Abstract
To investigate signal regulation models of gastric cancer, databases and literature were used to construct the signaling network in humans. Topological characteristics of the network were analyzed by CytoScape. After marking gastric cancer-related genes extracted from the CancerResource, GeneRIF, and COSMIC databases, the FANMOD software was used for the mining of gastric cancer-related motifs in a network with three vertices. The significant motif difference method was adopted to identify significantly different motifs in the normal and cancer states. Finally, we conducted a series of analyses of the significantly different motifs, including gene ontology, function annotation of genes, and model classification. A human signaling network was constructed, with 1643 nodes and 5089 regulating interactions. The network was configured to have the characteristics of other biological networks. There were 57,942 motifs marked with gastric cancer-related genes out of a total of 69,492 motifs, and 264 motifs were selected as significantly different motifs by calculating the significant motif difference (SMD) scores. Genes in significantly different motifs were mainly enriched in functions associated with cancer genesis, such as regulation of cell death, amino acid phosphorylation of proteins, and intracellular signaling cascades. The top five significantly different motifs were mainly cascade and positive feedback types. Almost all genes in the five motifs were cancer related, including EPOR, MAPK14, BCL2L1, KRT18, PTPN6, CASP3, TGFBR2, AR, and CASP7. The development of cancer might be curbed by inhibiting signal transductions upstream and downstream of the selected motifs.
Highlights
Numerous studies have shown that the abnormal transduction of cellular signaling is closely related to differentiation, apoptosis, and proliferation of cells, and to the occurrence, progression, and prognosis of disease [1]
After marking gastric cancer-related genes extracted from the CancerResource, GeneRIF, and COSMIC databases, the fast network motif detection (FANMOD) software was used for the mining of gastric cancer-related motifs in a network with three vertices
There were 57,942 motifs marked with gastric cancer-related genes out of a total of 69,492 motifs, and 264 motifs were selected as significantly different motifs by calculating the significant motif difference (SMD) scores
Summary
Numerous studies have shown that the abnormal transduction of cellular signaling is closely related to differentiation, apoptosis, and proliferation of cells, and to the occurrence, progression, and prognosis of disease [1]. According to studies of intercellular protein-protein interaction networks, the regulation of local signaling in normal tissue is different from that in tumors [2]. Motifs can react to external stimuli by regulating gene expression. Mining the cancer susceptibility genes, combined network motifs, and gene expression profiles [3] can improve the identification of target genes on tumor metastasis markedly [4,5]. About 90% of early gastric cancer patients with adequate treatment can survive for more than 5 years and be considered cured; the 5-year survival rate of advanced gastric cancer after treatment is less than 5% [6]. Early diagnosis is the key to improving treatment efficacy and increasing survival rate [7]
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Schedule a callMore From: Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologicas
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