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. 2010;12(6):R93.
doi: 10.1186/bcr2772. Epub 2010 Nov 9.

A genome-wide association scan on estrogen receptor-negative breast cancer

Jingmei Li  1 , Keith Humphreys, Hatef Darabi, Gustaf Rosin, Ulf Hannelius, Tuomas Heikkinen, Kristiina Aittomäki, Carl Blomqvist, Paul Dp Pharoah, Alison M Dunning, Shahana Ahmed, Maartje J Hooning, Antoinette Hollestelle, Rogier A Oldenburg, Lars Alfredsson, Aarno Palotie, Leena Peltonen-Palotie, Astrid Irwanto, Hui Qi Low, Garrett Hk Teoh, Anbupalam Thalamuthu, Juha Kere, Mauro D'Amato, Douglas F Easton, Heli Nevanlinna, Jianjun Liu, Kamila Czene, Per Hall
Affiliations

A genome-wide association scan on estrogen receptor-negative breast cancer

Jingmei Li et al. Breast Cancer Res. 2010.

Abstract

Introduction: Breast cancer is a heterogeneous disease and may be characterized on the basis of whether estrogen receptors (ER) are expressed in the tumour cells. ER status of breast cancer is important clinically, and is used both as a prognostic indicator and treatment predictor. In this study, we focused on identifying genetic markers associated with ER-negative breast cancer risk.

Methods: We conducted a genome-wide association analysis of 285,984 single nucleotide polymorphisms (SNPs) genotyped in 617 ER-negative breast cancer cases and 4,583 controls. We also conducted a genome-wide pathway analysis on the discovery dataset using permutation-based tests on pre-defined pathways. The extent of shared polygenic variation between ER-negative and ER-positive breast cancers was assessed by relating risk scores, derived using ER-positive breast cancer samples, to disease state in independent, ER-negative breast cancer cases.

Results: Association with ER-negative breast cancer was not validated for any of the five most strongly associated SNPs followed up in independent studies (1,011 ER-negative breast cancer cases, 7,604 controls). However, an excess of small P-values for SNPs with known regulatory functions in cancer-related pathways was found (global P = 0.052). We found no evidence to suggest that ER-negative breast cancer shares a polygenic basis to disease with ER-positive breast cancer.

Conclusions: ER-negative breast cancer is a distinct breast cancer subtype that merits independent analyses. Given the clinical importance of this phenotype and the likelihood that genetic effect sizes are small, greater sample sizes and further studies are required to understand the etiology of ER-negative breast cancers.

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Figures

Figure 1
Figure 1
Schematic diagram of analytical strategies for agnostic single marker association analysis and pathway analysis.
Figure 2
Figure 2
Summary of scoring procedure for assessment of common polygenic variation.
Figure 3
Figure 3
Genome-wide P-values (-log10P) of the logistic regression analysis plotted against chromosomal position.
Figure 4
Figure 4
Plot of regional association signals for rs361147 forwarded for validation.
Figure 5
Figure 5
Plot of regional association signals for rs7039994 forwarded for validation.
Figure 6
Figure 6
Plot of regional association signals for rs6993922 forwarded for validation.
Figure 7
Figure 7
Plot of regional association signals for rs4726078 forwarded for validation.
Figure 8
Figure 8
Plot of regional association signals for rs3777218 forwarded for validation.
Figure 9
Figure 9
Distribution of P-values of regulatory SNPs within KEGG cancer pathways (pathway identifiers beginning with hsa052*). *Global P-values of cancer-related regulatory SNPs with P < 0.05 in the genome-wide association analysis using the admixture maximum likelihood test (5,000 permutations) are 0.0028 (unadjusted), and 0.052 (with adjustments made to correct for population stratification).
Figure 10
Figure 10
Proportion of shared polygenic component between breast cancer estrogen receptor subtypes. Proportion of shared polygenic component between ER-positive and ER-negative target samples, with respect to their corresponding ER-positive training samples. Pt denotes P-value cut-off in training sample. a) Test for association between polygenic score and disease status (ER-positive/ER-negative) in the Swedish data, when all SNPs with P < 0.5 in the Finnish training set were considered. b) Test for association between polygenic score and disease status (ER-positive/ER-negative) in the Finnish data, when all SNPs with P < 0.5 in the Swedish training set were considered. c) Significance test for difference in scores (Finnish ER-positive breast cancers derived) between Swedish ER-negative and ER-positive breast cancers, adjusted for number of non-missing genotypes. Significance codes: '- ' 0.1 <P < 1 (that is, not significant). d) Significance test for difference in scores (Swedish ER-positive breast cancers derived) between Finnish ER-negative and ER-positive breast cancers, adjusted for number of non-missing genotypes. Significance codes: '*' 0.01 <P < 0.05.
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