Abstract 2512: Pan-cancer characterization of the tumor and immune microenvironment facilitates identification of cancer-specific biological signatures
Authors: Boyle Sean Michael , Abbott Charles , Levy Eric , Pyke Rachel Marty , Mellacheruvu Dattatreya , Zhang Simo , Tan Mengyao , McClory Rena , West John , Chen Richard 
Published: September 2020

Background: A better understanding of the characteristics of cancer across different indications is required to drive the development of personalized treatments, inform therapy decisions, and improve outcomes. Integrating data from the tumor and the immune system can enable the identification of comprehensive biological signatures and composite biomarkers for the improved stratification of responders/progressors. Here, we describe a pan cancer study, including an enhanced whole-exome and transcriptome sequencing approach, across over 500 samples representing 13 tumor types, analyzed at high depth using the ImmunoID NeXT platform.

Methods: We sequenced paired tumor-normal samples on the ImmunoID NeXT platform, an enhanced exome/transcriptome-based diagnostic platform that can simultaneously profile the tumor and immune microenvironment from a single FFPE sample, across all of the approximately 20,000 genes. For each sample, we analyzed a broad set of features focused on both the tumor and immune system. From DNA, we profiled small variants, CNAs, MSI status, oncoviruses, HLA LOH, and neoantigens. From RNA, we profiled gene expression, small variants, fusions, TILs, TCR, BCR, and immune signatures. Integrated analyses assessing the impact of each feature, both within and across tumor types, were performed across the cohort.

Results: Through immunogenomic analysis we identified striking differences in both tumor and TME profiles across cancer types. In addition to mutation and neoantigen burden, by. we also computed a composite neoantigen score for each sample, which we have shown in a separate melanoma study can be a stronger predictor of response to immunotherapy. The composite neoantigen score integrates neoantigen prediction with mechanisms of tumor escape that can affect neoantigen presentation, providing a more accurate model of the antigen presentation biology. We also looked at the distribution of HLA LOH using our DASH algorithm and found differences in LOH frequency between tumor types. For example, we found HLA LOH to be five timesmore common in lung cancer than breast cancer. Further, we profiled immune gene signatures, including Gejewski and Ribas signatures, highlighting varied immune activation across cancer types. Analysis of somatic alterations in pathways controlling cell growth, PI3K/AKT signaling, apoptosis, and other canonical pathways revealed malignancy-specific alteration frequencies. The varying frequency, and combination of these alterations is indicative of a complex hierarchy of cross-talk between pathways, which operates in a cancer specific manner.

Conclusions: We performed a broad integrated analysis of the tumor and immune microenvironment for over 500 samples across 13 different tumor types using the ImmunoID NeXT platform. This comprehensive profiling revealed significant differences between cancer types beyond mutational burden, including neoantigen burden, immune microenvironment differences, and incidence of putative tumor escape mechanisms

Citation Format: Sean Michael Boyle, Charles Abbott, Eric Levy, Rachel Marty Pyke, Dattatreya Mellacheruvu, Simo Zhang, Mengyao Tan, Rena McClory, John West, Richard Chen. Pan-cancer characterization of the tumor and immune microenvironment facilitates identification of cancer-specific biological signatures [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2512.