SNPs in lncRNA Regions and Breast Cancer Risk

lncRNA区域中的SNP与乳腺癌风险

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Abstract

Long non-coding RNAs (lncRNAs) play crucial roles in human physiology, and have been found to be associated with various cancers. Transcribed ultraconserved regions (T-UCRs) are a subgroup of lncRNAs conserved in several species, and are often located in cancer-related regions. Breast cancer is the most common cancer in women worldwide and the leading cause of female cancer deaths. We investigated the association of genetic variants in lncRNA and T-UCR regions with breast cancer risk to uncover candidate loci for further analysis. Our focus was on low-penetrance variants that can be discovered in a large dataset. We selected 565 regions of lncRNAs and T-UCRs that are expressed in breast or breast cancer tissue, or show expression correlation to major breast cancer associated genes. We studied the association of single nucleotide polymorphisms (SNPs) in these regions with breast cancer risk in the 122970 case samples and 105974 controls of the Breast Cancer Association Consortium's genome-wide data, and also by in silico functional analyses using Integrated Expression Quantitative trait and in silico prediction of GWAS targets (INQUISIT) and expression quantitative trait loci (eQTL) analysis. The eQTL analysis was carried out using the METABRIC dataset and analyses from GTEx and ncRNA eQTL databases. We found putative breast cancer risk variants (p < 1 × 10(-5)) targeting the lncRNA GABPB1-AS1 in INQUISIT and eQTL analysis. In addition, putative breast cancer risk associated SNPs (p < 1 × 10(-5)) in the region of two T-UCRs, uc.184 and uc.313, located in protein coding genes CPEB4 and TIAL1, respectively, targeted these genes in INQUISIT and in eQTL analysis. Other non-coding regions containing SNPs with the defined p-value and highly significant false discovery rate (FDR) for breast cancer risk association were discovered that may warrant further studies. These results suggest candidate lncRNA loci for further research on breast cancer risk and the molecular mechanisms.

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