Abstract
Abstract With the rapid advancement of immune therapy on cancer treatment, there is an increasing demand for accurate and comprehensive profile of tumor immunogenomics landscape in order to broaden our knowledge on predicting patient response as well as to facilitate drug development process. We established a cloud based analytical platform to comprehensively characterize genomic features that are potentially related to patients’ responses to immunotherapy. We implemented a neoantigen prediction pipeline based on whole exome sequencing (WES) and transcriptome sequencing data that integrates accurate HLA typing based on WES, somatic variant detection/phasing, RNA expression, class I MHC binding prediction as well as peptide epitope ranking. Among that, the HLA typing pipeline was validated using 73 Chinese and Japanese subjects covering >60 known class I HLA alleles with an accuracy above 95%. In addition, we also developed and validated methods to compute microsatellite instability (MSI) and tumor mutation burden (TMB) based on either a 600 gene panel or WES. Thirdly, this platform also enables the detection of HLA somatic variants and loss of heterozygosity events based on WES data. Next, we applied this analysis platform to process 127 samples across four cancer types (colon, rectal, endometrial and gastric) from TCGA as well as two Chinese cohorts of 100 non-small cell lung cancers and 30 esophageal squamous cell carcinomas sequenced at WuXi NextCODE. Within the TCGA cohort, the data reveals that patients with MSI High status produces significantly more neoantigens than patients with MS Stable status (7.06±4.60 vs 0.71±0.64, p = 7.65e-16, neo-peptides per Mb). Number of neopeptides predicted from each frameshift event is significantly higher than that from each missense mutation (1.30±1.56 vs 0.58±0.54, p = 2.86e-11, neo-peptides per Mb). We also observed strong correlation between TMB and neoantigen burden across multiple cancer types. In conclusion, we have developed a immunogenomics solution that captures tumors’ TMB, MSI, neoantigen as well as deleterious events associated with their HLAs. This platform will allow more comprehensive molecular features assessed to potentially improve the prediction of patients’ response to immune therapy. Citation Format: Jie Wang, Ao Li, Jiawei Wang, Zhaoze Cheng. A comprehensive immunogenomics profiling platform enables the exploration of the intricate relationship between TMB, MSI, Neoantigen and HLA status among multiple cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 754.
Published Version
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