ArticleScientific reports2022
A transcriptomic signature for prostate cancer relapse prediction identified from the differentially expressed genes between TP53 mutant and wild-type tumors.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Integrative advances in biomarker-driven prostate cancer management from genomic discovery to precision oncology.Discover oncology · 2026Review
- The RNA binding proteins LARP4A and LARP4B promote sarcoma and carcinoma growth and metastasis.iScience · 2024Article
- Understanding the Biological Basis of Polygenic Risk Scores and Disparities in Prostate Cancer: A Comprehensive Genomic Analysis.Cancer informatics · 2024Article
- The Development of a Gleason Score-Related Gene Signature for Predicting the Prognosis of Prostate Cancer.Journal of clinical medicine · 2022Article
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Abstract
For prostate cancer (PCa) patients, biochemical recurrence (BCR) is the first sign of disease relapse and the subsequent metastasis. TP53 mutations are relatively prevalent in advanced PCa forms. We aimed to utilize this knowledge to identify robust transcriptomic signatures for BCR prediction in patients with Gleason score ≥ 7 cancers, which cause most PCa deaths. Using the TCGA-PRAD dataset and the novel data-driven stochastic approach proposed in this study, we identified a 25-gene signature from the genes whose expression in tumors was associated with TP53 mutation statuses. The predictive strength of the signature was assessed by AUC and Fisher's exact test p-value according to the output of support vector machine-based cross validation. For the TCGA-PRAD dataset, the AUC and p-value were 0.837 and 5 × 10
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