A Tumor Microenvironment‐Derived CAF‐VEGF Model and Its Application in Biomarker Screening for HCC

HCC is a highly vascularized solid tumor that develops rapidly and has a poor prognosis. Previous studies have shown that fibroblasts and angiogenesis in the tumor microenvironment play significant roles in the progression of HCC, and the combined effect of both on HCC is worth exploring. Therefore, we developed the CAF-VEGF prognostic scoring model to assess the prognosis of HCC patients. Single-cell sequencing was done on cancer tissues and nearby normal tissues in the study using data that we downloaded from the GEO database. We used the CellChat and Monocle3 packages to analyze the angiogenesis pathways and differentiation trajectories of fibroblasts. Subsequently, we conducted functional enrichment on fibroblasts. We constructed the CAF-VEGF prognostic model using the COX and LASSO algorithms and evaluated its prognostic value through survival and ROC curves. Based on the prognostic model, we identified key genes through differential expression screening, WGCNA, and PPI network analysis. The conclusions were ultimately validated by expression experiments and functional assays. We found that fibroblasts had a higher infiltration rate in HCC tissues and successfully constructed a CAF-VEGF prognostic model in HCC, proving its effectiveness. Using the CAF-VEGF score, we identified the key molecular markers ESCO2 and WDHD1, both significantly upregulated in HCC cells. Their overexpression may lead to poor prognosis in HCC patients. Additionally, through experiments, we found that both can promote angiogenesis and enhance the proliferation and invasion-migration abilities of HCC cells. This study successfully constructed the CAF-VEGF prognostic model for HCC, and may help improve the prognosis of HCC patients. We also found that the genes WDHD1 and ESCO2 can promote HCC infiltration by regulating angiogenesis, providing insights for future HCC treatment.