Genome-Wide Transcript Profiling Reveals Novel Breast Cancer-Associated Intronic Sense RNAs

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RESEARCH ARTICLE

Genome-Wide Transcript Profiling Reveals Novel Breast Cancer-Associated Intronic Sense RNAs Sang Woo Kim1☯, Elane Fishilevich1☯, Gustavo Arango-Argoty1☯, Yuefeng Lin1, Guodong Liu1, Zhihua Li1, A. Paula Monaghan2*, Mark Nichols3*, Bino John1* 1 University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15260, United States of America, 2 Department of Neurobiology, University of Pittsburgh, 3501 Fifth Ave, Pittsburgh, Pennsylvania 15260, United States of America, 3 Department of Pharmacology and Chemical Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15260, United States of America ☯ These authors contributed equally to this work. * [email protected] (BJ); [email protected] (MN); [email protected] (APM)

Abstract OPEN ACCESS Citation: Kim SW, Fishilevich E, Arango-Argoty G, Lin Y, Liu G, Li Z, et al. (2015) Genome-Wide Transcript Profiling Reveals Novel Breast CancerAssociated Intronic Sense RNAs. PLoS ONE 10(3): e0120296. doi:10.1371/journal.pone.0120296 Academic Editor: Rajeev Samant, University of Alabama at Birmingham, UNITED STATES Received: July 16, 2014 Accepted: January 26, 2015 Published: March 23, 2015 Copyright: © 2015 Kim et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Non-coding RNAs (ncRNAs) play major roles in development and cancer progression. To identify novel ncRNAs that may identify key pathways in breast cancer development, we performed high-throughput transcript profiling of tumor and normal matched-pair tissue samples. Initial transcriptome profiling using high-density genome-wide tiling arrays revealed changes in over 200 novel candidate genomic regions that map to intronic regions. Sixteen genomic loci were identified that map to the long introns of five key protein-coding genes, CRIM1, EPAS1, ZEB2, RBMS1, and RFX2. Consistent with the known role of the tumor suppressor ZEB2 in the cancer-associated epithelial to mesenchymal transition (EMT), in situ hybridization reveals that the intronic regions deriving from ZEB2 as well as those from RFX2 and EPAS1 are down-regulated in cells of epithelial morphology, suggesting that these regions may be important for maintaining normal epithelial cell morphology. Paired-end deep sequencing analysis reveals a large number of distinct genomic clusters with no coding potential within the introns of these genes. These novel transcripts are only transcribed from the coding strand. A comprehensive search for breast cancer associated genes reveals enrichment for transcribed intronic regions from these loci, pointing to an underappreciated role of introns or mechanisms relating to their biology in EMT and breast cancer.

Data Availability Statement: All relevant data are within the paper and its Supporting Information files. Funding: The work was supported by American Cancer Society [RSG-09-054-01 to BJ] - www.cancer. org/, Magee-Womens foundation [0027467 to BJ] www.mwrif.org; and National Institutes of Health [GM079756 to BJ] - www.nih.gov. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist.

Introduction Advances in gene expression profiling using technologies such as whole genome tiling arrays (GTAs) and deep-sequencing (“next-gen”) within the last decade have resulted in the unexpected realization that ~90% of the human genome is transcribed [1, 2]. While many important classes of non-protein coding RNAs (ncRNAs) have been identified, ranging from small RNAs

PLOS ONE | DOI:10.1371/journal.pone.0120296 March 23, 2015

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Novel Breast Cancer-Associated Intronic Sense RNAs

such as microRNAs (miRNAs) to long noncoding RNAs (lncRNAs) [3], to extraordinarily long ncRNAs such as the 108 kb Air transcript [4], the functions of most ncRNAs remain unknown [5]. One approach to discover important RNAs is to identify those that are dysregulated in diseases. While genes can associate with a disease as a side-effect of an aberrant mechanism, minimally, the identification of disease-associated RNAs can lead to the discovery of new molecular mechanisms that can aid in the diagnosis or prognosis of the disease, and sometimes lead to a therapeutic path [6]. For example, transcriptome sequencing in cancer tissues has led to the discovery of novel ncRNAs such as PCAT-1, a specific regulator of cell proliferation [7] and chimeric, cancer-associated RNAs [8]. Breast cancer treatment has been revolutionized in the recent decades with the use of individual biomarkers such as ERα and HER2/neu [9]. Gene expression profiling studies in the past decade have also led to the development of multi-gene biomarkers [9] such as MammaPrint, a 70 gene diagnostic test used to evaluate whether patients would benefit from chemotherapy [10]. In addition to the clinically established biomarkers that are all based on protein-coding genes, several new promising candidate biomarkers have been found to correlate with breast cancer. Dozens of lncRNAs from the HOX gene cluster were recently found to have reduced expression in breast cancer [11], while other HOX lncRNAs were detected in primary tumors but not in metastatic breast cancer. The metastasis-associated HOTAIR, a 2.2 kb long intergenic ncRNA, is overexpressed in metastases, and its high level of expression in primary breast tumors is a predictor of metastasis and death [11]. These results may lead to the identification of new biomarkers, better understanding of molecular classification of breast cancer sub-types [12]. To identify biomarkers for breast cancer, we conducted an unbiased screen of the human transcriptome. We used GTAs for genome-wide expression profiling to identify genes that were altered in cancer versus control human breast cancer samples. Approximately 200 potential breast-cancer markers were identified and validated by quantitative PCR. This study focuses on 16 genomic regions that were significantly (p
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