Abstract 3946: Stratification of metastatic colorectal cancer patients using DNA and RNA sequencing and in-silico prediction of tumor antigens for consideration in immunotherapy

Colorectal cancer (CRC) is the third most common type of cancer in the United States. Although chemotherapy, radiation and targeted therapies can improve survival rates, recent studies have shown the potential benefit of immunotherapies to improve outcomes for patients with advanced CRC. Targeted therapies that use monoclonal antibodies (mAbs) to EGFR have been shown to benefit some CRC patients. Until recently, KRAS has been the only predictive biomarker for anti-EGFR therapy for metastatic CRC. However, 40% to 60% of patients with wild-type KRAS do not respond to anti-EGFR therapy. Therefore, to accurately predict patients’ response to treatments and improve clinical outcomes, additional prediction and treatment methods are imperative. One of the many efforts to improve prediction for CRC patient9s response to the anti-EGFR therapy is the development of gene expression based RAS signature scores for identification of RAS activated tumors independent of mutations in the KRAS gene. Recently there have been major advances in immunotherapeutic approaches in a wide variety of cancers. In solid tumors such as melanoma and colon cancers, immune checkpoints have been shown to improve clinical outcomes. There is considerable effort being placed on combinations of targeted therapy and immunotherapies to improve responses for these cancers. Similarly, since no single treatment can apply to all CRC patients, we aim to stratify patients using a combination of three methods: 1. RAS signature score based on the expression profile of 18 genes. This RAS signature score enables measurements of mitogen-activated protein/extracellular signal-regulated kinase (MEK) pathway functional output independent of tumor genotype. 2. Expression profile of immune checkpoint inhibitor target genes, such as PD1 and PDL1, and 3. In-silico prediction of neo-antigens and peptide binding affinity between tumor antigens derived from mutations and human HLA alleles. 55 FFPE samples were selected from a cohort of 468 samples with matching FF samples. These 55 samples have about 1:1:1 ratio of high, medium and low RAS scores. Here we showed our ability to obtain RAS signature scores with concordant results using different platforms including RNA-seq, targeted RNA-seq, Nanostring and Affymetrix microarray. Samples that have RAS activating mutations such as KRAS and BRAF have significant higher RAS scores (p Citation Format: FangYin Lo, Sharon Austin, Kellie Howard, Mollie McWhorter, Heather Collins, Amanda Leonti, Lindsey Maassel, Christopher Subia, Tuuli Saloranta, Nicole Christopherson, Kathryn Shiji, Shradha Patil, Saman Tahir, Sally Dow, Evan Anderson, Jon Oblad, Kerry Deutsch, Timothy Yeatman, Steven Anderson, Anup Madan. Stratification of metastatic colorectal cancer patients using DNA and RNA sequencing and in-silico prediction of tumor antigens for consideration in immunotherapy. [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 3946.