Risk assessment of cancer patients based on HLA-I alleles, neobinders and expression of cytokines

Advancements in cancer immunotherapy have shown significant outcomes in treating various types of cancers. In order to design effective immunotherapy, it is important to understand immune response of a patient based on its genomic profile. We compute prognostic biomarkers from 8346 cancer patients for twenty types of cancer. These prognostic biomarkers has been computed based on i) presence of 352 human leucocyte antigen class-I (HLA-I), ii) 660959 tumor-specific HLA1 neobinders and iii) expression profile of 153 cytokines. It was observed that survival risk of cancer patients depends on presence of certain type of HLA-I alleles; for example LIHC cancer patients with HLA-A*03:01 are on lower risk. Our analysis indicate that neobinders of HLA-I alleles have high correlation with overall survival of certain type of cancer patients. For example HLA-B*07:02 binders have 0.49 correlation with survival of LUSC and −0.77 with KICH cancer patients. It is clear from above analysis that HLA and their binders have major role in survival of cancer patients suffering from different types of cancer. In addition, we compute prognostic biomarkers for 20 types of cancer based on each type of cytokine expression. Higher expression of few cytokines is survival favourable like IL-2 for BLCA cancer patients whereas IL-5R survival unfavourable for KICH cancer patients. In order to facilitate scientific community we developed a web-based platform CancerHLA1 that maintain raw and analyzed data ( https://webs.iiitd.edu.in/raghava/cancerhla1/ ).