Friday November 30

West Coast Day 3

Immune Profiling

Immune Profiling in Cancer

Funding Sources


Single cell functionality serves as a predictive biomarker for overall survival of pancreatic cancer patients treated with GVAX vaccine

  • Polyfunctional Strength – the secretion of two more cytokines per cell, where the cytokine secretion intensity is tied to the cell which produced it, is a more accurate predictor of clinical outcome than flow cytometry, bulk protein analysis or gene array.
  • Single Cell Functionality has correlated with Objective Response across IO: CAR-T, Checkpoint Inhibitors and Cancer Vaccines
  • Polyfunctionality of CD4+ T-cells is a predictor of Overall Survival of patients treated with the GVAX Vaccine where post- versus pre-vaccination fold-change of the polyfunctional strength index was associated with patient overall survival (P = 0.001).
Vaccine Development

FluoroSpot analysis of immune memory against malaria vaccine candidate antigens

  • Benefits and possibilities of the FluoroSpot assay in vaccine research
  • Studying the kinetics of malaria-specific B-cells after infection
  • Analysis of B cell cross-reactivity against polymorphic malaria antigen MSP-2
  • What the future might hold for the FluoroSpot assay

An integrated machine-learning approach for improved prediction of clinically relevant neoantigens

  • Current neoantigen discovery algorithms are not optimal to predict presentation to the cell surface.
  • Here, we outline a high-performing machine learning approach, trained on mass-spectrometry data, that predicts naturally processed and presented antigens.
  • The predictor is integrated with several immune parameters, such as HLA binding, in a deep learning layer to predict bone fide neoantigens.
  • We illustrate its application to significantly improve the identification of neoantigen targets for personalized cancer immunotherapy

A Rational Systematic Approach to Find Combinations of Pharmacologic and Immune Therapies that Target Identifiable Oncogenic States

  • Defining oncogenic states
  • Selecting 5-10 oncogenic states and identifying state-specific immunological targets, including immune checkpoints, neoantigens/anti-tumor epitopes, antibodies, and chimeric antigen receptors
  • Developing a multifactorial predictive model for eachoncogenic state to identify the most effective combinations
  • Validation of these perturbagens in isogenic cell systems, cancer cell lines, genetically engineered mouse models, and patient-derived xenografts
  • Insight into the development of novel treatment strategies

Morning Networking Break & Poster Session

Vaccine Development

The impact of immune experience on responses to infection and vaccination

  • Microbial experience alters the mouse immune system to more closely reflect the human immune system in a number of important ways
  • With microbial experience, the T cell pool is largely represented by cells of an effector/memory phenotype
  • Increasing immune experience confers a protective advantage against some infections, but not others
  • T cell directed vaccines or 'weak' priming methods are less effective after immune experience

Networking Lunch & Poster Session

DAY 3 Plenary – The future of vaccine and immunotherapy development

Panel discussion
Panel discussion

Leveraging the power of AI & machine learning for accelerated vaccine & immunotherapy development

  • Applications of machine learning and predictive modeling
  • Using machine learning techniques to decipher the human microbiome
  • The increasing complexity of genomic data
  • How can we translate the success seen in precision medicine to chronic diseases?
  • Connecting deep phenotyping to genetics
  • Examples of collaborations and exciting new technologies.

Chair’s Closing Remarks & End of Congress

last published: 22/Nov/18 11:45 GMT



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Contact us

To sponsor or exhibit contact:
Oliver Breed
+44 (0)207 092 1156

To speak:
Lauren Sheppard
+44 (0)207 092 1211