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Combined analysis of keratinocyte cancers identifies novel genome-wide loci

The keratinocyte cancers (KC), basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) are the most common cancers in fair-skinned people. KC treatment represents the second highest cancer healthcare expenditure in Australia. Increasing our understanding of the genetic architecture of KC may pr...

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Autores principales: Liyanage, Upekha E, Law, Matthew H, Han, Xikun, An, Jiyuan, Ong, Jue-Sheng, Gharahkhani, Puya, Gordon, Scott, Neale, Rachel E, Olsen, Catherine M, MacGregor, Stuart, Whiteman, David C
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6737293/
https://www.ncbi.nlm.nih.gov/pubmed/31174203
http://dx.doi.org/10.1093/hmg/ddz121
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author Liyanage, Upekha E
Law, Matthew H
Han, Xikun
An, Jiyuan
Ong, Jue-Sheng
Gharahkhani, Puya
Gordon, Scott
Neale, Rachel E
Olsen, Catherine M
MacGregor, Stuart
Whiteman, David C
author_facet Liyanage, Upekha E
Law, Matthew H
Han, Xikun
An, Jiyuan
Ong, Jue-Sheng
Gharahkhani, Puya
Gordon, Scott
Neale, Rachel E
Olsen, Catherine M
MacGregor, Stuart
Whiteman, David C
author_sort Liyanage, Upekha E
collection PubMed
description The keratinocyte cancers (KC), basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) are the most common cancers in fair-skinned people. KC treatment represents the second highest cancer healthcare expenditure in Australia. Increasing our understanding of the genetic architecture of KC may provide new avenues for prevention and treatment. We first conducted a series of genome-wide association studies (GWAS) of KC across three European ancestry datasets from Australia, Europe and USA, and used linkage disequilibrium (LD) Score regression (LDSC) to estimate their pairwise genetic correlations. We employed a multiple-trait approach to map genes across the combined set of KC GWAS (total N = 47 742 cases, 634 413 controls). We also performed meta-analyses of BCC and SCC separately to identify trait specific loci. We found substantial genetic correlations (generally 0.5–1) between BCC and SCC suggesting overlapping genetic risk variants. The multiple trait combined KC GWAS identified 63 independent genome-wide significant loci, 29 of which were novel. Individual separate meta-analyses of BCC and SCC identified an additional 13 novel loci not found in the combined KC analysis. Three new loci were implicated using gene-based tests. New loci included common variants in BRCA2 (distinct to known rare high penetrance cancer risk variants), and in CTLA4, a target of immunotherapy in melanoma. We found shared and trait specific genetic contributions to BCC and SCC. Considering both, we identified a total of 79 independent risk loci, 45 of which are novel.
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spelling pubmed-67372932019-09-16 Combined analysis of keratinocyte cancers identifies novel genome-wide loci Liyanage, Upekha E Law, Matthew H Han, Xikun An, Jiyuan Ong, Jue-Sheng Gharahkhani, Puya Gordon, Scott Neale, Rachel E Olsen, Catherine M MacGregor, Stuart Whiteman, David C Hum Mol Genet Association Studies Article The keratinocyte cancers (KC), basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) are the most common cancers in fair-skinned people. KC treatment represents the second highest cancer healthcare expenditure in Australia. Increasing our understanding of the genetic architecture of KC may provide new avenues for prevention and treatment. We first conducted a series of genome-wide association studies (GWAS) of KC across three European ancestry datasets from Australia, Europe and USA, and used linkage disequilibrium (LD) Score regression (LDSC) to estimate their pairwise genetic correlations. We employed a multiple-trait approach to map genes across the combined set of KC GWAS (total N = 47 742 cases, 634 413 controls). We also performed meta-analyses of BCC and SCC separately to identify trait specific loci. We found substantial genetic correlations (generally 0.5–1) between BCC and SCC suggesting overlapping genetic risk variants. The multiple trait combined KC GWAS identified 63 independent genome-wide significant loci, 29 of which were novel. Individual separate meta-analyses of BCC and SCC identified an additional 13 novel loci not found in the combined KC analysis. Three new loci were implicated using gene-based tests. New loci included common variants in BRCA2 (distinct to known rare high penetrance cancer risk variants), and in CTLA4, a target of immunotherapy in melanoma. We found shared and trait specific genetic contributions to BCC and SCC. Considering both, we identified a total of 79 independent risk loci, 45 of which are novel. Oxford University Press 2019-09-15 2019-06-07 /pmc/articles/PMC6737293/ /pubmed/31174203 http://dx.doi.org/10.1093/hmg/ddz121 Text en © The Author(s) 2019. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Association Studies Article
Liyanage, Upekha E
Law, Matthew H
Han, Xikun
An, Jiyuan
Ong, Jue-Sheng
Gharahkhani, Puya
Gordon, Scott
Neale, Rachel E
Olsen, Catherine M
MacGregor, Stuart
Whiteman, David C
Combined analysis of keratinocyte cancers identifies novel genome-wide loci
title Combined analysis of keratinocyte cancers identifies novel genome-wide loci
title_full Combined analysis of keratinocyte cancers identifies novel genome-wide loci
title_fullStr Combined analysis of keratinocyte cancers identifies novel genome-wide loci
title_full_unstemmed Combined analysis of keratinocyte cancers identifies novel genome-wide loci
title_short Combined analysis of keratinocyte cancers identifies novel genome-wide loci
title_sort combined analysis of keratinocyte cancers identifies novel genome-wide loci
topic Association Studies Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6737293/
https://www.ncbi.nlm.nih.gov/pubmed/31174203
http://dx.doi.org/10.1093/hmg/ddz121
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