Identification of Platelet-related Genes and Immune Cells in Hepatocellular Carcinoma

Abstract

Background: Platelet activity plays a crucial role in the development of hepatocellular carcinoma (HCC). Objectives: This study aimed to investigate the prognostic role of platelet-related genes (PRGs) in HCC. Methods: This retrospective bioinformatics study used publicly available transcriptomic and clinical datasets. Differential expression analysis, weighted gene coexpression network analysis, Cox regression, and least absolute shrinkage and selection operator regression were used to identify optimal differentially expressed platelet-related genes associated with HCC in the The Cancer Genome Atlas (TCGA) cohort, using a curated PRG set. A risk score model was then constructed, and a nomogram integrating the risk score and independent prognostic factors was developed. Finally, differences in immune cell infiltration between risk groups were examined, and PRG-related pharmaceutical agents were explored. Results: Six signature genes (ABCC4, CD109, IGF1, GNG4, SPP2, and GNA14) were identified and used to establish a risk-score model. The model distinguished high-risk from low-risk patients in the training set (area under the curve = 0.776) and the validation set (area under the curve = 0.764). The high-risk group had significantly poorer overall survival (hazard ratio [HR] = 2.271; 95% CI, 1.580 - 3.262; log-rank P = 5.18 × 10-6). Multivariable Cox regression identified age, pathologic stage, and risk score (HR = 1.849; 95% CI, 1.249 - 2.736; P = 2.13 × 10-3) as independent prognostic factors. The nomogram showed good predictive performance for 1-, 3-, and 5-year survival (concordance index = 0.731, 0.780, and 0.789, respectively). Immune analysis revealed significant differences in 9 immune cell types between the high-risk and low-risk groups, and drug network analysis identified associations with 25 small-molecule drugs. Conclusions: A PRG-based prognostic classifier was developed to estimate clinical outcomes in patients with HCC. Because no treatment-response analysis was performed, the value of this classifier in guiding individualized therapy remains to be established.