ArticleBMC genomics2012
Identifying breast cancer risk loci by global differential allele-specific expression (DASE) analysis in mammary epithelial transcriptome.
Article in BMC genomics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed, 29 citations in OpenAlex.
- Identification of candidate causal variants and target genes at 41 breast cancer risk loci through differential allelic expression analysis.Scientific reports · 2024Article
- Caveolin-1, a Determinant of the Fate of MCF-7 Breast Cancer Cells.Breast cancer : basic and clinical research · 2024Article
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- Accelerated aging in normal breast tissue of women with breast cancer.Breast cancer research : BCR · 2021Article
- The Hypertension Related Gene G-Protein Coupled Receptor Kinase 4 Contributes to Breast Cancer Proliferation.Breast cancer : basic and clinical research · 2021Article
- Tumor suppressor genes and allele-specific expression: mechanisms and significance.Oncotarget · 2020Article
- The Protein Encoded by the CCDC170 Breast Cancer Gene Functions to Organize the Golgi-Microtubule Network.EBioMedicine · 2017Article
- LincIN, a novel NF90-binding long non-coding RNA, is overexpressed in advanced breast tumors and involved in metastasis.Breast cancer research : BCR · 2017Article
- Transcriptional Selectivity of Epigenetic Therapy in Cancer.Cancer research · 2017Article
- Extensive variation between tissues in allele specific expression in an outbred mammal.BMC genomics · 2015Article
- Alterations in Salivary Proteome following Single Twenty-Minute Session of Yogic Breathing.Evidence-based complementary and alternative medicine : eCAM · 2015Article
- Tumor haplotype assembly algorithms for cancer genomics.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2014Article
- Whole transcriptome RNA-Seq allelic expression in human brain.BMC genomics · 2013Article
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe 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.
resultsTo 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.
conclusionsOur study demonstrated for the first time that global DASE analysis is a powerful new approach to identify breast cancer risk allele(s).
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