Modanwal Shristi, Mulpuru Viswajit, Mishra Ashutosh, Mishra Nidhi
Department of Applied Sciences, Indian Institute of Information of Technology Allahabad, Prayagraj, Uttar Pradesh 211012 India.
Department of Bioinformatics, Vignan's Foundation for Science, Technology, and Research, Guntur, 522213 India.
3 Biotech. 2025 May;15(5):135. doi: 10.1007/s13205-025-04297-3. Epub 2025 Apr 19.
Transcriptomics has been entirely transformed by RNA-sequencing (RNA-seq) due to its high sensitivity, accuracy, and precision. This study analyzed RNA-seq data to identify potential biomarkers for prostate cancer (PCa), a serious health issue among aging men. Despite several existing studies, biomarkers that effectively detect PCa or its prognosis have yet to be entirely determined. The differentially expressed genes (DEGs) that are critical and clinically informative were identified in PCa patient samples that had been progression stage categorized into medium risk (MR) and high risk (HR). A total of 174 DEGs were found to be shared between MR and HR samples. Functional enrichment analysis revealed their involvement in crucial biological processes, such as p53 signaling, mitotic nuclear division, and inflammation. To further examine their interactions, a Protein-Protein Interaction (PPI) network was constructed, where key genes, such as KIF20A, TPX2, BUB1, BIRC5, BUB1B, and MKI67, were found in significant modules, hubs, and motifs. Several transcription factors, including STAT5B, MYC, and SOX5 controlled these genes. Heatmap analysis indicates that the expression of the six crucial genes (KIF20A, TPX2, BUB1, BIRC5, BUB1B, and MKI67) increases with progression from benign state to medium-risk and high-risk states. Additionally, a nomogram model was constructed to predict the prognostic value of these biomarkers. Among the studied genes, BIRC5, MKI67, and KIF20A are suggested as potential prognostic biomarkers, while NIFK and PPP1CC are suggested as new therapeutic targets. These findings indicate that these biomarkers show considerable promise in improving early detection and prognosis of PCa.
The online version contains supplementary material available at 10.1007/s13205-025-04297-3.
转录组学因RNA测序（RNA-seq）的高灵敏度、准确性和精确性而发生了彻底变革。本研究分析了RNA-seq数据，以确定前列腺癌（PCa）的潜在生物标志物，前列腺癌是老年男性面临的一个严重健康问题。尽管已有多项研究，但有效检测PCa或其预后的生物标志物尚未完全确定。在进展期已分类为中危（MR）和高危（HR）的PCa患者样本中，鉴定出了关键且具有临床信息价值的差异表达基因（DEG）。共发现174个DEG在MR和HR样本中共享。功能富集分析揭示了它们参与关键的生物学过程，如p53信号传导、有丝分裂核分裂和炎症。为了进一步研究它们的相互作用，构建了蛋白质-蛋白质相互作用（PPI）网络，在显著模块、枢纽和基序中发现了关键基因，如KIF20A、TPX2、BUB1、BIRC5、BUB1B和MKI67。包括STAT5B、MYC和SOX5在内的几种转录因子控制着这些基因。热图分析表明，六个关键基因（KIF20A、TPX2、BUB1、BIRC5、BUB1B和MKI67）的表达随着从良性状态进展到中危和高危状态而增加。此外，构建了列线图模型来预测这些生物标志物的预后价值。在所研究的基因中，BIRC5、MKI67和KIF20A被认为是潜在的预后生物标志物，而NIFK和PPP1CC被认为是新的治疗靶点。这些发现表明，这些生物标志物在改善PCa的早期检测和预后方面显示出相当大的前景。
在线版本包含可在10.1007/s13205-025-04297-3获取的补充材料。
