Identification and validation of mitochondrial oxidative stress- related prognostic signature with clinical characters and immune filtration in liver hepatocellular carcinoma

Abstract Background Mitochondrial oxidative stress has been shown to play a critical role in cancer development and progression. But there was relatively less research on the relationship between mitochondrial oxidative stress and LIHC. Methods Mitochondrial oxidative stress-related genes were collected from Genecards portals. Prognosis-linked genes (PLGs) were identified by univariate Cox regression analysis. A risk model was constructed based on PLGs using the least absolute shrinkage and selection operator (LASSO) analysis. The receiver operational feature (ROC) curve was used to detect the model’s prediction ability. The gene expression level of prognostic genes were verified in cell lines. Results We constructed a novel risk model on the basis of 9 prognostic genes (CYP2C19, CASQ2, LPL, TXNRD1, CACNA1S, SLC6A3, OXTR, BIRC5, and MMP1). The Kaplan-Meier survival analysis showed that patients with a low-risk score had a much better overall survival (OS) rate than those with a high-risk score. The prognostic risk score was determined to be an independent predictor of prognosis. Patients in the high-risk group had a less favorable tumor microenvironment, characterized by a lower degree of immune cell infiltration. In contrast, the low-risk group demonstrated a higher degree of immune cell infiltration, which could potentially contribute to a more effective anti-tumor immune response. Conclusion Our investigation uncovered the oncogenic role of mitochondrial oxidative stress in LIHC. For the first time, we established a risk prediction model for mitochondrial oxidative stress in LIHC.