A novel cancer-associated fibroblast signature for kidney renal clear cell carcinoma via integrated analysis of single-cell and bulk RNA-sequencing

Abstract

Abstract Cancer-associated fibroblasts (CAFs), integral components of the tumor microenvironment, play a pivotal role in tumor proliferation, metastasis, and clinical outcomes. However, its specific roles in Kidney Renal Clear Cell Carcinoma (KIRC) remain poorly understood. Employing the established Seurat single-cell analysis pipeline, we identified 21 CAFs marker genes. Subsequently, a prognostic signature consisting of 6 CAFs marker genes (RGS5, PGF, TPM2, GJA4, SEPT4, and PLXDC1) was developed in a cohort through univariate and LASSO Cox regression analyses. The model’s efficacy was then validated in an external cohort, with a remarkable predictive performance in 1-, 3-, and 5-year. Patients in the high-risk group exhibited significantly inferior survival outcomes (p < 0.001), and the risk score was an independent prognostic factor (p < 0.05). Distinct differences in immune cell profiles and drug susceptibility were observed between the two risk groups. In KIRC, the PGF-VEGFR1 signaling pathway displayed a notable increase. PGF expression was significantly elevated in tumor tissues, as demonstrated by quantitative real-time polymerase chain reaction. In vitro, transwell assays and CCK8 revealed that recombinant-PGF could enhance the capability of cell proliferation, migration, and invasion in 769P and 786-O cells. This study firstly developed a novel predictive model based on 6 CAFs genes for KIRC. Additionally, PGF may present a potential therapeutic target to enhance KIRC treatment.

Keywords

• Kidney renal clear cell carcinoma
• Cancer-associated fibroblast
• Single-cell RNA-sequencing
• Prognosis signature