Liver hepatocellular carcinoma (LIHC) is a primary malignancy, and there is a lack of effective treatment for advanced patients. Although numerous studies exist to reveal the carcinogenic mechanism of LIHC, few studies have integrated multi-omics data to systematically analyze pathogenesis and reveal potential therapeutic targets. Here, we integrated genomic variation data and RNA-seq profiles obtained by high-throughput sequencing to define high- and low-genomic instability samples. The mutational landscape was reported, and the advanced patients of LIHC were characterized by high-genomic instability. We found that the tumor microenvironment underwent metabolic reprograming driven by mutations accumulate to satisfy tumor proliferation and invasion. Further, the co-expression network identifies three mutant long non-coding RNAs as potential therapeutic targets, which can promote tumor progression by participating in specific carcinogenic mechanisms. Then, five potential prognostic markers (RP11-502I4.3, SPINK5, CHRM3, SLC5A12, and RP11-467L13.7) were identified by examining the association of genes and patient survival. By characterizing the immune landscape of LIHC, loss of immunogenicity was revealed as a key factor of immune checkpoint suppression. Macrophages were found to be significantly associated with patient risk scores, and high levels of macrophages accelerated patient mortality. In summary, the mutation-driven mechanism and immune landscape of LIHC revealed by this study will serve precision medicine.
S1159 Identification of Three Up-Regulated Hub Genes as Potential Diagnostic Markers, Prognostic Markers, and Therapeutic Targets in Hepatocellular Carcinoma by Integrated Bioinformatic Analysis
