scholarly journals Research for Expression and Prognostic Value of GABRD in Colon Cancer and Coexpressed Gene Network Construction Based on Data Mining

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Tao Liu ◽  
Yuejun Fang

Colon cancer is one of the top five cancers with the highest incidence rate in the world. In order to better understand the pathogenesis and progression of colon cancer, it is still necessary to investigate the abnormally expressed genes in cancer tissue. In this study, the Oncomine database was used for expression analysis, and it was found that the expression level of gamma-aminobutyric acid type A receptor subunit delta (GABRD) gene was upregulated in colon cancer tissue compared with that in normal tissue. UALCAN was used to analyze the expression of GABRD in different groups of age, gender, cancer stage, N stage, and histological subtype. Then, it was also found that the expression of GABRD in each subgroup of colon cancer tissue was all high compared with that in normal tissue. LinkedOmics was used to screen out the differentially expressed genes related to GABRD expression in colon cancer. GO annotation and KEGG pathway enrichment analyses found that the correlated genes may be related to breast cancer, human papillomavirus infection, Notch signaling pathway, and other pathways. Thereafter, GSEA was performed to obtain GABRD-related kinases, miRNAs, and transcription factors, and gene interaction networks were constructed. It was found that GABRD may be involved in cell cycle regulation. Finally, websites like GEPIA were used to detect the predictive ability of GABRD on the prognosis of patients with colon cancer. Kaplan-Meier analysis suggested that the upregulation of GABRD expression was related to the poor prognosis of patients with colon cancer. Overall, in this study, the potential role and prognostic ability of GABRD in colon cancer were explored through data mining, which can be a clue for further research on GABRD.

2016 ◽  
Author(s):  
Eric W. Martin ◽  
Ramiro Malgor ◽  
Vicente A. Resto ◽  
Douglas J. Goetz ◽  
Monica M. Burdick

2007 ◽  
Vol 1 (2) ◽  
pp. 205-215 ◽  
Author(s):  
P.A. Usher ◽  
A.M. Sieuwerts ◽  
A. Bartels ◽  
U. Lademann ◽  
H.J. Nielsen ◽  
...  

2014 ◽  
Vol 32 (15_suppl) ◽  
pp. e14636-e14636
Author(s):  
Michail L. Maleyko ◽  
Elena Frantsiyants ◽  
Yuri Gevorkyan ◽  
Ekaterina Komarova ◽  
Andrey Dashkov ◽  
...  

2003 ◽  
Vol 124 (4) ◽  
pp. A484
Author(s):  
Helen Martin ◽  
Barry Campbell ◽  
Manu Nayar ◽  
Helen Williams ◽  
Charles A. Hart ◽  
...  

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Camilla Natasha Cederbye ◽  
Jesper Andreas Palshof ◽  
Tine Plato Hansen ◽  
Anne Katrine Duun-Henriksen ◽  
Dorte Linnemann ◽  
...  

The Analyst ◽  
2017 ◽  
Vol 142 (8) ◽  
pp. 1207-1215 ◽  
Author(s):  
D. Petersen ◽  
L. Mavarani ◽  
D. Niedieker ◽  
E. Freier ◽  
A. Tannapfel ◽  
...  

The great capability of virtual staining for label-free classification of colon cancer tissue has been demonstrated via Raman spectral imaging.


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