Identification of novel diagnostic biomarkers for thyroid carcinoma
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Xiliang Wang1,2, Qing Zhang1, Zhiming Cai1, Yifan Dai3 and Lisha Mou1
1Shenzhen Xenotransplantation Medical Engineering Research and Development Center, Institute of Translational Medicine, Shenzhen Second People's Hospital, First Affiliated Hospital of Shenzhen University, Shenzhen 518035, China
2Department of Biochemistry in Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou 510080, China
3Jiangsu Key Laboratory of Xenotransplantation, Nanjing Medical University, Nanjing 210029, China
Lisha Mou, email: email@example.com
Keywords: thyroid carcinoma; bioinformatics; dysregulation network; biomarker
Received: June 27, 2017 Accepted: November 19, 2017 Published: December 04, 2017
Thyroid carcinoma (THCA) is the most universal endocrine malignancy worldwide. Unfortunately, a limited number of large-scale analyses have been performed to identify biomarkers for THCA. Here, we conducted a meta-analysis using 505 THCA patients and 59 normal controls from The Cancer Genome Atlas. After identifying differentially expressed long non-coding RNA (lncRNA) and protein coding genes (PCG), we found vast difference in various lncRNA-PCG co-expressed pairs in THCA. A dysregulation network with scale-free topology was constructed. Four molecules (LA16c-380H5.2, RP11-203J24.8, MLF1 and SDC4) could potentially serve as diagnostic biomarkers of THCA with high sensitivity and specificity. We further represent a diagnostic panel with expression cutoff values. Our results demonstrate the potential application of those four molecules as novel independent biomarkers for THCA diagnosis.
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