OncoTargets and therapy · 2019
Upregulation Of Protein Tyrosine Phosphatase Receptor Type C Associates To The Combination Of Hashimoto's Thyroiditis And Papillary Thyroid Carcinoma And Is Predictive Of A Poor Prognosis.
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Wu Yanmeizhi, Han Jun, Vladimirovna Kazakova Elena, Zhang Shumei, Lv Wenhua, Zhang Yan, Jamaspishvili Esma, Sun Jingxue, Fang Qingxiao, Meng Jingjing, Qiao Hong
Аннотация
INTRODUCTION: PTC is not generally considered a lethal disease, but prone to recurrence as the prognosis. Hashimoto's thyroiditis (HT) is an important factor that affects the prognosis of papillary thyroid carcinoma (PTC). It is crucial to find biomarkers to identify the combination of HT with PTC and to predict the prognosis.
METHODS: RNASeq data from the Cancer Genome Atlas (TCGA) database was used to screen differentially expressed genes (DEGs) of PTC with HT via the edgeR package of R software version 3.3.0. Also, the DEGs were applied to the DAVID web-based tool to determine the enrichment of gene functions via Gene Ontology (GO) analysis and to identify associated pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. By constructing protein interaction networks within Cytoscape software, we screened candidate genes and explored possible relationships with the clinical phenotype of PTC. Finally, additional thyroid tissue samples were collected to verify the results above.
RESULTS: After analyzing the RNA-Seq data of PTC patients from the Cancer Genomic Atlas, 497 differentially expressed PTC genes were found to be associated with HT, of which protein tyrosine phosphatase receptor type C (PTPRC), KIT, and COL1A1 were associated with tumor size and lymph node metastasis (p < 0.05). Verification of these results with another 30 thyroid tissues of clinical PTC patients revealed that the expression level of PTPRC in the PTC with HT group was higher than that in the PTC without HT group (p < 0.05) and the ROC curve showed a good discrimination (area under the curve = 0.846). However, the correlation with the clinical phenotype was not statistically significant (p > 0.05).
DISCUSSION: These data suggest that upregulation of PTPRC enhances the incidence of HT associated with PTC and is also predictive of a poor prognosis.
METHODS: RNASeq data from the Cancer Genome Atlas (TCGA) database was used to screen differentially expressed genes (DEGs) of PTC with HT via the edgeR package of R software version 3.3.0. Also, the DEGs were applied to the DAVID web-based tool to determine the enrichment of gene functions via Gene Ontology (GO) analysis and to identify associated pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. By constructing protein interaction networks within Cytoscape software, we screened candidate genes and explored possible relationships with the clinical phenotype of PTC. Finally, additional thyroid tissue samples were collected to verify the results above.
RESULTS: After analyzing the RNA-Seq data of PTC patients from the Cancer Genomic Atlas, 497 differentially expressed PTC genes were found to be associated with HT, of which protein tyrosine phosphatase receptor type C (PTPRC), KIT, and COL1A1 were associated with tumor size and lymph node metastasis (p < 0.05). Verification of these results with another 30 thyroid tissues of clinical PTC patients revealed that the expression level of PTPRC in the PTC with HT group was higher than that in the PTC without HT group (p < 0.05) and the ROC curve showed a good discrimination (area under the curve = 0.846). However, the correlation with the clinical phenotype was not statistically significant (p > 0.05).
DISCUSSION: These data suggest that upregulation of PTPRC enhances the incidence of HT associated with PTC and is also predictive of a poor prognosis.