MOLECULAR AND GENETIC DETERMINANTS OF SURGICAL OUTCOMES IN CANCER PATIENTS: A COMPREHENSIVE ANALYSIS OF BIOMARKERS, TUMOR BIOLOGY, AND POSTOPERATIVE PROGNOSIS

Abstract

Recurrence of prostate cancer after radical prostatectomy is a significant clinical issue, but little is known about the molecular programs involved in determining postoperative recurrence. Transcriptomic profiling provides a chance to discover biologically significant changes associated with the poor surgical outcome. The present work aimed to characterize transcriptomic differences associated with biochemical recurrence and to identify candidate genes and pathway-level programs linked to postoperative disease progression. A retrospective exploratory transcriptomic analysis was conducted using RNA sequencing data from prostate tumor samples with and without biochemical recurrence. Following preprocessing, replicate consolidation, log2 transformation, low-expression filtering, and quality control, 15 samples were retained. Differential expression analysis was performed using Welch’s t-test with Benjamini-Hochberg correction, and pathway-level alterations were examined using gene set enrichment analysis with Hallmark gene sets. The final cohort included 7 recurrence and 8 non recurrence cases. Principal component analysis demonstrated partial separation between groups. No genes remained significant after multiple-testing correction, although several transcripts showed low nominal p-values and moderate fold changes. In contrast, pathway analysis identified 34 significantly enriched pathways, with recurrent tumors demonstrating enrichment of androgen response, MYC targets, mTORC1 signaling, protein secretion, and fatty acid metabolism, while non recurrent tumors showed stronger immune and inflammatory signaling. These findings indicate that postoperative recurrence is associated with coordinated pathway-level reprogramming rather than isolated gene-level alterations, supporting the relevance of systems-level transcriptomic analysis in understanding recurrence biology.