

https://ki.mit.edu/files/ki/cfile/news/presskit/KI_Fact_Sheet_-_February_2018.pdf

January 28-29, 2019
Kresge Auditorium, MIT

Biological, chemical, and materials engineers are engaged at the forefront of immunology research. At their disposal is an analytical toolkit honed to solve problems in the petrochemical and materials industries, which share the presence of complex reaction networks, and convective and diffusive molecular transport. Powerful synthetic capabilities have also been crafted: binding proteins can be engineered with effectively arbitrary specificity and affinity, and multifunctional nanoparticles and gels have been designed to interact in highly specific fashions with cells and tissues. Fearless pursuit of knowledge and solutions across disciplinary boundaries characterizes this nascent discipline of immune engineering, synergizing with immunologists and clinicians to put immunotherapy into practice.

The 2019 symposium will include two poster sessions and four abstract-selected talks. Abstracts should be uploaded on the registration page. Abstract submission deadline is November 15, 2018. Registration closes December 14.

Featuring on Day 1, 1/28, 2019:

Dane Wittrup,, Koch Institute, MIT

IMMUNE BIOLOGY,

 

7 — Stephanie Dougan (Dana-Farber Cancer Institute) HMS, Department of Virology

  • Shared antigens may be the only option for many patients
  • Pathogens, self-antigens, tumor neoantigens, shared coexpressed
  • T cell affinity low or high TCRs – Augment priming
  • Radiation plus anti-CD40 induces vigorous T cell priming
  • TNF family co-stimulatory receptor signaling can be mimicked by IAP antagonists
  • SMACK – c-IAP12 – IAPi enhances function of many immune cells: B Cells, Dendritic cells,
  • Pancreatic cancer cell immunologic memory : Primary challenge, re-challenge
  • IAPi outperforms checkpoint blockade in T cell cold tumors
  • reduction of tumor burden gencitabine cross-presenting DCs and CD8 T cells – T cell low 6694c2
  • IAPi is a T cell-dependent immunotherapy in pancreatic cancer: MHC class I and IFN gemma sensing by tumor cells are critical for endogenous anti-tumor immunity and response to checkpoint blockade
  • T cells are catalytic, they can kill some tumors not all – Genes deleted in tumor cells
  • Intratumoral phagocytes are critical for endogenous: IAP antagonism increases phagocytosis in vivo
  • Model: T cells provide antigen specificity for sustained innate immune response
  • Antigen and adjuvants

12 — Michael Dustin (University of Oxford)

Delivery of T cell Effector function through extracellular vesicles

  • Laterally mobile ligands track receptor interaction
  • ICAM-1
  • Signaling of synapse – Sustain signaling by transient in microclusters TCR related to Invadipodia
  • Synaptic ectosome biogenisis Model: T cells: DOpamine cascade in germinal cell delivered to synaptic cleft – Effector CD40 – Transfer is cooperative
  • Synaptic ectosome composition
  • ESCRT pathway associated with synaptic ectosomes
  • Locatization, Microscopy (STORM, PALM, GSD)
  • Updated Model T cells Exosome transport Cytotoxic T cell granules CTLs release extracellular vescicles similar to T Helper with perforin and granzyme – CTL vesicles kill targets

6 — Darrell Irvine (MIT, Koch Institute; HHMI)

Innate immune recognition of glycosylation in nano particle vaccines

  • HIV Vaccines: Why is it such a challenge
  • HIV vaccine – Immunogen design – CD4 binding site-targeting
  • rational for nanoparticles forms of env immunogens
  • eOD-60mer nanoparticles vs Ferritin-trimer 8-mer
  • Nanoparticle delivery increases anti-Env titers substantially
  • Nanoparticles delivery accelerate the lymphatic system drainage
  • Immunogens drives to lymph nodes: nanoparticles changes environment in the lumph nodes
  • kidney medula – lymphatic system drainage
  • Liposome conjugate allows SOSIP – the germinal center:m training ground for immune response
  • nanoparticle – mechanism of germinal center targeting
  • GC targeting is dependent on complement component CIQ – activation: Mannose-binding lectins recognize eOD-60mer but not eOD monomer or trimers
  • Engineering follicle delivery through synthetic glycans: eOD-60mer nanoparticles vs Ferritin-trimer 8-mer (density dependent)
  • SUMMARY – HIV env nanopartices activate a bridge between innate and adaptive immunity
  • Multiple formulations of nanoparticles shows rapid immune response, comparison with influenza vaccine

 

2 — Tyler Jacks (MIT, Koch Institute; HHMI) – Tumor Biology Lab

Exploring tumor-immune interactions with genetically engineered Cancer Models – A case of Lung Cancer

  • Factors controlling tumor progression – genetically-engineered model of lung adenocarcinoma, metastasis causing death
  • Infiltration of cells: SEQUENCE EXOME – NO TUMOR BURDEN,
  • Exome sequencing reveals few mutations in KP model
  • Programmed neoantogen expression in the KP model: Kras, p53 – both are well researched in Lung cancer – immune cell dependent – tumors escape immune response due to immunosuppression – regulatory T cells most important in this model system
  • tissue specific responses to antigens
  • Lung Cancer – late stage — Programmed neo-antigen expression
  • Single cell mRNA sequencing of CD* T cell over time – sort cells, 8 weeks, 12 weeks, 20 weeks – progression of single cell similarity lymph cells vs lungs cells – cell identities  – transcription activation of dysfunction in cells
  • SIIN+ CD8 T cells show markers of dysfunction over time – up regulated signs of exhaustion,
  • T cells becomes exhausted, checkpoint inhibitors beyond a certain point – has no capacity  –
  • Interrogating markers of T cell dysfunction – chance biology of cells by CRISPR Cas9 – EGR2 at 2 weeks dysfunctioning is reduced – presence of EDR2 mutant class plays a role in cell metabolism – cell becomes more functional by modification protocols
  • Effects of CRISPR-mediated vs Combinatorial effects of CRISPR-mediated mutation of inhibitory models

 

8 — Max Krummel (University of California, San Francisco)

Dynamic Emergent behavior in Immune Systems

 

  • T cells are captured on tumor margins (without desired cytotoxicity)
  • Myeloid cells Underlie Intratumoral T cell capture
  • Anti tumor (CD4 CD8) vs Pro-tumor (CD9)
  • If many cells predicting Outcome more favorable – cellular abundance
  • Alternative T Cell reactions in Tissue: T-Helper 1, T-Helper 2
  • Gene expression association between two genes:
  • NK and cDC1 numbers are tightly linked and correlated with response to checkpoint blockage
  • A CD4-Enhaced Class of Melanoma Patients Also can be Checkpoint
  • CD4 T cells in Cancer – control tumors on their on
  • If high ICOS and CD4
  • Stimulate CD4: pull out of lymph nodes cells mCD301B
  • CD4 T cell proliferation but they don’t make PD1 ICOS CD4T
  • CD4 – required: Regulatory T Cells control CS4-dependent Tumor control via Lymph Node depletion (dLN)
  • If CD4 depleted, Lymph Node (LN) connected
  • Regulatory of PD1 ICOS CD4T
  • CD8 CD4 Tumor Affinity
  • Melanoma – T-reg hi or low – Responders are T-reg hi they have CD8
  • Existing Paired presence of T-reg, together with cDC2 number classifies Pt with better CD4
  • In Head and Neck: DC needed to stimulate immune response by CD4
  • Architypes of Immune systems in Tumors – Generally
  • CLASS I, II, III, IV – phynotypic
  • IMMUNE “ACCOMODATION” ARCHYTYPES: MYELOID TUNING OF ARCHITYPES
  • Myeloid function and composition

 

11 — Mikael Pittet (Massachusetts General Hospital)

Myeloid Cells in Cancer

  • complexity of Myeloid
  • Myeloid cells for cancer therapy: Outcomes good and bad: Tumor suppressing vs Tumor Promoting
  • Myeloid and immunotherapy
  • aPD-1 mAbs do not bind IL-12+DCs (scRNAseq): DC Classical and PlasmaCytoid (Allon Klein)
  • Indirect mechanism AFTER a-PD-1 Treatment
  • IFN-gamma Sensing Fosters IL-12 & therapeutic Responses
  • a PD-1-Mediated Activation of Tumor Immunity – Direct activation and the ‘Licensing’ Model

 

1 — Bob Schreiber (Wash University of St. Louis)

Neoantigens and the molecular basis of Cancer Immnutherapy

 

NeoAntigens (NEON Therapeutics, Co-Founder

  • MHC- I, MCH-II, tumor specific vaccine, if BOTH present THEN Clinical therapeutic efficacy is enhanced
  • Cancer Immunoediting to Personalized Cancer Vaccines
  • neoedited Tumors,
  • Tumor vaccines: Tumor Associated Antigens vs Tumor Specific Neoantigens
  • MCH Class II Immune responses to Cancer
  • CD4+
  • Immune Checkpoint Blockade Therapy eliminates T3 Sarcomas via a CD4+ CD8+ T cell dependent Mechanism
  • Control mAb vs (alphaPD-1 CTLA-4) vs (alphaPD-1 CTLA-4) + alpha CD8
  • Mutant Class II Neoepitopes: mltgb1 is the best peptide found
  • Cell Response CD4+ to T3
  • T3 – Median Mutant Affinity Value vs Affinity + Abundance: Prediction N711Y Mutant
  • MHC-II
  • Oncogene-Driven (Kras – G12D-p53 -/- =KP
  • KP Sarcomas  – do not Prime for their own rejection upon re-Challenge: Average Tumor Diameter
  • KP Sarcomas lack Strong Class I Neoepitopes MCA Sarcoma vs KP Sarcomas: Mutant Affinity
  • KP Sarcomas: Kras – G12D-p53
  • MHC Class I and Class II: Promotes PRIMING of mLama4-Specific CD8+ T Cells when KP.mLama4 Tumors express the mltgb1
  • mltgb1 enhances generation of mLama4-Specific CTL
  • controls: (alpha-PD-1), (PD-1 + CD4+)
  • Vaccine protects against T3 Outgrowth
  • CONCLUSIONS: Optimal CD8+ T cells mediated immune responses to T3 sarcomas require CD4+ T cell help

 

9 — Stefani Spranger (MIT, Koch Institute)

The role of Tumor-resident Dendritic Cells for productive anti-tumor immune response

  • CD8+ T cell T cell-inflamed Tumor vs Non-T cell inflamed Tumor
  • Tumor cell intrinsic – Workflow to identify oncogenic pathways differentially activated between T cell-inflamed
  • T cell infiltration (Braf PTEN CD3 T cells/total living cells
  • Response to checkpoint blockade
  • Non-T cell-inflamed – is LACK OF T CELL INFILTRATION – do not accumulate in Tumor,
  • Tumor-intrinsic Beta-catenin signaling mediates lack of T cell infiltration
  • Adoptive transfer of effector CT cells fails to control Beta – T cells remain motile and migrate in a directional fashion after tumor eradication
  • CD103 dendritic cells – Tumor-residing Braf3-driven CD103
  • Cross-presenting cDC1 are essential for effector T cells
  • How can we raise the curve and increase the number of long-term survivors
  • Understanding the role of tumor-resident DC
  • Accumulation of CD103 DC independent of T cells
  • Regression tumor mount T cell response independent of DC1 DC
  • Induction of anti-tumor immunity is independent of the canonical
  • Single cell RNA-Seq reveal new subset to regressiong tumors and stimulate T cells via non-conventional
  • Working hypothesis: productive anti-tumor immunity depends on multiple tumor-resident DC subsets

 

 

5 — Melody Swartz (University of Chicago)

Lymphangiogenesis and immunomodulation

  • Lymphangiogenesisfor in Inflammation
  • Immunosuppression drives metastasis
  • promotion of resolution in disease progression
  • Tumors uses lymphatic system vessels
  • Tumor VEGF-C enhances immune cell interactions with lymphatic system
  • Lymphangiogenesis promore immune suppression in the tumor microenvironment
  • Recruitment of immune cells system: Dendritic Cells,
  • Lymphangiogenesis melanomas – highly responsive to immunotherapy : Vaccination
  • Lymphangiogenesis promote antigen spreading
  • Lymphangiogenesis potentiation: CCL21, CCR7
  • Lymphangiogenesis attractive to Native T cells, in VEGF-C tumors
  • T cell homing inhibitors vs block T cell egress inhibitors – Immunotherapy induces T cell killing
  • Allergic airway inflammation is driven lung and lymph node Lymphangiogenesis
  • Innate Immune cell infiltration reduced
  • Memory recall responses reflect adaptive immunity
  •  pathology exacerbated with VEGFR-3 blockade response of memory recall cell is enhanced
  • VEGFR-3 signaling shifts T call balance, and CCL@1, from Lymph nodes to Lung
  • Differential changes in T cell balance between lung vs adaptive immune response to allergic airway inflammation
  • Lymphangiogenesis in the lung, competition with adaptive immune response to allergic airway inflammation in the lung

 

4 — Cathy Wu, Dana Farber Cancer Institute, HMS – CoFounder of NEON

Building better personal cancer vaccines

  • Vaccine: up to 20 personalized neoantigens as SLPs with adjuvant (polyICLC)
  • high risk melanoma – RESULTS: new immune responses – new responses mutiple immune responses CD4 & CD8: mutated vs Wild type  differences
  • Enduring complete radiographic responses after Neovax + alpha-PD-1 treatment (anti-PD-1)
  • NeoVax vs IVAC MutaNOME
  • Ex vivo responses to assay peptide pools – immune response identified
  • NeoVax: ‘warming’ a cold tumor
  • immune cell infiltration – not studied in Glioblastoma which is a pooled tumor: TCR repertoire and MHC. Available materials: PBMC vs Fresh frozen and FFPE tumor material: Blood va FF brain tissue sequencing
  • Pt 8 neoantigen-specific clonotypesID’s – reactive T cells track to the brain after vaccination
  • Single cells from brain tissue vs single cells from neoantigen specific T cells – intratumoral neoantigen-specific T cells: mutARGAP35-specific T cell identified at site of disease – breakthrough for Brain Tumor #vaccine based neoantigen-specific T cell at intracranial site
  • VAX steering the Immune system
  • commission at Dana Farber – Prediction algorithms of denovo neoantigen targets: Newly profiled peptides to train a model vs peptide in the DB – Single vs Multi-allele HLA peptide sequencing by MassSpectroscopy
  • Mono-allelic MS data reveals novel motifs and sub-motifs
  • Endogenous signals contribution to predictive power
  • NeuroNets Algoriths : Integrative models identify tumor-presented epitopes more accurately than models without training like NeuroNets
  • 5778 class I peptides from 4 cancers class I allele
  • CONCLUSIONS: proteosomal processing endogenous signals transcriptome

 

Poster Presenters

3 — Scott Wilson,  U of Chicago

Antigen-specific Tolerance: A Cure for Autoimmunity

  • Activation of auto-reactive T cell
  • Leveraging the Liver’s Tolerogenic Environment for the Induction of Antigen-specific Tolerance
  • Design Criteria for HAPC- Targeting Platform – Target Antigens to HAPCs
  • Minimal biomaterial footprint
  • Deliver system Hepatic APC-targeting Glycosylations
  • IV INJECTION: OVAALBUMIN OVA-P(GALINAC), P(GLCNAC), SUPRESS T CELL RESPONSE
  • Glyco-conjucates Abate T cells response – Reduced cytokine production &  increased T-regs

 

1- — Noor Momin, MIT, Prof. K. Dane Wittrup Lab

The role of Collagen and Cytokines in Immunotherapy drug development

 

  • Cytokine therapies have poor therapeutic windows
  • Intratumoral Cytokine Delivery: Expectation vs Reality
  • Anchor intratumorally adm cytokines to collagen and protein
  • collagen abundent (toxicity) and long-lived (maximize efficacy)
  • Lumican – homology model – mediate collagen-anchoring? How to mediate anchoring
  • Lumican fusion to IL-2 improves treatment efficacy however toxic – Anti-TAA mAb – TA99 vs IL-2
  • Best efficacy in Lumican-MSA-IL-2 vs MSA-IL2
  • Lumican-cytokines improve control of distant lesions – Lumican-fusion potentiates systemic anti-tumor immunity
  • Lumican-cytokines efficacious in Braf/Pten GEMM
  • Lumican fusion cytokine IL-2 IL-12 Binds collagen

 

 

 

 

Read Full Post »

Older Posts »

%d bloggers like this: