Identifying colon cancer stage related genes and their cellular pathways

Abstract

In the world, colon cancer is regarded as one of the most common deadly cancer. Due to the lack of a better understanding of its prognosis system, this prevailing cancer has the second-highest morbidity and mortality rate compared with other cancers. A variety of genes are responsible to participate in colon cancer and the molecular mechanism is almost unsure. In addition, various studies have been done to identify the differentially expressed genes to investigate the dysfunctions of the genes but most of them did it individually. In this study, we constructed a functional interaction network for identifying the group of genes that conduct cellular functions and Protein-Protein Interaction network, which aims to better understanding protein functions and their biological relationships. A functional evolution network was also generated to analyze the dysfunctions from initial stage to later stage of colon cancer by investigating the gene modules and their molecular functions. The results show that the proposed evolution network is able to detect the significant cellular functions, which can be used to explore the evolution process of colon cancer. Moreover, a total of 10 core genes associated with colon cancer were identified, which were INS, SNAP25, GRIA2, SST, GCG, PVALB, SLC17A7, SLC32A1, SLC17A6, and NPY, respectively. The responsible candidate genes and corresponding pathways presented in this study could be used to develop new tumor indicators and novel therapeutic targets for the prevention and treatment of colon cancer.

Keywords: cancer evolution; cancer stage; colon cancer; differentially expressed gene; functional evolution network.

FIGURE 1

The overall framework of the proposed method.

FIGURE 2

Comparison between 4 DE sets. List1: S1 and Normal, List2: S2 and Normal, List3: S3 and Normal, List4: S4 and Normal; where 0 indicates up-regulated genes, $\underset{¯}{0}$ represents down-regulated genes and $0$ denotes contra-regulated genes (however there are no contra-regulated genes).

FIGURE 3

FI network for each stage, where each node is a differentially expressed gene and edge represents the interaction between genes. (A) is the FI network for stage I, (B) represents the FI network built by DEG-Stage II, (C) and (D) are the FI network for stage III and stage IV.

FIGURE 4

The Pathway Interaction Network. The correlation between 4 DE sets of pathways was obtained and expressed in this network. This network was constructed by combining the 7 cluster networks. Each node is a cluster of different stages which contained several numbers of genes and the edges represent the number of related genes. The thick edges were selected by overlapping genes counts between connected nodes. Red nodes or “A”: DE set I, green nodes or “B”: DE set II, purple nodes or “C”: DE set III, blue nodes or “D”: DE set IV.

FIGURE 5

Pathway analysis by clustered heatmap analysis of four stages where pathways were selected by the KEGG pathway enrichment analysis. The functional components identified from the KEGG pathway enrichment analysis are presented row-wise (right side) and each stage is presented column-wise (bottom). The color intensities indicate the enrichment score of each KEGG pathway with a color gradient that moves from light yellow to maroon. The dendrogram indicates the similarity between pathways as well as stages.

FIGURE 6

Protein-Protein Interaction (PPI) Network of intersection DEGs.

FIGURE 7

This sub-network shows the connection between hub genes. Red color denotes the degree of connectivity is highest and yellow color means the lowest degree of connectivity and the color changes from red to yellow means the degree of connectivity decreases.