Abstract
BACKGROUND: Hepatocellular carcinoma (HCC) is a prevalent and highly aggressive malignancy. Phagocytic regulatory factors (PRFs) play a crucial role in regulating the progression of HCC. This study aimed to investigate the prognostic and immunological features of HCC based on phagocytic regulatory factor-related genes (PFRGs). METHODS: The single-sample gene set enrichment analysis (ssGSEA) was employed to evaluate the enrichment scores of PFRGs in the The Cancer Genome Atlas (TCGA)-Liver Hepatocellular Carcinoma (LIHC) cohort. Univariate, least absolute shrinkage and selection operator (LASSO), and multivariate regression analyses were conducted to identify prognostic feature genes. The prognostic performance of the risk model was evaluated using receiver operating characteristic (ROC) curves, and Kaplan-Meier (K-M) curves were utilized to assess the overall survival probability of patients in each risk group. The ssGSEA and CIBERSORT algorithms were applied to examine immune landscape infiltration in HCC, while the CellMiner database was used to identify anti-tumor drugs significantly correlated with signature gene. RESULTS: We identified nine prognostic feature genes, namely CD5L, SLA2, FLT3, GPR18, BCL11B, CTSV, UBASH3A, XCR1, and KLRK1. The K-M curve showed that those in the low-risk bracket tended to have a better survival outcome. Additionally, the low-risk group exhibited significantly higher levels of immune cell infiltration increased expression of immune checkpoint genes. Regarding treatment, Belinostat, Dabrafenib, and Sorafenib showed higher sensitivity in the low-risk group, whereas Docetaxel demonstrated greater sensitivity in the high-risk category. CONCLUSIONS: This study offers a comprehensive analysis of the immune landscape characteristics and potential anticancer drugs in HCC based on PFRGs, providing valuable insights and novel perspectives for the treatment of HCC patients.