AUTHOR=Mou Zhuofan , Spencer Jack , Knight Bridget , John Joseph , McCullagh Paul , McGrath John S. , Harries Lorna W. 

TITLE=Gene expression analysis reveals a 5-gene signature for progression-free survival in prostate cancer

JOURNAL=Frontiers in Oncology

VOLUME=Volume 12 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2022.914078

DOI=10.3389/fonc.2022.914078

ISSN=2234-943X

ABSTRACT=Prostate cancer (PCa) is the second most common male cancer worldwide but effective biomarkers for the presence or progression-risk of disease are currently elusive. We carried out transcriptome-wide gene expression analysis in a series of 9 matched histologically-confirmed PCa and benign samples and developed a minimal progression-free survival (PFS) associated gene signature (GS) (PCBP1, PABPN1, PTPRF, DANCR and MYC) using least absolute shrinkage and selection operator (LASSO) and stepwise multivariate Cox regression analyses The signature was then validated in The Cancer Genome Atlas prostate adenocarcinoma (TCGA-PRAD) dataset. We were able to predict PFS over 1-, 3-, and 5-years in the TCGA-PRAD dataset, with area under the curve (AUC) of 0.64 to 0.78, and our signature remained as a prognostic factor independent of age, Gleason score, and pathological T and N stages. A nomogram combining signature and Gleason score was constructed which demonstrated improved predictive capability for PFS (AUC: 0.71-0.85), and was superior to the CPG model alone in predicting PFS. In conclusion, we have identified and validated a novel five-gene signature and established a nomogram that effectively predicted PFS in patients with PCa. The findings may improve current prognosis tools for PFS and contribute to clinical decision-making in PCa treatment.