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. 2017 Feb 23:3:4.
doi: 10.1038/s41523-017-0005-y. eCollection 2017.

Constitutional variants are not associated with HER2-positive breast cancer: results from the SIGNAL/PHARE clinical cohort

Xavier Pivot  1 , Gilles Romieu  2 , Pierre Fumoleau  3 , Maria Rios  4 , Hervé Bonnefoi  5 , Thomas Bachelot  6 , Patrick Soulié  7 , Christelle Jouannaud  8 , Hugues Bourgeois  9 , Thierry Petit  10 , Isabelle Tennevet  11 , David Assouline  12 , Marie-Christine Mathieu  13 , Jean-Philippe Jacquin  14 , Sandrine Lavau-Denes  15 , Ariane Darut-Jouve  16 , Jean-Marc Ferrero  17 , Carole Tarpin  18 , Christelle Lévy  19 , Valérie Delecroix  20 , Véronique Trillet-Lenoir  21 , Oana Cojocarasu  22 , Jérôme Meunier  23 , Jean-Yves Pierga  24 , Cécile Agostini  25 , Pierre Kerbrat  26 , Céline Faure-Mercier  27 , Hélène Blanché  28 , Mourad Sahbatou  28 , Anne Boland  29 , Delphine Bacq  29 , Céline Besse  29 , Fabien Calvo  13 , Alexia Renaud  30 , Jean-François Deleuze  28   29 , Iris Pauporté  27 , Gilles Thomas  31 , David G Cox  30
Affiliations

Constitutional variants are not associated with HER2-positive breast cancer: results from the SIGNAL/PHARE clinical cohort

Xavier Pivot et al. NPJ Breast Cancer. .

Abstract

Human epidermal growth factor receptor 2-positive breast cancer is a subtype of interest regarding its outcome and the impressive impact of human epidermal growth factor receptor 2 targeted therapy. Constitutional variants may be involved in the aetiology of human epidermal growth factor receptor 2-positive breast cancer, and we propose a case-case study to test the hypothesis that single nucleotide polymorphisms may be associated with human epidermal growth factor receptor 2 status. A Genome-Wide Association Study was used in a cohort of 9836 patients from the SIGNAL/PHARE study (NCT00381901-RECF1098). The main goal was to identify variants specifically related to human epidermal growth factor receptor 2-positive breast cancer. A two-staged genotyping strategy was carried out to cover as large a proportion of the genome as possible. All subjects were genotyped using the Illumina HumanCore Exome chip set. Principal Components Analysis and k-means were then used to characterize the ancestry of the participants. A random sample of subjects from the main "European" cluster was genotyped with the Omni5 chip set. These data were then used to impute missing genotypes from the remaining subjects genotyped only using the HumanCore Exome array. From the 9836 patients, a total of 8703 cases including 3230 patients with human epidermal growth factor receptor 2-positive breast cancer were analyzed. Despite having 80% power to detect an odds ratio of 1.23 in this population, no variant achieved genome-wide significance for association with the occurrence of human epidermal growth factor receptor 2-positive breast cancer vs. any other subtype of breast tumour. Our study was unable to identify constitutional polymorphisms that are strongly associated with human epidermal growth factor receptor 2-positive status among breast cancer patients.

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Figures

Fig. 1
Fig. 1
Subjects retained for analyses based on genotyping
Fig. 2
Fig. 2
Manhattan plot of associations between SNPs and HER2 status. Association testing has been carried out using the additive model and logistic regression using the ProbABEL function. Models were corrected for the first two principal components and age at diagnosis. The blue horizontal line represents the arbitrary 1.0 × 10−5 threshold, while the red horizontal line corresponds to the empiric threshold of 1.48 × 10−7 as calculated using simpleM followed by Bonferroni correction
Fig. 3
Fig. 3
Quantile–Quantile plot of p-values from the GWAS of HER2 status. Analyses from 8703 patients, 3230 of whom are HER2-positive, are represented. 914144 variants were included in these analyses. The gray area highlights the zone of potentially associated variants
Fig. 4
Fig. 4
LocusView 1 plot of SNP with the strongest association with HER2 status. Adjusted for age and the two first component of the PCA
See this image and copyright information in PMC

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