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Archive for the ‘Diagnostic Immunology’ Category


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

During pregnancy, the baby is mostly protected from harmful microorganisms by the amniotic sac, but recent research suggests the baby could be exposed to small quantities of microbes from the placenta, amniotic fluid, umbilical cord blood and fetal membranes. One theory is that any possible prenatal exposure could ‘pre-seed’ the infant microbiome. In other words, to set the right conditions for the ‘main seeding event’ for founding the infant microbiome.

When a mother gives birth vaginally and if she breastfeeds, she passes on colonies of essential microbes to her baby. This continues a chain of maternal heritage that stretches through female ancestry for thousands of generations, if all have been vaginally born and breastfed. This means a child’s microbiome, that is the trillions of microorganisms that live on and in him or her, will resemble the microbiome of his/her mother, the grandmother, the great-grandmother and so on, if all have been vaginally born and breastfed.

As soon as the mother’s waters break, suddenly the baby is exposed to a wave of the mother’s vaginal microbes that wash over the baby in the birth canal. They coat the baby’s skin, and enter the baby’s eyes, ears, nose and some are swallowed to be sent down into the gut. More microbes form of the mother’s gut microbes join the colonization through contact with the mother’s faecal matter. Many more microbes come from every breath, from every touch including skin-to-skin contact with the mother and of course, from breastfeeding.

With formula feeding, the baby won’t receive the 700 species of microbes found in breast milk. Inside breast milk, there are special sugars called human milk oligosaccharides (HMO’s) that are indigestible by the baby. These sugars are designed to feed the mother’s microbes newly arrived in the baby’s gut. By multiplying quickly, the ‘good’ bacteria crowd out any potentially harmful pathogens. These ‘good’ bacteria help train the baby’s naive immune system, teaching it to identify what is to be tolerated and what is pathogen to be attacked. This leads to the optimal training of the infant immune system resulting in a child’s best possible lifelong health.

With C-section birth and formula feeding, the baby is not likely to acquire the full complement of the mother’s vaginal, gut and breast milk microbes. Therefore, the baby’s microbiome is not likely to closely resemble the mother’s microbiome. A baby born by C-section is likely to have a different microbiome from its mother, its grandmother, its great-grandmother and so on. C-section breaks the chain of maternal heritage and this break can never be restored.

The long term effect of an altered microbiome for a child’s lifelong health is still to be proven, but many studies link C-section with a significantly increased risk for developing asthma, Type 1 diabetes, celiac disease and obesity. Scientists might not yet have all the answers, but the picture that is forming is that C-section and formula feeding could be significantly impacting the health of the next generation. Through the transgenerational aspect to birth, it could even be impacting the health of future generations.

References:

https://blogs.scientificamerican.com/guest-blog/shortchanging-a-babys-microbiome/

https://www.ncbi.nlm.nih.gov/pubmed/23926244

https://www.ncbi.nlm.nih.gov/pubmed/26412384

https://www.ncbi.nlm.nih.gov/pubmed/25290507

https://www.ncbi.nlm.nih.gov/pubmed/25974306

https://www.ncbi.nlm.nih.gov/pubmed/24637604

https://www.ncbi.nlm.nih.gov/pubmed/22911969

https://www.ncbi.nlm.nih.gov/pubmed/25650398

https://www.ncbi.nlm.nih.gov/pubmed/27362264

https://www.ncbi.nlm.nih.gov/pubmed/27306663

http://www.mdpi.com/1099-4300/14/11/2036

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4464665/

https://www.ncbi.nlm.nih.gov/pubmed/24848255

https://www.ncbi.nlm.nih.gov/pubmed/26412384

https://www.ncbi.nlm.nih.gov/pubmed/28112736

http://ndnr.com/gastrointestinal/the-infant-microbiome-how-environmental-maternal-factors-influence-its-development/

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Multiple copies of the alpha tryptase gene drive Tryptase elevations may contribute to symptoms of dizziness and lightheadedness, skin flushing and itching, gastrointestinal complaints, chronic pain, and bone and joint problems

 

Reporter: Aviva Lev-Ari, PhD, RN

 

Monday, October 17, 2016

NIH scientists uncover genetic explanation for frustrating syndrome

Previously unexplained symptoms found associated with multiple copies of a single gene.

Other studies have indicated that four to six percent of the general public has high tryptase levels. While not all of these people experience symptoms, many do, raising the possibility that this mildly prevalent trait in some cases drives the symptoms, although how it does so remains unclear.

“This work suggests that multiple alpha tryptase gene copies might underlie health issues that affect a substantial number of people,” said NIAID Director Anthony S. Fauci, M.D. “Identifying one genetic cause for high tryptase opens the door for us to develop strategies for diagnosing and treating people carrying this genetic change.”

Previously,NIH’s National Institute of Allergy and Infectious Diseases (NIAID) researchers had observed that a combination of chronic and sometimes debilitating symptoms, such as hives, irritable bowel syndrome and overly flexible joints, runs in some families and is associated with high tryptase levels. Many affected family members with high tryptase also reported symptoms consistent with disorders of autonomic nervous system function (dysautonomia), including postural orthostatic tachycardia syndrome (POTS), which is characterized by dizziness, faintness and an elevated heartbeat when standing up.

SOURCE

https://www.nih.gov/news-events/news-releases/nih-scientists-uncover-genetic-explanation-frustrating-syndrome

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Milestones in Physiology & Discoveries in Medicine and Genomics: Request for Book Review Writing on Amazon.com


physiology-cover-seriese-vol-3individualsaddlebrown-page2

Milestones in Physiology

Discoveries in Medicine, Genomics and Therapeutics

Patient-centric Perspective 

http://www.amazon.com/dp/B019VH97LU 

2015

 

 

Author, Curator and Editor

Larry H Bernstein, MD, FCAP

Chief Scientific Officer

Leaders in Pharmaceutical Business Intelligence

Larry.bernstein@gmail.com

Preface

Introduction 

Chapter 1: Evolution of the Foundation for Diagnostics and Pharmaceuticals Industries

1.1  Outline of Medical Discoveries between 1880 and 1980

1.2 The History of Infectious Diseases and Epidemiology in the late 19th and 20th Century

1.3 The Classification of Microbiota

1.4 Selected Contributions to Chemistry from 1880 to 1980

1.5 The Evolution of Clinical Chemistry in the 20th Century

1.6 Milestones in the Evolution of Diagnostics in the US HealthCare System: 1920s to Pre-Genomics

 

Chapter 2. The search for the evolution of function of proteins, enzymes and metal catalysts in life processes

2.1 The life and work of Allan Wilson
2.2  The  evolution of myoglobin and hemoglobin
2.3  More complexity in proteins evolution
2.4  Life on earth is traced to oxygen binding
2.5  The colors of life function
2.6  The colors of respiration and electron transport
2.7  Highlights of a green evolution

 

Chapter 3. Evolution of New Relationships in Neuroendocrine States
3.1 Pituitary endocrine axis
3.2 Thyroid function
3.3 Sex hormones
3.4 Adrenal Cortex
3.5 Pancreatic Islets
3.6 Parathyroids
3.7 Gastointestinal hormones
3.8 Endocrine action on midbrain
3.9 Neural activity regulating endocrine response

3.10 Genomic Promise for Neurodegenerative Diseases, Dementias, Autism Spectrum, Schizophrenia, and Serious Depression

 

Chapter 4.  Problems of the Circulation, Altitude, and Immunity

4.1 Innervation of Heart and Heart Rate
4.2 Action of hormones on the circulation
4.3 Allogeneic Transfusion Reactions
4.4 Graft-versus Host reaction
4.5 Unique problems of perinatal period
4.6. High altitude sickness
4.7 Deep water adaptation
4.8 Heart-Lung-and Kidney
4.9 Acute Lung Injury

4.10 Reconstruction of Life Processes requires both Genomics and Metabolomics to explain Phenotypes and Phylogenetics

 

Chapter 5. Problems of Diets and Lifestyle Changes

5.1 Anorexia nervosa
5.2 Voluntary and Involuntary S-insufficiency
5.3 Diarrheas – bacterial and nonbacterial
5.4 Gluten-free diets
5.5 Diet and cholesterol
5.6 Diet and Type 2 diabetes mellitus
5.7 Diet and exercise
5.8 Anxiety and quality of Life
5.9 Nutritional Supplements

 

Chapter 6. Advances in Genomics, Therapeutics and Pharmacogenomics

6.1 Natural Products Chemistry

6.2 The Challenge of Antimicrobial Resistance

6.3 Viruses, Vaccines and immunotherapy

6.4 Genomics and Metabolomics Advances in Cancer

6.5 Proteomics – Protein Interaction

6.6 Pharmacogenomics

6.7 Biomarker Guided Therapy

6.8 The Emergence of a Pharmaceutical Industry in the 20th Century: Diagnostics Industry and Drug Development in the Genomics Era: Mid 80s to Present

6.09 The Union of Biomarkers and Drug Development

6.10 Proteomics and Biomarker Discovery

6.11 Epigenomics and Companion Diagnostics

 

Chapter  7

Integration of Physiology, Genomics and Pharmacotherapy

7.1 Richard Lifton, MD, PhD of Yale University and Howard Hughes Medical Institute: Recipient of 2014 Breakthrough Prizes Awarded in Life Sciences for the Discovery of Genes and Biochemical Mechanisms that cause Hypertension

7.2 Calcium Cycling (ATPase Pump) in Cardiac Gene Therapy: Inhalable Gene Therapy for Pulmonary Arterial Hypertension and Percutaneous Intra-coronary Artery Infusion for Heart Failure: Contributions by Roger J. Hajjar, MD

7.3 Diagnostics and Biomarkers: Novel Genomics Industry Trends vs Present Market Conditions and Historical Scientific Leaders Memoirs

7.4 Synthetic Biology: On Advanced Genome Interpretation for Gene Variants and Pathways: What is the Genetic Base of Atherosclerosis and Loss of Arterial Elasticity with Aging

7.5 Diagnosing Diseases & Gene Therapy: Precision Genome Editing and Cost-effective microRNA Profiling

7.6 Imaging Biomarker for Arterial Stiffness: Pathways in Pharmacotherapy for Hypertension and Hypercholesterolemia Management

7.7 Neuroprotective Therapies: Pharmacogenomics vs Psychotropic drugs and Cholinesterase Inhibitors

7.8 Metabolite Identification Combining Genetic and Metabolic Information: Genetic association links unknown metabolites to functionally related genes

7.9 Preserved vs Reduced Ejection Fraction: Available and Needed Therapies

7.10 Biosimilars: Intellectual Property Creation and Protection by Pioneer and by

7.11 Demonstrate Biosimilarity: New FDA Biosimilar Guidelines

 

Chapter 7.  Biopharma Today

8.1 A Great University engaged in Drug Discovery: University of Pittsburgh

8.2 Introduction – The Evolution of Cancer Therapy and Cancer Research: How We Got Here?

8.3 Predicting Tumor Response, Progression, and Time to Recurrence

8.4 Targeting Untargetable Proto-Oncogenes

8.5 Innovation: Drug Discovery, Medical Devices and Digital Health

8.6 Cardiotoxicity and Cardiomyopathy Related to Drugs Adverse Effects

8.7 Nanotechnology and Ocular Drug Delivery: Part I

8.8 Transdermal drug delivery (TDD) system and nanotechnology: Part II

8.9 The Delicate Connection: IDO (Indolamine 2, 3 dehydrogenase) and Cancer Immunology

8.10 Natural Drug Target Discovery and Translational Medicine in Human Microbiome

8.11 From Genomics of Microorganisms to Translational Medicine

8.12 Confined Indolamine 2, 3 dioxygenase (IDO) Controls the Homeostasis of Immune Responses for Good and Bad

 

Chapter 9. BioPharma – Future Trends

9.1 Artificial Intelligence Versus the Scientist: Who Will Win?

9.2 The Vibrant Philly Biotech Scene: Focus on KannaLife Sciences and the Discipline and Potential of Pharmacognosy

9.3 The Vibrant Philly Biotech Scene: Focus on Computer-Aided Drug Design and Gfree Bio, LLC

9.4 Heroes in Medical Research: The Postdoctoral Fellow

9.5 NIH Considers Guidelines for CAR-T therapy: Report from Recombinant DNA Advisory Committee

9.6 1st Pitch Life Science- Philadelphia- What VCs Really Think of your Pitch

9.7 Multiple Lung Cancer Genomic Projects Suggest New Targets, Research Directions for Non-Small Cell Lung Cancer

9.8 Heroes in Medical Research: Green Fluorescent Protein and the Rough Road in Science

9.9 Issues in Personalized Medicine in Cancer: Intratumor Heterogeneity and Branched Evolution Revealed by Multiregion Sequencing

9.10 The SCID Pig II: Researchers Develop Another SCID Pig, And Another Great Model For Cancer Research

Epilogue

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On its way for an IPO: mRNA platform, Moderna, Immune Oncology is recruiting 100 new Life Scientists in Cambridge, MA

Curator: Aviva Lev-Ari, PhD, RN

 

Deals:

Moderna has now raised $1.9 billion from investors like AstraZeneca – 9% stack [AstraZeneca’s Pascal Soriot helped get that all started with a whopping $240 million upfront in its 2013 deal, which was tied to $180 million in milestones.], with another $230 million on the table from grants. In addition to the financing announcement this morning, Moderna is also unveiling a pact to develop a new Zika vaccine, with BARDA putting up $8 million to get the program started while offering an option on $117 million more to get through a successful development program.

Novel Strategy in Biotech:

in biotech. Instead of grabbing one or two new drugs and setting out to gather proof-of-concept data to help establish its scientific credibility, the company has harvested a huge windfall of cash and built a large organization before even entering the clinic. And it did that without turning to an IPO.

Pipeline include:

  • The deal with AstraZeneca covers new drugs for cardiovascular, metabolic and renal diseases as well as cancer.
  • partners filed a European application to start a Phase I study of AZD8601, an investigational mRNA-based therapy that encodes for vascular endothelial growth factor-A (VEGF-A)
  • Moderna CEO spelled out plans to get the first 6 new drugs in the clinic by the end of 2016.
  • The first human study was arranged for the infectious disease drug mRNA 1440, which began an early stage study in 2015.
  • Moderna built up a range of big preclinical partnerships.
  • CEO Bancel says the number of drugs in development has swelled to 11, with the first set of data slated to be released in 2017.
  • Moderna also plans to add about 10 drugs to the clinic by next summer,

 

SOURCES

UPDATED: Booming Moderna is raising $600M while ramping up manufacturing and clinical studies

$1.9B in: Moderna blueprints $100M facility, plans to double the pipeline after a $474M megaround

http://endpts.com/moderna-blueprints-100m-facility-plans-to-double-the-pipeline-after-a-474m-megaround/?utm_source=Sailthru&utm_medium=email&utm_campaign=Issue:%202016-09-07%20BioPharma%20Dive%20%5Bissue:7155%5D&utm_term=BioPharma%20Dive

 

Moderna Therapeutics Deal with Merck: Are Personalized Vaccines here?

Curator & Reporter: Stephen J. Williams, PhD – August 11, 2016

https://pharmaceuticalintelligence.com/2016/08/11/moderna-therapeutics-deal-with-merck-are-personalized-vaccines-here/

 

at #JPM16 – Moderna Therapeutics turns away an extra $200 million: with AstraZeneca (collaboration) & with Merck ($100 million investment)

Reporter: Aviva Lev-Ari, PhD, RN – January 13, 2016

https://pharmaceuticalintelligence.com/2016/01/13/at-jpm16-moderna-therapeutics-turns-away-an-extra-200-million-with-astrazeneca-collaboration-with-merck-100-million-investment/

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Inotuzumab Ozogamicin: Success in relapsed/refractory Acute Lymphoblastic Leukemia (ALL)

Reporter: Aviva Lev-Ari, PhD, RN

 

About Inotuzumab Ozogamicin

Inotuzumab ozogamicin is an investigational antibody-drug conjugate (ADC) comprised of a monoclonal antibody (mAb) targeting CD22,9 a cell surface antigen expressed on approximately 90 percent of B-cell malignancies,10 linked to a cytotoxic agent. When inotuzumab ozogamicin binds to the CD22 antigen on malignant B-cells, it is internalized into the cell, where the cytotoxic agent calicheamicin is released to destroy the cell.11

Inotuzumab ozogamicin originates from a collaboration between Pfizer and Celltech, now UCB. Pfizer has sole responsibility for all manufacturing, clinical development and commercialization activities for this molecule.

Acute lymphoblastic leukemia (ALL)

is an aggressive type of leukemia with high unmet need and a poor prognosis in adults.4The current standard treatment is intensive, long-term chemotherapy.5 In 2015, it is estimated that 6,250 cases of ALL will be diagnosed in the United States6, with about 1 in 3 cases in adults. Only approximately 20 to 40 percent of newly diagnosed adults with ALL are cured with current treatment regimens.7 For patients with relapsed or refractory adult ALL, the five-year overall survival rate is less than 10 percent.8

REFERENCES

1 Fielding A. et al. Outcome of 609 adults after relapse of acute lymphoblastic leukemia (ALL); an MRC UKALL12/ECOG 2993 study. Blood. 2006; 944-950.

2 U.S. Food and Drug Administration Safety and Innovation Act. Available at: http://www.gpo.gov/fdsys/pkg/PLAW-112publ144/pdf/PLAW-112publ144.pdf(link is external).Accessed July 11, 2015.

3 U.S. Food and Drug Administration Frequently Asked Questions: Breakthrough Therapies. Available at:http://www.fda.gov/RegulatoryInformation/Legislation/FederalFoodDrugandCosmeticActFDCAct/SignificantAmendmentstotheFDCAct/FDASIA/ucm341027.htm(link is external). Accessed July 11, 2015.

4 National Cancer Institute: Adult Acute Lymphoblastic Leukemia Treatment (PDQ®) – General Information About Adult Acute Lymphoblastic Leukemia (ALL). Available at:http://www.cancer.gov/cancertopics/pdq/treatment/adultALL/HealthProfessional/page1(link is external). Accessed July 11, 2015.

5 American Cancer Society: Typical treatment of acute lymphocytic leukemia. Available at:http://www.cancer.org/cancer/leukemia-acutelymphocyticallinadults/detailedguide/leukemia-acute-lymphocytic-treating-typical-treatment(link is external). Accessed July 11, 2015.

6 American Cancer Society: What are the key statistics about acute lymphocytic leukemia? Available at:http://www.cancer.org/cancer/leukemia-acutelymphocyticallinadults/detailedguide/leukemia-acute-lymphocytic-key-statistics(link is external). Accessed February 18, 2015.

7 Manal Basyouni A. et al. Prognostic significance of survivin and tumor necrosis factor-alpha in adult acute lymphoblastic leukemia. doi:10.1016/j.clinbiochem.2011.08.1147.

8 Fielding A. et al. Outcome of 609 adults after relapse of acute lymphoblastic leukemia (ALL); an MRC UKALL12/ECOG 2993 study. Blood. 2006; 944-950.

9 Clinicaltrials.gov. A Study of Inotuzumab Ozogamicin versus Investigator’s Choice of Chemotherapy in Patients with Relapsed or Refractory Acute Lymphoblastic Leukemia. Available at: http://www.clinicaltrials.gov/ct2/show/NCT01564784?term=inotuzumab&rank=7(link is external). Accessed July 11, 2015.

10 Leonard J et al. Epratuzumab, a Humanized Anti-CD22 Antibody, in Aggressive Non-Hodgkin’s Lymphoma: a Phase I/II Clinical Trial Results. Clinical Cancer Research. 2004; 10: 5327-5334.

11 DiJoseph JF. Antitumor Efficacy of a Combination of CMC-544 (Inotuzumab Ozogamicin), a CD22-Targeted Cytotoxic Immunoconjugate of Calicheamicin, and Rituximab against Non-Hodgkin’s B-Cell Lymphoma. Clin Cancer Res. 2006; 12: 242-250.

SOURCE

http://www.pfizer.com/news/press-release/press-release-detail/pfizer_s_inotuzumab_ozogamicin_receives_fda_breakthrough_therapy_designation_for_acute_lymphoblastic_leukemia_all

Other related article Published on this Open Access Online Scientific Journal include the following:

STORY OF A LEUKEMIA FIGHTER

Nicole L. Gularte, MBA

https://pharmaceuticalintelligence.com/2016/08/21/cancer-the-future-immunotherapy/

https://pharmaceuticalintelligence.com/?s=Acute+Lymphoblastic+Leukemia+%28ALL%29+

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Keystone Symposia on Molecular and Cellular Biology – 2016-2017 Forthcoming Conferences in Life Sciences

Reporter: Aviva Lev-Ari, PhD, RN

2016-2017 Forthcoming Conferences in Life Sciences by topic:

DNA Replication and Recombination (Z2)
April 2 – 6, 2017 | Santa Fe, New Mexico, USA
Scientific Organizers: John F.X. Diffley, Anja Groth and Scott Keeney

Immunology

Translational Vaccinology for Global Health (S1)
October 25 – 29, 2016 | London, United Kingdom
Scientific Organizers: Christopher L. Karp, Gagandeep Kang and Rino Rappuoli

Hemorrhagic Fever Viruses (S3)
December 4 – 8, 2016 | Santa Fe, New Mexico, USA
Scientific Organizers: William E. Dowling and Thomas W. Geisbert

Cell Plasticity within the Tumor Microenvironment (A1)
January 8 – 12, 2017 | Big Sky, Montana, USA
Scientific Organizers: Sergei Grivennikov, Florian R. Greten and Mikala Egeblad

TGF-ß in Immunity, Inflammation and Cancer (A3)
January 9 – 13, 2017 | Taos, New Mexico, USA
Scientific Organizers: Wanjun Chen, Joanne E. Konkel and Richard A. Flavell

New Developments in Our Basic Understanding of Tuberculosis (A5)
January 14 – 18, 2017 | Vancouver, British Columbia, Canada
Scientific Organizers: Samuel M. Behar and Valerie Mizrahi

PI3K Pathways in Immunology, Growth Disorders and Cancer (A6)
January 19 – 23, 2017 | Santa Fe, New Mexico, USA
Scientific Organizers: Leon O. Murphy, Klaus Okkenhaug and Sabina C. Cosulich

Biobetters and Next-Generation Biologics: Innovative Strategies for Optimally Effective Therapies (A7)
January 22 – 26, 2017 | Snowbird, Utah, USA
Scientific Organizers: Cherié L. Butts, Amy S. Rosenberg, Amy D. Klion and Sachdev S. Sidhu

Obesity and Adipose Tissue Biology (J4)
January 22 – 26, 2017 | Keystone, Colorado, USA
Scientific Organizers: Marc L. Reitman, Ruth E. Gimeno and Jan Nedergaard

Inflammation-Driven Cancer: Mechanisms to Therapy (J7)
February 5 – 9, 2017 | Keystone, Colorado, USA
Scientific Organizers: Fiona M. Powrie, Michael Karin and Alberto Mantovani

Autophagy Network Integration in Health and Disease (B2)
February 12 – 16, 2017 | Copper Mountain, Colorado, USA
Scientific Organizers: Ivan Dikic, Katja Simon and J. Wade Harper

Asthma: From Pathway Biology to Precision Therapeutics (B3)
February 12 – 16, 2017 | Keystone, Colorado, USA
Scientific Organizers: Clare M. Lloyd, John V. Fahy and Sally Wenzel-Morganroth

Viral Immunity: Mechanisms and Consequences (B4)
February 19 – 23, 2017 | Santa Fe, New Mexico, USA
Scientific Organizers: Akiko Iwasaki, Daniel B. Stetson and E. John Wherry

Lipidomics and Bioactive Lipids in Metabolism and Disease (B6)
February 26 – March 2, 2017 | Tahoe City, California, USA
Scientific Organizers: Alfred H. Merrill, Walter Allen Shaw, Sarah Spiegel and Michael J.O.Wakelam

Bile Acid Receptors as Signal Integrators in Liver and Metabolism (C1)
March 3 – 7, 2017 | Monterey, California, USA
Scientific Organizers: Luciano Adorini, Kristina Schoonjans and Scott L. Friedman

Cancer Immunology and Immunotherapy: Taking a Place in Mainstream Oncology (C7)
March 19 – 23, 2017 | Whistler, British Columbia, Canada
Scientific Organizers: Robert D. Schreiber, James P. Allison, Philip D. Greenberg and Glenn Dranoff

Pattern Recognition Signaling: From Innate Immunity to Inflammatory Disease (X5)
March 19 – 23, 2017 | Banff, Alberta, Canada
Scientific Organizers: Thirumala-Devi Kanneganti, Vishva M. Dixit and Mohamed Lamkanfi

Type I Interferon: Friend and Foe Alike (X6)
March 19 – 23, 2017 | Banff, Alberta, Canada
Scientific Organizers: Alan Sher, Virginia Pascual, Adolfo García-Sastre and Anne O’Garra

Injury, Inflammation and Fibrosis (C8)
March 26 – 30, 2017 | Snowbird, Utah, USA
Scientific Organizers: Tatiana Kisseleva, Michael Karin and Andrew M. Tager

Immune Regulation in Autoimmunity and Cancer (D1)
March 26 – 30, 2017 | Whistler, British Columbia, Canada
Scientific Organizers: David A. Hafler, Vijay K. Kuchroo and Jane L. Grogan

B Cells and T Follicular Helper Cells – Controlling Long-Lived Immunity (D2)
April 23 – 27, 2017 | Whistler, British Columbia, Canada
Scientific Organizers: Stuart G. Tangye, Ignacio Sanz and Hai Qi

Mononuclear Phagocytes in Health, Immune Defense and Disease (D3)
April 30 – May 4, 2017 | Austin, Texas, USA
Scientific Organizers: Steffen Jung and Miriam Merad

Modeling Viral Infections and Immunity (E1)
May 1 – 4, 2017 | Estes Park, Colorado, USA
Scientific Organizers: Alan S. Perelson, Rob J. De Boer and Phillip D. Hodgkin

Integrating Metabolism and Immunity (E4)
May 29 – June 2, 2017 | Dublin, Ireland
Scientific Organizers: Hongbo Chi, Erika L. Pearce, Richard A. Flavell and Luke A.J. O’Neill

Neuroinflammation: Concepts, Characteristics, Consequences (E5)
June 19 – 23, 2017 | Keystone, Colorado, USA
Scientific Organizers: Richard M. Ransohoff, Christopher K. Glass and V. Hugh Perry

Infectious Diseases

Translational Vaccinology for Global Health (S1)
October 25 – 29, 2016 | London, United Kingdom
Scientific Organizers: Christopher L. Karp, Gagandeep Kang and Rino Rappuoli

Hemorrhagic Fever Viruses (S3)
December 4 – 8, 2016 | Santa Fe, New Mexico, USA
Scientific Organizers: William E. Dowling and Thomas W. Geisbert

Cellular Stress Responses and Infectious Agents (S4)
December 4 – 8, 2016 | Santa Fe, New Mexico, USA
Scientific Organizers: Margo A. Brinton, Sandra K. Weller and Beth Levine

New Developments in Our Basic Understanding of Tuberculosis (A5)
January 14 – 18, 2017 | Vancouver, British Columbia, Canada
Scientific Organizers: Samuel M. Behar and Valerie Mizrahi

Autophagy Network Integration in Health and Disease (B2)
February 12 – 16, 2017 | Copper Mountain, Colorado, USA
Scientific Organizers: Ivan Dikic, Katja Simon and J. Wade Harper

Viral Immunity: Mechanisms and Consequences (B4)
February 19 – 23, 2017 | Santa Fe, New Mexico, USA
Scientific Organizers: Akiko Iwasaki, Daniel B. Stetson and E. John Wherry

Malaria: From Innovation to Eradication (B5)
February 19 – 23, 2017 | Kampala, Uganda
Scientific Organizers: Marcel Tanner, Sarah K. Volkman, Marcus V.G. Lacerda and Salim Abdulla

Type I Interferon: Friend and Foe Alike (X6)
March 19 – 23, 2017 | Banff, Alberta, Canada
Scientific Organizers: Alan Sher, Virginia Pascual, Adolfo García-Sastre and Anne O’Garra

HIV Vaccines (C9)
March 26 – 30, 2017 | Steamboat Springs, Colorado, USA
Scientific Organizers: Andrew B. Ward, Penny L. Moore and Robin Shattock

Modeling Viral Infections and Immunity (E1)
May 1 – 4, 2017 | Estes Park, Colorado, USA
Scientific Organizers: Alan S. Perelson, Rob J. De Boer and Phillip D. Hodgkin

Metabolic Diseases

Mitochondria Communication (A4)
January 14 – 18, 2017 | Taos, New Mexico, USA
Scientific Organizers: Jared Rutter, Cole M. Haynes and Marcia C. Haigis

Diabetes (J3)
January 22 – 26, 2017 | Keystone, Colorado, USA
Scientific Organizers: Jiandie Lin, Clay F. Semenkovich and Rohit N. Kulkarni

Obesity and Adipose Tissue Biology (J4)
January 22 – 26, 2017 | Keystone, Colorado, USA
Scientific Organizers: Marc L. Reitman, Ruth E. Gimeno and Jan Nedergaard

Microbiome in Health and Disease (J8)
February 5 – 9, 2017 | Keystone, Colorado, USA
Scientific Organizers: Julie A. Segre, Ramnik Xavier and William Michael Dunne

Bile Acid Receptors as Signal Integrators in Liver and Metabolism (C1)
March 3 – 7, 2017 | Monterey, California, USA
Scientific Organizers: Luciano Adorini, Kristina Schoonjans and Scott L. Friedman

Sex and Gender Factors Affecting Metabolic Homeostasis, Diabetes and Obesity (C6)
March 19 – 22, 2017 | Tahoe City, California, USA
Scientific Organizers: Franck Mauvais-Jarvis, Deborah Clegg and Arthur P. Arnold

Neuronal Control of Appetite, Metabolism and Weight (Z5)
May 9 – 13, 2017 | Copenhagen, Denmark
Scientific Organizers: Lora K. Heisler and Scott M. Sternson

Gastrointestinal Control of Metabolism (Z6)
May 9 – 13, 2017 | Copenhagen, Denmark
Scientific Organizers: Randy J. Seeley, Matthias H. Tschöp and Fiona M. Gribble

Integrating Metabolism and Immunity (E4)
May 29 – June 2, 2017 | Dublin, Ireland
Scientific Organizers: Hongbo Chi, Erika L. Pearce, Richard A. Flavell and Luke A.J. O’Neill

Neurobiology

Transcriptional and Epigenetic Control in Stem Cells (J1)
January 8 – 12, 2017 | Olympic Valley, California, USA
Scientific Organizers: Konrad Hochedlinger, Kathrin Plath and Marius Wernig

Neurogenesis during Development and in the Adult Brain (J2)
January 8 – 12, 2017 | Olympic Valley, California, USA
Scientific Organizers: Alysson R. Muotri, Kinichi Nakashima and Xinyu Zhao

Rare and Undiagnosed Diseases: Discovery and Models of Precision Therapy (C2)
March 5 – 8, 2017 | Boston, Massachusetts, USA
Scientific Organizers: William A. Gahl and Christoph Klein

mRNA Processing and Human Disease (C3)
March 5 – 8, 2017 | Taos, New Mexico, USA
Scientific Organizers: James L. Manley, Siddhartha Mukherjee and Gideon Dreyfuss

Synapses and Circuits: Formation, Function, and Dysfunction (X1)
March 5 – 8, 2017 | Santa Fe, New Mexico, USA
Scientific Organizers: Tony Koleske, Yimin Zou, Kristin Scott and A. Kimberley McAllister

Connectomics (X2)
March 5 – 8, 2017 | Santa Fe, New Mexico, USA
Scientific Organizers: Olaf Sporns, Danielle Bassett and Jeremy Freeman

Neuronal Control of Appetite, Metabolism and Weight (Z5)
May 9 – 13, 2017 | Copenhagen, Denmark
Scientific Organizers: Lora K. Heisler and Scott M. Sternson

Neuroinflammation: Concepts, Characteristics, Consequences (E5)
June 19 – 23, 2017 | Keystone, Colorado, USA
Scientific Organizers: Richard M. Ransohoff, Christopher K. Glass and V. Hugh Perry

Plant Biology

Phytobiomes: From Microbes to Plant Ecosystems (S2)
November 8 – 12, 2016 | Santa Fe, New Mexico, USA
Scientific Organizers: Jan E. Leach, Kellye A. Eversole, Jonathan A. Eisen and Gwyn Beattie

Structural Biology

Frontiers of NMR in Life Sciences (C5)
March 12 – 16, 2017 | Keystone, Colorado, USA
Scientific Organizers: Kurt Wüthrich, Michael Sattler and Stephen W. Fesik

Technologies

Cell Plasticity within the Tumor Microenvironment (A1)
January 8 – 12, 2017 | Big Sky, Montana, USA
Scientific Organizers: Sergei Grivennikov, Florian R. Greten and Mikala Egeblad

Precision Genome Engineering (A2)
January 8 – 12, 2017 | Breckenridge, Colorado, USA
Scientific Organizers: J. Keith Joung, Emmanuelle Charpentier and Olivier Danos

Transcriptional and Epigenetic Control in Stem Cells (J1)
January 8 – 12, 2017 | Olympic Valley, California, USA
Scientific Organizers: Konrad Hochedlinger, Kathrin Plath and Marius Wernig

Protein-RNA Interactions: Scale, Mechanisms, Structure and Function of Coding and Noncoding RNPs (J6)
February 5 – 9, 2017 | Banff, Alberta, Canada
Scientific Organizers: Gene W. Yeo, Jernej Ule, Karla Neugebauer and Melissa J. Moore

Lipidomics and Bioactive Lipids in Metabolism and Disease (B6)
February 26 – March 2, 2017 | Tahoe City, California, USA
Scientific Organizers: Alfred H. Merrill, Walter Allen Shaw, Sarah Spiegel and Michael J.O.Wakelam

Connectomics (X2)
March 5 – 8, 2017 | Santa Fe, New Mexico, USA
Scientific Organizers: Olaf Sporns, Danielle Bassett and Jeremy Freeman

Engineered Cells and Tissues as Platforms for Discovery and Therapy (K1)
March 9 – 12, 2017 | Boston, Massachusetts, USA
Scientific Organizers: Laura E. Niklason, Milica Radisic and Nenad Bursac

Frontiers of NMR in Life Sciences (C5)
March 12 – 16, 2017 | Keystone, Colorado, USA
Scientific Organizers: Kurt Wüthrich, Michael Sattler and Stephen W. Fesik

October 2016

Translational Vaccinology for Global Health (S1)
October 25 – 29, 2016 | London, United Kingdom
Scientific Organizers: Christopher L. Karp, Gagandeep Kang and Rino Rappuoli

November 2016

Phytobiomes: From Microbes to Plant Ecosystems (S2)
November 8 – 12, 2016 | Santa Fe, New Mexico, USA
Scientific Organizers: Jan E. Leach, Kellye A. Eversole, Jonathan A. Eisen and Gwyn Beattie

December 2016

Hemorrhagic Fever Viruses (S3)
December 4 – 8, 2016 | Santa Fe, New Mexico, USA
Scientific Organizers: William E. Dowling and Thomas W. Geisbert

Cellular Stress Responses and Infectious Agents (S4)
December 4 – 8, 2016 | Santa Fe, New Mexico, USA
Scientific Organizers: Margo A. Brinton, Sandra K. Weller and Beth Levine

January 2017

Cell Plasticity within the Tumor Microenvironment (A1)
January 8 – 12, 2017 | Big Sky, Montana, USA
Scientific Organizers: Sergei Grivennikov, Florian R. Greten and Mikala Egeblad

Precision Genome Engineering (A2)
January 8 – 12, 2017 | Breckenridge, Colorado, USA
Scientific Organizers: J. Keith Joung, Emmanuelle Charpentier and Olivier Danos

Transcriptional and Epigenetic Control in Stem Cells (J1)
January 8 – 12, 2017 | Olympic Valley, California, USA
Scientific Organizers: Konrad Hochedlinger, Kathrin Plath and Marius Wernig

Neurogenesis during Development and in the Adult Brain (J2)
January 8 – 12, 2017 | Olympic Valley, California, USA
Scientific Organizers: Alysson R. Muotri, Kinichi Nakashima and Xinyu Zhao

TGF-ß in Immunity, Inflammation and Cancer (A3)
January 9 – 13, 2017 | Taos, New Mexico, USA
Scientific Organizers: Wanjun Chen, Joanne E. Konkel and Richard A. Flavell

Mitochondria Communication (A4)
January 14 – 18, 2017 | Taos, New Mexico, USA
Scientific Organizers: Jared Rutter, Cole M. Haynes and Marcia C. Haigis

New Developments in Our Basic Understanding of Tuberculosis (A5)
January 14 – 18, 2017 | Vancouver, British Columbia, Canada
Scientific Organizers: Samuel M. Behar and Valerie Mizrahi

PI3K Pathways in Immunology, Growth Disorders and Cancer (A6)
January 19 – 23, 2017 | Santa Fe, New Mexico, USA
Scientific Organizers: Leon O. Murphy, Klaus Okkenhaug and Sabina C. Cosulich

Biobetters and Next-Generation Biologics: Innovative Strategies for Optimally Effective Therapies (A7)
January 22 – 26, 2017 | Snowbird, Utah, USA
Scientific Organizers: Cherié L. Butts, Amy S. Rosenberg, Amy D. Klion and Sachdev S. Sidhu

Diabetes (J3)
January 22 – 26, 2017 | Keystone, Colorado, USA
Scientific Organizers: Jiandie Lin, Clay F. Semenkovich and Rohit N. Kulkarni

Obesity and Adipose Tissue Biology (J4)
January 22 – 26, 2017 | Keystone, Colorado, USA
Scientific Organizers: Marc L. Reitman, Ruth E. Gimeno and Jan Nedergaard

Omics Strategies to Study the Proteome (A8)
January 29 – February 2, 2017 | Breckenridge, Colorado, USA
Scientific Organizers: Alan Saghatelian, Chuan He and Ileana M. Cristea

Epigenetics and Human Disease: Progress from Mechanisms to Therapeutics (A9)
January 29 – February 2, 2017 | Seattle, Washington, USA
Scientific Organizers: Johnathan R. Whetstine, Jessica K. Tyler and Rab K. Prinjha

Hematopoiesis (B1)
January 31 – February 4, 2017 | Banff, Alberta, Canada
Scientific Organizers: Catriona H.M. Jamieson, Andreas Trumpp and Paul S. Frenette

February 2017

Noncoding RNAs: From Disease to Targeted Therapeutics (J5)
February 5 – 9, 2017 | Banff, Alberta, Canada
Scientific Organizers: Kevin V. Morris, Archa Fox and Paloma Hoban Giangrande

Protein-RNA Interactions: Scale, Mechanisms, Structure and Function of Coding and Noncoding RNPs (J6)
February 5 – 9, 2017 | Banff, Alberta, Canada
Scientific Organizers: Gene W. Yeo, Jernej Ule, Karla Neugebauer and Melissa J. Moore

Inflammation-Driven Cancer: Mechanisms to Therapy (J7)
February 5 – 9, 2017 | Keystone, Colorado, USA
Scientific Organizers: Fiona M. Powrie, Michael Karin and Alberto Mantovani

Microbiome in Health and Disease (J8)
February 5 – 9, 2017 | Keystone, Colorado, USA
Scientific Organizers: Julie A. Segre, Ramnik Xavier and William Michael Dunne

Autophagy Network Integration in Health and Disease (B2)
February 12 – 16, 2017 | Copper Mountain, Colorado, USA
Scientific Organizers: Ivan Dikic, Katja Simon and J. Wade Harper

Asthma: From Pathway Biology to Precision Therapeutics (B3)
February 12 – 16, 2017 | Keystone, Colorado, USA
Scientific Organizers: Clare M. Lloyd, John V. Fahy and Sally Wenzel-Morganroth

Viral Immunity: Mechanisms and Consequences (B4)
February 19 – 23, 2017 | Santa Fe, New Mexico, USA
Scientific Organizers: Akiko Iwasaki, Daniel B. Stetson and E. John Wherry

Malaria: From Innovation to Eradication (B5)
February 19 – 23, 2017 | Kampala, Uganda
Scientific Organizers: Marcel Tanner, Sarah K. Volkman, Marcus V.G. Lacerda and Salim Abdulla

Lipidomics and Bioactive Lipids in Metabolism and Disease (B6)
February 26 – March 2, 2017 | Tahoe City, California, USA
Scientific Organizers: Alfred H. Merrill, Walter Allen Shaw, Sarah Spiegel and Michael J.O.Wakelam

March 2017

Bile Acid Receptors as Signal Integrators in Liver and Metabolism (C1)
March 3 – 7, 2017 | Monterey, California, USA
Scientific Organizers: Luciano Adorini, Kristina Schoonjans and Scott L. Friedman

Rare and Undiagnosed Diseases: Discovery and Models of Precision Therapy (C2)
March 5 – 8, 2017 | Boston, Massachusetts, USA
Scientific Organizers: William A. Gahl and Christoph Klein

mRNA Processing and Human Disease (C3)
March 5 – 8, 2017 | Taos, New Mexico, USA
Scientific Organizers: James L. Manley, Siddhartha Mukherjee and Gideon Dreyfuss

Kinases: Next-Generation Insights and Approaches (C4)
March 5 – 9, 2017 | Breckenridge, Colorado, USA
Scientific Organizers: Reid M. Huber, John Kuriyan and Ruth H. Palmer

Synapses and Circuits: Formation, Function, and Dysfunction (X1)
March 5 – 8, 2017 | Santa Fe, New Mexico, USA
Scientific Organizers: Tony Koleske, Yimin Zou, Kristin Scott and A. Kimberley McAllister

Connectomics (X2)
March 5 – 8, 2017 | Santa Fe, New Mexico, USA
Scientific Organizers: Olaf Sporns, Danielle Bassett and Jeremy Freeman

Tumor Metabolism: Mechanisms and Targets (X3)
March 5 – 9, 2017 | Whistler, British Columbia, Canada
Scientific Organizers: Brendan D. Manning, Kathryn E. Wellen and Reuben J. Shaw

Adaptations to Hypoxia in Physiology and Disease (X4)
March 5 – 9, 2017 | Whistler, British Columbia, Canada
Scientific Organizers: M. Celeste Simon, Amato J. Giaccia and Randall S. Johnson

Engineered Cells and Tissues as Platforms for Discovery and Therapy (K1)
March 9 – 12, 2017 | Boston, Massachusetts, USA
Scientific Organizers: Laura E. Niklason, Milica Radisic and Nenad Bursac

Frontiers of NMR in Life Sciences (C5)
March 12 – 16, 2017 | Keystone, Colorado, USA
Scientific Organizers: Kurt Wüthrich, Michael Sattler and Stephen W. Fesik

Sex and Gender Factors Affecting Metabolic Homeostasis, Diabetes and Obesity (C6)
March 19 – 22, 2017 | Tahoe City, California, USA
Scientific Organizers: Franck Mauvais-Jarvis, Deborah Clegg and Arthur P. Arnold

Cancer Immunology and Immunotherapy: Taking a Place in Mainstream Oncology (C7)
March 19 – 23, 2017 | Whistler, British Columbia, Canada
Scientific Organizers: Robert D. Schreiber, James P. Allison, Philip D. Greenberg and Glenn Dranoff

Pattern Recognition Signaling: From Innate Immunity to Inflammatory Disease (X5)
March 19 – 23, 2017 | Banff, Alberta, Canada
Scientific Organizers: Thirumala-Devi Kanneganti, Vishva M. Dixit and Mohamed Lamkanfi

Type I Interferon: Friend and Foe Alike (X6)
March 19 – 23, 2017 | Banff, Alberta, Canada
Scientific Organizers: Alan Sher, Virginia Pascual, Adolfo García-Sastre and Anne O’Garra

Injury, Inflammation and Fibrosis (C8)
March 26 – 30, 2017 | Snowbird, Utah, USA
Scientific Organizers: Tatiana Kisseleva, Michael Karin and Andrew M. Tager

HIV Vaccines (C9)
March 26 – 30, 2017 | Steamboat Springs, Colorado, USA
Scientific Organizers: Andrew B. Ward, Penny L. Moore and Robin Shattock

Immune Regulation in Autoimmunity and Cancer (D1)
March 26 – 30, 2017 | Whistler, British Columbia, Canada
Scientific Organizers: David A. Hafler, Vijay K. Kuchroo and Jane L. Grogan

Molecular Mechanisms of Heart Development (X7)
March 26 – 30, 2017 | Keystone, Colorado, USA
Scientific Organizers: Benoit G. Bruneau, Brian L. Black and Margaret E. Buckingham

RNA-Based Approaches in Cardiovascular Disease (X8)
March 26 – 30, 2017 | Keystone, Colorado, USA
Scientific Organizers: Thomas Thum and Roger J. Hajjar

April 2017

Genomic Instability and DNA Repair (Z1)
April 2 – 6, 2017 | Santa Fe, New Mexico, USA
Scientific Organizers: Julia Promisel Cooper, Marco F. Foiani and Geneviève Almouzni

DNA Replication and Recombination (Z2)
April 2 – 6, 2017 | Santa Fe, New Mexico, USA
Scientific Organizers: John F.X. Diffley, Anja Groth and Scott Keeney

B Cells and T Follicular Helper Cells – Controlling Long-Lived Immunity (D2)
April 23 – 27, 2017 | Whistler, British Columbia, Canada
Scientific Organizers: Stuart G. Tangye, Ignacio Sanz and Hai Qi

Mononuclear Phagocytes in Health, Immune Defense and Disease (D3)
April 30 – May 4, 2017 | Austin, Texas, USA
Scientific Organizers: Steffen Jung and Miriam Merad

May 2017

Modeling Viral Infections and Immunity (E1)
May 1 – 4, 2017 | Estes Park, Colorado, USA
Scientific Organizers: Alan S. Perelson, Rob J. De Boer and Phillip D. Hodgkin

Angiogenesis and Vascular Disease (Z3)
May 8 – 12, 2017 | Santa Fe, New Mexico, USA
Scientific Organizers: M. Luisa Iruela-Arispe, Timothy T. Hla and Courtney Griffin

Mitochondria, Metabolism and Heart (Z4)
May 8 – 12, 2017 | Santa Fe, New Mexico, USA
Scientific Organizers: Junichi Sadoshima, Toren Finkel and Åsa B. Gustafsson

Neuronal Control of Appetite, Metabolism and Weight (Z5)
May 9 – 13, 2017 | Copenhagen, Denmark
Scientific Organizers: Lora K. Heisler and Scott M. Sternson

Gastrointestinal Control of Metabolism (Z6)
May 9 – 13, 2017 | Copenhagen, Denmark
Scientific Organizers: Randy J. Seeley, Matthias H. Tschöp and Fiona M. Gribble

Aging and Mechanisms of Aging-Related Disease (E2)
May 15 – 19, 2017 | Yokohama, Japan
Scientific Organizers: Kazuo Tsubota, Shin-ichiro Imai, Matt Kaeberlein and Joan Mannick

Single Cell Omics (E3)
May 26 – 30, 2017 | Stockholm, Sweden
Scientific Organizers: Sarah Teichmann, Evan W. Newell and William J. Greenleaf

Integrating Metabolism and Immunity (E4)
May 29 – June 2, 2017 | Dublin, Ireland
Scientific Organizers: Hongbo Chi, Erika L. Pearce, Richard A. Flavell and Luke A.J. O’Neill

Cell Death and Inflammation (K2)
May 29 – June 2, 2017 | Dublin, Ireland
Scientific Organizers: Seamus J. Martin and John Silke

June 2017

Neuroinflammation: Concepts, Characteristics, Consequences (E5)
June 19 – 23, 2017 | Keystone, Colorado, USA
Scientific Organizers: Richard M. Ransohoff, Christopher K. Glass and V. Hugh Perry

SOURCE

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Pull at Cancer’s Levers

Curator: Larry H. Bernstein, MD, FCAP

 

Driving Cancer Immunotherapy 

The Stakes in Immuno-Oncology Are Too High for Researchers to Pull at Cancer’s Levers Blindly. Researchers Need a System.

  • Within the past decade or so, a revolutionary idea has emerged in the minds of scientists, physicians, and medical experts. Instead of using man-made chemicals to treat cancer, let us instead unleash the power of our own bodies upon the malignancy.

    This idea is the inspiration behind cancer immunotherapy, which is, according to most experts, a therapeutic approach that involves training the immune system to fight off cancer. In the words of one expert, cancer immunotherapy means “taking the immune system’s inherent properties and turbo charging those to fight cancer.”

    Cancer immunotherapy technologies are being developed to accomplish
    several tasks:

    • Enhance the molecular targeting of cancer cells
    • Report the rate of killing by specific immune agents
    • Direct immune cells toward tumor destruction.

    Since its inception, the field has evolved, and it continues to do so. It began with in vivo investigations of tumor growth and development, and it progressed through laboratory investigations of cellular morphology and survival curves. And now it is adopting pathway analysis to guide therapeutic development and improve patient care.

    To begin to understand cancer immunotherapy, one must understand how the immune system targets tumor cells. One of the prominent adaptive components of the immune system is the T cell, which responds to perceived threats through the massive increase in clonal T cells targeted in some way toward the diseased cell or pathogen.

  • The T-Cell Repertoire

    Adaptive Biotechnologies’ immunoSEQ Assay, a high-throughput research platform for immune system profiling, is designed to generate sequencer-ready libraries using highly optimized primer sets in a multiplex PCR format that targets T- and B-cell receptor genes. This image depicts how the assay’s two-step PCR process can be used to quantify the clonal diversity of immune cells.

    Immunologists call this process VJD rearrangement. It happens during T-lymphocyte development and affects three gene regions, the variable (V), the diversity (D), and the joining (J) regions. This rearrangement of the genetic code allow for the structural diversity in T-cell receptors responsible for antigenic specificity including antigenic targets on tumor cells. In the case of cancer, specificity is complicated because the tumor is actually part of the body itself, one of the reasons cancers naturally evade detection.

    The specificity problem would always hinder attempts to goad the immune system into attacking cancer, scientists realized, unless technologies emerged that could efficiently track the clonal diversity of T cells inside patients. Existing technologies, such as spectratyping, were inadequate.  In 2007, when Dr. Robins and his collaborators began developing the technology, only 10,000 T-cell receptor sequences had been reported in all the literature using older methodologies.

    “The immunology field of the time had no connection with high-throughput sequencing,” notes Dr. Robins, recalling his days as a computational biologist for the Fred Hutchinson Cancer Research Center. “It became clear that instead of using this old technology to look at T-cell receptors, we could just directly sequence them—if we could amplify them correctly.”

    With its first experiment, Dr. Robins’ team ended up with six million T-cell receptor sequences. “Our approach,” Dr. Robins modestly suggests, “kind of changed the scale of what we were able to do.” The team went on to develop advanced multiplex sequencing technology, doing work that essentially started the field of immune sequencing. “Previously,” maintains Dr. Robins, “no one had ever been able to quantitatively do a multiplex PCR.”

    Adaptive Biotechnologies’ product, the ImmunoSEQ® assay, uses several hundred primer pairs to quantify the clonal diversity of T cells. Using this technology, researchers and clinicians can focus on T-cell clones that are expanded specifically in or near a tumor or that are circulating in the blood stream.

    “You obviously can’t get a serial sample of the tumor,” explains Dr. Robins, “but you can get serial samples of blood,” allowing for immune cell repertoire tracking during the progression of a disease. The technology is already being used to assess leukemias in the clinic, directly tracking the leukemia itself based on the massive clonal expansion of a single cancerous B or T cell.

    Eventually, Dr. Robins’ team hopes to monitor serial changes in T cell clones before, during, and after therapeutic intervention. The team has even developed a tumor infiltrating lymphocyte (TIL) assay to examine clones that are attracted to tumors.

     

Circulating Tumor Cells

“Years ago, they were just interested in what was happening in the tumor,” says Daniel Adams, senior research scientist at Creatv MicroTech. “Now people have realized that the immune system is reacting to the tumor.”

Scientists such as Adams have been tracking tumor cells and tumor-modified stromal cells, as well as components of the non-adaptive immune system, directly within the bloodstream to examine changes that occur over time.

“We can’t go back in to re-biopsy the patient every year, or every time there is a recurrence,” says Adams, “It’s just not feasible.”

That is why Creatv MicroTech, with locations in Maryland and New Jersey, has developed the CellSieve, a mechanical cell filter. The CellSieve, which improves on older technology through better polymers and engineering, isolates circulating tumor cells (CTCs) and stromal cells in order to capture them for further clinical analysis.

Isolation, culture and expansion of cells isolated on CellSieve™. (A) MCF-7 cells spiked into vacutainers, isolated by filtration and cultured on CellSieve for 2-3 weeks. A 3 dimensional cluster attributed to this cell line is seen on the filter. (green=anti-cytokeratin, blue=DAPI) (B) PANC-1 cells spiked into vacutainers, isolated by filtration and grown on CellSieve for 2-3 weeks. PANC-1 is seen growing as a monolayer on the filter. (C) SKBR3 cells are spiked into blood, filtered by CellSieve. The CTCs are identified by presence of anti-cytokeratin and anti-EpCAM, and absence of anti-CD45. After CTCs are counted, cells are subtyped by HER2 FISH. (D) SKBR3 cells are spiked into vacutainers, isolated by filtration and grown on CellSieve for 2-3 weeks. Expanded colonies were directly analyzed as a whole colony and as individual cells, molecularly by HER2/CR17 FISH probes. (E) Circulating stromal cell, e.g. a 70 µm giant cancer associated macrophage can be identified for clinical use, myeloid marker in red. (F) A cell of interest can be identified and restained with immunotherapeutic biomarkers, e.g. PD-L1 (green) and PD-1 (purple). (G) After filtration, cells were identified with histopathological stains (e.g. H&E) for cytological analysis. (H) After H&E, external cell structures were analyzed by SEM. [Creatv MicroTech].

 

“As a patient goes through therapy, the patient’s resistance builds, and the cancer recurs in different subpopulations,” states Adams. “And after a few years, the original tumor mass is no longer applicable to what is growing in the patient farther down the road.”

Although CTCs are exceedingly rare in the bloodstream, with just one or two in every 5 to 10 mL of blood, and although these cells have a very low viability, the surviving CTCs have a high prognostic value.

“We looked at 30 to 40 breast cancer patients over two years,” reports Adams. “And we showed that if you have a dividing CTC, you have a 90% chance of dying in two years and a 100% chance of dying within two and half years.”

Furthermore, the immune system response can be tracked, says Adams, by examining stromal cells, which can also be collected with the CellSieve filtration device. That is, these cells can be collected serially. Much recent evidence supports the conclusion that stromal cells in the tumor environment co-evolve with the tumor, suggesting that stromal marker changes reflect tumor changes.

“There is this plethora of stromal cells and tumor cells out there in the circulation for you to look at,” declares Adams. “Once the cells are isolated, you can subject them to pathological approaches, biomarker approaches, or molecular approaches—or all of the above.”

A MicroTech Creatv study published in the Royal Society of Chemistry showed the efficacy of following up CTC isolation with techniques such as fluorescence in situ hybridization (FISH), histopathological analysis, and cell culture.

Cancer-Killing Assays

Diverse mechanisms are at play in cancer biology. Our understanding of these mechanisms contributes to a couple of virtuous cycles. It strengthens and is strengthened by diagnostic approaches, such as immune- and tumor-cell monitoring. The same could be said of therapeutic approaches. Cancer biology will inform and be informed by cancer immunotherapies such as adoptive cell transfer. To maintain the virtuous cycle, however, it will be necessary to conduct in vitro testing.

“There is no doubt that immunotherapy is going to play a major role in the treatment of cancer,” says Brandon Lamarche, Ph.D., technical communicator and scientist at ACEA Biosciences. “Regardless of what the route is, what is going to have to happen in terms of the research area is that you need an effective cell-killing assay.”

ACEA Biosciences, a San Diego-based company, has developed a microtiter plate that is coated with gold electrodes across 75% of the well bottoms. When the microtiter plates are placed in the company’s xCELLigence plate reader, the electrodes enable the detection of changes in cell morphology and viability through electrical impedance.

“The instrument provides a weak electric potential to the electrodes on the plate, so you get electrons flowing between these electrodes,” explains Dr. Lamarche. Researchers can then apply reagents or non-adherent immune cell suspensions to adherent cancer cells and examine the effect.

Dr. Lamarche asserts that the xCELLigence system overcomes problems that bedevil competing cell-killing assays. These problems include leaky and radioactive labels, such as chromium 51, and assays that can only provide users with an endpoint for cell killing. “With xCELLigence,” he insists, “you’re getting the full spectrum of what’s happening, and there’s all kinds of subtleties in the cell-killing curves that are very informative in terms of the biology.”

ACEA would like to see the xCELLigence system become the new standard in cell-killing assays from standard research to clinical testing on patient tumors. Dr. Lamarche envisions a day when patient tumor cells are quickly screened with therapeutic scenarios to determine the most efficacious killing option. “xCELLigence technology,” he suggests, “enables you to quickly sample a broad spectrum of conditions with a very simple workflow.”

Bioinformatics of Immuno-Oncology

From monitoring to treatment modalities, the field of cancer immunotherapy is aided by bioinformatics-minded data-mining experts, such as the analysts at Thompson-Reuters who are compiling data archives and applying advanced analytics to find new targets. “Essentially,” says Richard Harrison Ph.D., the company’s chief scientific officer for the life science division, “for every stage within pharmaceutical drug development, we have a database associated with that.”

The analysts at Thompson-Reuters curate and compile databases such as MedaCore and Cortellis, which they provide to their clients to help them with their research and clinical studies. “We can take customer data, and using our tools and our pathway maps, we can help them understand what their data is telling them,” explains Dr. Harrison.

Matt Wampole, Ph.D., a solutions scientist at Thompson-Reuters, spends his days reaching out and working with customers to help them understand and better use the company’s products. “Bench researchers,” he points out, “don’t necessarily know what is upstream of whatever expression change might be leading to a particular change in regulation.” Dr. Wampole indicates that he is part of a “solution team” that aids clients in determining important signaling cascades, regulators, and so on.

“We have a group of individuals who are very ‘skilling’ experts in the field,” Dr. Wampole continues, “including experts in the areas such as biostatistics, data curation, and data analytics. These experts help clients identify models, stratify patients, understand mechanisms, and look into disease mechanisms.”

Dr. Harrison sums up the Thompson-Reuters approach as follows: “We look for master regulators that can serve as both targets and biomarkers.” By examining the gene signatures from both the patient and from curated datasets, in the case of cancer immunotherapy, they hope to segregate patients according to what drugs will work best for them.

  • “We are working with a number of pharmaceutical companies to put our approach into practice for clinical trials,” informs Dr. Harrison. The approach has already been applied in several studies, including one that used data analysis of cell lines to help predict drug response in patients. Another study helped stratify glioblastoma patients.

  • Tumor-Targeted Delivery Platform

    PsiOxus Therapeutics, which is focused on immune therapeutics in oncology, has developed a patented platform for tumor-targeted delivery based on its oncolytic vaccine, Enadenotucirev (EnAd), which can be delivered systemically via intravenous administration.

    According to company officials, EnAd’s anti-cancer scope can be expanded by adding new genes, thereby enabling the creation of a broad range of unique immuno-oncology therapeutics. In a recent study conducted at the University of Oxford, researchers led by Philip G. Jakeman, Ph.D., sought to improve the models for evaluating cancer therapeutics by introducing ex vivo methodologies for research into colorectal cancer.

    The ex vivo approach utilized was able to exploit a major advantage by preserving the three-dimensional architecture of the tumor and its associated compartments, including immune cells. The study, which was presented at the International Summit on Oncolytic Viral Therapeutics in Quebec, showed the tissue slice model can provide a novel means to assessing an oncolytic vaccine in a system that more accurately recapitulates human tumors, provide a more stringent test for oncolytic viruses, such as EnAd, and allow study of the human immune cells within the tumor 3D context.

    By maintaining the components of the tumor immune microenvironment, this new methodology could become useful in analyzing anti-viral responses within tumors, or even in evaluating therapeutics that target immunosuppressive tumor micro-environments, noted the Oxford team.

     

 

Deciphering the Cancer Transcriptome

A Rogue’s Gallery of Malignant Outliers May Hide in Transcriptome Profiles That Emphasize Averages

http://www.genengnews.com/gen-articles/deciphering-the-cancer-transcriptome/5729/

 

The key link between genomic instability and cancer progression is transcriptome dynamics. The shifts in transcriptome dynamics that contribute to cancer evolution may come down to statistical outliers. [iStock/zmeel]

  • In recent years, scientists have adopted a gene-centric view of cancer, a tendency to see each malignant transformation as the consequence of alterations in a discrete number of genes or pathways. These alterations are, fortunately, absent from healthy cells, but they pervert malignant cells.

    The gene-centric view takes in molecular landscapes illuminated by genomic and transcriptomic technologies. For example, genomes can be cost-effectively sequenced within hours. Such capabilities have made it possible to interrogate associations between genotypes and phenotypes for increasing numbers of conditions, and to collect data from progressively larger patient groups.

    As genomic and transcriptomic technologies rise, they reveal much—but much remains hidden, too. Perhaps these technologies are less like the sun and more like the proverbial streetlight, the one that narrows our searches because we’re inclined to stay in the light, even though what we hope to find may lie in the shadows.

    “Each individual study that looks at the cancer transcriptome is impressive and tells a convincing story, but if we put several high-quality papers together, there are very few genes that overlap,” says Henry H. Heng, Ph.D., professor of molecular medicine, genetics, and pathology at Wayne State University. “This shows that something is wrong.”

  • Distinct Karyotypes

    One of the major observations in Dr. Heng’s lab is that the intra- and intertumor cellular heterogeneity results in nearly every cancer cell having a unique, distinct karyotype, that is, an important but often ignored genotype. “Biological systems need a lot of heterogeneity,” notes Dr. Heng. “People like to think that this is noise, but heterogeneity is a fundamental buffer system for biological function to be achievable. Moreover, it is the key agent for cellular adaptation.”

    To capture the degree of genomic heterogeneity at the genome level and its impact on cancer cell growth, Dr. Heng and colleagues performed serial dilutions to isolate single mouse ovarian surface epithelial cells that had undergone spontaneous transformation. Spectral karyotyping revealed that within a short timeframe each of these unstable cells exhibited a very distinct karyotype. In these unstable cells, cloning at the level of the karyotype was not possible.

    Stable cells exhibited a normal growth distribution, i.e., no subset of stable cells contributed disproportionately to the overall growth of the cell population. In contrast, unstable cell populations showed a non-normal growth distribution, with few cells contributing most to the cell population’s growth. For example, a single unstable colony contributed more than 70% to the cell population’s growth. This finding suggests that although average profiles can be used to describe non-transformed cells, they cannot be taken to represent the biology of malignant cells.

    “Most people who study the transcriptome want to get rid of the noise, but the noise is in fact the strategy that cancer uses to be successful,” explains Dr. Heng. “Each individual cancer cell is very weak but together the entity becomes very robust.”

    In a recent model that Dr. Heng and colleagues proposed, system inheritance visualizes chromosomes not merely as the vehicle for transmitting genetic information, but as the genetic network organizer that shapes the physical interactions between genes in the three-dimensional space. Based on this model, individual genes represent parts of the system. The same genes can be reorganized to form different systems, and chromosomal instability becomes more important than the contribution of individual genes and pathways to cancer biology.

    The vital link between genomic instability and cancer progression is transcriptome dynamics, and the shifts in those dynamics that contribute to cancer evolution may come down to statistical outliers.

    “Transcriptome studies rarely focus on single-cell analyses, which means important outliers are frequently ignored,” declares Dr. Heng. “This preoccupation with uninformative averages explains why we have learned so little despite having examined so many transcriptomes.”

  • Chimeras and Fusion Genes

    “Our focus is on chimeric RNA molecules,” says Laising Yen, Ph.D, assistant professor of pathology at Baylor College of Medicine. “This category of RNAs is very special because their sequences come from different genes.”

    In a study that was designed to capture chimeric RNAs in prostate cancer, Dr. Yen and his colleagues performed high-throughput sequencing of the transcriptomes from human prostate cancer samples. “We found far more chimeric RNAs, in terms of abundance, and a number of species that are not seen in normal tissue,” reports Dr. Yen. This approach identified over 2,300 different chimeric RNA species. Some of these chimeras were present in prostate cancer cell lines, but not in primary human prostate epithelium cells, which points toward their relevance in cancer.

    “Most of these chimeric RNAs do not have a genomic counterpart, which means that they could be produced by trans-splicing,” explains Dr. Yen. During trans-splicing, individual RNAs are generated and trans-spliced together as a single RNA, which provides a mechanism for generating a chimera.

    “The other possibility is that in cancer cells, where gene–gene boundaries are known to become broken, chimeras can be formed by cis-splicing from a very long transcript that encodes several neighboring genes located on the same chromosome,” informs Dr. Yen. Chimeric RNAs formed by either of these two mechanisms can potentially translate into fusion proteins, and these aberrant proteins may have oncogenic consequences.

    Another effort in Dr. Yen’s laboratory focuses on chromosomal aberrations in ovarian cancer. One of the hallmarks of ovarian cancer is the high degree of genomic rearrangement and the increased genomic instability.

    “When we looked at ovarian cancers, we did not find as many chimeric RNAs,” notes Dr. Yen. “But we found many fusion genes.” Gene fusions, similarly to chimeric RNAs, increase the diversity of the cellular proteome, which could be used selectively by cancer cells to increase their rates of proliferation, survival, and migration.

    A recent study in Dr. Yen’s lab identified BCAM-AKT2, a recurrent fusion gene that is specific and unique to high-grade serous ovarian cancer. BCAM-AKT2 is the only fusion gene in this malignancy that was proved to be translated into a fusion kinase in patients, which points toward its functional significance and potential therapeutic value.

    “Recurrent fusion genes, which are repeatedly found in many patients in precisely made forms, indicate that there is a reason that they are present,” concludes Dr. Yen. “This might have important therapeutic implications.”

  • Context-Specific Patterns

    “We contributed to a study of tumor gene expresssion that we are currently revisiting because so much more data has become available,” says Barbara Stranger, Ph.D., assistant professor, Institute for Genomics and Systems Biology, University of Chicago. “The data is being processed in homogenized analytic pipelines, and we can look at many more tumor types across the Cancer Genome Atlas than a few years ago.”

    Previously, Dr. Stranger and colleagues performed expression quantitative trait loci (eQTL) analyses to examine mRNA and miRNA expression in breast, colon, kidney, lung, and prostate cancer samples. This approach identified 149 known cancer risk loci, 42 of which were significantly associated with expression of at least one transcript.

    Causal alleles are being prioritized using a fine-mapping strategy that integrated the eQTL analysis with genome-wide DNAseI hypersensitivity profiles obtained from ENCODE data. These analyses are focusing on capturing differences across tumors and on performing comparisons with normal tissue, and one of the challenges is the lack of normal tissue from the same patients.

    “But still there is a lot of power in these analyses because they are based on large-scale genomic datasets. Also, these tumor datasets can be compared with large-scale normal tissue genomics datasets, such as the NIH’s Genotype-Tissue Expression (GTEx) project,” clarifies Dr. Stranger. “This helps us characterize differences between those tumors and normal tissue in terms of the genetics of gene regulation.”

    An ongoing effort in Dr. Stranger’s laboratory involves elucidating how the effect of genetic polymorphisms is shaped by context. Stimulated cellular states, cell-type differences, cellular senescence, and disease are some of the contexts that are known to impact genetic polymorphisms.

    “We have seen a lot of context specificity,” states Dr. Stranger. “Our observations suggest that a genetic polymorphism can have a specific effect in regulating a particular gene or transcript in one context, and another effect in another context.”

    Another example of cellular context is sex, and an active area of investigation in Dr. Stranger’s lab proposes to dissect the manner in which sex differences shape the regulatory effects of genetic polymorphisms.

    “Thinking about sex-specific differences is not very different from thinking about a different cellular environment,” notes Dr. Stranger.

    The expression of specific transcription factors can be determined by sex; consequently, a polymorphism that interacts with a transcription factor may have functional outcomes that can be seen in only one of the sexes.

    “There are gene-level and gene-splicing differences that we see in normal tissues between males and females, and we want to take the same approach and look at the cancer context to see whether the genetic regulation of gene expression and transcript splicing is different between individuals and whether it has a sex bias,” concludes Dr. Stranger. “Finally, we want to see how that differs in cancer relative to normal tissues.”

    Early Clinical Impact

An increasing number of clinicians are adding the cancer transcriptome to their precision medicine program. They have found that the transcriptome is important in identifying clinically impactful results. [iStock/DeoSum]

“Over the last two years,” says Andrew Kung, M.D., Ph.D., chief of the Division of Pediatric Hematology, Oncology, and Stem Cell Transplantation at Columbia University Medical Center, “we have included the cancer transcriptome as part of our precision medicine program.” Dr. Kung and colleagues developed a clinical genomics test that includes whole-exome sequencing of tumors and normal tissue and RNA-seq of the tumor.

“Our results show that the transcriptome is very important in identifying clinically impactful results,” asserts Dr. Kung. “The technology has really moved from a research tool to real clinical application.” In fact, the test has been approved by New York State for use in cancer patients.

The data from transcriptome profiling has enabled identification of translocations, verification of somatic alterations, and assessment of expression levels of cancer genes.  Dr. Kung and his colleagues are using genomic information for initial diagnosis and prognostic decisions, as well as the investigation of potentially actionable alterations and the monitoring of disease response.

To gain insight into gene-expression changes, transcriptome analysis usually compares two different types of tissues or cells. For example, analyses may attempt to identify differentially expressed genes in cancer cells and normal cells.

“In patients with cancer, we usually do not have access to the normal cell of origin, making it harder to identify the genes that are over- or under-expressed,” explains Dr. Kung. “Fortunately, the vast amounts of existing gene-expression data allow us to identify genes whose expression are most changed relative to models built on the expression data aggregated across large existing datasets.”

These genomic technologies were first used to augment the care of pediatric patients at Columbia. The technologies were so successful that they attracted philanthropic funding, which is being used to expand access to genomic testing to all children with high-risk cancer across New York City.

Other related articles published in this Open Access Online Scientific Journal include the following:

Immunotherapy in Combination, 2016 MassBio Annual Meeting  03/31/2016 8:00 AM – 04/01/2016 3:00 PM Royal Sonesta Hotel, Cambridge, MA

Live Press Coverage: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2016/04/01/plenary-session-immunotherapy-in-combination-2016-massbio-annual-meeting-03312016-800-am-04012016-300-pm-royal-sonesta-hotel-cambridge-ma/

 

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