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Open Access Research article

Identifying breast cancer risk loci by global differential allele-specific expression (DASE) analysis in mammary epithelial transcriptome

Chuan Gao1, Karthik Devarajan2, Yan Zhou3, Carolyn M Slater1, Mary B Daly4 and Xiaowei Chen1*

Author affiliations

1 Cancer Epigenetics Program, Fox Chase Cancer Center, 333 Cottman Avenue, Philadelphia, PA, 19111, USA

2 Department of Biostatics and Bioinformatics, Fox Chase Cancer Center, Philadelphia, PA, 19111, USA

3 Department of Biostatics and Bioinformatics, Fox Chase Cancer Center, Philadelphia, PA, 19111, USA

4 Department of Clinical Genetics, Fox Chase Cancer Center, Philadelphia, PA, 19111, USA

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Citation and License

BMC Genomics 2012, 13:570  doi:10.1186/1471-2164-13-570

Published: 30 October 2012

Abstract

Background

The significant mortality associated with breast cancer (BCa) suggests a need to improve current research strategies to identify new genes that predispose women to breast cancer. Differential allele-specific expression (DASE) has been shown to contribute to phenotypic variables in humans and recently to the pathogenesis of cancer. We previously reported that nonsense-mediated mRNA decay (NMD) could lead to DASE of BRCA1/2, which is associated with elevated susceptibility to breast cancer. In addition to truncation mutations, multiple genetic and epigenetic factors can contribute to DASE, and we propose that DASE is a functional index for cis-acting regulatory variants and pathogenic mutations, and that global analysis of DASE in breast cancer precursor tissues can be used to identify novel causative alleles for breast cancer susceptibility.

Results

To test our hypothesis, we employed the Illumina® Omni1-Quad BeadChip in paired genomic DNA (gDNA) and double-stranded cDNA (ds-cDNA) samples prepared from eight BCa patient-derived normal mammary epithelial lines (HMEC). We filtered original array data according to heterozygous genotype calls and calculated DASE values using the Log ratio of cDNA allele intensity, which was normalized to the corresponding gDNA. We developed two statistical methods, SNP- and gene-based approaches, which allowed us to identify a list of 60 candidate DASE loci (DASE ≥ 2.00, P ≤ 0.01, FDR ≤ 0.05) by both methods. Ingenuity Pathway Analysis of DASE loci revealed one major breast cancer-relevant interaction network, which includes two known cancer causative genes, ZNF331 (DASE = 2.31, P = 0.0018, FDR = 0.040) and USP6 (DASE = 4.80, P = 0.0013, FDR = 0.013), and a breast cancer causative gene, DMBT1 (DASE=2.03, P = 0.0017, FDR = 0.014). Sequence analysis of a 5′ RACE product of DMBT1 demonstrated that rs2981745, a putative breast cancer risk locus, appears to be one of the causal variants leading to DASE in DMBT1.

Conclusions

Our study demonstrated for the first time that global DASE analysis is a powerful new approach to identify breast cancer risk allele(s).

Keywords:
Differential allele-specific expression; Breast cancer susceptibility; SNP array; DMBT1