Abstract A051: A comprehensive, highly accurate genomics platform for precision immunotherapy: Simultaneously characterize tumors and the TME from a single FFPE sample

• Published in: Molecular cancer therapeutics 2019-12, Vol.18 (12_Supplement), p.A051-A051
• Main Authors: Power, Robert, Bartha, Gabor, Harris, Jason, Boyle, Sean Michael, Levy, Eric, Milani, Pamela, Tandon, Prateek, Li, Robin, Chinnappa, Manjula, McNitt, Paul, McClory, Rena, Morra, Massimo, Saldivar, Sebastian, Clark, Michael, Haudenschild, Christian, Newburn, Erin, Johnson, Christelle, West, John
• Format: Article
• Language: English
• ISSN: 1535-7163; 1538-8514
• DOI: 10.1158/1535-7163.TARG-19-A051

Immunogenomic profiling of the tumor and the tumor microenvironment (TME) is critical for identifying new biomarkers of immunotherapy response, understanding resistance, and enabling the development of personalized immunotherapies. However, running a comprehensive array of biomarker assays for each patient sample is often impractical given limited sample quantity, processing complexity, and prohibitive cost. To address these challenges, we developed a novel, augmented exome and transcriptome-based platform that simultaneously characterizes the tumor and TME from a single FFPE sample. We co-optimized the design of our sequencing assays and analytics to increase performance for the detection of somatic SNVs, indels, CNAs, and fusions across ~20,000 genes, as well as the evaluation of neoantigens, expression signatures, HLA typing and LOH, TCR/BCR repertoires, oncoviruses, tumor-infiltrating lymphocytes (TILs), clinically-actionable mutations, tumor mutational burden (TMB), and MSI status. We developed novel methods to sequence difficult regions of the exome and to extend coverage to key immunogenomic biomarkers. Analytic pipelines were designed to utilize assay optimizations to achieve higher accuracy than with other platforms. We then validated the platform for diagnostic and therapeutic use. With as little as 50ng of DNA per FFPE sample and co-extracted RNA, this platform completely covers between 17% to 40% more genes compared to a non-augmented exome, thus increasing sensitivity to somatic mutations and putative neoantigens. For neoantigen performance, we generated immune-peptidomic data from mono-allelic HLA transfected cell-lines and trained neural networks to predict neoepitope binding to MHC, demonstrating a higher precision (0.88) across alleles than publicly available tools (0.9 and >0.94, respectively). For TILs, we developed signatures for CD4, CD8 T-cells, and other immune cells, demonstrating concordance with synthetic and CyTOF-derived validation sets. For HLA typing, we achieve an accuracy of 99.1% for HLA Class I, and 95% for HLA Class II typing calls, and have developed a novel tool for HLA LOH detection. We demonstrate sensitive detection of HPV, EBV, HCV, HTLV, and KSHV in known samples, and accurate MSI and TMB assessment. Finally, for diagnostic reporting, we achieve high sensitivity and spec