Landscape of oncoviral genotype and co-infection via Human papilloma and Hepatitis B viral tumor in-situ profiling

Hepatitis B virus (HBV) and human papillomavirus (HPV) infection are known risk factors for developing several cancers. However, the effect of viral genotype and co-infection in actually driving oncogenesis remains unclear. We have developed and deployed a new scalable, high throughput tool (ViralMine) for sensitive and precise oncoviral genotype deconvolution using tumor RNA sequencing data from 537 virally infected liver, cervical, and head and neck tumors. We provide the first comprehensive integrative landscape of tumor-viral gene expression, viral antigen immunogenicity, patient survival, and mutational profiling organized by tumor onco-viral genotype. We find that HBV and HPV genotype, and surprisingly high rates of multi-genotype co-infection, serve as significant predictors of patient survival, tumor immune responsiveness, and APOBEC activity modulation. Finally, we demonstrate that HPV genotype strongly associates with viral onco-gene expression over cancer type, implying expression may be similar across episomal and stochastic integration-based infections. Significance Statement We demonstrate that scalable, high-accuracy oncoviral genotyping, gene expression, and co-infection estimation is feasible from legacy tumor RNA-seq data. While HBV and HPV genotype are known risk factors for oncogenesis, viral genotype and co-infection are shown to strongly associate with disease progression, patient survival, mutational signatures, and putative tumor neoantigen immunogenicity, facilitating novel clinical associations with infections.