ArticleClinical and experimental medicine2025
Multi-omics unravel heterogeneity of glucose metabolism reprogramming in gastric cancer.
Article in Clinical and experimental medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Evaluation of translational potential of mRNA vaccine candidate antigens for pancreatic cancer: a systematic review based on clinical evidence and stratified prioritization strategies.Frontiers in immunology · 2026Pooled it
- The evolving landscape of the Warburg effect in gastric cancer: From molecular mechanisms to targeted therapy.Clinical and translational medicine · 2026Review
- Cellular Origins and Context-Dependent Prognostic Effects of Lactate Metabolism Genes Reveal Novel Molecular Subtypes in Gastric Cancer.Current issues in molecular biology · 2026Article
- Significance of the geriatric nutritional risk index and body composition as prognostic indicators in gastric cancer patients.Frontiers in oncology · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gastric cancer (GC) presents striking survival disparities: 85-100% for early-stage versus only 5-20% for advanced disease. Glucose metabolic reprogramming (GMS)-a cancer hallmark linked to the Warburg effect-fuels tumor progression and immune evasion via lactate. This study uses multi-omics data to delineate GMS heterogeneity and its clinical relevance in GC. Single-cell, spatial, and bulk transcriptomic data were integrated. BayesPrism deconvoluted bulk data, CytoTRACE2, CellChat, and NicheNet analyzed cell trajectories, communication, and ligand-receptor regulation, respectively. MOVICS performed multi-omics (mRNA, methylation, mutation, and lncRNA) clustering of TCGA-STAD. Mime1 integrated machine learning to build a prognostic model based on GMS-related genes and CS2/TOP2A features. Differential expression and functional enrichment explored mechanisms. Verification of expression differences in key genes using qPCR. In gastric cancer research, GMS scores exhibit significant enrichment. Single-cell analysis identified a TOP2A
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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.