Identification of potential biomarkers and drugs for papillary thyroid cancer based on gene expression profile analysis

Qu,Ting; Li,Yan‑Ping; Li,Xiao‑Hong; Chen,Yan

doi:10.3892/mmr.2016.5855

Identification of potential biomarkers and drugs for papillary thyroid cancer based on gene expression profile analysis

Authors:
- Ting Qu
- Yan‑Ping Li
- Xiao‑Hong Li
- Yan Chen
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Affiliations: Department of Pharmacy, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang 150001, P.R. China, Department of Endodontics, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang 150001, P.R. China
Published online on: October 19, 2016 https://doi.org/10.3892/mmr.2016.5855
Pages: 5041-5048
Copyright: © Qu et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

The present study aimed to systematically examine the molecular mechanisms of papillary thyroid cancer (PTC), and identify potential biomarkers and drugs for the treatment of PTC. Two microarray data sets (GSE3467 and GSE3678), containing 16 PTC samples and 16 paired normal samples, were downloaded from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) were identified using the Linear Models for Microarray Analysis package. Subsequently, the common DEGs were screened for functional and pathway enrichment analysis using the Database for Annotation Visualization and Integrated Discovery. The representative interaction subnetwork was further derived using Molecular Complex Detection software. In addition, the potential drugs for the hub DEGs in the subnetwork were screened from DrugBank and the potential drug‑like ligands, which interacted with genes, were selected using MTiOpenScreen. A total of 167 common DEGs, including 77 upregulated and 90 downregulated DEGs, were screened. The common DEGs were associated with the functions of plasma membrane, extracellular matrix, response to steroid hormone stimulus and cell adhesion, and the pathways of tyrosine metabolism and cell adhesion molecules were significantly enriched. A total of eight common DEGs (MET, SERPINA1, LGALS3, FN1, TNFRSF11B, LAMB3 and COL13A1) were involved in the subnetwork. The two drugs, lanoteplase and ocriplasmin, and four drugs, β‑mercaptoethanol, recombinant α 1‑antitrypsin, PPL‑100 and API, were found for FN1 and SERPINA1, respectively. The common DEGs identified may be potential biomarkers for PCT. FN1 and SERPINA1 may be involved in PTC by regulating epithelial‑to‑mesenchymal transition and responding to steroid hormone stimuli, respectively. Ocriplasmin, β‑mercaptoethanol and recombinant α 1‑antitrypsin may be potential drugs for the treatment of PTC.

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