ArticleTranslational cancer research2025
Establishment of a prognostic model and immune profiling based on phagocytic regulatory genes in hepatocellular carcinoma.
Article in Translational cancer research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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 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.
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