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Genetic variation in the genome-wide predicted estrogen response element-related sequences is associated with breast cancer development.

ABSTRACT: INTRODUCTION: Estrogen forms a complex with the estrogen receptor (ER) that binds to estrogen response elements (EREs) in the promoter region of estrogen-responsive genes, regulates their transcription, and consequently mediates physiological or tumorigenic effects. Thus, sequence variants in EREs have the potential to affect the estrogen-ER-ERE interaction. In this study, we examined the hypothesis that genetic variations of EREs are associated with breast cancer development. METHODS: This case-control study involved 815 patients of Asian descent with incident breast cancer and 821 healthy female controls. A total of 13,737 ERE sites in the whole genome predicted by a genome-wide computational algorithm were blasted with single-nucleotide polymorphism (SNP) sequences. Twenty-one SNPs located within 2,000 bp upstream or within introns 1 and 2 of putative genes and with a minor allele frequency greater than 5% were identified and genotyped. Frequencies of SNPs were compared between cases and controls to identify SNPs associated with cancer susceptibility. RESULTS: A significant combined effect of rs12539530, an ERE SNP in intron 2 of NRCAM which codes for a cell adhesion molecule, and SNPs of ESR1, the gene coding for ER, on breast cancer risk was found. Interestingly, this combined effect was more significant in women who had experienced a longer period of lifetime estrogen exposure, supporting a hormonal etiology of this SNP in breast tumorigenesis. CONCLUSIONS: Our findings provide support for a role of genetic variation in ERE-ESR1 in determining susceptibility of breast cancer development.

SUBMITTER: Yu JC

PROVIDER: S-EPMC3109581 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature

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Genetic variation in the genome-wide predicted estrogen response element-related sequences is associated with breast cancer development.

Yu Jyh-Cherng JC Hsiung Chia-Ni CN Hsu Huan-Ming HM Bao Bo-Ying BY Chen Shou-Tung ST Hsu Giu-Cheng GC Chou Wen-Cheng WC Hu Ling-Yueh LY Ding Shian-Ling SL Cheng Chun-Wen CW Wu Pei-Ei PE Shen Chen-Yang CY

Breast cancer research : BCR 20110131 1

<h4>Introduction</h4>Estrogen forms a complex with the estrogen receptor (ER) that binds to estrogen response elements (EREs) in the promoter region of estrogen-responsive genes, regulates their transcription, and consequently mediates physiological or tumorigenic effects. Thus, sequence variants in EREs have the potential to affect the estrogen-ER-ERE interaction. In this study, we examined the hypothesis that genetic variations of EREs are associated with breast cancer development.<h4>Methods< ...[more]

PMID: 21281495

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Project description:Genome-wide association studies (GWAS) have identified more than 90 susceptibility loci for breast cancer, but the underlying biology of those associations needs to be further elucidated. More genetic factors for breast cancer are yet to be identified but sample size constraints preclude the identification of individual genetic variants with weak effects using traditional GWAS methods. To address this challenge, we utilized a gene-level expression-based method, implemented in the MetaXcan software, to predict gene expression levels for 11,536 genes using expression quantitative trait loci and examine the genetically-predicted expression of specific genes for association with overall breast cancer risk and estrogen receptor (ER)-negative breast cancer risk. Using GWAS datasets from a Challenge launched by National Cancer Institute, we identified TP53INP2 (tumor protein p53-inducible nuclear protein 2) at 20q11.22 to be significantly associated with ER-negative breast cancer (Z = -5.013, p = 5.35×10-7, Bonferroni threshold = 4.33×10-6). The association was consistent across four GWAS datasets, representing European, African and Asian ancestry populations. There are 6 single nucleotide polymorphisms (SNPs) included in the prediction of TP53INP2 expression and five of them were associated with estrogen-receptor negative breast cancer, although none of the SNP-level associations reached genome-wide significance. We conducted a replication study using a dataset outside of the Challenge, and found the association between TP53INP2 and ER-negative breast cancer was significant (p = 5.07x10-3). Expression of HP (16q22.2) showed a suggestive association with ER-negative breast cancer in the discovery phase (Z = 4.30, p = 1.70x10-5) although the association was not significant after Bonferroni adjustment. Of the 249 genes that are 250 kb within known breast cancer susceptibility loci identified from previous GWAS, 20 genes (8.0%) were statistically significant associated with ER-negative breast cancer (p<0.05), compared to 582 (5.2%) of 11,287 genes that are not close to previous GWAS loci. This study demonstrated that expression-based gene mapping is a promising approach for identifying cancer susceptibility genes.

Dataset Information

Genetic variation in the genome-wide predicted estrogen response element-related sequences is associated with breast cancer development.

Publications

Genetic variation in the genome-wide predicted estrogen response element-related sequences is associated with breast cancer development.

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