The occurrence and development of colorectal cancer is a complex process of steps, phases and polygene. We did data preprocessing of the five microarray datasets of colorectal cancer that were from the public database (GEO) by bioinformatics tools in this article, Cancer Outlier Profile Analysis was used to select differentially expressed genes, and KEGG and GeneGO database were used to search the pathways which were related to the differentially expressed genes. With the GeneGO database, the rate which gene overlap is less than pathway overlap is 70%. 105 of the 262 pathways were confirmed to be related to colorectal cancer, and four pathways were shared in four datasets at least. 19.2 percent of genes in the (L)-selenoaminoacids incorporation in proteins during translation pathway was confirmed to be related to colorectal cancer. This pathway may be a new colorectal cancer-related pathway, but it needs further experimental testing. Through meta-analysis of microarray expression profilings at pathway level, we verified that the analysis at pathway level was more reproducible than that at gene level. And it is meaningful to understand the molecular mechanism of occurrence and development of colorectal cancer more better.
Source: http://www.res-medical.com/oncology/53776
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