Genetic factors, Helicobacter pylori infection, salt over-uptake, decreased vegetable/fruit consumption, smoking, and metabolic syndrome are risk factors of human gastric cancer. Germline mutations of CDH1 gene, and SNPs of PTPN11 (SHP2), TLR4, IL1B, TNFA, BMP6, GDF15 and RUNX3 genes are associated with gastric cancer. Helicobacter pylori activates CagA-SHP2-ERK and peptidoglycan-NOD1-NFkappaB signaling cascades in gastric epithelial cells using type IV secretion system, and also TRAF6-MAP3K7-NFkappaB and TRAF6-MAP3K7-AP-1 signaling cascades in epithelial and immune cells through lipopolysaccharide recognition by TLR2 or TLR4. IL-1beta, IL-6, IL-8, TNFalpha and IFNgamma are elevated in gastric mucosa with Helicobacter pylori infection. IL-6 and TNFalpha induce upregulation of WNT5A and WNT10B, respectively. WNT signals are transduced to beta-catenin-TCF/LEF, RhoA, JNK, PKC, NFAT, and NLK signaling cascades. WNT-beta-catenin-TCF/LEF signaling induces upregulation of MYC, CCND1, WISP1, FGF20, JAG1 and DKK1 genes. Notch signals are transduced to CSL-NICD-MAML and NFkappaB signaling cascades. FGF signals are transduced to ERK, PI3K-AKT, PKC, and NFAT signaling cascades. Helicobacter pylori infection induces SHH upregulation in parietal cell lineage, while BMP signals induce IHH upregulation in pit cell lineage. Hedgehog signals induce upregulation of GLI1, PTCH1, CCND2, FOXL1, JAG2 and SFRP1 genes. JAG1 and JAG2 activate Notch signaling, while DKK1 and SFRP1 inhibit WNT signaling. Stem cell signaling network, consisting of WNT, Notch, FGF, Hedgehog and BMP signaling pathways, is activated during chronic Helicobacter pylori infection. Epigenetic silencing of SFRP1 gene occurs in the earlier stage of carcinogenesis in the stomach, while amplification and overexpression of FGFR2 gene in the later stage. Dysregulation of the stem cell signaling network due to the accumulation of germline mutation, SNP, Helicobacter pylori infection, epigenetic change and genetic alteration gives rise to gastric cancer. SNP typing and custom-made microarray analyses on genes encoding stem cell signaling molecules could be utilized for the personalized medicine.