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  • Review Article
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Post-GWAS in prostate cancer: from genetic association to biological contribution

Abstract

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 substantial 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 focus 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 these post-GWAS analyses 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 this Review, we describe the molecular basis of several important prostate cancer-causal variants with an emphasis on using post-GWAS analysis to gain insight into cancer aetiology. In addition to discussing the current status of post-GWAS studies, we also summarize the main molecular mechanisms of potential causal variants at prostate cancer risk loci and explore the major challenges in moving from association to functional studies and their implication in clinical translation.

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Fig. 1: Representation of the post-GWAS pipeline.
Fig. 2: Approaches for experimental validation of causal SNPs.
Fig. 3: Pathway enrichment analysis of causal variants in prostate cancer.

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Acknowledgements

The authors are grateful for a Queensland University of Technology Postgraduate Award (QUTPRA), an Australian National Health and Medical Research Council (NHMRC) Career Development Fellowship (CDF) and a Principal Research Fellowship and Cancer Australia Priority-Driven Collaborative Cancer Research (PdCCRS) funding.

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S.F. researched data for the article, substantially contributed to discussion of content, wrote the article and reviewed and/or edited it before submission. T.K. substantially contributed to discussion of content and reviewed and/or edited the article before submission. J.C. reviewed and/or edited the article before submission. J.B. substantially contributed to the discussion of content and reviewed and/or edited the article before submission.

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Correspondence to Jyotsna Batra.

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Related links

BLUEPRINT Epigenome: http://www.blueprint-epigenome.eu

ENCODE: https://www.encodeproject.org

FunSeq2: http://funseq2.gersteinlab.org

GTEx: https://www.gtexportal.org/home

GtRNAdb: http://gtrnadb.ucsc.edu

GWAS4D: http://mulinlab.tmu.edu.cn/gwas4d/gwas4d/gwas4d/gwas4d_server

Haploreg: https://pubs.broadinstitute.org/mammals/haploreg/haploreg.php

Haplotype Reference Consortium: http://www.haplotype-reference-consortium.org

LS-SNP/BDP: http://modbase.compbio.ucsf.edu/LS-SNP/Queries.html

MiTranscriptome: http://mitranscriptome.org

MutationAssessor: http://mutationassessor.org/r3

PolyPhen2: http://genetics.bwh.harvard.edu/pph2

Roadmap: http://www.roadmapepigenomics.org

SIFT: http://siftdna.org/www/Extended_SIFT_chr_coords_submit.html

SnoRNABase: https://www-snorna.biotoul.fr

Supplementary information

Glossary

Heritability

The genetic component of a trait and/or disease.

Twin studies

Large-scale studies to evaluate the role of genetic and environmental influence on the development of a disease by comparison between monozygotic and dizygotic twins.

Familial segregation studies

Studies to estimate the genetic inheritance of a disease using family data.

Familial relative risk

(FRR). Inherited predisposition of a disease in an individual.

Polygenic risk score

(PRS). Also called genetic risk score; a number that indicates genetic liability to a trait on the basis of variation in multiple genetic loci and their associated weights.

Linkage disequilibrium

Nonrandom correlation of alleles in a haplotype. The degree of correlation is estimated by the r2 value, ranging from 0 to 1; r2 = 0 shows complete linkage equilibrium, whereas r2 > 0.9 represents highly correlated linkage disequilibrium single-nucleotide polymorphisms.

Haplotypes

Groups of alleles located on a chromosome that are likely to be inherited together.

Pleiotropic effect

An effect that occurs when one gene influences two or more diseases.

Non-coding SNPs

Functional variants located within intragenic or intergenic and/or non-coding regions of the genome modulating the expression of the assigned gene.

Expression quantitative trait loci

(eQTLs). Potential functional germline variants that affect the expression of target genes. Cis-eQTLs are local eQTLs that are located on the same chromosome as their target genes. Trans-eQTLs are distant eQTLs that are located on a different chromosome than their target genes.

Coding SNPs

Single-nucleotide polymorphisms (SNPs) located within exonic regions of genes.

Gleason score

A pathohistological score from a prostate biopsy or surgical sample used to determine the prognostic risk level of men with prostate cancer.

Super-enhancers

A group of putative enhancers in close genomic proximity with unusually high levels of transcription factor-binding sites.

CpG islands

DNA sequences with high repetition of the nucleotides cytosine and guanidine.

Genetic heterogeneity

The presence of different frequencies and combinations of germline variants in populations of different ethnicities.

Minor allele frequency

The frequency of the less common allele of a single-nucleotide polymorphism in a given population.

Copy number variations

A distinct class of germline polymorphisms consisting of longer sequences than small insertion and/or deletions.

Mendelian randomization

A method in epidemiology using inherited genetic variants to infer a causal relationship of an exposure and a disease outcome.

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Farashi, S., Kryza, T., Clements, J. et al. Post-GWAS in prostate cancer: from genetic association to biological contribution. Nat Rev Cancer 19, 46–59 (2019). https://doi.org/10.1038/s41568-018-0087-3

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