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Archive for the ‘Cancer Vaccines: Targeting Cancer Genes for Immunotherapy’ Category


Inhibitory CD161 receptor recognized as a potential immunotherapy target in glioma-infiltrating T cells by single-cell analysis

Reporter: Dr. Premalata Pati, Ph.D., Postdoc

 

Brain tumors, especially the diffused Gliomas are of the most devastating forms of cancer and have so-far been resistant to immunotherapy. It is comprehended that T cells can penetrate the glioma cells, but it still remains unknown why infiltrating cells miscarry to mount a resistant reaction or stop the tumor development.

Gliomas are brain tumors that begin from neuroglial begetter cells. The conventional therapeutic methods including, surgery, chemotherapy, and radiotherapy, have accomplished restricted changes inside glioma patients. Immunotherapy, a compliance in cancer treatment, has introduced a promising strategy with the capacity to penetrate the blood-brain barrier. This has been recognized since the spearheading revelation of lymphatics within the central nervous system. Glioma is not generally carcinogenic. As observed in a number of cases, the tumor cells viably reproduce and assault the adjoining tissues, by and large, gliomas are malignant in nature and tend to metastasize. There are four grades in glioma, and each grade has distinctive cell features and different treatment strategies. Glioblastoma is a grade IV glioma, which is the crucial aggravated form. This infers that all glioblastomas are gliomas, however, not all gliomas are glioblastomas.

Decades of investigations on infiltrating gliomas still take off vital questions with respect to the etiology, cellular lineage, and function of various cell types inside glial malignancies. In spite of the available treatment options such as surgical resection, radiotherapy, and chemotherapy, the average survival rate for high-grade glioma patients remains 1–3 years (1).

A recent in vitro study performed by the researchers of Dana-Farber Cancer Institute, Massachusetts General Hospital, and the Broad Institute of MIT and Harvard, USA, has recognized that CD161 is identified as a potential new target for immunotherapy of malignant brain tumors. The scientific team depicted their work in the Cell Journal, in a paper entitled, “Inhibitory CD161 receptor recognized in glioma-infiltrating T cells by single-cell analysis.” on 15th February 2021.

To further expand their research and findings, Dr. Kai Wucherpfennig, MD, PhD, Chief of the Center for Cancer Immunotherapy, at Dana-Farber stated that their research is additionally important in a number of other major human cancer types such as 

  • melanoma,
  • lung,
  • colon, and
  • liver cancer.

Dr. Wucherpfennig has praised the other authors of the report Mario Suva, MD, PhD, of Massachusetts Common Clinic; Aviv Regev, PhD, of the Klarman Cell Observatory at Broad Institute of MIT and Harvard, and David Reardon, MD, clinical executive of the Center for Neuro-Oncology at Dana-Farber.

Hence, this new study elaborates the effectiveness of the potential effectors of anti-tumor immunity in subsets of T cells that co-express cytotoxic programs and several natural killer (NK) cell genes.

The Study-

IMAGE SOURCE: Experimental Strategy (Mathewson et al., 2021)

 

The group utilized single-cell RNA sequencing (RNA-seq) to mull over gene expression and the clonal picture of tumor-infiltrating T cells. It involved the participation of 31 patients suffering from diffused gliomas and glioblastoma. Their work illustrated that the ligand molecule CLEC2D activates CD161, which is an immune cell surface receptor that restrains the development of cancer combating activity of immune T cells and tumor cells in the brain. The study reveals that the activation of CD161 weakens the T cell response against tumor cells.

Based on the study, the facts suggest that the analysis of clonally expanded tumor-infiltrating T cells further identifies the NK gene KLRB1 that codes for CD161 as a candidate inhibitory receptor. This was followed by the use of 

  • CRISPR/Cas9 gene-editing technology to inactivate the KLRB1 gene in T cells and showed that CD161 inhibits the tumor cell-killing function of T cells. Accordingly,
  • genetic inactivation of KLRB1 or
  • antibody-mediated CD161 blockade

enhances T cell-mediated killing of glioma cells in vitro and their anti-tumor function in vivo. KLRB1 and its associated transcriptional program are also expressed by substantial T cell populations in other forms of human cancers. The work provides an atlas of T cells in gliomas and highlights CD161 and other NK cell receptors as immune checkpoint targets.

Further, it has been identified that many cancer patients are being treated with immunotherapy drugs that disable their “immune checkpoints” and their molecular brakes are exploited by the cancer cells to suppress the body’s defensive response induced by T cells against tumors. Disabling these checkpoints lead the immune system to attack the cancer cells. One of the most frequently targeted checkpoints is PD-1. However, recent trials of drugs that target PD-1 in glioblastomas have failed to benefit the patients.

In the current study, the researchers found that fewer T cells from gliomas contained PD-1 than CD161. As a result, they said, “CD161 may represent an attractive target, as it is a cell surface molecule expressed by both CD8 and CD4 T cell subsets [the two types of T cells engaged in response against tumor cells] and a larger fraction of T cells express CD161 than the PD-1 protein.”

However, potential side effects of antibody-mediated blockade of the CLEC2D-CD161 pathway remain unknown and will need to be examined in a non-human primate model. The group hopes to use this finding in their future work by

utilizing their outline by expression of KLRB1 gene in tumor-infiltrating T cells in diffuse gliomas to make a remarkable contribution in therapeutics related to immunosuppression in brain tumors along with four other common human cancers ( Viz. melanoma, non-small cell lung cancer (NSCLC), hepatocellular carcinoma, and colorectal cancer) and how this may be manipulated for prevalent survival of the patients.

References

(1) Anders I. Persson, QiWen Fan, Joanna J. Phillips, William A. Weiss, 39 – Glioma, Editor(s): Sid Gilman, Neurobiology of Disease, Academic Press, 2007, Pages 433-444, ISBN 9780120885923, https://doi.org/10.1016/B978-012088592-3/50041-4.

Main Source

Mathewson ND, Ashenberg O, Tirosh I, Gritsch S, Perez EM, Marx S, et al. 2021. Inhibitory CD161 receptor identified in glioma-infiltrating T cells by single-cell analysis. Cell.https://www.cell.com/cell/fulltext/S0092-8674(21)00065-9?elqTrackId=c3dd8ff1d51f4aea87edd0153b4f2dc7

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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

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, 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

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Published by

Mike Wood
Marketing Executive at Biotech Forecasts
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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. hashtagcelltherapy hashtaggenetherapy hashtagimmunotherapy hashtagcancertreatment hashtagcartcell hashtagregenerativemedicine hashtagbiotech hashtagcancer

 

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

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Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Symposium: New Drugs on the Horizon Part 3 12:30-1:25 PM

Reporter: Stephen J. Williams, PhD

New Drugs on the Horizon: Part 3
Introduction

Andrew J. Phillips, C4 Therapeutics

  • symposium brought by AACR CICR and had about 30 proposals for talks and chose three talks
  • unfortunately the networking event is not possible but hope to see you soon in good health

ABBV-184: A novel survivin specific T cell receptor/CD3 bispecific therapeutic that targets both solid tumor and hematological malignancies

Edward B Reilly
AbbVie Inc. @abbvie

  • T-cell receptors (TCR) can recognize the intracellular targets whereas antibodies only recognize the 25% of potential extracellular targets
  • survivin is expressed in multiple cancers and correlates with poor survival and prognosis
  • CD3 bispecific TCR to survivn (Ab to CD3 on T- cells and TCR to survivin on cancer cells presented in MHC Class A3)
  • ABBV184  effective in vivo in lung cancer models as single agent;
  • in humanized mouse tumor models CD3/survivin bispecific can recruit T cells into solid tumors; multiple immune cells CD4 and CD8 positive T cells were found to infiltrate into tumor
  • therapeutic window as measured by cytokine release assays in tumor vs. normal cells very wide (>25 fold)
  • ABBV184 does not bind platelets and has good in vivo safety profile
  • First- in human dose determination trial: used in vitro cancer cell assays to determine 1st human dose
  • looking at AML and lung cancer indications
  • phase 1 trial is underway for safety and efficacy and determine phase 2 dose
  • survivin has very few mutations so they are not worried about a changing epitope of their target TCR peptide of choice

The discovery of TNO155: A first in class SHP2 inhibitor

Matthew J. LaMarche
Novartis @Novartis

  • SHP2 is an intracellular phosphatase that is upstream of MEK ERK pathway; has an SH2 domain and PTP domain
  • knockdown of SHP2 inhibits tumor growth and colony formation in soft agar
  • 55 TKIs there are very little phosphatase inhibitors; difficult to target the active catalytic site; inhibitors can be oxidized at the active site; so they tried to target the two domains and developed an allosteric inhibitor at binding site where three domains come together and stabilize it
  • they produced a number of chemical scaffolds that would bind and stabilize this allosteric site
  • block the redox reaction by blocking the cysteine in the binding site
  • lead compound had phototoxicity; used SAR analysis to improve affinity and reduce phototox effects
  • was very difficult to balance efficacy, binding properties, and tox by adjusting stuctures
  • TNO155 is their lead into trials
  • SHP2 expressed in T cells and they find good combo with I/O with uptick of CD8 cells
  • TNO155 is very selective no SHP1 inhibition; SHP2 can autoinhibit itself when three domains come together and stabilize; no cross reactivity with other phosphatases
  • they screened 1.5 million compounds and got low hit rate so that is why they needed to chemically engineer and improve on the classes they found as near hits

Closing Remarks

 

Xiaojing Wang
Genentech, Inc. @genentech

Follow on Twitter at:

@pharma_BI

@AACR

@CureCancerNow

@pharmanews

@BiotechWorld

@HopkinsMedicine

#AACR20

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Live Conference Coverage of AACR 2020 Annual Virtual Meeting; April 27-28, 2020

Reporter: Stephen J. Williams, Ph.D.

The American Association for Cancer Research (AACR) will hold its Annual Meeting as a Virtual Online Format.  Registration is free and open to all, including non members.  Please go to

https://www.aacr.org/meeting/aacr-annual-meeting-2020/aacr-virtual-annual-meeting-i/?utm_source=Salesforce%20Marketing%20Cloud&utm_medium=Email&utm_campaign=&sfmc_s=0031I00000WsBJxQAN

to register for this two day meeting.  Another two day session will be held in June 2020 and will focus more on basic cancer research.

Please follow @pharma_BI who will be live Tweeting Real Time Notes from this meeting using the hashtag

#AACR20

And @StephenJWillia2

The following is a brief summary of the schedule.  Please register and go to AACR for detailed information on individual sessions.

 

AACR VIRTUAL ANNUAL MEETING I: SCHEDULE AT A GLANCE

AACR Virtual Annual Meeting I is available free Register Now

VIRTUAL MEETING I: BROWSER REQUIREMENTS AND ACCESSVIRTUAL MEETING I: FAQVIRTUAL MEETING I: MEETING PLANNER (ABSTRACT TITLES)

Presentation titles are available through the online meeting planner. The program also includes six virtual poster sessions consisting of brief slide videos. Poster sessions will not be presented live but will be available for viewing on demand. Poster session topics are as follows:

  • Phase I Clinical Trials
  • Phase II Clinical Trials
  • Phase III Clinical Trials
  • Phase I Trials in Progress
  • Phase II Trials in Progress
  • Phase III Trials in Progress

Schedule updated April 24, 2020

MONDAY, APRIL 27

Channel 1 Channel 2 Channel 3
9:00 a.m.-9:30 a.m.
Opening Session
_______________________
9:30 a.m.-11:40 a.m.
Opening Clinical Plenary
_______________________
11:40 a.m.-2:00 p.m.
Clinical Plenary: Immunotherapy Clinical Trials 1
_______________________
___ 11:45 a.m.-1:30 p.m.
Minisymposium: Emerging Signaling Vulnerabilities in Cancer
_______________________
___ 11:45 a.m.-1:15 p.m.
Minisymposium: Advances in Cancer Drug Design and Discovery
__________________________
2:00 p.m.-4:50 p.m.
Clinical Plenary: Lung Cancer Targeted Therapy
_______________________
___ 1:55 p.m.-4:15 p.m.
Clinical Plenary: Breast Cancer Therapy
_______________________
___ 1:30 p.m.-3:30 p.m.
Minisymposium: Drugging Undrugged Cancer Targets
__________________________
4:50 p.m.-6:05 p.m.
Symposium: New Drugs on the Horizon 1_______________________
___ 4:50 p.m.-5:50 p.m.
Minisymposium: Therapeutic Modification of the Tumor Microenvironment or Microbiome
_______________________
___ 4:00 p.m.-6:00 p.m.
Minisymposium: Advancing Cancer Research Through An International Cancer Registry: AACR Project GENIE Use Cases__________________________

All session times are EDT.

TUESDAY, APRIL 28

Channel 1 Channel 2 Channel 3
9:00 a.m.-101:00 a.m.
Clinical Plenary: COVID-19 and Cancer
__________________________
11:00 a.m.-1:35 p.m.
Clinical Plenary: Adoptive Cell Transfer Therapy__________________________
___ 10:45 a.m.-12:30 p.m.
Symposium: New Drugs on the Horizon 2_________________________
___ 10:45 a.m.-12:30 p.m.
Minisymposium: Translational Prevention Studies
______________________
___ 12:30 p.m.-1:25 p.m.
Symposium: New Drugs on the Horizon 3
_________________________
___ 12:30 p.m.-2:15 p.m.
Minisymposium: Non-coding RNAs in Cancer
______________________
1:35 p.m.-3:35 p.m.
Clinical Plenary: Early Detection and ctDNA__________________________
___ 1:30 p.m.-3:50 p.m.
Clinical Plenary: Immunotherapy Clinical
Trials 2
_________________________
___ 2:15 p.m.-3:45 p.m.
Minisymposium: Novel Targets and Therapies______________________
3:35 p.m.-5:50 p.m.
Minisymposium: Predictive Biomarkers for Immunotherapeutics__________________________
___ 3:50 p.m.-5:35 p.m.
Minisymposium: Evaluating Cancer Genomics from Normal Tissues through Evolution to Metastatic Disease
_________________________
___ 4:00 p.m.-4:55 p.m.
Clinical Plenary: Targeted Therapy______________________
5:00 p.m.-5:45 p.m.
Symposium: NCI Activities– COVID-19 and Cancer Research
Dinah Singer, NCI
______________________
5:45 p.m.-6:00 p.m.
Closing Session
______________________

All session times are EDT.

 

 

 

Day

 

Session Type

Topic Tracks

For more on @pharma_BI and LPBI Group Conference Coverage in Real Time please go to

https://pharmaceuticalintelligence.com/press-coverage/

and

 

 

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An Intelligent DNA Nanorobot to Fight Cancer by Targeting HER2 Expression

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

3.2.9

3.2.9   An Intelligent DNA Nanorobot to Fight Cancer by Targeting HER2 Expression, 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

HER2 is an important prognostic biomarker for 20–30% of breast cancers, which is the most common cancer in women. Overexpression of the HER2 receptor stimulates breast cells to proliferate and differentiate uncontrollably, thereby enhancing the malignancy of breast cancer and resulting in a poor prognosis for affected individuals. Current therapies to suppress the overexpression of HER2 in breast cancer mainly involve treatment with HER2-specific monoclonal antibodies. However, these monoclonal anti-HER2 antibodies have severe side effects in clinical trials, such as diarrhea, abnormal liver function, and drug resistance. Removing HER2 from the plasma membrane or inhibiting the gene expression of HER2 is a promising alternative that could limit the malignancy of HER2-positive cancer cells.

DNA origami is an emerging field of DNA-based nanotechnology and intelligent DNA nanorobots show great promise in working as a drug delivery system in healthcare. Different DNA-based nanorobots have been developed as affordable and facile therapeutic drugs. In particular, many studies reported that a tetrahedral framework nucleic acid (tFNA) could serve as a promising DNA nanocarrier for many antitumor drugs, owing to its high biocompatibility and biosecurity. For example, tFNA was reported to effectively deliver paclitaxel or doxorubicin to cancer cells for reversing drug resistance, small interfering RNAs (siRNAs) have been modified into tFNA for targeted drug delivery. Moreover, the production and storage of tFNA are not complicated, and they can be quickly degraded in lysosomes by cells. Since both free HApt and tFNA can be diverted into lysosomes, so,  combining the HApt and tFNA as a novel DNA nanorobot (namely, HApt-tFNA) can be an effective strategy to improve its delivery and therapeutic efficacy in treating HER2-positive breast cancer.

Researchers reported that a DNA framework-based intelligent DNA nanorobot for selective lysosomal degradation of tumor-specific proteins on cancer cells. An anti-HER2 aptamer (HApt) was site-specifically anchored on a tetrahedral framework nucleic acid (tFNA). This DNA nanorobot (HApt-tFNA) could target HER2-positive breast cancer cells and specifically induce the lysosomal degradation of the membrane protein HER2. An injection of the DNA nanorobot into a mouse model revealed that the presence of tFNA enhanced the stability and prolonged the blood circulation time of HApt, and HApt-tFNA could therefore drive HER2 into lysosomal degradation with a higher efficiency. The formation of the HER2-HApt-tFNA complexes resulted in the HER2-mediated endocytosis and digestion in lysosomes, which effectively reduced the amount of HER2 on the cell surfaces. An increased HER2 digestion through HApt-tFNA further induced cell apoptosis and arrested cell growth. Hence, this novel DNA nanorobot sheds new light on targeted protein degradation for precision breast cancer therapy.

It was previously reported that tFNA was degraded by lysosomes and could enhance cell autophagy. Results indicated that free Cy5-HApt and Cy5-HApt-tFNA could enter the lysosomes; thus, tFNA can be regarded as an efficient nanocarrier to transmit HApt into the target organelle. The DNA nanorobot composed of HApt and tFNA showed a higher stability and a more effective performance than free HApt against HER2-positive breast cancer cells. The PI3K/AKT pathway was inhibited when membrane-bound HER2 decreased in SK-BR-3 cells under the action of HApt-tFNA. The research findings suggest that tFNA can enhance the anticancer effects of HApt on SK-BR-3 cells; while HApt-tFNA can bind to HER2 specifically, the compounded HER2-HApt-tFNA complexes can then be transferred and degraded in lysosomes. After these processes, the accumulation of HER2 in the plasma membrane would decrease, which could also influence the downstream PI3K/AKT signaling pathway that is associated with cell growth and death.

However, some limitations need to be noted when interpreting the findings: (i) the cytotoxicity of the nanorobot on HER2-positive cancer cells was weak, and the anticancer effects between conventional monoclonal antibodies and HApt-tFNA was not compared; (ii) the differences in delivery efficiency between tFNA and other nanocarriers need to be confirmed; and (iii) the confirmation of anticancer effects of HApt-tFNA on tumors within animals remains challenging. Despite these limitations, the present study provided novel evidence of the biological effects of tFNA when combined with HApt. Although the stability and the anticancer effects of HApt-tFNA may require further improvement before clinical application, this study initiates a promising step toward the development of nanomedicines with novel and intelligent DNA nanorobots for tumor treatment.

References:

https://pubs.acs.org/doi/10.1021/acs.nanolett.9b01320

https://www.ncbi.nlm.nih.gov/pubmed/27939064

https://www.ncbi.nlm.nih.gov/pubmed/11694782

https://www.ncbi.nlm.nih.gov/pubmed/27082923

https://www.ncbi.nlm.nih.gov/pubmed/25365825

https://www.ncbi.nlm.nih.gov/pubmed/26840503

https://www.ncbi.nlm.nih.gov/pubmed/29802035

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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

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Gender affects the prevalence of the cancer type, 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.

 

Gender of a person can affect the kinds of cancer-causing mutations they develop, according to a genomic analysis spanning nearly 2,000 tumours and 28 types of cancer. The results show striking differences in the cancer-causing mutations found in people who are biologically male versus those who are biologically female — not only in the number of mutations lurking in their tumours, but also in the kinds of mutations found there.

 

Liver tumours from women were more likely to carry mutations caused by a faulty system of DNA mending called mismatch repair, for instance. And men with any type of cancer were more likely to exhibit DNA changes thought to be linked to a process that the body uses to repair DNA with two broken strands. These biases could point researchers to key biological differences in how tumours develop and evolve across sexes.

 

The data add to a growing realization that sex is important in cancer, and not only because of lifestyle differences. Lung and liver cancer, for example, are more common in men than in women — even after researchers control for disparities in smoking or alcohol consumption. The source of that bias, however, has remained unclear.

In 2014, the US National Institutes of Health began encouraging researchers to consider sex differences in preclinical research by, for example, including female animals and cell lines from women in their studies. And some studies have since found sex-linked biases in the frequency of mutations in protein-coding genes in certain cancer types, including some brain cancers and advanced melanoma.

 

But the present study is the most comprehensive study of sex differences in tumour genomes so far. It looks at mutations not only in genes that code for proteins, but also in the vast expanses of DNA that have other functions, such as controlling when genes are turned on or off. The study also compares male and female genomes across many different cancers, which can allow researchers to pick up on additional patterns of DNA mutations, in part by increasing the sample sizes.

 

Researchers analysed full genome sequences gathered by the International Cancer Genome Consortium. They looked at differences in the frequency of 174 mutations known to drive cancer, and found that some of these mutations occurred more frequently in men than in women, and vice versa. When they looked more broadly at the loss or duplication of DNA segments in the genome, they found 4,285 sex-biased genes spread across 15 chromosomes.

 

There were also differences found when some mutations seemed to arise during tumour development, suggesting that some cancers follow different evolutionary paths in men and women. Researchers also looked at particular patterns of DNA changes. Such patterns can, in some cases, reflect the source of the mutation. Tobacco smoke, for example, leaves behind a particular signature in the DNA.

 

Taken together, the results highlight the importance of accounting for sex, not only in clinical trials but also in preclinical studies. This could eventually allow researchers to pin down the sources of many of the differences found in this study. Liver cancer is roughly three times as common in men as in women in some populations, and its incidence is increasing in some countries. A better understanding of its aetiology may turn out to be really important for prevention strategies and treatments.

 

References:

 

https://www.nature.com/articles/d41586-019-00562-7?utm_source=Nature+Briefing

 

https://www.nature.com/news/policy-nih-to-balance-sex-in-cell-and-animal-studies-1.15195

 

https://www.ncbi.nlm.nih.gov/pubmed/26296643

 

https://www.biorxiv.org/content/10.1101/507939v1

 

https://www.ncbi.nlm.nih.gov/pubmed/25985759

 

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Pancreatic cancer survival is determined by ratio of two enzymes, 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.

 

Protein kinase C (PKC) isozymes function as tumor suppressors in increasing contexts. These enzymes are crucial for a number of cellular activities, including cell survival, proliferation and migration — functions that must be carefully controlled if cells get out of control and form a tumor. In contrast to oncogenic kinases, whose function is acutely regulated by transient phosphorylation, PKC is constitutively phosphorylated following biosynthesis to yield a stable, autoinhibited enzyme that is reversibly activated by second messengers. Researchers at University of California San Diego School of Medicine found that another enzyme, called PHLPP1, acts as a “proofreader” to keep careful tabs on PKC.

 

The researchers discovered that in pancreatic cancer high PHLPP1 levels lead to low PKC levels, which is associated with poor patient survival. They reported that the phosphatase PHLPP1 opposes PKC phosphorylation during maturation, leading to the degradation of aberrantly active species that do not become autoinhibited. They discovered that any time an over-active PKC is inadvertently produced, the PHLPP1 “proofreader” tags it for destruction. That means the amount of PHLPP1 in patient’s cells determines his amount of PKC and it turns out those enzyme levels are especially important in pancreatic cancer.

 

This team of researchers reversed a 30-year paradigm when they reported evidence that PKC actually suppresses, rather than promotes, tumors. For decades before this revelation, many researchers had attempted to develop drugs that inhibit PKC as a means to treat cancer. Their study implied that anti-cancer drugs would actually need to do the opposite — boost PKC activity. This study sets the stage for clinicians to one day use a pancreatic cancer patient’s PHLPP1/PKC levels as a predictor for prognosis, and for researchers to develop new therapeutic drugs that inhibit PHLPP1 and boost PKC as a means to treat the disease.

 

The ratio — high PHLPP1/low PKC — correlated with poor prognoses: no pancreatic patient with low PKC in the database survived longer than five-and-a-half years. On the flip side, 50 percent of the patients with low PHLPP1/high PKC survived longer than that. While still in the earliest stages, the researchers hope that this information might one day aid pancreatic diagnostics and treatment. The researchers are next planning to screen chemical compounds to find those that inhibit PHLPP1 and restore PKC levels in low-PKC-pancreatic cancer cells in the lab. These might form the basis of a new therapeutic drug for pancreatic cancer.

 

References:

 

https://health.ucsd.edu/news/releases/Pages/2019-03-20-two-enzymes-linked-to-pancreatic-cancer-survival.aspx?elqTrackId=b6864b278958402787f61dd7b7624666

 

https://www.ncbi.nlm.nih.gov/pubmed/30904392

 

https://www.ncbi.nlm.nih.gov/pubmed/29513138

 

https://www.ncbi.nlm.nih.gov/pubmed/18511290

 

https://www.ncbi.nlm.nih.gov/pubmed/28476658

 

https://www.ncbi.nlm.nih.gov/pubmed/28283201

 

https://www.ncbi.nlm.nih.gov/pubmed/24231509

 

https://www.ncbi.nlm.nih.gov/pubmed/28112438

 

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Immunoediting can be a constant defense in the cancer landscape


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/

 

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Immunotherapy may help in glioblastoma survival


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/

 

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