ArticleEuropean urology focus2018
DESNT: A Poor Prognosis Category of Human Prostate Cancer.
Article in European urology focus, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.
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Who cites it
24 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Transcriptomic analysis of castration, chemo-resistant and metastatic prostate cancer elucidates complex genetic crosstalk leading to disease progression.Functional & integrative genomics · 2021Pooled it
- Gene-body DNA methylation of ONECUT2 predicts its expression and prostate cancer aggressiveness in needle biopsies.Biomarker research · 2026Article
- Article
- CTHRC1 expresses in cancer-associated fibroblasts and is associated with resistance to anti-androgen therapy in prostate cancer.Genes & genomics · 2025Article
- Unmasking Neuroendocrine Prostate Cancer with a Machine Learning-Driven Seven-Gene Stemness Signature That Predicts Progression.International journal of molecular sciences · 2024Article
- Unmasking Neuroendocrine Prostate Cancer with a Machine Learning-Driven 7-Gene Stemness Signature that Predicts Progression.medRxiv : the preprint server for health sciences · 2024Article
- An 18-gene signature of recurrence-associated endothelial cells predicts tumor progression and castration resistance in prostate cancer.British journal of cancer · 2024Article
- Genomic evolution shapes prostate cancer disease type.Cell genomics · 2024Article
- A reliable transcriptomic risk-score applicable to formalin-fixed paraffin-embedded biopsies improves outcome prediction in localized prostate cancer.Molecular medicine (Cambridge, Mass.) · 2024Article
- Integrative multi-omics analysis unveils stemness-associated molecular subtypes in prostate cancer and pan-cancer: prognostic and therapeutic significance.Journal of translational medicine · 2023Article
- Inhibition of the serine/threonine kinase BUB1 reverses taxane resistance in prostate cancer.iScience · 2023Article
- Tumor immune contexture predicts recurrence after prostatectomy and efficacy of androgen deprivation and immunotherapy in prostate cancer.Journal of translational medicine · 2023Article
- Combining Molecular Subtypes with Multivariable Clinical Models Has the Potential to Improve Prediction of Treatment Outcomes in Prostate Cancer at Diagnosis.Current oncology (Toronto, Ont.) · 2022Article
- SR9009 inhibits lethal prostate cancer subtype 1 by regulating the LXRα/FOXM1 pathway independently of REV-ERBs.Cell death & disease · 2022Article
- Validation of diagnostic nomograms based on CE-MS urinary biomarkers to detect clinically significant prostate cancer.World journal of urology · 2022Article
- A comparative study of PCS and PAM50 prostate cancer classification schemes.Prostate cancer and prostatic diseases · 2021Article
- Article
- Derivation and Application of Molecular Signatures to Prostate Cancer: Opportunities and Challenges.Cancers · 2021Review
- Histone methyltransferase DOT1L coordinates AR and MYC stability in prostate cancer.Nature communications · 2020Article
- Article
Corrections and comments
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Authors and funding
23 authors.
Funding
Abstract
backgroundA critical problem in the clinical management of prostate cancer is that it is highly heterogeneous. Accurate prediction of individual cancer behaviour is therefore not achievable at the time of diagnosis leading to substantial overtreatment. It remains an enigma that, in contrast to breast cancer, unsupervised analyses of global expression profiles have not currently defined robust categories of prostate cancer with distinct clinical outcomes.
objectiveTo devise a novel classification framework for human prostate cancer based on unsupervised mathematical approaches. DESIGN, SETTING, AND
participantsOur analyses are based on the hypothesis that previous attempts to classify prostate cancer have been unsuccessful because individual samples of prostate cancer frequently have heterogeneous compositions. To address this issue, we applied an unsupervised Bayesian procedure called Latent Process Decomposition to four independent prostate cancer transcriptome datasets obtained using samples from prostatectomy patients and containing between 78 and 182 participants. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Biochemical failure was assessed using log-rank analysis and Cox regression analysis. RESULTS AND LIMITATIONS: Application of Latent Process Decomposition identified a common process in all four independent datasets examined. Cancers assigned to this process (designated DESNT cancers) are characterized by low expression of a core set of 45 genes, many encoding proteins involved in the cytoskeleton machinery, ion transport, and cell adhesion. For the three datasets with linked prostate-specific antigen failure data following prostatectomy, patients with DESNT cancer exhibited poor outcome relative to other patients (p=2.65×10
conclusionsOur results demonstrate the existence of a novel poor prognosis category of human prostate cancer and will assist in the targeting of therapy, helping avoid treatment-associated morbidity in men with indolent disease. PATIENT SUMMARY: Prostate cancer, unlike breast cancer, does not have a robust classification framework. We propose that this failure has occurred because prostate cancer samples selected for analysis frequently have heterozygous compositions (individual samples are made up of many different parts that each have different characteristics). Applying a mathematical approach that can overcome this problem we identify a novel poor prognosis category of human prostate cancer called DESNT.
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