Single-Cell Analysis Combined with Mendelian Randomization Identifies Genes Associated with Prostate Cancer Cells
Year: 2025
Type: article
Abstract: PURPOSE: Prostate cancer is the second most common male cancer, with incidence increasing with age. When prostate cancer extends beyond the prostatic capsule, treatment options and prognosis change significantly. This study aims to investigate prognostic genes related to capsular invasion in prostate cancer by integrating single-cell data with Mendelian randomization (MR) analysis. MATERIALS AND METHODS: Single-cell sequencing data from six prostate cancer cases were obtained from the Gene Expression Omnibus (GEO) database. Cell clustering and annotation were performed using R, and high-dimensional weighted gene co-expression network analysis (hdWGCNA) identified differentially expressed genes in advanced-stage cancer. Single nucleotide polymorphism loci corresponding to these genes were retrieved from the UK Biobank (UKB), and MR exposure data were acquired from the ukb-b-13348 dataset. MR analysis assessed the impact of hdWGCNA-identified genes. Clinical and gene expression data from TCGA and GEO were analyzed using univariate Cox regression to evaluate gene effects on prognosis. Cellular functional experiments and immunohistochemistry assessed gene expression and function in prostate cancer. RESULTS: expression in both normal and tumor tissues, particularly in the tumor group. CONCLUSIONS: may play a crucial role in the progression of prostate cancer and could serve as a prognostic predictor and therapeutic target for the disease.
DOI: 10.5534/wjmh.240298
Authors: Weizhuo Wang, Kaiyu Lu, Xi Zhang, Kai Wei, Gang Cheng, Zheng Tang, Mingwei Zhan, Caibin Fan, Xu Fu
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4409825280