Developing And Verifying A Necroptic Gene-Based Prognostic Index In Patients With Hepatocellular Carcinoma

Abstract Hepatocellular carcinoma (HCC) is the sixth leading cancer throughout the world and ranks fourth in cancer mortality. Necroptosis modulates tumorigenesis, metastasis, and treatment resistance. However, gene sets related to necroptosis in HCC are rarely analyzed. Hence, it is vital to assess the clinicopathological influence of necroptosis in a large HCC patient population. Our goal in this research was to develop a novel HCC prognostic indicator based on necroptosis. To that end, we examined 132 necroptosis related genes (NRGs) and recognized 36 differentially expressed NRGs (DE-NRGs) in the Cancer Genome Atlas (TCGA) cohort. Using both uni- and multivariate Cox regression models, we selected 4 NRGs, which can be employed to categorize HCC cases into low- or high-risk groups. Based on our survival analysis, the overall survival (OS) duration of high-risk cases was markedly shorter, in comparison with low-risk cases. We also verified using COX regression analysis that NRGs can serve as stand-alone prognostic indicators of HCC prognosis. Moreover, the area under the curve (AUC) of the combined prediction model was 0.807. Lastly, we also verified the validity of our model using the Gene Expression Omnibus (GEO) dataset. In summary, a state-of-the-art NRG-based HCC prognostic indicator is established to accurately predict the outcome of HCC cases to aid clinicians in the efficient planning and designing of personalized anti-HCC therapy.