ArticleNature communications2022
Development and validation of a prognostic and predictive 32-gene signature for gastric cancer.
Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers, 3 of them syntheses that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
70 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Predicting Immunotherapy Efficacy with Machine Learning in Gastrointestinal Cancers: A Systematic Review and Meta-Analysis.International journal of molecular sciences · 2025Pooled it
- Current status and trends of machine learning applied in clinical research of gastric cancer from 2004 to 2023: global bibliometric and visual analysis.Frontiers in oncology · 2025Pooled it
- Machine Learning Models for the Identification of Prognostic and Predictive Cancer Biomarkers: A Systematic Review.International journal of molecular sciences · 2023Pooled it
- Use of machine learning-based integration to develop an immune-related signature for improving prognosis in patients with gastric cancer.Scientific reports · 2023Trial
- Multimodal features and prognostic risk assessment in locally advanced gastric cancer patients following neoadjuvant therapy based on machine learning algorithms: a multicenter study.Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association · 2026Article
- Multi-omics dissection of FOXA1 reveals cancer-type-specific transcriptional networks and functional risk variants.iScience · 2026Article
- Immune niche composed of C1QNature communications · 2026Article
- Advances in the molecular subtyping of gastric cancer.World journal of surgical oncology · 2026Review
- Artificial intelligence in immunotherapy: revolutionizing diagnostic and therapeutic applications in cancer and autoimmune diseases.Clinical and experimental medicine · 2026Review
- Article
- Artificial intelligence and machine learning-driven advancements in gastrointestinal cancer: Paving the way for precision medicine.World journal of gastroenterology · 2026Review
- Article
- Precision treatment of gastrointestinal tumours and liver disease interaction mechanisms based on multi-omics data and microbiome hubs.Frontiers in cellular and infection microbiology · 2026Review
- Overcoming resistance to anti-PD-L1 immunotherapy: mechanisms, combination strategies, and future directions.Molecular cancer · 2025Review
- PARP inhibitors in gastric cancer: unlocking precision oncology.The oncologist · 2025Review
- Age-Stratified Clinicopathological Features and Efficacy of Adjuvant Chemotherapy in Resectable Gastric Cancer: An East-West Population-Based Study.Current oncology (Toronto, Ont.) · 2025Article
- CT Scans Understage Lymph Nodes in Gastric and Gastroesophageal Adenocarcinoma.Journal of surgical oncology · 2025Article
- An integrative analysis combining bioinformatics, network pharmacology and experimental methods identified key genes of EGCG targets in Nasopharyngeal Carcinoma.Discover oncology · 2025Article
- An overview of computational methods in single-cell transcriptomic cell type annotation.Briefings in bioinformatics · 2025Review
- Beyond Biomarkers: Machine Learning-Driven Multiomics for Personalized Medicine in Gastric Cancer.Journal of personalized medicine · 2025Review
10 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
16 authors.
Funding
Abstract
Genomic profiling can provide prognostic and predictive information to guide clinical care. Biomarkers that reliably predict patient response to chemotherapy and immune checkpoint inhibition in gastric cancer are lacking. In this retrospective analysis, we use our machine learning algorithm NTriPath to identify a gastric-cancer specific 32-gene signature. Using unsupervised clustering on expression levels of these 32 genes in tumors from 567 patients, we identify four molecular subtypes that are prognostic for survival. We then built a support vector machine with linear kernel to generate a risk score that is prognostic for five-year overall survival and validate the risk score using three independent datasets. We also find that the molecular subtypes predict response to adjuvant 5-fluorouracil and platinum therapy after gastrectomy and to immune checkpoint inhibitors in patients with metastatic or recurrent disease. In sum, we show that the 32-gene signature is a promising prognostic and predictive biomarker to guide the clinical care of gastric cancer patients and should be validated using large patient cohorts in a prospective manner.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.