19 December 2019 : Clinical Research
Identification of Long Non-Coding RNA Expression Profiles and Co-Expression Genes in Thyroid Carcinoma Based on The Cancer Genome Atlas (TCGA) DatabaseYun Zhang1B, Taobo Jin1C, Haipeng Shen1D, Junfeng Yan1E, Ming Guan1F, Xin Jin1AG*
Med Sci Monit 2019; 25:9752-9769
BACKGROUND: Thyroid carcinoma is a malignancy with high morbidity and mortality. Genetic alterations play pivot roles in the pathogenesis of thyroid carcinoma, where long noncoding RNA (lncRNA) have been identified to be crucial. This study sought to investigate the biological functions of lncRNA expression profiles in thyroid carcinoma.
MATERIAL AND METHODS: The lncRNAs expression profiles were acquired from The Cancer Genome Atlas (TCGA) database according to 510 thyroid cancer tissues and 58 normal thyroid tissues. By using R package edgeR, differentially expressed RNAs were obtained. Also, an overall survival model was established based on Cox regression and clinical data then testified by Kaplan-Meier plot, receiver operating characteristic (ROC)-curve and C-index analysis. We investigated the co-expressed genes with lncRNAs involved in the prognostic model, as well as Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was conducted R package clusterProfile.
RESULTS: A total of 352 lncRNAs were identified as differentially expressed in thyroid carcinoma, and an overall survival model consisting of 8 signature lncRNAs was proposed (ROC=0.862, C-index=0.893, P<0.05), 3 of which (DOCK9-DT, FAM111A-DT, and LINC01736) represent co-expressed mRNAs. However, as an oncogene, only FAM111A-DT increased the prognostic risk in thyroid carcinoma. Furthermore, we found differential genes LINC01016, LHX1-DT, IGF2-AS, ND MIR1-1HG-AS1, significantly related to lymph node metastasis (P<0.05).
CONCLUSIONS: In this study, we clarified the differential lncRNA expression profiles which were related to the tumorigenesis and prognosis in thyroid carcinoma. Our results provide new rationale and understandings to the pathogenesis and regulatory mechanisms of thyroid carcinoma.
Keywords: carcinogenesis, RNA, Long Noncoding, Databases, Genetic, Gene Expression, Gene Expression Profiling, Gene Expression Regulation, Neoplastic, gene ontology, Gene Regulatory Networks, Kaplan-Meier Estimate, MicroRNAs, Prognosis, Proportional Hazards Models, RNA, Messenger, ROC Curve, Receptors, Virus, Survival Analysis, transcriptome
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