Establishment of nucleic acid sensing pathways-based model in predicting response to immunotherapy and targeted drug in hepatitis virus-related hepatocellular carcinoma.

Abstract

Hepatocellular carcinoma (HCC) accounts for 80% of liver cancers, while 70%-80% of HCC developed from chronic liver disease with hepatitis B virus (HBV) and hepatitis C virus (HCV) infection as the major etiology. Immunotherapy is assuming a role as a pillar of HCC treatment, but the remarkable immune-mediated responses are restricted in a minority of patients. Nucleic acid sensing (NAS) pathways are the central pathway of the innate immune system and antiviral immune response to viral infection, but their role in hepatitis virus-related HCC remains undetermined. In our study, we performed a comprehensive bioinformatics analysis based on transcriptomic data of hepatitis virus related-HCCtissues collected from multiple public data sets. Two subgroups were validated based on NAS-relatedgenes in virus-related HCC patients, which were defined as NAS-activatedsubgroups and NAS-suppressed subgroups based on the expression of NAS-related genes. On this basis, a NAS-related risk score (NASRS) predictive model was established for risk stratification and prognosis prediction in the hepatitis virus-related HCC (TCGA-LIHCand ICGC cohorts). The predictive values of the NASRS in prognosis and immunotherapy were also verified in multiple data sets. A nomogram was also established to facilitate the clinical use of NASRS and demonstrate its effectiveness through different approaches. Additionally, six potential drugs binding to the core target of the NAS signature were predicted via molecular docking strategy. We subsequently evaluated the cytotoxic capabilities of potential drug in vitro and in vivo. Based on these results, we conclude that the NASRS model could serve as a power prognostic biomarker and predict responses to immunotherapy, which is meaningful in clinical decision-making of hepatitis virus-related HCC patients.