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Analysis of Differentially Expressed Genes, MMP3 and TESC, and Their Potential Value in Molecular Pathways in Colon Adenocarcinoma: A Bioinformatics Approach.
- Source :
- BioMedInformatics; Sep2022, Vol. 2 Issue 3, p474-491, 18p
- Publication Year :
- 2022
-
Abstract
- Despite the great progress in its early diagnosis and treatment, colon adenocarcinoma (COAD) is still poses important issues to clinical management. Therefore, the identification of novel biomarkers or therapeutic targets for this disease is important. Using UALCAN, the top 25 upregulated and downregulated genes in COAD were identified. Then, a Kaplan–Meier plotter was employed for these genes for survival analysis, revealing the correlation with overall survival rate only for MMP3 (Matrix Metallopeptidase 3) and TESC (Tescalcin). Despite this, the mRNA expression levels were not correlated with the tumor stages or nodal metastatic status. MMP3 and TESC are relevant targets in COAD that should be additionally validated as biomarkers for early diagnosis and prevention. Ingenuity Pathway Analysis revealed the top relevant network linked to Post-Translational Modification, Protein Degradation, and Protein Synthesis, where MMP3 was at the core of the network. Another important network was related to cell cycle regulation, TESC being a component of this. We should also not underestimate the complex regulatory mechanisms mediated by the interplay of the multiple other regulatory molecules, emphasizing the interconnection with molecules related to invasion and migration involved in COAD, that might serve as the basis for the development of new biomarkers and therapeutic targets. [ABSTRACT FROM AUTHOR]
- Subjects :
- ADENOCARCINOMA
COLON (Anatomy)
CANCER treatment
THERAPEUTICS
BIOMARKERS
Subjects
Details
- Language :
- English
- ISSN :
- 26737426
- Volume :
- 2
- Issue :
- 3
- Database :
- Complementary Index
- Journal :
- BioMedInformatics
- Publication Type :
- Academic Journal
- Accession number :
- 159273270
- Full Text :
- https://doi.org/10.3390/biomedinformatics2030030