Microarray analysis of differentially-expressed genes and linker genes associated with the molecular mechanism of colorectal cancer

Abstract

Colorectal cancer (CRC) is one of the most prevalent malignancies worldwide and remains the third leading cause of cancer-associated mortality. The present study aimed to fully elucidate the pathogenesis of CRC and identify associated genes in tumor development. Microarray GSE44076, GSE41328 and GSE44861 datasets were downloaded from the Gene Expression Omnibus database and integrated with meta-analysis. Differentially-expressed genes (DEGs) were identified from CRC samples compared with adjacent non-cancerous controls using the Limma package in R, followed by functional analysis using the Database for Annotation, Visualization, and Integrated Discovery online tool. A protein-protein interaction (PPI) network of DEGs and linker genes was constructed using NetBox software and modules were also mined. Functional annotation was performed for modules with a maximum number of nodes. Subsequent to meta-analysis to pool the data, one dataset that included 327 samples involved in 11,081 genes was obtained. A total of 697 DEGs were identified between CRC samples and adjacent non-cancerous controls. In the PPI network, modules 1 and 5 contained the maximum number of nodes. Collagen, type I, α1 (COL1A1), COL1A2 and matrix metallopeptidase 9 (MMP9) in module 1 and UDP-glucose 6-dehydrogenase (UGDH), aldehyde dehydrogenase 1 family, member A1 (ALDH1A1), fatty acid binding protein 4 (FABP4) and monoglyceride lipase (MGLL) in module 5 exhibited a high degree of connectivity. Functional analysis indicated that the genes in module 1 were involved in extracellular matrix (ECM)-associated functions and that the genes in module 5 were involved in metabolism-related functions. Overall, significant DEGs and linker genes, namely COL1A1, COL1A2, MMP9, UGDH, ALDH1A1, FABP4 and MGLL, play a crucial role in the development of CRC via regulating the ECM and cell metabolism.

Keywords: colorectal cancer; linker gene; module; protein-protein interaction.

Figure 1.

Results of normalization. The upper image represents data prior to normalization, the middle image represents the data adjusted for the batch effect and the image below represents data after normalization.

Figure 1.

Results of normalization. The upper image represents data prior to normalization, the middle image represents the data adjusted for the batch effect and the image below represents data after normalization.

Figure 2.

Functional enrichment map of upregulated differentially-expressed genes (DEGs). The nodes represent the enriched functions of the upregulated genes. Edge thickness is proportional to the number of overlapped genes between the different functions. The size of the nodes is proportional to the number of DEGs.

Figure 3.

Functional enrichment map of downregulated differentially-expressed genes (DEGs). The nodes represent the enriched functions of the downregulated genes. Edge thickness is proportional to the number of overlapped genes between the different functions. The size of the nodes is proportional to the number of DEGs.

Figure 4.

Protein-protein interaction network of up-regulated genes and linker genes. The coloration of the nodes is representative of the genes in different modules. Circular nodes represent differentially-expressed genes and rhombic nodes represent linker genes.

Figure 5.

Protein-protein interaction network of downregulated genes and linker genes. The coloration of the nodes is representative of the genes in different modules. Circular nodes represent differentially-expressed genes and rhombic nodes represent linker genes.