Mechanism of Helicobacter pylori Induced Gastric Cancer: Role of the Signal Transducer and Activator of Transcription Pathway
Bibliographic record
Abstract
Infection with the gut-pathogen Helicobacter pylori is the single, most important risk factor in the development of gastric cancer. Although there is a rising incidence in mortality resulting from this malignancy, the exact mechanism underlying the initiation and progression of bacterial-induced gastric tumorigenesis is still not completely understood. Several studies implicate the activation of the Signal Transducer and Activator of Transcription 3 (STAT3) signaling pathway as a cellular trigger for promoting carcinogenes. In this thesis, I studied the role of the STAT3 signaling pathway in H. pylori mediated tumorigenesis, and attempted to delineate mechanisms involved. I have found that H. pylori activates the STAT3 signaling pathway both in vitro and in vivo, to promote carcinogenesis. Pivotal for H. pylori mediated STAT3 activation are the bacterial effector protein CagA and host receptor components, the gp130 and the IL-6αR subunits. Further investigation into the mechanism of STAT3 induction identified a key role for cholesterol-enriched membrane lipid rafts. Bacterial invasion and CagA injection into host cells was also dependent on lipid raft integrity. Co-fractionation via the use of sucrose gradients, which permits the isolation of lipid rafts, identified H. pylori CagA to be associated with these membrane microdomains. CagA, once injected into the cell, appears to interact with the inner leaflet of the host plasma membrane via a charge association that either directly or indirectly anchors it to the negatively charged anionic lipids in the cytoplasmic membrane. In addition, janus kinases were recruited to rafts upon H. pylori infection. In this thesis, I present a dynamic model of STAT3 activation, which requires the interaction of lipid raft associated proteins, H. pylori CagA and recruited JAKs with non-lipid raft receptor components to support STAT3 signaling. This study is significant since it provides insight into the possible mechanisms by which H. pylori induces gastric cancer and furthermore, it facilitates the development of novel therapeutic targets directed against bacterial induced carcinogenesis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".