Role of Helicobacter pylori Infection and Host Genetic Polymorphisms in Gastric Cancer Susceptibility: A Systematic Review
Bibliographic record
Abstract
Background: Despite ongoing efforts, gastric cancer remains a leading cause of cancer-related death worldwide, with its high risk primarily attributed to Helicobacter pylori (H. pylori) infection. However, the development of gastric cancer is influenced not only by bacterial virulence but also by host genetic susceptibility. Methods: To determine the potential association between specific SNPs, such as IL-6 rs1800795, PRKAA1 rs13361707, and HULC rs7770772, and gastric cancer risk in H. pylori-infected populations, a systematic review of cohort and case-control studies was conducted. Results: In the presence of risk alleles of inflammatory cytokine genes, such as IL-6 rs1800795 and IL-10, the amplification of susceptibility to gastric carcinoma was significantly higher in H. pylori positive individuals. In East Asians, the PRKAA1 rs13361707 polymorphism had an additive effect with H. pylori infection and with CagA-positive strains. Additionally, the HULC rs7770772 polymorphism synergistically enhanced gastric cancer risk in conjunction with bacterial infection. Other SNPs, including IL-18RAP rs917997 and IL-32 rs2015620, were associated with chronic atrophic gastritis and intestinal metaplasia and were implicated in the progression of gastric cancer. A Hispanic group with H. pylori infection and gastric cancer showed a common increase in HLA-Class II polymorphisms, such as HLA-DQA101 and HLA-DQB106, which are associated with decreased H. pylori susceptibility and an increased risk of gastric cancer. Furthermore, H. pylori influences host immunity through the regulation of microRNA-mediated modifications of HLA-II expression, which manipulates the immune response and facilitates immune evasion. Conclusion: Our findings demonstrate that the pathogenesis of gastric cancer involves an intricate interplay between H. pylori infection, host genetic susceptibility, and environmental factors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".