Abstract
Prostate cancer (PCa) ranks among the most prevalent malignancies worldwide. Within the tumor microenvironment (TME), cancer-associated fibroblasts (CAFs) play a crucial role in influencing tumor evolution and progression. To elucidate their prognostic significance, we extracted and integrated PCa data from The Cancer Genome Atlas and the GSE70768, GSE70769, and GSE116918 datasets. Differentially expressed CAF-related genes between normal and tumor tissues were identified, and their associations with CAF subtypes and clinicopathological characteristics were explored through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses. Based on these features, we constructed a CAF-related prognostic model using multivariate Cox and least absolute shrinkage and selection operator regression analyses. A 9-gene signature (LMCD1, CXCL2, UNC5B, THBS2, JAM3, PIGR, SCUBE2, SRD5A2, and PCGEM1) was identified to generate a CAFs score for predicting biochemical recurrence risk. Further analyses of the TME, genetic mutations, and drug sensitivity revealed that this signature was closely associated with tumor immunity and treatment response. Collectively, this model highlights the pivotal role of CAFs in shaping the TME and provides novel insights for prognostic prediction and therapeutic strategies in PCa.