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Nongenic cancer-risk SNPs affect oncogenes, tumour-suppressor genes, and immune function

BACKGROUND: Genome-wide association studies (GWASes) have identified many noncoding germline single-nucleotide polymorphisms (SNPs) that are associated with an increased risk of developing cancer. However, how these SNPs affect cancer risk is still largely unknown. METHODS: We used a systems biology...

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Autores principales: Fagny, Maud, Platig, John, Kuijjer, Marieke Lydia, Lin, Xihong, Quackenbush, John
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7028992/
https://www.ncbi.nlm.nih.gov/pubmed/31806877
http://dx.doi.org/10.1038/s41416-019-0614-3
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author Fagny, Maud
Platig, John
Kuijjer, Marieke Lydia
Lin, Xihong
Quackenbush, John
author_facet Fagny, Maud
Platig, John
Kuijjer, Marieke Lydia
Lin, Xihong
Quackenbush, John
author_sort Fagny, Maud
collection PubMed
description BACKGROUND: Genome-wide association studies (GWASes) have identified many noncoding germline single-nucleotide polymorphisms (SNPs) that are associated with an increased risk of developing cancer. However, how these SNPs affect cancer risk is still largely unknown. METHODS: We used a systems biology approach to analyse the regulatory role of cancer-risk SNPs in thirteen tissues. By using data from the Genotype-Tissue Expression (GTEx) project, we performed an expression quantitative trait locus (eQTL) analysis. We represented both significant cis- and trans-eQTLs as edges in tissue-specific eQTL bipartite networks. RESULTS: Each tissue-specific eQTL network is organised into communities that group sets of SNPs and functionally related genes. When mapping cancer-risk SNPs to these networks, we find that in each tissue, these SNPs are significantly overrepresented in communities enriched for immune response processes, as well as tissue-specific functions. Moreover, cancer-risk SNPs are more likely to be ‘cores’ of their communities, influencing the expression of many genes within the same biological processes. Finally, cancer-risk SNPs preferentially target oncogenes and tumour-suppressor genes, suggesting that they may alter the expression of these key cancer genes. CONCLUSIONS: This approach provides a new way of understanding genetic effects on cancer risk and provides a biological context for interpreting the results of GWAS cancer studies.
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spelling pubmed-70289922020-02-27 Nongenic cancer-risk SNPs affect oncogenes, tumour-suppressor genes, and immune function Fagny, Maud Platig, John Kuijjer, Marieke Lydia Lin, Xihong Quackenbush, John Br J Cancer Article BACKGROUND: Genome-wide association studies (GWASes) have identified many noncoding germline single-nucleotide polymorphisms (SNPs) that are associated with an increased risk of developing cancer. However, how these SNPs affect cancer risk is still largely unknown. METHODS: We used a systems biology approach to analyse the regulatory role of cancer-risk SNPs in thirteen tissues. By using data from the Genotype-Tissue Expression (GTEx) project, we performed an expression quantitative trait locus (eQTL) analysis. We represented both significant cis- and trans-eQTLs as edges in tissue-specific eQTL bipartite networks. RESULTS: Each tissue-specific eQTL network is organised into communities that group sets of SNPs and functionally related genes. When mapping cancer-risk SNPs to these networks, we find that in each tissue, these SNPs are significantly overrepresented in communities enriched for immune response processes, as well as tissue-specific functions. Moreover, cancer-risk SNPs are more likely to be ‘cores’ of their communities, influencing the expression of many genes within the same biological processes. Finally, cancer-risk SNPs preferentially target oncogenes and tumour-suppressor genes, suggesting that they may alter the expression of these key cancer genes. CONCLUSIONS: This approach provides a new way of understanding genetic effects on cancer risk and provides a biological context for interpreting the results of GWAS cancer studies. Nature Publishing Group UK 2019-12-06 2020-02-18 /pmc/articles/PMC7028992/ /pubmed/31806877 http://dx.doi.org/10.1038/s41416-019-0614-3 Text en © The Author(s) 2019 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Fagny, Maud
Platig, John
Kuijjer, Marieke Lydia
Lin, Xihong
Quackenbush, John
Nongenic cancer-risk SNPs affect oncogenes, tumour-suppressor genes, and immune function
title Nongenic cancer-risk SNPs affect oncogenes, tumour-suppressor genes, and immune function
title_full Nongenic cancer-risk SNPs affect oncogenes, tumour-suppressor genes, and immune function
title_fullStr Nongenic cancer-risk SNPs affect oncogenes, tumour-suppressor genes, and immune function
title_full_unstemmed Nongenic cancer-risk SNPs affect oncogenes, tumour-suppressor genes, and immune function
title_short Nongenic cancer-risk SNPs affect oncogenes, tumour-suppressor genes, and immune function
title_sort nongenic cancer-risk snps affect oncogenes, tumour-suppressor genes, and immune function
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7028992/
https://www.ncbi.nlm.nih.gov/pubmed/31806877
http://dx.doi.org/10.1038/s41416-019-0614-3
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