Systematic identification of functionally relevant risk alleles to stratify aggressive versus indolent prostate cancer
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Salpie Nowinski1, Aida Santaolalla2, Ben O’Leary3, Massimo Loda4, Ayesha Mirchandani1, Mark Emberton5, Mieke Van Hemelrijck2 and Anita Grigoriadis1
1Cancer Bioinformatics, Innovation Hub, Guy’s Cancer Centre, King’s College London, London, UK
2Translational Oncology & Urology Research, King’s College London, London, UK
3Breast Cancer NOW Centre, The Institute of Cancer Research, The Royal Marsden Hospital, London, UK
4Department of Oncologic Pathology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
5Division of Surgery and Interventional Science, University College London, London, UK
Anita Grigoriadis, email: [email protected]
Keywords: prostate cancer; active surveillance; GWAS; functional risk alleles; somatic copy number aberrations
Received: November 30, 2017 Accepted: January 25, 2018 Published: February 05, 2018
Novel approaches for classification, including molecular features, are needed to direct therapy for men with low-grade prostate cancer (PCa), especially men on active surveillance. Risk alleles identified from genome-wide association studies (GWAS) could improve prognostication. Those risk alleles that coincided with genes and somatic copy number aberrations associated with progression of PCa were selected as the most relevant for prognostication.
In a systematic literature review, a total of 698 studies were collated. Fifty-three unique SNPs residing in 29 genomic regions, including 8q24, 10q11 and 19q13, were associated with PCa progression. Functional studies implicated 21 of these single nucleotide polymorphisms (SNPs) as modulating the expression of genes in the androgen receptor pathway and several other oncogenes. In particular, 8q24, encompassing MYC, harbours a high density of SNPs conferring unfavourable pathological characteristics in low-grade PCa, while a copy number gain of MYC in low-grade PCa was associated with prostate-specific antigen recurrence after radical prostatectomy.
By combining GWAS data with gene expression and structural rearrangements, risk alleles were identified that could provide a new basis for developing a prognostication tool to guide therapy for men with early prostate cancer.
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