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A Genome Wide Meta-Analysis Study for Identification of Common Variation Associated with Breast Cancer Prognosis

OBJECTIVE: Genome wide association studies (GWAs) of breast cancer mortality have identified few potential associations. The concordance between these studies is unclear. In this study, we used a meta-analysis of two prognostic GWAs and a replication cohort to identify the strongest associations and...

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Autores principales: Rafiq, Sajjad, Khan, Sofia, Tapper, William, Collins, Andrew, Upstill-Goddard, Rosanna, Gerty, Susan, Blomqvist, Carl, Aittomäki, Kristiina, Couch, Fergus J., Liu, Jianjun, Nevanlinna, Heli, Eccles, Diana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4272267/
https://www.ncbi.nlm.nih.gov/pubmed/25526632
http://dx.doi.org/10.1371/journal.pone.0101488
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author Rafiq, Sajjad
Khan, Sofia
Tapper, William
Collins, Andrew
Upstill-Goddard, Rosanna
Gerty, Susan
Blomqvist, Carl
Aittomäki, Kristiina
Couch, Fergus J.
Liu, Jianjun
Nevanlinna, Heli
Eccles, Diana
author_facet Rafiq, Sajjad
Khan, Sofia
Tapper, William
Collins, Andrew
Upstill-Goddard, Rosanna
Gerty, Susan
Blomqvist, Carl
Aittomäki, Kristiina
Couch, Fergus J.
Liu, Jianjun
Nevanlinna, Heli
Eccles, Diana
author_sort Rafiq, Sajjad
collection PubMed
description OBJECTIVE: Genome wide association studies (GWAs) of breast cancer mortality have identified few potential associations. The concordance between these studies is unclear. In this study, we used a meta-analysis of two prognostic GWAs and a replication cohort to identify the strongest associations and to evaluate the loci suggested in previous studies. We attempt to identify those SNPs which could impact overall survival irrespective of the age of onset. METHODS: To facilitate the meta-analysis and to refine the association signals, SNPs were imputed using data from the 1000 genomes project. Cox-proportional hazard models were used to estimate hazard ratios (HR) in 536 patients from the POSH cohort (Prospective study of Outcomes in Sporadic versus Hereditary breast cancer) and 805 patients from the HEBCS cohort (Helsinki Breast Cancer Study). These hazard ratios were combined using a Mantel-Haenszel fixed effects meta-analysis and a p-value threshold of 5×10(−8) was used to determine significance. Replication was performed in 1523 additional patients from the POSH study. RESULTS: Although no SNPs achieved genome wide significance, three SNPs have significant association in the replication cohort and combined p-values less than 5.6×10(−6). These SNPs are; rs421379 which is 556 kb upstream of ARRDC3 (HR = 1.49, 95% confidence interval (CI) = 1.27–1.75, P = 1.1×10(−6)), rs12358475 which is between ECHDC3 and PROSER2 (HR = 0.75, CI = 0.67–0.85, P = 1.8×10(−6)), and rs1728400 which is between LINC00917 and FOXF1. CONCLUSIONS: In a genome wide meta-analysis of two independent cohorts from UK and Finland, we identified potential associations at three distinct loci. Phenotypic heterogeneity and relatively small sample sizes may explain the lack of genome wide significant findings. However, the replication at three SNPs in the validation cohort shows promise for future studies in larger cohorts. We did not find strong evidence for concordance between the few associations highlighted by previous GWAs of breast cancer survival and this study.
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spelling pubmed-42722672014-12-26 A Genome Wide Meta-Analysis Study for Identification of Common Variation Associated with Breast Cancer Prognosis Rafiq, Sajjad Khan, Sofia Tapper, William Collins, Andrew Upstill-Goddard, Rosanna Gerty, Susan Blomqvist, Carl Aittomäki, Kristiina Couch, Fergus J. Liu, Jianjun Nevanlinna, Heli Eccles, Diana PLoS One Research Article OBJECTIVE: Genome wide association studies (GWAs) of breast cancer mortality have identified few potential associations. The concordance between these studies is unclear. In this study, we used a meta-analysis of two prognostic GWAs and a replication cohort to identify the strongest associations and to evaluate the loci suggested in previous studies. We attempt to identify those SNPs which could impact overall survival irrespective of the age of onset. METHODS: To facilitate the meta-analysis and to refine the association signals, SNPs were imputed using data from the 1000 genomes project. Cox-proportional hazard models were used to estimate hazard ratios (HR) in 536 patients from the POSH cohort (Prospective study of Outcomes in Sporadic versus Hereditary breast cancer) and 805 patients from the HEBCS cohort (Helsinki Breast Cancer Study). These hazard ratios were combined using a Mantel-Haenszel fixed effects meta-analysis and a p-value threshold of 5×10(−8) was used to determine significance. Replication was performed in 1523 additional patients from the POSH study. RESULTS: Although no SNPs achieved genome wide significance, three SNPs have significant association in the replication cohort and combined p-values less than 5.6×10(−6). These SNPs are; rs421379 which is 556 kb upstream of ARRDC3 (HR = 1.49, 95% confidence interval (CI) = 1.27–1.75, P = 1.1×10(−6)), rs12358475 which is between ECHDC3 and PROSER2 (HR = 0.75, CI = 0.67–0.85, P = 1.8×10(−6)), and rs1728400 which is between LINC00917 and FOXF1. CONCLUSIONS: In a genome wide meta-analysis of two independent cohorts from UK and Finland, we identified potential associations at three distinct loci. Phenotypic heterogeneity and relatively small sample sizes may explain the lack of genome wide significant findings. However, the replication at three SNPs in the validation cohort shows promise for future studies in larger cohorts. We did not find strong evidence for concordance between the few associations highlighted by previous GWAs of breast cancer survival and this study. Public Library of Science 2014-12-19 /pmc/articles/PMC4272267/ /pubmed/25526632 http://dx.doi.org/10.1371/journal.pone.0101488 Text en © 2014 Rafiq et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Rafiq, Sajjad
Khan, Sofia
Tapper, William
Collins, Andrew
Upstill-Goddard, Rosanna
Gerty, Susan
Blomqvist, Carl
Aittomäki, Kristiina
Couch, Fergus J.
Liu, Jianjun
Nevanlinna, Heli
Eccles, Diana
A Genome Wide Meta-Analysis Study for Identification of Common Variation Associated with Breast Cancer Prognosis
title A Genome Wide Meta-Analysis Study for Identification of Common Variation Associated with Breast Cancer Prognosis
title_full A Genome Wide Meta-Analysis Study for Identification of Common Variation Associated with Breast Cancer Prognosis
title_fullStr A Genome Wide Meta-Analysis Study for Identification of Common Variation Associated with Breast Cancer Prognosis
title_full_unstemmed A Genome Wide Meta-Analysis Study for Identification of Common Variation Associated with Breast Cancer Prognosis
title_short A Genome Wide Meta-Analysis Study for Identification of Common Variation Associated with Breast Cancer Prognosis
title_sort genome wide meta-analysis study for identification of common variation associated with breast cancer prognosis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4272267/
https://www.ncbi.nlm.nih.gov/pubmed/25526632
http://dx.doi.org/10.1371/journal.pone.0101488
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