Transcriptomic signatures of prostate cancer progression: a comprehensive RNA-seq study

被引:0
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作者
Shristi Modanwal [1 ]
Viswajit Mulpuru [2 ]
Ashutosh Mishra [1 ]
Nidhi Mishra [1 ]
机构
[1] Indian Institute of Information of Technology Allahabad,Department of Applied Sciences
[2] Vignan’s Foundation for Science,Department of Bioinformatics
[3] Technology,undefined
[4] and Research,undefined
关键词
Prostate cancer; Prognostic biomarker; PPI network; Gene ontology; Nomogram; DEGs; Diagnostic biomarker;
D O I
10.1007/s13205-025-04297-3
中图分类号
学科分类号
摘要
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.
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