Identification of miRNA signature in cancer-associated fibroblast to predict recurrent prostate cancer.

ABSTRACT

BACKGROUND: Cancer-associated fibroblasts (CAFs) are one of the major components of prostate stromal cells, which play a crucial part in tumor development and treatment resistance. This study aimed to establish a model of CAFs-related microRNAs (miRNAs) to assess prognostic differences, tumor microenvironments, and screening of anticancer drugs by integrating data from single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (buRNA-seq). METHODS: scRNA-seq and buRNA-seq data of primary prostate cancer (PCa) were downloaded from Gene Expression Omnibus and The Cancer Genome Atlas databases. Statistical methods including Least absolute shrinkage and selection operator (Lasso), Lasso penalized, Random Forest, Random Forest Combination, and Support Vector Machine (SVM) were performed to select hub miRNAs. Pathway analyses and assessment of infiltrating immune cells were conducted using Gene Set Enrichment Analysis and the CIBERSORT algorithm. The expression of CAFs-related miRNAs in fibroblast cell lines were validated through quantitative real-time PCR. Cell Counting Kit 8 (CCK8), wound-healing, clone formation, and cell migration assays were used to explore cell proliferation, growth, and migration in vitro. A mouse xenograft model was established to investigate the effect of CAFs on tumor growth in vivo. RESULTS: Through single-cell transcriptomics analysis in 34 PCa patients, 89 CAFs-related mRNAs were identified. A prognostic model based on 9 CAFs-related miRNAs (hsa-miR-1258, hsa-miR-133b, hsa-miR-222-3p, hsa-miR-145-3p, hsa-miR-493-5p, hsa-miR-96-5p, hsa-miR-15b-5p, hsa-miR-106b-5p, and hsa-miR-191-5p) was established to predict biochemical recurrence (BCR). We have determined through two prediction methods that NVP-TAE684 may be the optimal targeted therapy drug for treating CAFs. Downregulation of hsa-miR-106b-5p in CAFs significantly suppressed cell proliferation, migration, and colony formation in vitro. In vivo studies using a xenograft model further confirmed that hsa-miR-106b-5p downregulation significantly reduced tumor growth. CONCLUSION: Our findings conducted an integrated bioinformatic analysis to develop a CAFs-related miRNAs model that provides prognostic insights into individualized and precise treatment for prostate adenocarcinoma patients. Downregulation of miR-106b-5p in CAFs significantly suppressed tumor growth, suggesting a potential therapeutic target for cancer treatment.