Abstract 1833: Identification of abnormally expressed lincRNAs in breast cancer using high-density SNP arrays.
Authors: Jiang Zhengyu , Zhou Yan , Devarajan Karthik , Slater Carolyn M. , Daly Mary B. , Chen Xiaowei 
Published: August 2014

Abstract
Background: The intergenic portion of the human genome is pervasively transcribed to produce large numbers of long intergenic non-coding RNAs (lincRNAs), which are tentatively defined as RNA molecules of more than 200 nucleotides. LincRNAs participate in and regulate a wide array of transcriptional and posttranscriptional processes in both physiological and disease conditions. While dysregulation of lincRNAs expression has been observed in some cancers, their expression signatures in breast cancer are poorly characterized. Here, we established a novel genome-wide approach, employing high-density SNP arrays, to globally identify lincRNA genes whose expression is altered in breast cancers.
Methods: Both genomic DNA (gDNA) and double-stranded cDNA (ds-cDNA) samples from primary breast tumor and matched adjacent normal cells were hybridized onto Illumina HumanOmni5 BeadChips. This platform includes a total of 2,435,915 SNP loci dispersed at an average interval of ∼700 nt through the intergenic region of the human genome. We mapped annotated lincRNA genes or the linc-transcriptome to a subset of 332,539 or 8,661 SNP loci, which were included in our analysis for five tumor-normal paired primary human mammary epithelial cells (HMECs). Using gDNA intensity signals as a reference, differential expression of lincRNAs between tumor and normal samples were obtained through normalization, filtering and statistical analysis using paired t-tests.
Results: We found 47 lincRNA transcripts that were dysregulated in tumors (P&lt;0.01, FDR&lt;0.2, &gt;2-fold change), including 28 lincRNA transcripts being up-regulated, and 19 lincRNA transcripts being down-regulated. RT-qPCR was used to validate the top 14 gene hits (P&lt;0.005, FDR&lt;0.15, &gt;4-fold change). Expression profiling for these candidate lincRNAs were also extended to 12 established breast cancer and 4 non-cancerous cell lines. The up- and down- regulation patterns of these lincRNAs among different cell lines showed great variability in both their direction and magnitude of changes, indicating differential regulation of lincRNA levels and the roles they play in breast cancer cell lines.
Conclusions: This study established a novel high-resolution SNP array-based approach to identify specific lincRNAs. These breast cancer-susceptible lincRNAs could be putative regulators that contribute to breast tumorigenesis and offer tremendous potential for future investigations of their functional roles.
This work was kindly supported by the FCCC Personalized Risk and Prevention Keystone, the Susan G. Komen for the Cure (KG100274), and Eileen Stein Jacoby Fund.
Citation Format: Zhengyu Jiang, Yan Zhou, Karthik Devarajan, Carolyn M. Slater, Mary B. Daly, Xiaowei Chen. Identification of abnormally expressed lincRNAs in breast cancer using high-density SNP arrays. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 1833. doi:10.1158/1538-7445.AM2013-1833