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  • Gene expression differences between thyroid carcinoma, thyroid adenoma and normal thyroid tissue.

Gene expression differences between thyroid carcinoma, thyroid adenoma and normal thyroid tissue.

Oncology reports (2018-10-03)
Quan Wang, Yilin Shen, Bin Ye, Haixia Hu, Cui Fan, Tan Wang, Yuqin Zheng, Jingrong Lv, Yan Ma, Mingliang Xiang
摘要

To identify differences in gene expression profiles of infected cells between thyroid carcinoma (C), thyroid adenoma (A) and normal thyroid (N) epithelial cells, differentially expressed genes were identified using three pairwise comparisons with the GEO2R online tool. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were used to classify them at the functional level. The most significant cluster in the N vs. A pairwise comparison had four hub genes: Insulin-like growth factor 2, Von Willebrand factor (VWF), multimerin 1 (MMRN1) and complement factor D (CFD). In N vs. C, the most significant cluster had 19 genes: IGF2, early growth response 2, transcription factor 3, KIT proto‑oncogene receptor tyrosine kinase, SMAD family member 9, MLLT3 super elongation complex subunit, runt related transcription factor 1, CFD, actinin α 1, SWI/SNF related matrix associated actin dependent regulator of chromatin subfamily a member 4, JunD proto‑oncogene AP‑1 transcription factor subunit, serum response factor (SRF), FosB proto‑oncogene, AP‑1 transcription factor subunit, connective tissue growth factor (CTGF), SRC proto‑oncogene, non‑receptor tyrosine kinase, MMRN1, SRY‑box 9, early growth response 3 and ETS variant 4. In A vs. C, the most significant cluster had 14 genes: BCL2-like 1, galectin 3, MCL1 BCL2 family apoptosis regulator, DNA damage inducible transcript 3, BCL2 apoptosis regulator, CTGF, matrix metallopeptidase 7, early growth response 1, kinase insert domain receptor, TIMP metallopeptidase inhibitor 1, apolipoprotein E, VWF, cyclin D1 and placental growth factor. Histological evidence was presented to confirm the makeup of the hubs prior to logistic regression analysis to differentiate benign and malignant neoplasms. The results of the present study may aid in the search for novel potential biomarkers for the differential diagnosis, prognosis and development of drug targets of thyroid neoplasm.