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Accepted Version (PDF 1MB) This may be the author’s version of a work that was submitted/accepted for publication in the following source: Farashi, Samaneh, Kryza, Thomas, Clements, Judith,& Batra, Jyotsna (2019) Post-GWAS in prostate cancer: from genetic association to biological con- tribution. Nature Reviews Cancer, 19(1), pp. 46-59. This file was downloaded from: https://eprints.qut.edu.au/124207/ c Consult author(s) regarding copyright matters This work is covered by copyright. Unless the document is being made available under a Creative Commons Licence, you must assume that re-use is limited to personal use and that permission from the copyright owner must be obtained for all other uses. If the docu- ment is available under a Creative Commons License (or other specified license) then refer to the Licence for details of permitted re-use. It is a condition of access that users recog- nise and abide by the legal requirements associated with these rights. If you believe that this work infringes copyright please provide details by email to [email protected] Notice: Please note that this document may not be the Version of Record (i.e. published version) of the work. Author manuscript versions (as Sub- mitted for peer review or as Accepted for publication after peer review) can be identified by an absence of publisher branding and/or typeset appear- ance. If there is any doubt, please refer to the published source. https://doi.org/10.1038/s41568-018-0087-3 Post-GWAS in prostate cancer: from genetic association to biological contribution Samaneh Farashi1,2, Thomas Kryza1,2, Judith Clements1,2, Jyotsna Batra1,2* 1Cancer Program, School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, 4102, Australia. 2Australian Prostate Cancer Research Centre – Queensland, Queensland University of Technology, Translational Research Institute, 37 Kent Street, Woolloongabba, Queensland, 4102, Australia. Genome-wide association studies (GWAS) have been successful in deciphering the genetic component of predisposition to many human complex diseases including prostate cancer. Germline variants identified by GWAS progressively unravelled the significant knowledge gap concerning prostate cancer heritability. With the beginning of the post-GWAS era, more and more studies reveal that in addition to their value as risk markers, germline variants can exert active roles in prostate oncogenesis. Consequently, current research efforts are focused on exploring the biological mechanisms underlying specific susceptibility loci known as causal variants by applying novel and precise analytical methods to available GWAS data. Results obtained from the aforementioned post-GWAS have highlighted the potential of exploiting prostate cancer-risk associated germline variants to identify new gene networks and signalling pathways involved in prostate tumorigenesis. In reviewing this new field of cancer biology, we describe the molecular basis of several important prostate cancer causal variants with an emphasis on leveraging post-GWAS in yielding a much deeper insight into cancer aetiology. In addition to discussing the current status of post-GWAS studies, we also summarise the main molecular mechanisms of promising causal variants underlying prostate cancer-risk loci and argue the major challenges in moving from association to functional studies and their implication in clinical translation. Introduction Prostate cancer (PrCa) is the second most common cancer in men worldwide and is particularly prevalent amongst men aged >79 years1. As for most cancers, environmental 1 factors increase the risk to develop PrCa2, 3. In addition, the genetic component plays a significant role in PrCa aetiology as there is high reported heritability (57%), together with the elevated risk of PrCa in African American men and patients with family history4, 5. Estimations of the heritability and familial risk of PrCa have been partly explained by large twin and familial segregation studies, respectively4. Population-based studies such as genome-wide association studies (GWAS) have explained substantial familial relative risk (FRR, 28.4%) of PrCa5. For more than a decade, GWAS has been the gold standard to discover the link between germline variants and complex diseases, including PrCa6, 7. To date, GWAS has identified >160 common loci associated with PrCa susceptibility5, 8, 9. This large number suggests a multi- or poly-genic model of prostate carcinogenesis and has added to our knowledge of polygenic risk score (PRS) in PrCa allowing improved genetic disease prediction. Ever since the first GWAS, a post-GWAS strategy has been proposed with the ultimate goal of understanding the biological consequences behind risk loci10, 11. Further functional studies confirmed the active role of several risk loci in PrCa13,14, thus providing greater understanding of the assigned genes5, 12-16. An important observation of the follow-up analysis of GWAS data in PrCa is that risk loci are often located within/near genes and/or regulate genes that define key events in tumourigenesis including cell cycle or DNA repair machinery (ATM, TERT, MYC, MDM2), inflammatory response (IL8RB, TNF and LILRA3)17 and metabolism (JAZF1, HNF1B)18-20. Consequently, it is now recognised that associated genes/regions represent ‘tumour-causal loci’ and may play an active role in oncogenesis21. This fundamentally changes the canonical belief of the non-deleterious effect of germline variants. Thus, follow-up studies of GWAS could delineate the functional mechanisms of these effects. To illustrate the importance of post-GWAS in cancer biology, in this review, we summarise the molecular consequences of several well-established causal loci identified in PrCa. In particular, we emphasise on the necessity of a well-designed post-GWAS approach (FIG 1,2) to further elucidate gene networks and biological pathways involved in PrCa. Consequently, identification of novel involved genes may enhance the translational potential of the GWAS data. This can lead to the discovery of promising targets for therapeutic intervention, new biomarkers for early detection, and predicting disease aggressiveness enable us to precisely and efficiently predict treatment outcomes8, 22. 2 Fine-mapping of the GWAS loci to pinpoint candidate causal variants During the GWAS era it was already known that the risk loci are complex due to linkage disequilibrium (LD) (BOX 1)23, consequently identification of the causal variant is additionally complicated. To precisely identify causal variant(s) underlying an observed PrCa-GWAS signal, the region needs to be fine-mapped while accounting for SNPs in LD24,25. Moreover, imputation methods have been developed using reference panels of human haplotypes to statistically determine non-genotyped sequences24. Several fine-mapping efforts have refined independent causal SNPs16,23,25,26 involved in PrCa such as TERT15 and HNF1B16. Remarkably, the contribution of germline variants to the FRR of PrCa has increased by 4.4%, from 24% to 28.4%, as a consequence of fine-mapping of associated loci5,16. Fine mapping of particular cancer-risk associated regions extensively reported by GWAS27,28 such as the 8q2429, 22q1330 and 17q1226 loci suggests these regions harbour gene(s) that are mediators in PrCa as well as other types of cancers due to their pleiotropic effect8,24,29. Functional variants in PrCa: upgraded from simple witnesses to active players Several criteria need to be met for a SNP to be considered as a causal variant in PrCa (BOX 1). Notably, the SNP should have an impact, likely small, on molecular or cellular systems of prostate and/or relative cells/tissue(s). On the one hand, when localised in a gene coding region, a SNP could affect the properties of the encoded protein and modulate its molecular/biological functions in the prostate microenvironment (FIG 2A). On the other hand, a SNP localised in a non-coding region, is likely to affect the expression of one or several genes through different molecular mechanisms (FIG 2B-D). Many post-GWAS studies focussed on understanding the upstream regulatory effects of non-coding SNPs known as expression quantitative trait loci (eQTLs) on the genes in the vicinity of the fine-mapped SNPs5,16. These co-localised GWAS-eQTLs have been considered as causal variants in this review (BOX 1). FIGURE 2 illustrates some of the experimental approaches that have been used in previous studies, with a particular focus on the functional role of SNPs within the Kallikrein-related peptidase 3 (KLK3) gene. Prostate specific antigen (PSA) encoded by the KLK3 gene has been a major subject of interest with respect to detection bias as elevated levels of PSA are used to trigger diagnostic biopsies that often lead to unnecessary treatment since the PSA test alone cannot discriminate aggressive from indolent disease31. 3 A functional role of coding variants modulating PSA function (FIG 2A) also non-coding variants (FIG 2B,D) changing the PSA level have been described. Determination of the status of these and other variants associated with changed PSA levels32 in men could shed some light on why some men have low levels of PSA but still have PrCa and allow the development of a more “personalised” PSA test taking into account these germline variants. In addition to the regulatory role of non-coding SNPs on protein coding genes, they can affect the expression and stability of non-coding RNAs (ncRNAs) subsequently modifying their regulatory function33
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