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Identifying breast cancer risk loci by global differential allele-specific expression (DASE) analysis in mammary epithelial transcriptome
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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3532379/ https://www.ncbi.nlm.nih.gov/pubmed/23107584 http://dx.doi.org/10.1186/1471-2164-13-570 |
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author | Gao, Chuan Devarajan, Karthik Zhou, Yan Slater, Carolyn M Daly, Mary B Chen, Xiaowei |
author_facet | Gao, Chuan Devarajan, Karthik Zhou, Yan Slater, Carolyn M Daly, Mary B Chen, Xiaowei |
author_sort | Gao, Chuan |
collection | PubMed |
description | 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). |
format | Online Article Text |
id | pubmed-3532379 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-35323792013-01-03 Identifying breast cancer risk loci by global differential allele-specific expression (DASE) analysis in mammary epithelial transcriptome Gao, Chuan Devarajan, Karthik Zhou, Yan Slater, Carolyn M Daly, Mary B Chen, Xiaowei BMC Genomics Research Article 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). BioMed Central 2012-10-30 /pmc/articles/PMC3532379/ /pubmed/23107584 http://dx.doi.org/10.1186/1471-2164-13-570 Text en Copyright ©2012 Gao et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Gao, Chuan Devarajan, Karthik Zhou, Yan Slater, Carolyn M Daly, Mary B Chen, Xiaowei Identifying breast cancer risk loci by global differential allele-specific expression (DASE) analysis in mammary epithelial transcriptome |
title | Identifying breast cancer risk loci by global differential allele-specific expression (DASE) analysis in mammary epithelial transcriptome |
title_full | Identifying breast cancer risk loci by global differential allele-specific expression (DASE) analysis in mammary epithelial transcriptome |
title_fullStr | Identifying breast cancer risk loci by global differential allele-specific expression (DASE) analysis in mammary epithelial transcriptome |
title_full_unstemmed | Identifying breast cancer risk loci by global differential allele-specific expression (DASE) analysis in mammary epithelial transcriptome |
title_short | Identifying breast cancer risk loci by global differential allele-specific expression (DASE) analysis in mammary epithelial transcriptome |
title_sort | identifying breast cancer risk loci by global differential allele-specific expression (dase) analysis in mammary epithelial transcriptome |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3532379/ https://www.ncbi.nlm.nih.gov/pubmed/23107584 http://dx.doi.org/10.1186/1471-2164-13-570 |
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