Abstract
Prostate cancer (PCa) is a prevalent malignancy of the male reproductive system and ranks as the second most common cancer in men worldwide. The prognosis and clinical management of PCa are closely linked to its pathological grade; however, the high heterogeneity of the disease poses significant challenges in these assessments. Prostate cancer associated 3 (PCA3), an upregulated long non-coding RNA (lncRNA) in PCa, has been established as a urinary biomarker for PCa detection. Nevertheless, its potential role in distinguishing pathological grades remains unclear. In this study, we investigated the association between PCA3 expression and PCa pathological grades. First, we conducted a pan-cancer bioinformatics analysis of PCA3 expression across 32 cancer types, confirming its high specificity for PCa. Next, we performed least absolute shrinkage and selection operator (LASSO) regression, identifying 18 GS-associated lncRNAs. A Gaussian distribution analysis revealed that PCA3 exhibited the strongest PCa-specific expression among these lncRNAs. Furthermore, logistic regression analysis demonstrated that PCA3 expression was significantly higher in poorly differentiated PCa than in well-differentiated PCa. To validate these findings, we constructed a PCA3 promoter-driven transcriptional reporter system, which exhibited elevated activity in lower-grade PCa, reinforcing the differential expression pattern of PCA3 across pathological grades. Our findings suggest that PCA3 could serve as a robust and clinically valuable biomarker for predicting PCa pathological grade.