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Identification and analysis of genes associated with papillary thyroid carcinoma by bioinformatics methods.

ABSTRACT: The molecular mechanism of the occurrence and development of papillary thyroid carcinoma (PTC) has been widely explored, but has not been completely elucidated. The present study aimed to identify and analyze genes associated with PTC by bioinformatics methods. Two independent datasets were downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) between PTC tissues and matched non-cancerous tissues were identified using GEO2R tool. The common DEGs in the two datasets were screened out by VennDiagram package, and analyzed by the following tools: KOBAS, Database for Annotation, Visualization, and Integrated Discovery (DAVID), Search tool for the retrieval of interacting genes/proteins (STRING), UALCAN and Gene expression profiling interactive analysis (GEPIA). A total of 513 common DEGs, including 259 common up-regulated and 254 common down-regulated genes in PTC, were screened out. These common up-regulated and down-regulated DEGs were most significantly enriched in cytokine-cytokine receptor interaction and metabolic pathways, respectively. Protein-protein interactions (PPI) network analysis showed that the up-regulated genes: FN1, SDC4, NMU, LPAR5 and the down-regulated genes: BCL2 and CXCL12 were key genes. Survival analysis indicated that the high expression of FN1 and NMU genes significantly decreased disease-free survival of patients with thyroid carcinoma. In conclusion, the genes and pathways identified in the current study will not only contribute to elucidating the pathogenesis of PTC, but also provide prognostic markers and therapeutic targets for PTC.

SUBMITTER: Zhang S

PROVIDER: S-EPMC6443946 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Identification and analysis of genes associated with papillary thyroid carcinoma by bioinformatics methods.

Zhang Shulong S Wang Quan Q Han Qi Q Han Huazhong H Lu Pinxiang P

Bioscience reports 20190402 4

The molecular mechanism of the occurrence and development of papillary thyroid carcinoma (PTC) has been widely explored, but has not been completely elucidated. The present study aimed to identify and analyze genes associated with PTC by bioinformatics methods. Two independent datasets were downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) between PTC tissues and matched non-cancerous tissues were identified using GEO2R tool. The common DEGs in the ...[more]

PMID: 30872410

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Project description:BackgroundThis study aimed to identify the key genes associated with prognosis in thyroid cancer (TC), and to explore potential pathways.MethodsGSE66783, GSE58545, and GSE129562 datasets were used to identify differentially expressed genes (DEGs) between tumor and normal tissues, followed by KEGG analyses on DEGs. The protein-protein interaction (PPI) network of DEGs was subsequently constructed to find the top 10 hub genes and seed genes in the whole network. Furthermore, the mRNA expressions of hub genes and prognostic values were explored. Regarding the seed gene, pathway activity score and GSEA analyses were conducted as well.Results1) A total of 183 DEGs were consistently expressed in three datasets comprising 76 up-regulated and 107 down-regulated genes. DEGs were mainly enriched in the p53 signaling pathway, complement and coagulation cascades, and hedgehog signaling pathway. 2) The top 10 hub genes, including CCND1, TIMP1, ICAM1, MET, PLAU, LDLR, PLAUR, ITGA2, ITGA3, and LGALS3, were identified. All hub genes were highly expressed in TC compared with normal samples. 3) High expression of CCND1, TIMP1, MET, and LGALS3 statistically correlated with a favorable prognosis of patients. Poor survival was observed in patients with ITGA2 and ITGA3 high expression. There was no association between ICAM1, PLAU, and PLAUR expression and survival of patients. LGALS3 and TIMP1 were further identified as independent prognostic factors in TC. 4) Among 10 hub genes, TIMP1 was determined as the seed gene, indicating its significance in the whole network. We further found that in most of the famous cancer-related pathways, TIMP1 higher expression caused a lower pathway activity, suggesting its inhibitory effect to these pathways in TC. In addition, TIMP1 positively correlated with the p53 signaling pathway, complement, and coagulation cascades involved in TC.ConclusionThe present study provided seven prognosis-associated genes in TC and revealed several significant pathways, which contributed to elucidate the pathogenesis of TC.

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Identification and analysis of genes associated with papillary thyroid carcinoma by bioinformatics methods.

Publications

Identification and analysis of genes associated with papillary thyroid carcinoma by bioinformatics methods.

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