Niu Wenkang, Zhang Tingting, Ma Lei
College of Life Science, Shihezi University, Shihezi 832000, China.
Key Laboratory of Oasis Town and Mountain-Basin System Ecology of Bingtuan, Shihezi University, Shihezi 832000, China.
Genes (Basel). 2025 Apr 29;16(5):527. doi: 10.3390/genes16050527.
Prostate cancer (PCa) is the most frequently diagnosed malignancy in the male genitourinary tract. However, the regulatory mechanism of competitive endogenous RNAs (ceRNAs) in PCa remains unclear. In this study, we first performed immune scores of mRNA data from 481 PCa samples using single-sample Gene Set Enrichment Analysis (ssGSEA). Based on the immune scores, we then evaluated the tumor immune microenvironment and analyzed 28 types of immune cells in PCa, we constructed a comprehensive network with four lncRNAs (MEG3, PCAT1, SNHG19, TRG-AS1), three miRNAs (hsa-miR-488-3p, hsa-miR-210-5p, hsa-miR-137), and twenty-seven mRNAs (including H2AFJ, THBS1, HPGD). Among the 28 immune cell types, seven immune cell types were found to be significantly associated with clinical characteristics. These network nodes have prognostic significance in multiple cancers and play critical roles in malignancy development, indicating the network's predictive capability. We also observed a strong correlation (r = 0.6) between T-helper type 1 (Th1) cells and lncRNA network modules. The network connectivity highlights the association between immune therapy biomarkers for PCa, particularly those related to H2AFJ, THBS1, and HPGD. These findings provide valuable insights into the ceRNA regulatory network and its implications for immune-based therapies in PCa.
前列腺癌(PCa)是男性泌尿生殖道中最常被诊断出的恶性肿瘤。然而,PCa中竞争性内源性RNA(ceRNA)的调控机制仍不清楚。在本研究中,我们首先使用单样本基因集富集分析(ssGSEA)对481个PCa样本的mRNA数据进行免疫评分。基于免疫评分,我们随后评估了肿瘤免疫微环境并分析了PCa中的28种免疫细胞,构建了一个包含四个长链非编码RNA(MEG3、PCAT1、SNHG19、TRG-AS1)、三个微小RNA(hsa-miR-488-3p、hsa-miR-210-5p、hsa-miR-137)和二十七个信使RNA(包括H2AFJ、THBS1、HPGD)的综合网络。在28种免疫细胞类型中,发现有七种免疫细胞类型与临床特征显著相关。这些网络节点在多种癌症中具有预后意义,并在恶性肿瘤发展中起关键作用,表明该网络具有预测能力。我们还观察到1型辅助性T细胞(Th1)与长链非编码RNA网络模块之间存在强相关性(r = 0.6)。网络连通性突出了PCa免疫治疗生物标志物之间的关联,特别是那些与H2AFJ、THBS1和HPGD相关的标志物。这些发现为ceRNA调控网络及其对PCa免疫治疗的意义提供了有价值的见解。