ArticleBiomolecules2023
Epigenetic and Tumor Microenvironment for Prognosis of Patients with Gastric Cancer.
Article in Biomolecules, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed, 26 citations in OpenAlex.
- Claudin proteins as emerging therapeutic targets for solid tumours.Nature reviews. Cancer · 2026Review
- A machine learning-based epigenetic signature reveals YTHDC1 stabilizes POU5F1 to oppose tumor progression.Journal of translational medicine · 2026Article
- ITPG: an immune-related transcriptomic predictive model for gastric cancer prognosis.Translational cancer research · 2026Article
- Spatial immune cell architecture after gastric cancer surgery predicts prognosis.World journal of gastrointestinal surgery · 2026Article
- OLFML2B promotes hepatocellular carcinoma malignancy via the PI3K/AKT-EMT axis and correlates with an immunosuppressive tumor microenvironment.Frontiers in immunology · 2026Article
- Role of Aldo-Keto reductase family 1 member C in cancer progression: a special focus on the role of AKR1C1 in pancreatic cancer.Medical oncology (Northwood, London, England) · 2025Article
- Identifying Potential Diagnostic and Therapeutic Targets for Infantile Hemangioma Using WGCNA and Machine Learning Algorithms.Biochemical genetics · 2025Article
- A novel machine learning-based predictive model for gastric cancer.Translational cancer research · 2025Article
- Beyond Biomarkers: Machine Learning-Driven Multiomics for Personalized Medicine in Gastric Cancer.Journal of personalized medicine · 2025Review
- Integrative analysis and prognostication in gastric cancer: unveiling the role of mitochondrial genomics with the MLRScore model.Discover oncology · 2025Article
- KLK8: charting new territories in left ventricular hypertrophy biomarker research.Biomarkers in medicine · 2025Article
- The Oncogenic Role of UBXN1 in Gastric Cancer Is Attributed to the METTL16-Mediated m6A Methylation and Histone Modifications.Cancer medicine · 2025Article
- Article
- Advances in small extracellular vesicles: roles in the tumor microenvironment and epithelial ovarian cancer diagnosis and treatment.Frontiers in oncology · 2025Review
- Deep Learning and Single-Cell Sequencing Analyses Unveiling Key Molecular Features in the Progression of Carotid Atherosclerotic Plaque.Journal of cellular and molecular medicine · 2024Article
- The dual role of LOXL4 in the pathogenesis and development of human malignant tumors: a narrative review.Translational cancer research · 2024Review
- Amlodipine inhibits Synaptotagmin-4's oncogenic activity on gastric cancer proliferation by targeting calcium signaling.Functional & integrative genomics · 2024Article
- Decoding the Versatile Landscape of Autophagic Protein VMP1 in Cancer: A Comprehensive Review across Tissue Types and Regulatory Mechanisms.International journal of molecular sciences · 2024Review
- Epigenetic modulation of cytokine expression in gastric cancer: influence on angiogenesis, metastasis and chemoresistance.Frontiers in immunology · 2024Review
- Comprehensive bioinformatics analysis of the solute carrier family and preliminary exploration of SLC25A29 in lung adenocarcinoma.Cancer cell international · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundEpigenetics studies heritable or inheritable mechanisms that regulate gene expression rather than altering the DNA sequence. However, no research has investigated the link between TME-related genes (TRGs) and epigenetic-related genes (ERGs) in GC.
methodsA complete review of genomic data was performed to investigate the relationship between the epigenesis tumor microenvironment (TME) and machine learning algorithms in GC.
resultsFirstly, TME-related differential expression of genes (DEGs) performed non-negative matrix factorization (NMF) clustering analysis and determined two clusters (C1 and C2). Then, Kaplan-Meier curves for overall survival (OS) and progression-free survival (PFS) rates suggested that cluster C1 predicted a poorer prognosis. The Cox-LASSO regression analysis identified eight hub genes (
conclusionThe study identified some hub genes that could be useful in predicting prognosis and management in GC.
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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.