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Enrichment of Up-Regulated and Down-Regulated Gene Clusters Using Gene Ontology, Mirnas and Lncrnas in Colorectal Cancer Publisher Pubmed



Fattahi F1 ; Kiani J1 ; Khosravi M2 ; Vafaei S1 ; Mohammadi A3 ; Madjd Z1, 4 ; Najafi M5
Authors
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Authors Affiliations
  1. 1. Department of Molecular Medicine, Faculty of Advanced Technologies in Medicine, Iran University of Medical Sciences, Tehran, Iran
  2. 2. Medicine Biochemistry, Qom Branch, Islamic Azad University, Qom, Iran
  3. 3. Biochemistry Department, Tarbiat Modares University, Tehran, Iran
  4. 4. Oncopathology Research Center, Iran University of Medical Sciences, Tehran, Iran
  5. 5. Biochemistry Department, Faculty of Medical Sciences, Iran University of Medical Sciences, Tehran, Iran

Source: Combinatorial Chemistry and High Throughput Screening Published:2019


Abstract

Aim and Objective: It is interesting to find the gene signatures of cancer stages based on the omics data. The aim of study was to evaluate and to enrich the array data using gene ontology and ncRNA databases in colorectal cancer. Methods: The human colorectal cancer data were obtained from the GEO databank. The downregulated and up-regulated genes were identified after scoring, weighing and merging of the gene data. The clusters with high-score edges were determined from gene networks. The miRNAs related to the gene clusters were identified and enriched. Furthermore, the long non-coding RNA (lncRNA) networks were predicted with a central core for miRNAs. Results: Based on cluster enrichment, genes related to peptide receptor activity (1.26E-08), LBD domain binding (3.71E-07), rRNA processing (2.61E-34), chemokine (4.58E-19), peptide receptor (1.16E-19) and ECM organization (3.82E-16) were found. Furthermore, the clusters related to the non-coding RNAs, including hsa-miR-27b-5p, hsa-miR-155-5p, hsa-miR-125b-5p, hsa-miR-21-5p, hsa-miR-30e-5p, hsa-miR-588, hsa-miR-29-3p, LINC01234, LINC01029, LINC00917, LINC00668 and CASC11 were found. Conclusion: The comprehensive bioinformatics analyses provided the gene networks related to some non-coding RNAs that might help in understanding the molecular mechanisms in CRC. © 2019 Bentham Science Publishers.