ArticleJournal of cancer research and clinical oncology2018
Validation of a 10-gene molecular signature for predicting biochemical recurrence and clinical metastasis in localized prostate cancer.
Article in Journal of cancer research and clinical oncology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Assessment of biochemical recurrence of prostate cancer (Review).International journal of oncology · 2019Pooled it
- Evaluating the prognosis of prostate cancer through metabolic pathways.Discover oncology · 2025Article
- Predicting prostate cancer recurrence: Introducing PCRPS, an advanced online web server.Heliyon · 2024Article
- Article
- A Novel Angiogenesis-Related Gene Signature to Predict Biochemical Recurrence of Patients with Prostate Cancer following Radical Therapy.Journal of oncology · 2022Article
- A novel immune-related gene-based prognostic signature to predict biochemical recurrence in patients with prostate cancer after radical prostatectomy.Cancer immunology, immunotherapy : CII · 2021Article
- Gene signatures predict biochemical recurrence-free survival in primary prostate cancer patients after radical therapy.Cancer medicine · 2021Article
- Expression of ISL1 and its partners in prostate cancer progression and neuroendocrine differentiation.Journal of cancer research and clinical oncology · 2021Article
- Novel Gene Signatures Predictive of Patient Recurrence-Free Survival and Castration Resistance in Prostate Cancer.Cancers · 2021Article
- Article
- A 10-gene signature as a predictor of biochemical recurrence after radical prostatectomy in patients with prostate cancer and a Gleason score ≥7.Oncology letters · 2020Article
- A novel gene signature to predict immune infiltration and outcome in patients with prostate cancer.Oncoimmunology · 2020Article
- Prognostic Significance of Serum PSA Level and Telomerase, VEGF and GLUT-1 Protein Expression for the Biochemical Recurrence in Prostate Cancer Patients after Radical Prostatectomy.Pathology oncology research : POR · 2020Article
- Construction and Validation of a Robust Cancer Stem Cell-Associated Gene Set-Based Signature to Predict Early Biochemical Recurrence in Prostate Cancer.Disease markers · 2020Article
- Identification of a Transcriptomic Prognostic Signature by Machine Learning Using a Combination of Small Cohorts of Prostate Cancer.Frontiers in genetics · 2020Article
- A Three-Gene Classifier Associated With MicroRNA-Mediated Regulation Predicts Prostate Cancer Recurrence After Radical Prostatectomy.Frontiers in genetics · 2019Article
- Development and validation of lncRNAs-based nomogram for prediction of biochemical recurrence in prostate cancer by bioinformatics analysis.Journal of Cancer · 2019Article
- Identification of seven long noncoding RNAs signature for prediction of biochemical recurrence in prostate cancer.Asian journal of andrologyArticle
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8 authors.
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Abstract
purposeTo validate a previously characterized 10-gene signature in prostate cancer with implication to distinguish aggressive and indolent disease within low and intermediate patients' risk groups.
methodsA case-control study design used to select 545 patients from the Mayo clinic tumor registry who underwent radical prostatectomy. A training set from this cohort (n = 359) was used to build a 10-gene model, based on high-dimensional discriminant analysis (HDDA10) to predict several endpoints of clinical patients' outcome. An independent set (n = 219) from the same institution was used as validation set.
resultsHDDA10 showed significant performance for predicting metastasis (Mets) (AUC 0.68, p = 6.4E - 6) and biochemical recurrence (BCR) (AUC = 0.65, p = 0.003) in the validation set outperforming Gleason grade grouping (GG) for BCR (AUC 0.57, p = 0.03) and with comparable performance for Mets endpoint (GG AUC 0.66, p = 8.1E - 5). HDDA10 prognostic significance was superior to any clinical-pathological parameter within GG2 + 3 (GS7) patients achieving an AUC of 0.74 (p = 0.0037) for BCR compared to Gleason pattern 4 (AUC 0.64) (p = 0.015) and AUC for Mets of 0.68 versus AUC of 0.65 for Gleason pattern 4 (p = 0.01). HDDA10 remained significant for both BCR and Mets in multivariate analysis, suggesting that it can be used to increase accuracy in stratifying patients eligible for active surveillance.
conclusionHDDA10 is of added value to GG and other clinical-pathological parameters in predicting BCR and Mets endpoint, especially in the low to intermediate patients' risk groups. HDDA10 prognostic value should be further validated prospectively in stratifying patients specifically in low to intermediate GS (GG1-2), such as active surveillance programs.
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