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.