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Copyright: ©Author(s) 2026. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See permissions. Published by Baishideng Publishing Group Inc.
World J Clin Oncol. Oct 24, 2026; 17(10): 125453
Published online Oct 24, 2026. doi: 10.5306/wjco.125453
Helicobacter pylori virulence gene expression defines a stage-associated transcriptional signature in gastric cancer
Oliver Mbuthia, Ishrat Mahjabeen, Mahmood Kayani, Azhar Mehmood, Jael Obiero, Takashi Matsumoto, Kefa Bosire, Marianne Mureithi
Oliver Mbuthia, Department of Medical Microbiology and Immunology, University of Nairobi, Kenyatta National Hospital, Nairobi P O Box 30197-00100, Nairobi City, Kenya
Ishrat Mahjabeen, Mahmood Kayani, Azhar Mehmood, Department of Biosciences, COMSATS University Islamabad, Islamabad 45550, Pakistan
Jael Obiero, Department of Reproductive Health and Biology, Kenya Institute of Primate Research, Nairobi P O Box 24481-00502, Nairobi City, Kenya
Takashi Matsumoto, Department of Environmental and Preventive Medicine, Oita University Faculty of Medicine, Yufu 879-5593, Japan
Kefa Bosire, Department of Pharmacy and Pharmacognosy, University of Nairobi, Nairobi P O Box 30197-00100, Kenya
Marianne Mureithi, KAVI - Institute of Clinical Research, University of Nairobi, Nairobi P O Box 30197-00100, Kenya
Author contributions: Mbuthia O conceived and designed the study, established the analytical methodology, obtained funding, conducted the formal analysis, curated the data, and prepared the initial manuscript draft; Mahjabeen I participated in sample and data collection, supplied laboratory resources, and contributed to methodology and data curation; Kayani M supervised the project, provided essential resources and administrative support, and critically revised the manuscript; Mehmood A participated in data collection and curation, supplied resources, and critically revised the manuscript; Bosire K contributed to methodology, supervision, and critical manuscript revision; Matsumoto T contributed to methodology, validation, supervision, and critical manuscript revision; Obiero J contributed to study methodology and validation, supervised the work, and critically revised the manuscript; Mureithi M contributed to study design, supervision, and manuscript revision; and all authors read and approved the final version of the manuscript.
AI contribution statement: The authors declare that generative artificial intelligence tools were not used to generate data or conduct formal statistical analysis in this study. Google Gemini was used for language alignment and editing of the initial manuscript draft, and Claude (Anthropic) was used for language editing and manuscript refinement during subsequent revisions, including improvements to grammatical clarity, sentence structure, and terminological consistency. This use did not alter the scientific content, interpretation of the data, or conclusions, for which the authors retain sole responsibility.
Supported by the United Nations Educational, Scientific and Cultural Organization - The World Academy of Sciences and COMSATS University Islamabad, No. 3240320712.
Institutional review board statement: Approval for the study protocol was obtained from the Institutional Review Board of COMSATS University Islamabad and from participating clinical centers [Ref: CIIT/Bio/ERB/17/15]. All study procedures conformed to the Declaration of Helsinki. Gastric biopsy specimens were collected only after patients had provided written informed consent for use of their samples in molecular research.
Informed consent statement: Before sample collection, written informed consent was obtained from every participant for use of gastric biopsy specimens in molecular research. Participant confidentiality was protected by de-identifying all specimens and assigning a unique study ID before analysis.
Conflict-of-interest statement: All authors declare that they have no conflict of interest to disclose.
STROBE statement: The authors have read the STROBE Statement-checklist of items, and the manuscript was prepared and revised according to the STROBE Statement-checklist of items.
Data sharing statement: Data generated and/or analyzed in the current study are available from the corresponding author on reasonable request.
Corresponding author: Oliver Mbuthia, PhD, Department of Medical Microbiology and Immunology, University of Nairobi, Kenyatta National Hospital, Nairobi P O Box 30197-00100, Nairobi City, Kenya. oliver.mbuthia@nairobi.msf.org
Received: July 9, 2026
Revised: August 26, 2026
Accepted: October 8, 2026
Published online: October 24, 2026
Processing time: 107 Days and 10.1 Hours
Abstract
BACKGROUND

Helicobacter pylori (H. pylori) is an important risk factor for gastric adenocarcinoma; however, clinical outcomes differ substantially according to the virulence profile of the infecting strain. Diagnostic approaches currently used generally determine pathogen status in a binary manner and therefore do not capture complex molecular variation among strains or variation associated with different disease stages.

AIM

To determine whether H. pylori virulence gene expression varies across clinical stages of gastric cancer (GC) and whether such variation can be used to establish a transcriptional signature associated with disease stage.

METHODS

A two-tier molecular framework was applied to 400 participants recruited in Pakistan, comprising 200 GC cases and 200 non-malignant controls. Tier one examined the prevalence and risk associations of four virulence genes: Cytotoxin-associated gene A (cagA), vacuolating cytotoxin A (vacA), blood group antigen-binding adhesin A (babA), and induced by contact with epithelium gene A (iceA). Tier two quantified transcript expression in 159 H. pylori-positive GC cases spanning tumor-node-metastasis stages I-IV. Relationships between expression and clinical stage were analyzed by ordinal logistic regression, principal component analysis, and a recursive partitioning (decision tree) classifier. Receiver operating characteristic analysis and cross-validation were used to evaluate model performance.

RESULTS

Tier one demonstrated a distinct hierarchy among virulence factors: vacA had the strongest association [odds ratio (OR) = 22.9], with cagA ranking second (OR = 18.7). Tier two identified stage-related differences in virulence gene expression, most notably a decline in babA expression, while cagA and vacA remained comparatively elevated at later disease stages. In multivariate analysis, babA downregulation (OR = 0.536, P < 0.001) and iceA expression (OR = 0.802, P = 0.010) emerged as the most significant independent predictors of clinical stage. In internal validation, the combined four-gene signature yielded an area under the curve (AUC) of 0.769 (95%CI: 0.687-0.851) for overall stage discrimination. This apparent AUC fell to a pooled 5-fold cross-validated AUC of 0.747 (95%CI: 0.664-0.823) on held-out folds, indicating good generalizability. The decision-tree classifier separated early stages (I-II) from advanced stages (III-IV) with an apparent AUC of 0.867 (95%CI: 0.802-0.932; sensitivity 74.5%, 95%CI: 61.6-84.2%; specificity 81.7%, 95%CI: 73.2-88.0%) on the full cohort, which fell to a nested cross-validated AUC of 0.68 (95%CI: 0.59-0.77; sensitivity 54.5%, 95%CI: 41.5-67.0%; specificity 75.0%, 95%CI: 65.9-82.3%) on held-out folds.

CONCLUSION

Expression of H. pylori virulence genes differs across stages of GC. This hypothesis-generating transcriptional signature demonstrated superior discriminatory performance compared with individual gene markers in internal validation. Pending external validation in independent cohorts, it may provide molecular information that complements conventional histopathological evaluation in GC.

Keywords: Helicobacter pylori; Gastric cancer; Virulence factors; Transcriptional profiling; Gene expression; Stage-associated transcriptional signature; Disease staging

Core Tip: Standard diagnostic approaches for Helicobacter pylori generally establish whether the organism is present but do not resolve heterogeneity within gastric cancer. This study evaluates an expression-based discrimination model using a combined four-gene virulence transcript signature (cytotoxin-associated gene A, vacuolating cytotoxin A, blood group antigen-binding adhesin A, and induced by contact with epithelium gene A). The model identifies a stage-associated “adherence-to-invasion” transcriptional shift and, through a decision-tree classifier, discriminates early from advanced clinical stages with an area under the curve of 0.867, falling to 0.68 on nested cross-validation, a promising but modest signal warranting external validation.

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