Table 2 Immune Profiling and Data Sharing Projects Presented at the SITC Workshop
From: SITC 2018 workshop report: Immuno-Oncology Biomarkers: State of the Art
Name of Project | Institution | Approach |
|---|---|---|
Tumor Neoantigen Selection Alliance (TESLA) | Parker Institute for Cancer Immunotherapy | Support efforts to develop safe and effective neoantigen vaccines through effective neo-epitope prediction algorithms and high-quality epitope validation sets. |
MANAFEST | Johns Hopkins Bloomberg-Kimmel Institute for Cancer Immunotherapy | An assay that combines whole exome sequencing, T cell receptor sequencing, and bioinformatics to identify targetable mutation-associated neoantigens. |
APOLLO | MD Anderson Cancer Center | Biomarker discovery by analyzing tissue samples collected during pre-treatment, treatment and progression. |
ECOG 1608 Biomarker project | Sidra Medicine Doha and ECOG-ACRIN | Combination of cellular immune monitoring assays, in vitro stimulation, protein profiling, genotyping, and transcriptomic analysis of PBMCs to estimate the proportion and functional orientation of immune cell subtypes. |
Immunoscore/Immunoprofiling | Society for Immunotherapy of Cancer (SITC) | Objectively measure tumor immune infiltrates using digital imaging technology to demonstrate correlations with patient prognosis. Develop standards for next generation multiplex assays. |
IBEX (Iterative Bleaching Extends Multi-pleXity) | National Institutes of Health | An iterative staining method detecting more than 40 protein markers to highlight immune-tumor interactions. |
Peptide MHC tetramer staining | Agency for Science, Technology and Research | To identify antigen-specific T cells while preserving phenotypic profiles, and without requiring in vitro expansion. |
Multiplexed ion beam imaging (MIBI) | Stanford University | Determine what cell phenotypes are present in a sample, how the discovered phenotypes are spatially distributed relative to one another, and how identified phenotypes are related to a disease state. |
1000 Immunomes Project (1KIP) | Stanford University | A systems biology approach to the discovery of biomarkers associated with systemic chronic inflammation. |
Neoantigen Fitness Model | Icahn School of Medicine | A mechanistic model representing the process of immune cell neoantigen recognition to predict tumor response to therapy. |
imCORE global network | Genentech | Centralized testing of samples for data quality monitoring and public access to standardized clinical trial data. |
Project GENIE (Genomics Evidence Neoplasia Information Exchange) | American Association for Cancer Research (AACR) | An international cancer registry that links clinical genotypes to patient outcomes. |
Oncology Research Information Exchange Network (ORIEN) | M2Gen | A cancer center alliance based on the common use of the Total Cancer Care (TCC) protocol to accelerate cancer discovery through collaborative learning, partnership and data sharing. |
Sparkathon Project TimIOs | Society for Immunotherapy of Cancer (SITC) | Cross-study analysis of patient response to help further the understanding of tumor heterogeneity in treating patients with immunotherapy. |