ArticleFrontiers in cellular and infection microbiology2022
A Multi-Omics Study on the Effect of Helicobacter Pylori-Related Genes in the Tumor Immunity on Stomach Adenocarcinoma.
Article in Frontiers in cellular and infection microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 17 citations in OpenAlex.
- The interplay between recovery and immunity in infectious and non-communicable diseases.Frontiers in cellular and infection microbiology · 2026Review
- Deep learning for smartphone-aided detection system of Helicobacter Pylori in gastric biopsy.Scientific reports · 2025Article
- Multi-omics analysis of Helicobacter pylori-associated gastric cancer identifies hub genes as a novel therapeutic biomarker.Briefings in bioinformatics · 2025Article
- Efficacy and safety of sintilimab combined with trastuzumab and chemotherapy in HER2-positive advanced gastric or gastroesophageal junction cancer.Frontiers in immunology · 2025Article
- A Prognostic Riskscore Model Related toInternational journal of genomics · 2025Article
- Comprehensive analysis of T-cell regulatory factors and tumor immune microenvironment in stomach adenocarcinoma.BMC cancer · 2024Article
- Multi-omics Combined with Machine Learning Facilitating the Diagnosis of Gastric Cancer.Current medicinal chemistry · 2024Review
- Exploration of gastric carcinogenesis from the relationship between bile acids and intestinal metaplasia and intragastric microorganisms (H. pylori and non-H. pylori).Journal of cancer research and clinical oncology · 2023Review
- Metabolite Alterations and Interactions with Microbiota in Helicobacter pylori-Associated Gastric Lesions.Microbiology spectrum · 2023Article
- Identification of a six-gene signature to predict survival and immunotherapy effectiveness of gastric cancer.Frontiers in oncology · 2023Article
- Construction of mRNA prognosis signature associated with differentially expressed genes in early stage of stomach adenocarcinomas based on TCGA and GEO datasets.European journal of medical research · 2022Article
- An Immune Signature for Risk Stratification and Therapeutic Prediction in Helicobacter pylori-Infected Gastric Cancer.Cancers · 2022Article
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Methods: HP infection-induced mutation patterns of STAD samples from six cohorts were comprehensively assessed based on 73 HP-related genes, which were then correlated with the immune cell-infiltrating characteristics of the tumor microenvironment (TME). The risk signature was constructed to quantify the influence of HP infection on individual tumors. Subsequently, an accurate nomogram was generated to improve the clinical applicability of the risk signature. We conducted immunohistochemical experiments and used the Affiliated Hospital of Youjiang Medical University for Nationalities (AHYMUN) cohort data set with survival information to further verify the clinical value of this risk signature. Results: Two distinct HP-related mutation patterns with different immune cell-infiltrating characteristics (ICIC) and survival possibility were identified. We demonstrated that the evaluation of HP infection-induced mutation patterns of tumor could assist the prediction of stages, phenotypes, stromal activity, genetic diversity, and patient prognosis. A low risk score involved an increased mutation burden and activation of immune responses, with a higher 5-year survival rate and enhanced response to anti-PD-1/L1 immunotherapy, while a high risk score involved stromal activation and poorer survival. The efficiency of the risk signature was further evidenced by the nomogram. Conclusions: STAD patients with a low risk score demonstrated significant therapeutic advantages and clinical benefits. HP infection-induced mutations play a nonnegligible role in STAD development. Quantifying the HP-related mutation patterns of individual tumors will contribute to phenotype classification, guide more effective targeted and personalized therapies, and enable more accurate predictions of metastasis and prognosis.
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