Research Article Circulating Long RNAs in Serum Extracellular Vesicles: Their Characterization and Potential Application as Biomarkers for Diagnosis of Colorectal Cancer Lei Dong 1,2,3 , Wanrun Lin 1,2,3 , Peng Qi 1,2,3 , Mi-die Xu 1,2,3 , Xiaoben Wu 4 , Shujuan Ni 1,2,3 , Dan Huang 1,2,3 , Wei-wei Weng 1,2,3 , Cong Tan 1,2,3 , Weiqi Sheng 1,2,3 , Xiaoyan Zhou 1,2,3 , and Xiang Du 1,2,3 Abstract Background: Long noncoding RNA (lncRNA) and mRNAs are long RNAs (200 nucleotides) compared with miRNAs. In blood, long RNAs may be protected by serum extracellular vesicles, such as apoptotic bodies (AB), microvesicles (MV), and exosomes (EXO). They are potential biomarkers for iden- tifying cancer. Methods: Sera from 76 preoperative colorectal cancer patients, 76 age- and sex-matched healthy subjects, and 20 colorectal adenoma patients without colorectal cancer were collected. We investigated the distribution of long RNAs into the three vesicles. Seventy-nine cancer-related long RNAs were chosen and detected using qPCR. Results: The quantity of long RNA has varying distribution among three subtypes of extracellular vesicles in serum. Most mRNA and lncRNA genes had higher quantity in EXOs than that in ABs and MVs, whereas MVs contain lowest quantity. We investigated 79 long RNAs chosen from The Cancer Genome Atlas and the LncRNADisease database in the sera of healthy patients, and those with colorectal cancer. In the training and test sets, the AUCs were 0.936 and 0.877, respectively. The AUC of total serum RNA was lower (0.857) than that of exosomal RNA in the same samples (0.936). Conclusion: The present study shows that exosomal mRNAs and lncRNAs in serum could be used as biomarkers to detect colorectal cancer. Impact: Among three types of vesicles in sera, EXOs were the richest reservoir for almost all measured long RNAs. The combi- nation of two mRNAs, KRTAP5-4 and MAGEA3, and one lncRNA, BCAR4, could be potential candidates to detect colorectal cancer. Cancer Epidemiol Biomarkers Prev; 25(7); 1158–66. Ó2016 AACR. Introduction Cancer has become the leading cause of morbidity and mor- tality globally. It is estimated that the death toll of cancer will continue to increase in the coming decades. Lack of effective early diagnosis, efficient monitoring, and cancer management are among the main drivers of increased cancer deaths (1). For example, colorectal cancer is the third most common cancer and the third leading cause of cancer-related death in men and women in the United States. Every year, it is estimated that more than 130,000 people will be diagnosed with colorectal cancer, and about 50,000 people will die of the disease (2). Minimally invasive and clinically validated biomarkers that can detect cancer at an early stage and be able to monitor its progression are urgently needed. RNA plays an important role in carcinogenesis. There are various types of RNA in the human body. Messenger RNA (mRNA, average length 1,000–1,500), microRNA (miRNA, 200 nucleotides), and long noncoding RNA (lncRNAs, 200 nucleotides) are closely studied due to their association with cancer. mRNAs, such as adenomatous polyposis coli (APC), and Kirsten rat sarcoma viral oncogene homolog (KRAS) can directly participate in the development of colorectal cancer as tumor suppressor genes and oncogenes (3). As non- coding RNAs, miRNA, and lncRNA can indirectly result in up- or downregulation of targeted mRNAs specific to tumor pro- moters or inhibitor genes, nearly 100 dysregulated miRNAs have been identified in relation to colorectal cancer, and each is able to affect the expression of more than one targeted mRNA (4). lncRNAs affect cancer through various mechanism, such as chromatin remodeling, chromatin interaction, competing endogenous RNAs, and natural antisense transcripts. More than a dozen lncRNAs are associated with colorectal cancer (5). The number of colorectal cancer–related lncRNAs is expected to rise as research progresses. Circulating nucleic acids (CNA) are novel sources used to hunt cancer biomarkers (6, 7). Compared with DNA, RNA directly represents the expression level of certain genes, which might 1 Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China. 2 Department of Oncology, Shanghai Medical Col- lege, Fudan University, Shanghai, China. 3 Institute of Pathology, Fudan University, Shanghai, China. 4 Clinical Laboratory, Shandong Provincial Hospital, Jinan, Shandong, China. Note: Supplementary data for this article are available at Cancer Epidemiology, Biomarkers & Prevention Online (http://cebp.aacrjournals.org/). L. Dong and W. Lin contributed equally to this article. Corresponding Author: Xiang Du, Fudan University Shanghai Cancer Center, 270 Dongan Road, Xuhui District, Shanghai 200032, China. Phone: 086-21- 64175590; Fax: 086-21-64174774; E-mail: dx2008cn@163.com doi: 10.1158/1055-9965.EPI-16-0006 Ó2016 American Association for Cancer Research. Cancer Epidemiology, Biomarkers & Prevention Cancer Epidemiol Biomarkers Prev; 25(7) July 2016 1158 Downloaded from http://aacrjournals.org/cebp/article-pdf/25/7/1158/2281435/1158.pdf by guest on 19 June 2022