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    Genomic evaluation of multiparametric magnetic resonance imaging-visible and -nonvisible lesions in clinically localised prostate cancer

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    Authors
    Parry, Marina
    Srivastava, Shambhavi
    Ali, Adnan
    Cannistraci, Alession
    Antonello, Jenny
    Barros-Silva, Joao D
    Ubertini, Valentina
    Ramani, Vijay A C
    Lau, Maurice W
    Shanks, Jonathan H
    Nonaka, Daisuke
    Oliveira, Pedro
    Hambrock, Thomas
    Leong, Hui Sun
    Dhomen, Nathalie
    Miller, Crispin J
    Brady, Ged
    Dive, Caroline
    Clarke, Noel W
    Marais, Richard
    Baena, Esther
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    Affiliation
    Molecular Oncology, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park, UK
    Issue Date
    2019
    
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    Abstract
    BACKGROUND: The prostate cancer (PCa) diagnostic pathway is undergoing a radical change with the introduction of multiparametric magnetic resonance imaging (mpMRI), genomic testing, and different prostate biopsy techniques. It has been proposed that these tests should be used in a sequential manner to optimise risk stratification. OBJECTIVE: To characterise the genomic, epigenomic, and transcriptomic features of mpMRI-visible and -nonvisible PCa in clinically localised disease. DESIGN, SETTING, AND PARTICIPANTS: Multicore analysis of fresh prostate tissue sampled immediately after radical prostatectomy was performed for intermediate- to high-risk PCa. INTERVENTION: Low-pass whole-genome, exome, methylation, and transcriptome profiling of patient tissue cores taken from microscopically benign and cancerous areas in the same prostate. Circulating free and germline DNA was assessed from the blood of five patients. OUTCOME MEASUREMENT AND STATISTICAL ANALYSIS: Correlations between preoperative mpMRI and genomic characteristics of tumour and benign prostate samples were assessed. Gene profiles for individual tumour cores were correlated with existing genomic classifiers currently used for prognostication. RESULTS AND LIMITATIONS: A total of 43 prostate cores (22 tumour and 21 benign) were profiled from six whole prostate glands. Of the 22 tumour cores, 16 were tumours visible and six were tumours nonvisible on mpMRI. Intratumour genomic, epigenomic, and transcriptomic heterogeneity was found within mpMRI-visible lesions. This could potentially lead to misclassification of patients using signatures based on copy number or RNA expression. Moreover, three of the six cores obtained from mpMRI-nonvisible tumours harboured one or more genetic alterations commonly observed in metastatic castration-resistant PCa. No circulating free DNA alterations were found. Limitations include the small cohort size and lack of follow-up. CONCLUSIONS: Our study supports the continued use of systematic prostate sampling in addition to mpMRI, as avoidance of systematic biopsies in patients with negative mpMRI may mean that clinically significant tumours harbouring genetic alterations commonly seen in metastatic PCa are missed. Furthermore, there is inconsistency in individual genomics when genomic classifiers are applied. PATIENT SUMMARY: Our study shows that tumour heterogeneity within prostate tumours visible on multiparametric magnetic resonance imaging (mpMRI) can lead to misclassification of patients if only one core is used for genomic analysis. In addition, some cancers that were missed by mpMRI had genomic aberrations that are commonly seen in advanced metastatic prostate cancer. Avoiding biopsies in mpMRI-negative cases may mean that such potentially lethal cancers are missed.
    Citation
    Parry MA, Srivastava S, Ali A, Cannistraci A, Antonello J, Barros-Silva JD, et al. Genomic evaluation of multiparametric magnetic resonance imaging-visible and -nonvisible lesions in clinically localised prostate cancer Cancer. Eur Urol Oncol. 2019 Feb;2(1):1-11.
    Journal
    European Urology Oncology
    URI
    http://hdl.handle.net/10541/621748
    DOI
    10.1016/j.euo.2018.08.005
    PubMed ID
    30929837
    Additional Links
    https://dx.doi.org/10.1016/j.euo.2018.08.005
    Type
    Article
    Language
    en
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.euo.2018.08.005
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