<p>Prostate cancer is a heterogeneous malignancy with a complex tumor microenvironment (TME) composed of various cellular components, including fibroblasts. These fibroblasts, particularly cancer-associated fibroblasts (CAFs), are crucial in shaping the TME and influencing cancer progression. Catechol-O-methyltransferase (COMT), a key enzyme involved in the metabolism of catecholamines and oxidative stress regulation, has recently been implicated in cancer biology. This study aims to explore the molecular landscape of fibroblasts in prostate cancer and evaluate the prognostic significance of COMT expression in this context. We performed an integrated single-cell RNA sequencing (scRNA-seq) analysis on prostate cancer samples from Gene Expression Omnibus (GEO) databases. Fibroblast subpopulations were identified through clustering, and functional gene signatures for each subgroup were characterized. Prognostic analysis was carried out using univariate and multivariate Cox regression to identify genes associated with patient survival, culminating in a risk score model using data from the Cancer Genome Atlas (TCGA). Additionally, immunofluorescence assays were used to validate COMT expression in tumor-derived fibroblasts. Our single-cell sequencing analysis revealed three distinct fibroblast subpopulations, each with unique gene expression profiles linked to extracellular matrix remodeling, immune modulation, and cellular stress responses. COMT was identified as a key gene in tumor-derived fibroblasts, with its expression significantly higher in tumor samples compared to normal tissues. The risk score model, based on COMT and other fibroblast-associated genes (QSOX1, TAX1BP3, CCDC66, MTCH1, ARL2BP), successfully stratified patients into high-risk and low-risk groups, with higher risk scores correlating with poorer survival outcomes. Immunostaining confirmed the overexpression of COMT in tumor-derived fibroblasts, consistent with bioinformatics analysis. This study underscores the significant role of fibroblasts, particularly CAFs, in prostate cancer progression. Our findings highlight COMT as a critical regulator of the tumor microenvironment and a promising prognostic marker. The integration of single-cell RNA-seq with clinical data offers new insights into fibroblast heterogeneity and the potential for COMT as a therapeutic target in prostate cancer. Further research is needed to validate these findings and explore the mechanistic role of COMT in prostate cancer progression and therapeutic resistance.</p>

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Comprehensive single-cell transcriptomic analysis reveals fibroblast subpopulations and the prognostic association of COMT in prostate cancer progression全面的单细胞转录组分析揭示了成纤维细胞亚群,并探讨了 COMT 在前列腺癌进展中的预后关联全面的单细胞转录组分析揭示了成纤维细胞亚群,并探讨了 COMT 在前列腺癌进展中的预后关联

  • Weimin Shan,
  • Bo Guan,
  • Weiwei Ma,
  • Runzhe Fan,
  • Di Cui,
  • Zongyao Hao

摘要

Prostate cancer is a heterogeneous malignancy with a complex tumor microenvironment (TME) composed of various cellular components, including fibroblasts. These fibroblasts, particularly cancer-associated fibroblasts (CAFs), are crucial in shaping the TME and influencing cancer progression. Catechol-O-methyltransferase (COMT), a key enzyme involved in the metabolism of catecholamines and oxidative stress regulation, has recently been implicated in cancer biology. This study aims to explore the molecular landscape of fibroblasts in prostate cancer and evaluate the prognostic significance of COMT expression in this context. We performed an integrated single-cell RNA sequencing (scRNA-seq) analysis on prostate cancer samples from Gene Expression Omnibus (GEO) databases. Fibroblast subpopulations were identified through clustering, and functional gene signatures for each subgroup were characterized. Prognostic analysis was carried out using univariate and multivariate Cox regression to identify genes associated with patient survival, culminating in a risk score model using data from the Cancer Genome Atlas (TCGA). Additionally, immunofluorescence assays were used to validate COMT expression in tumor-derived fibroblasts. Our single-cell sequencing analysis revealed three distinct fibroblast subpopulations, each with unique gene expression profiles linked to extracellular matrix remodeling, immune modulation, and cellular stress responses. COMT was identified as a key gene in tumor-derived fibroblasts, with its expression significantly higher in tumor samples compared to normal tissues. The risk score model, based on COMT and other fibroblast-associated genes (QSOX1, TAX1BP3, CCDC66, MTCH1, ARL2BP), successfully stratified patients into high-risk and low-risk groups, with higher risk scores correlating with poorer survival outcomes. Immunostaining confirmed the overexpression of COMT in tumor-derived fibroblasts, consistent with bioinformatics analysis. This study underscores the significant role of fibroblasts, particularly CAFs, in prostate cancer progression. Our findings highlight COMT as a critical regulator of the tumor microenvironment and a promising prognostic marker. The integration of single-cell RNA-seq with clinical data offers new insights into fibroblast heterogeneity and the potential for COMT as a therapeutic target in prostate cancer. Further research is needed to validate these findings and explore the mechanistic role of COMT in prostate cancer progression and therapeutic resistance.