SRC and TP53 play critical role in low-grade dysplasia colorectal mucosa transformation into cancer
Gastroenterology and Hepatology from Bed to Bench,
Vol. 11 No. Supplement 1 (2018),
11 Azar 2018
,
Page s105-s110
https://doi.org/10.22037/ghfbb.v0i0.1534
Abstract
Aim: Determination of crucial genes that are involved in onset and progress of dysplasia of colorectal mucosa is the aim of this study.
Background: Management of dysplasia as one of the risk factors of colon cancer is very challenging. Molecular studies could be helpful in this matter. Here, the transcriptome profile of low-grade dysplasia in colon tissue in comparison with normal one is studied by protein-protein interaction (PPI) network analysis.
Methods: For detecting differentially expressed genes (DEGs) of dysplasia lesion, the data was downloaded from the gene chip GSE31106, platform GPL1261, GSM770092-94 as normal colorectal mucosa group and GSM770098-100 as low-grade dysplasia colorectal mucosa from the Gene Expression Omnibus database (GEO). The expression profile is evaluated by GEO2R and a network of DEGs is constructed and analyzed by Cytoscape algorithms.
Results: The findings indicate that a PPI network analysis of 113 DEGs is consist of 8 nodes that 6 of them are common with inflammation state. Only SRC and TP53 were recognized as the specific makers for dysplasia. In this respect, a subnetwork of these two genes introduce a panel of 8 nodes consist of HRAS, MYC, PIK3CA, PIK3CB, PIK3CD, PIK3CG, SRC, and TP53.
Conclusion: It can be concluded that SRC and TP53 may play prominent role in dysplasia pathogenicity after running validation tests.
Keywords: Dysplasia lesion, Colorectal cancer, Protein-protein interaction network analysis.
(Please cite as: Asadzadeh-Aghdaei H, Zamanian Azodi M, Vafaee R, Moravvej Farshi H, Naderi N. SRC and TP53 play critical role in low-grade dysplasia colorectal mucosa transformation into cancer. Gastroenterol Hepatol Bed Bench 2018;11(Suppl. 1):S104-S110).
- Dysplasia lesion
- Colorectal cancer
- Protein-protein interaction network analysis.
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