Identification of CAF signature genes and construction of CAF-based risk signature in hepatocellular carcinoma by multi-omics analysis.

通过多组学分析鉴定肝细胞癌 CAF 特征基因并构建基于 CAF 的风险特征。

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BACKGROUND: Cancer-associated fibroblasts (CAFs) play a critical role in hepatocellular carcinoma (HCC) progression. This study aimed to develop a CAF-based risk signature model for predicting prognosis and identifying potential therapeutic targets. METHODS: Single-cell RNA sequencing (scRNA-seq) and spatial transcriptomic RNA (stRNA) were employed to identify CAF signature genes and their spatial distribution in HCC tissues. Immunohistochemistry (IHC) was used to validate candidate protein expression. A CAFs-based risk signature model was developed using multivariate Cox regression. Functional experiments were performed to evaluate the role of OLFML2B in the effects of CAFs on HepG2 cell proliferation and invasion. RESULTS: scRNA-seq analysis of dataset GSE242889 found CAFs as pivotal regulators in the HCC microenvironment. Four CAF signature genes (NDUFA4L, OLFML2B, SEMA5B and RASL12) were negatively correlated with HCC patient survival. IHC staining further validated significant upregulation of NDUFA4L, OLFML2B, SEMA5B and RASL12 in HCC tissues. The CAF risk model constructed based on four CAF signature genes demonstrated prognostic predictive value for HCC patients. Moreover, silencing OLFML2B markedly attenuated the CAF-induced proliferation and invasion of HepG2 cells. CONCLUSION: This study presents a novel CAF-based risk model that can exhibits accurately predict the prognosis of HCC patients. Furthermore, knockdown of OLFML2B attenuates the CAF-induced HCC progression, suggesting it as a potential therapeutic target.

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