ArticleThe American journal of pathology2012
Genome abnormalities precede prostate cancer and predict clinical relapse.
Article in The American journal of pathology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed, 42 citations in OpenAlex.
- Whole-genome methylation sequencing reveals distinct impact of differential methylations on gene transcription in prostate cancer.The American journal of pathology · 2013Trial
- Immuno-targeting the ectopic phosphorylation sites of PDGFRA generated by MAN2A1-FER fusion in HCC.Hepatology communications · 2024Article
- Multi-omics approach for identifying CNV-associated lncRNA signatures with prognostic value in prostate cancer.Non-coding RNA research · 2024Article
- Fusion Gene Detection in Prostate Cancer Samples Enhances the Prediction of Prostate Cancer Clinical Outcomes from Radical Prostatectomy through Machine Learning in a Multi-Institutional Analysis.The American journal of pathology · 2023Article
- Deep Learning-Based Multi-Omics Integration Robustly Predicts Relapse in Prostate Cancer.Frontiers in oncology · 2022Article
- DICER-AS1 functions as competing endogenous RNA that targets CSR1 by sponging microRNA-650 and suppresses gastric cancer progression.The Journal of international medical research · 2021Article
- Gene Duplication and Gene Fusion Are Important Drivers of Tumourigenesis during Cancer Evolution.Genes · 2021Review
- Breast and prostate cancers harbor common somatic copy number alterations that consistently differ by race and are associated with survival.BMC medical genomics · 2020Article
- Exome sequencing identified six copy number variations as a prediction model for recurrence of primary prostate cancers with distinctive prognosis.Translational cancer research · 2020Article
- Identification of recurrent fusion genes across multiple cancer types.Scientific reports · 2019Article
- Genome-wide Association Study (GWAS) of Germline Copy Number Variations (CNVs) Reveal Genetic Risks of Prostate Cancer in Chinese population.Journal of Cancer · 2018Article
- Oncogenic activity of amplified miniature chromosome maintenance 8 in human malignancies.Oncogene · 2017Article
- Methylation in benign prostate and risk of disease progression in men subsequently diagnosed with prostate cancer.International journal of cancer · 2016Article
- Oncogenic Activity of miR-650 in Prostate Cancer Is Mediated by Suppression of CSR1 Expression.The American journal of pathology · 2015Article
- Discovery and Classification of Fusion Transcripts in Prostate Cancer and Normal Prostate Tissue.The American journal of pathology · 2015Review
- Genomic Copy Number Variations in the Genomes of Leukocytes Predict Prostate Cancer Clinical Outcomes.PloS one · 2015Article
- Novel fusion transcripts associate with progressive prostate cancer.The American journal of pathology · 2014Article
- An integrative CGH, MSI and candidate genes methylation analysis of colorectal tumors.PloS one · 2014Article
- High fidelity copy number analysis of formalin-fixed and paraffin-embedded tissues using Affymetrix Cytoscan HD chip.PloS one · 2014Article
- Metallothionein 1 h tumour suppressor activity in prostate cancer is mediated by euchromatin methyltransferase 1.The Journal of pathology · 2013Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
Abstract
The prediction of prostate cancer clinical outcome remains a major challenge after the diagnosis, even with improved early detection by prostate-specific antigen (PSA) monitoring. To evaluate whether copy number variation (CNV) of the genomes in prostate cancer tumor, in benign prostate tissues adjacent to the tumor (AT), and in the blood of patients with prostate cancer predicts biochemical (PSA) relapse and the kinetics of relapse, 241 samples (104 tumor, 49 matched AT, 85 matched blood, and 3 cell lines) were analyzed using Affymetrix SNP 6.0 chips. By using gene-specific CNV from tumor, the genome model correctly predicted 73% (receiver operating characteristic P = 0.003) cases for relapse and 75% (P < 0.001) cases for short PSA doubling time (PSADT, <4 months). The gene-specific CNV model from AT correctly predicted 67% (P = 0.041) cases for relapse and 77% (P = 0.015) cases for short PSADT. By using median-sized CNV from blood, the genome model correctly predicted 81% (P < 0.001) cases for relapse and 69% (P = 0.001) cases for short PSADT. By using median-sized CNV from tumor, the genome model correctly predicted 75% (P < 0.001) cases for relapse and 80% (P < 0.001) cases for short PSADT. For the first time, our analysis indicates that genomic abnormalities in either benign or malignant tissues are predictive of the clinical outcome of a malignancy.
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