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.