Identification of tumor antigens and anoikis-based molecular subtypes in the hepatocellular carcinoma immune microenvironment: implications for mRNA vaccine development and precision treatment

Abstract Hepatocellular carcinoma (HCC) represents a formidable malignancy with high lethality. Nonetheless, the development of vaccine and establishment prognostic models for precise personalized treatment HCC still encounter big challenges. Thus, aim this study was to develop vaccines explore anoikis-based based on RNA sequencing data in GEO datasets (GSE10143, GSE76427) TCGA-LIHC cohort. Potential antigens were identified using GEPIA2, cBioPortal, TIMER2. Anoikis-related subtypes gene clusters defined by consensus clustering 566 liver cancer samples 28 anoikis regulators, we further analyzed their relationship immune microenvironment HCC. A predictive model anoikis-related long noncoding RNAs (lncRNAs) developed accurately predict prognosis. Seven overexpressed genes associated prognosis tumor-infiltrating antigen-presenting cells as potential tumor mRNA vaccines. Two (ARGs) two different characteristics validated cohorts. The between showed cell infiltration molecular characteristics. Furthermore, score seven lncRNAs LASSO regression constructed, low-risk group having favorable prognosis, “hot” microenvironment, better response immunotherapy. CCNB1, CDK1, DNASE1L3, KPNA2, PRC1, PTTG, UBE2S first promising Besides, innovatively propose subtypes, which not only enable stratification patients but also provide blueprint identifying optimal candidates vaccines, enhancing immunotherapeutic strategies.