Abstract
Hepatocellular carcinoma (HCC) is a global health challenge with an increasing incidence worldwide. Cancer-associated fibroblasts (CAFs) function critically in HCC initiation and development. However, the prognostic significance of CAF-related gene signatures in HCC remains unknown. Therefore, the specific functions of CAF-related genes in HCC were investigated to help develop potential therapeutic strategies. In this study, CAF-related genes were screened from three CAF-related gene sets. HCC data from the Gene Expression Omnibus (GEO) database was applied to verify the screened CAF-related genes. Cluster analysis was used to identify clusters based on the expression pattern of CAF-related genes and two identified clusters were found to have a significant difference in overall survival (OS) and progression free intervals (PFI). The prognosis of HCC patients was predicted using the prognostic risk score model developed based on HCC data from The Cancer Genome Atlas (TCGA) databases. High-risk group patients had a worse OS than those in low-risk group in TCGA. These results were validated in International Cancer Genome Consortium (ICGC) database. Moreover, combining the clinicopathological characteristics related to prognosis with the model, a nomogram was built for a more accurate prediction of OS of HCC patients. In addition, analyses of immune infiltration characteristics of tumor microenvironment (TME), chemosensitivity, and immunotherapy response were conducted to further evaluate the prognostic value of CAF-related genes. Patients with low-risk scores were found to have higher chemosensitivity to cisplatin, doxorubicin, and sorafenib. Individuals with high-risk scores were found with a higher expression of most immune checkpoints which indicated patients with high-risk scores may benefit more from treatment with immune checkpoint inhibitors. Furthermore, a correlation between immune infiltration characteristics of TME and patients with different risk levels was found. These findings provide a possibility for the further development of personalized treatments in HCC.