Hepatocellular carcinoma (HCC) is a primary malignancy with increasing incidence and poor prognosis. Heterogeneity originating from genomic instability is one of the critical reasons of poor outcomes. However, the studies of underlying mechanisms and pathways affected by mutations are still not intelligible. Currently, integrative molecular-level studies using multiomics approaches enable comprehensive analysis for cancers, which is pivotal for personalized therapy and mortality reduction. In this study, genomic and transcriptomic data of HCC are obtained from The Cancer Genome Atlas (TCGA) to investigate the affected coding and non-coding RNAs, as well as their regulatory network due to certain mutational signatures of HCC. Different types of RNAs have their specific enriched biological functions in mutational signature-specific HCCs, upregulated coding RNAs are predominantly associated with lipid metabolism-related pathways, and downregulated coding RNAs are enriched in axonogenesis for tumor microenvironment generation. Additionally, differentially expressed miRNAs are inclined to concentrate in cancer-related signaling pathways. Some of these RNAs also serve as prognostic factors that help predict the survival outcome of HCCs with certain mutational signatures. Furthermore, deregulation of competing endogenous RNA (ceRNA) regulatory network is identified, which suggests a potential therapy via interference of miRNA activity for mutational signature-specific HCC. This study proposes a projection approach to reduce therapeutic complexity from genomic mutations to transcriptomic alterations. Through this method, we identify genes and pathways critical for mutational signature-specific HCC and further discover a series of prognostic markers indicating patient survival outcome.