Abstract 5291: OncoMD: A powerful genomics data analysis and interpretation platform for cancer discovery research

Abstract

Abstract Cancer cells gain fitness advantage over normal cells by accumulating mutations over time. Next Generation DNA sequencing technologies have made the detection of genetic alterations in tumor genomes affordable. Powerful data analysis and interpretation tools enable extraction of disease-relevant information from diverse genomics data to guide diagnosis and treatment decisions. We have built a robust cancer analytics platform OncoMD that combines tumor mutation profiles, expression signatures, copy number variations, epigenetic alterations and drug sensitivity to create a holistic view of human cancer enabling discovery of new targets for therapy and prognosis. We have analyzed the rich mutational data captured in OncoMD to identify potential T-cell neo-epitopes in different cancers and examined their prevalence in the context of the tumor microenvironment. The presence of T-cell neo-epitopes alone is not sufficient to sensitize tumors to immunotherapy drugs and requires cooperation from the tumor microenvironment. Although mutational burden was a strong predictor of T-cell neo-epitopes in our analysis, other genetic alterations such as overexpression, splicing, gene-fusions and insertions/deletions can produce altered peptides exhibiting high affinity binding to HLA class I and II molecules in cancers with low burden of missense mutations. We determined the number of potential T-cell neo-epitopes after classifying tumors based on their epithelial, stromal and immune cell content using gene expression signatures. We observed that the normalized T-cell neo-epitope burden was strongly anti-correlated with the T-cell content of the tumors, compared to their epithelial or stromal content. Together, our findings suggest that tumors enriched in T-cells may be subjected to immunoediting processes and carry relatively fewer T-cell neo-epitopes to avoid elimination. These tumors are likely to respond to immunotherapy treatments. Citation Format: Ravi Gupta, Kiran V. Paul, Kartik Kumaramangalam, Sam Santhosh, Amitabha Chaudhuri. OncoMD: A powerful genomics data analysis and interpretation platform for cancer discovery research. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 5291.