ReviewFrontiers in immunology2025
Harnessing glycolysis in gastric cancer: molecular targets, therapeutic strategies, and clinical horizons.
Review in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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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
10 citing papers in PubMed.
- Metabolic and muscular adaptations to dietary succinate in Tan sheep: Insights from transcriptomics.Animal nutrition (Zhongguo xu mu shou yi xue hui) · 2026Article
- The evolving landscape of the Warburg effect in gastric cancer: From molecular mechanisms to targeted therapy.Clinical and translational medicine · 2026Review
- Metabolic remodeling by circular RNAs in gastric tumorigenesis: From mechanisms to biomarker discovery (Review).International journal of oncology · 2026Review
- Multidimensional Regulatory Network and Spatiotemporal Specificity of FOXO Transcription Factors in Digestive System Tumors: Recent Advances.International journal of molecular sciences · 2026Review
- Role of histone modifications in gastric cancer (Review).International journal of oncology · 2026Review
- Tumor microenvironment dynamics in gastric cancer pathogenesis and therapeutic resistance.Molecular cancer · 2026Review
- Amino Acid Metabolic Enzymes in Gastric Cancer: Roles and Mechanisms in Tumorigenesis and Progression.Oncology research · 2026Review
- PTM encoding: decoding the mechanisms of exercise-induced metabolic memory through spatiotemporal modification networks.Frontiers in sports and active living · 2026Review
- Glycolytic reprogramming in precancerous lesions of gastric cancer progression: pathogenesis and therapeutic potential.Frontiers in oncology · 2026Review
- Research hotspots and frontiers in the tumor microenvironment of gastric cancer: a bibliometric review from 2005 to 2024.Translational cancer research · 2025Article
Corrections and comments
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Authors and funding
2 authors.
Funding
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Abstract
Gastric cancer (GC) continues to rank among the leading causes of cancer-related mortality globally, with treatment resistance and recurrence posing significant clinical hurdles. While surgical interventions, chemotherapy, and targeted therapies are available, their efficacy in managing advanced or metastatic forms of the disease remains constrained. This review provided an overview of the role of glycolytic reprogramming in gastric cancer, emphasizing the complex regulation by epigenetic mechanisms, non-coding RNAs, post-translational modifications, and oncogenic signaling pathways. This review discusses how epigenetic mechanisms, including m6A methylation and ceRNA networks involving circRNAs and microRNAs, modulate key glycolytic enzymes such as PKM2, HK2, and PGK1, thereby promoting tumor growth, metastasis, and chemoresistance. The study also emphasizes the impact of post-translational modifications like succinylation and ubiquitination on enzyme activity, affecting glycolytic flux and tumor adaptability. Additionally, the article details the crosstalk between glycolytic pathways and oncogenic signaling networks, including hypoxia-inducible factors and YAP/TAZ transcriptional regulators, which sustain tumor stemness and immune evasion. Therapeutic strategies targeting these metabolic vulnerabilities-such as inhibiting m6A regulators, disrupting ceRNA interactions, and modulating enzyme modifications-are discussed as potential approaches to improve gastric cancer treatment. Overall, we underscores the complexity of metabolic regulation in gastric cancer and proposes that targeting its epigenetic and signaling networks offers promising avenues for innovative therapies to overcome resistance and hinder tumor progression.
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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 Socratic graph.