Identification of differentially expressed genes and signaling pathways in papillary thyroid cancer: a study based on integrated microarray and bioinformatics analysis

被引:14
作者
Sun, Tuanqi [1 ,2 ]
Guan, Qing [1 ,2 ]
Wang, Yunjun [1 ,2 ]
Qian, Kai [3 ]
Sun, Wenyu [2 ,4 ]
Ji, Qinghai [1 ,2 ]
Wu, Yi [1 ,2 ]
Guo, Kai [3 ]
Xiang, Jun [1 ,2 ]
机构
[1] Fudan Univ, Shanghai Canc Ctr, Dept Head & Neck Surg, Shanghai, Peoples R China
[2] Fudan Univ, Shanghai Med Coll, Dept Oncol, Shanghai, Peoples R China
[3] Shanghai Jiao Tong Univ, Renji Hosp, Sch Med, Dept Head & Neck Surg, Shanghai, Peoples R China
[4] Fudan Univ, Dept Ultrasonog, Shanghai Canc Ctr, Shanghai, Peoples R China
关键词
Differentially expressed genes (DEGs); biomarkers; Gene Expression Omnibus (GEO); papillary thyroid carcinoma (PTC); LONG NONCODING RNA; TERT PROMOTER MUTATIONS; CLINICOPATHOLOGICAL FEATURES; BRAF(V600E) MUTATION; BRAF MUTATIONS; CARCINOMA; CELLS; PREVALENCE; SECRETION; PROGNOSIS;
D O I
10.21037/gs-20-673
中图分类号
R61 [外科手术学];
学科分类号
摘要
Background: The techniques of DNA microarray and bioinformatic analysis have exhibited efficiency in identifying dysregulated gene expression in human cancers. In this study, we used integrated bioinformatics analysis to improve our understanding of the pathogenesis of papillary thyroid cancer (PTC). Methods: In this study, we integrated four Gene Expression Omnibus (GEO) datasets, GSE33630, GSE35570, GSE60542 and GSE29265, including 136 normal samples and 157 PTC specimens. The contents of the four datasets are based on GPL570, an Affymetrix Human Genome U133 Plus 2.0 array. Gene ontology (GO) analysis was used to identify characteristic the biological attributes of differentially expressed genes (DEGs) between PTC and normal samples. GO annotation was performed on the DEGs obtained, and the process relied on the DAVID online tool. Kyoto Encyclopedia of Genes and Genomes (KEGG) approach enrichment analyses were adopted to obtain the basic functions of the DEGs. The KOBAS online analysis database was used to complete DEG KEGG pathway comparison and analysis. The search tool (STRING) database was mainly used to search for interacting genes and complete the construction of protein-protein interaction (PPI) networks. Results: Five hundred-ninety DEGs were consistently expressed in the four datasets; 327 of them were upregulated, while 263 were downregulated. Ten DEGs, including five upregulated (ENTPD1, THRSP, KLK10, ADAMTS9, MIR31HG) and five downregulated (SCARA5, EPHB1, CHRDL1, LOC440934, FOXP2) genes, were randomly selected for q-PCR in our own tissue samples to validate the integrated data. The most highly enriched GO terms were extracellular exosome (GO:0070062), cell adhesion (GO:0070062), positive regulation of gene expression (GO:0010628), and extracellular matrix ( ECM) organization (GO:0030198). KEGG pathway analysis was performed, and it was found that abnormally expressed genes effectively participated in pathways such as tyrosine metabolism, complement and coagulation cascades, cell adhesion molecules (CAMs), transcriptional misregulation and ECM-receptor interaction pathways. Conclusions: Five hundred-ninety DEGs were identified in PTC by integrated microarray analysis. The GO and KEGG analyses presented here suggest that the DEGs were enriched in extracellular exosome, tyrosine metabolism, CAMs, complement and coagulation cascades, transcriptional misregulation and ECMreceptor interaction pathways. Functional studies of PTC should focus on these pathways.
引用
收藏
页码:629 / 644
页数:16
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