ArticleTranslational andrology and urology2021
Identification and validation of a six immune-related gene signature for prediction of biochemical recurrence in localized prostate cancer following radical prostatectomy.
Article in Translational andrology and urology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Evaluating the prognosis of prostate cancer through metabolic pathways.Discover oncology · 2025Article
- Prognostic and Predictive Value of Machine Learning-Based Biomarker and Pathomics Signatures in Patients With Prostate Cancer.Cancer science · 2025Observational
- Predicting prostate cancer recurrence: Introducing PCRPS, an advanced online web server.Heliyon · 2024Article
- Tumor immune contexture predicts recurrence after prostatectomy and efficacy of androgen deprivation and immunotherapy in prostate cancer.Journal of translational medicine · 2023Article
- Identification and Validation of FGF-Related Prognostic Signatures in Prostate Cancer.Disease markers · 2023Article
- Characterization of a Pyroptosis-Related Signature for Prognosis Prediction and Immune Microenvironment Infiltration in Prostate Cancer.Computational and mathematical methods in medicine · 2022Article
- Energy Metabolism-Related Gene Prognostic Index Predicts Biochemical Recurrence for Patients With Prostate Cancer Undergoing Radical Prostatectomy.Frontiers in immunology · 2022Article
- A Gene Prognostic Index Associated With Epithelial-Mesenchymal Transition Predicting Biochemical Recurrence and Tumor Chemoresistance for Prostate Cancer.Frontiers in oncology · 2021Article
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10 authors.
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Abstract
backgroundProstate cancer (PCa) is the second lethal heterogeneous cancer among males worldwide, and approximately 20% of PCa patients following radical prostatectomy (RP) will undergo biochemical recurrence (BCR). This study is aimed to identify the immune-related gene signature that can predict BCR in localized PCa following RP.
methodsExpression profile of genes together with clinical parameters from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus database (GEO) and the immune-related genes from the Molecular Signatures Database v4.0 were applied to construct and validate the gene signature. The Cox regression analyses were conducted to identify the candidate genes and establish the gene signature. To estimate the prognostic power of the risk score, the time-dependent receiver operating characteristic (ROC) analysis and Harrell's index of concordance (C-index) were utilized. We also established a nomogram to forecast the probability of patients' survival.
resultsA total of 268 patients from the TCGA and 77 patients from GSE70770 and six immune-related genes (
conclusionsThis signature could serve as an independent prognostic factor for BCR. Incorporation of our signature into traditional risk classification might further stratify patients with different prognosis, which could assist practitioners in developing clinical decision-making.
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