Cargando…
Identification and Validation of Novel Genes in Anaplastic Thyroid Carcinoma via Bioinformatics Analysis
PURPOSE: The conventional interventions of anaplastic thyroid carcinoma (ATC) patients are mainly through surgery, chemotherapy, and radiotherapy; however, it is hardly to improve survival rate. We aimed to investigate the differential expressed genes (DEGs) between ATC and normal thyroid gland thro...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7550107/ https://www.ncbi.nlm.nih.gov/pubmed/33116838 http://dx.doi.org/10.2147/CMAR.S250792 |
_version_ | 1783592905214001152 |
---|---|
author | Wang, Shengnan Wu, Jing Guo, Congcong Shang, Hongxia Yao, Jinming Liao, Lin Dong, Jianjun |
author_facet | Wang, Shengnan Wu, Jing Guo, Congcong Shang, Hongxia Yao, Jinming Liao, Lin Dong, Jianjun |
author_sort | Wang, Shengnan |
collection | PubMed |
description | PURPOSE: The conventional interventions of anaplastic thyroid carcinoma (ATC) patients are mainly through surgery, chemotherapy, and radiotherapy; however, it is hardly to improve survival rate. We aimed to investigate the differential expressed genes (DEGs) between ATC and normal thyroid gland through bioinformatics analysis of the microarray datasets and find new potential therapeutic targets for ATC. METHODS: Microarray datasets GSE9115, GSE29265, GSE33630, GSE53072, and GSE65144 were downloaded from Gene Expression Omnibus (GEO) database. Compared with the normal tissue, GEO2R was conducted to screen the DEGs in each chip under the condition of |log FC| > l, adjusted P‐values (adj. P) < 0.05. The Retrieval of Interacting Genes (STRING) database was used to calculate PPI networks of DEGs with a combined score >0.4 as the cut-off criteria. The hub genes in the PPI network were visualized and selected according to screening conditions in Cytoscape software. In addition, the novel genes in ATC were screened for survival analysis using Kaplan–Meier plotter from those hub genes and validated by RT-qPCR. RESULTS: A total of 284 overlapping DEGs were obtained, including 121 upregulated and 161 downregulated DEGs. A total of 232 DEGs were selected by STRING database. The 50 hub genes in the PPI network were chosen according to three screening conditions. In addition, the Kaplan–Meier plotter database confirmed that high expressions of ANLN, CENPF, KIF2C, TPX2, and NDC80 were negatively correlated with poor overall survival of ATC patients. Finally, RT-qPCR experiments showed that KIF2C and CENPF were significantly upregulated in ARO cells and CAL-62 cells when compared to Nthy-ori 3–1 cells, TPX2 was upregulated only in CAL-62 cells, while ANLN and NDC80 were obviously decreased in ARO cells and CAL-62 cells. CONCLUSION: Our study suggested that CENPF, KIF2C, and TPX2 might play a significant role in the development of ATC, which could be further explored as potential biomarkers for the treatment of ATC. |
format | Online Article Text |
id | pubmed-7550107 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Dove |
record_format | MEDLINE/PubMed |
spelling | pubmed-75501072020-10-27 Identification and Validation of Novel Genes in Anaplastic Thyroid Carcinoma via Bioinformatics Analysis Wang, Shengnan Wu, Jing Guo, Congcong Shang, Hongxia Yao, Jinming Liao, Lin Dong, Jianjun Cancer Manag Res Original Research PURPOSE: The conventional interventions of anaplastic thyroid carcinoma (ATC) patients are mainly through surgery, chemotherapy, and radiotherapy; however, it is hardly to improve survival rate. We aimed to investigate the differential expressed genes (DEGs) between ATC and normal thyroid gland through bioinformatics analysis of the microarray datasets and find new potential therapeutic targets for ATC. METHODS: Microarray datasets GSE9115, GSE29265, GSE33630, GSE53072, and GSE65144 were downloaded from Gene Expression Omnibus (GEO) database. Compared with the normal tissue, GEO2R was conducted to screen the DEGs in each chip under the condition of |log FC| > l, adjusted P‐values (adj. P) < 0.05. The Retrieval of Interacting Genes (STRING) database was used to calculate PPI networks of DEGs with a combined score >0.4 as the cut-off criteria. The hub genes in the PPI network were visualized and selected according to screening conditions in Cytoscape software. In addition, the novel genes in ATC were screened for survival analysis using Kaplan–Meier plotter from those hub genes and validated by RT-qPCR. RESULTS: A total of 284 overlapping DEGs were obtained, including 121 upregulated and 161 downregulated DEGs. A total of 232 DEGs were selected by STRING database. The 50 hub genes in the PPI network were chosen according to three screening conditions. In addition, the Kaplan–Meier plotter database confirmed that high expressions of ANLN, CENPF, KIF2C, TPX2, and NDC80 were negatively correlated with poor overall survival of ATC patients. Finally, RT-qPCR experiments showed that KIF2C and CENPF were significantly upregulated in ARO cells and CAL-62 cells when compared to Nthy-ori 3–1 cells, TPX2 was upregulated only in CAL-62 cells, while ANLN and NDC80 were obviously decreased in ARO cells and CAL-62 cells. CONCLUSION: Our study suggested that CENPF, KIF2C, and TPX2 might play a significant role in the development of ATC, which could be further explored as potential biomarkers for the treatment of ATC. Dove 2020-10-08 /pmc/articles/PMC7550107/ /pubmed/33116838 http://dx.doi.org/10.2147/CMAR.S250792 Text en © 2020 Wang et al. http://creativecommons.org/licenses/by-nc/3.0/ This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). |
spellingShingle | Original Research Wang, Shengnan Wu, Jing Guo, Congcong Shang, Hongxia Yao, Jinming Liao, Lin Dong, Jianjun Identification and Validation of Novel Genes in Anaplastic Thyroid Carcinoma via Bioinformatics Analysis |
title | Identification and Validation of Novel Genes in Anaplastic Thyroid Carcinoma via Bioinformatics Analysis |
title_full | Identification and Validation of Novel Genes in Anaplastic Thyroid Carcinoma via Bioinformatics Analysis |
title_fullStr | Identification and Validation of Novel Genes in Anaplastic Thyroid Carcinoma via Bioinformatics Analysis |
title_full_unstemmed | Identification and Validation of Novel Genes in Anaplastic Thyroid Carcinoma via Bioinformatics Analysis |
title_short | Identification and Validation of Novel Genes in Anaplastic Thyroid Carcinoma via Bioinformatics Analysis |
title_sort | identification and validation of novel genes in anaplastic thyroid carcinoma via bioinformatics analysis |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7550107/ https://www.ncbi.nlm.nih.gov/pubmed/33116838 http://dx.doi.org/10.2147/CMAR.S250792 |
work_keys_str_mv | AT wangshengnan identificationandvalidationofnovelgenesinanaplasticthyroidcarcinomaviabioinformaticsanalysis AT wujing identificationandvalidationofnovelgenesinanaplasticthyroidcarcinomaviabioinformaticsanalysis AT guocongcong identificationandvalidationofnovelgenesinanaplasticthyroidcarcinomaviabioinformaticsanalysis AT shanghongxia identificationandvalidationofnovelgenesinanaplasticthyroidcarcinomaviabioinformaticsanalysis AT yaojinming identificationandvalidationofnovelgenesinanaplasticthyroidcarcinomaviabioinformaticsanalysis AT liaolin identificationandvalidationofnovelgenesinanaplasticthyroidcarcinomaviabioinformaticsanalysis AT dongjianjun identificationandvalidationofnovelgenesinanaplasticthyroidcarcinomaviabioinformaticsanalysis |