Rare germline genetic variation in PAX8 transcription factor binding sites and susceptibility to epithelial ovarian cancer.

Breast Cancer Colorectal Endometrial Ovarian PAX8 burden test non-coding rare variants transcription factor whole genome

Journal

American journal of epidemiology
ISSN: 1476-6256
Titre abrégé: Am J Epidemiol
Pays: United States
ID NLM: 7910653

Informations de publication

Date de publication:
27 Aug 2024
Historique:
received: 05 05 2023
revised: 29 11 2023
accepted: 03 05 2024
medline: 28 8 2024
pubmed: 28 8 2024
entrez: 27 8 2024
Statut: aheadofprint

Résumé

Common genetic variation throughout the genome together with rare coding variants identified to date explain about a half of the inherited genetic component of epithelial ovarian cancer risk. It is likely that rare variation in the non-coding genome will explain some of the unexplained heritability, but identifying such variants is challenging. The primary problem is lack of statistical power to identifying individual risk variants by association as power is a function of sample size, effect size and allele frequency. Power can be increased by using burden tests which test for association of carriers of any variant in a specified genomic region. This has the effect of increasing the putative effect allele frequency. PAX8 is a transcription factor that plays a critical role in tumour progression, migration and invasion. Furthermore, regulatory elements proximal to target genes of PAX8 are enriched for common ovarian cancer risk variants. We hypothesised that rare variation in PAX8 binding sites are also associated with ovarian cancer risk, but unlikely to be associated with risk of breast, colorectal or endometrial cancer. We have used publicly available, whole-genome sequencing data from the UK 100,000 Genomes Project to evaluate the burden of rare variation in PAX8 binding sites across the genome. Data were available for 522 ovarian cancers, 2,984 breast cancers, 2,696 colorectal cancers, 836 endometrial cancers and 2253 non-cancer controls. Active binding sites were defined using data from multiple PAX8 and H3K27 ChIPseq experiments. We found no association between the burden of rare variation in PAX8 binding sites (defined in several ways) and risk of ovarian, breast or endometrial cancer. An apparent association with colorectal cancer was likely to be a technical artefact as a similar association was also detected for rare variation in random regions of the genome. Despite the null result this study provides a proof-of -principle for using burden testing to identify rare, non-coding germline genetic variation associated with disease. Larger sample sizes available from large-scale sequencing projects together with improved understanding of the function of the non-coding genome will increase the potential of similar studies in the future.

Identifiants

pubmed: 39191651
pii: 7742775
doi: 10.1093/aje/kwae301
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© The Author(s) 2024. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health.

Auteurs

Suzana A M Ezquina (SAM)

Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.

Michelle Jones (M)

Center for Bioinformatics and Functional Genomics, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, United States.

Ed Dicks (E)

Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.

Amber de Vries (A)

Center for Bioinformatics and Functional Genomics, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, United States.

Pei-Chen Peng (PC)

Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, United States.

Kate Lawrenson (K)

Center for Bioinformatics and Functional Genomics, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, United States.

Rosario I Corona (RI)

Department of Human Genetics, University of California, Los Angeles, United States.

Jonathan Tyrer (J)

Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, United Kingdom.

Dennis Hazelett (D)

Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, United States.

James Brenton (J)

Department of Oncology, University of Cambridge, Cambridge, UK.

Antonis Antoniou (A)

Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.

Simon A Gayther (SA)

Center for Bioinformatics and Functional Genomics, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, United States.

Paul D P Pharoah (PDP)

Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, United States.

Classifications MeSH