Helicobacter pylori-related risk predictors of gastric cancer: The latest models, challenges, and future prospects

Helicobacter pylori is known as an important determinant of preneoplastic lesions or gastric cancer (GC) risk. The bacterial genotypes may determine the clinical outcomes. However, the evidence for these associations has varied between and within continents, and the actual effect of each gene and corresponding allelic variants are still debatable. In recent years, two new models have been proposed to predict the risk of GC; the phylogeographic origin of H. pylori strains and a disrupted co-evolution between H. pylori and its human host, which potentially explain the geographic differences in the risk of H. pylori-related cancer. However, these models and earlier ones based on putative virulence factors of the bacterium may not fully justify differences in the incidence of GC, reflecting that new theories should be developed and examined. Notably, the new findings also support the role of ancestry-specific germline alteration in contributing to the ethnic/population differences in cancer risk. Moreover the high and low incidence areas of GC have shown differences in transmission ecology, largely affecting the composition of H. pylori populations. As a new hypothesis, it is proposed that any high-risk population may have its own specific risk loci (or variants) as well as new H. pylori strains with national/maybe regional gene pools that should be considered. The latter is seen in the Americas where the rapid evolution of distinct H. pylori subpopulations has been occurred. It is therefore proposed that the deep sequencing of both H. pylori and its human host is simultaneously performed in GC patients and age-sex-matched controls from high-risk areas. The expression and functional activities of the identified new determinants of GC must then be assessed and matched with human and pathogen ancestry, because some of risk loci are ancestry-specific. In addition, potential study-level covariates and moderator variables (eg physical conditions, life styles, gastric microbiome, etc) linked to causal relationships, and their impact, should be recognized and controlled.