ArticleClinical and translational gastroenterology2019
Whole Genome Messenger RNA Profiling Identifies a Novel Signature to Predict Gastric Cancer Survival.
Article in Clinical and translational gastroenterology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
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Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Systematic Review of Prognostic Gene Signature in Gastric Cancer Patients.Frontiers in bioengineering and biotechnology · 2020Pooled it
- CDX2-UPK1B-PIK3IP1-PI3K/AKT signaling axis regulates gastric cancer cell invasion and migration and influences patient prognosis.Experimental and therapeutic medicine · 2026Article
- Exploring the significance of fatty acid metabolism reprogramming in the pathogenesis of cancer and anticancer therapy.Annals of medicine · 2025Review
- Identification of gastric cancer subtypes based on disulfidptosis-related genes: GPC3 as a novel biomarker for prognosis prediction.Discover oncology · 2024Article
- Whole Exome-Wide Association Identifies Rare Variants inCancers · 2024Article
- Bioinformatics Analysis and Validation of Potential Markers Associated with Prediction and Prognosis of Gastric Cancer.International journal of molecular sciences · 2024Review
- Pachydermoperiostosis combined with pyloric gland adenoma with foveolar-type adenoma.United European gastroenterology journal · 2024Article
- KRT13 and UPK1B for differential diagnosis between metastatic lung carcinoma from oral squamous cell carcinoma and lung squamous cell carcinoma.Scientific reports · 2023Article
- Aberrant methylation in neurofunctional gene serves as a hallmark of tumorigenesis and progression in colorectal cancer.BMC cancer · 2023Article
- A 9‑gene expression signature to predict stage development in resectable stomach adenocarcinoma.BMC gastroenterology · 2022Article
- Key Molecules of Fatty Acid Metabolism in Gastric Cancer.Biomolecules · 2022Review
- Identification of a seven-cell cycle signature predicting overall survival for gastric cancer.Aging · 2022Article
- DNA Repair and Replication-Related Gene Signature Based on Tumor Mutation Burden Reveals Prognostic and Immunotherapy Response in Gastric Cancer.Journal of oncology · 2022Article
- Revisiting social MPE: an integration of molecular pathological epidemiology and social science in the new era of precision medicine.Expert review of molecular diagnostics · 2021Article
- Article
- A universal molecular prognostic score for gastrointestinal tumors.NPJ genomic medicine · 2021Article
- Tetraspanins: Novel Molecular Regulators of Gastric Cancer.Frontiers in oncology · 2021Review
- The prediction of survival in Gastric Cancer based on a Robust 13-Gene Signature.Journal of Cancer · 2021Article
- Identification of biomarkers predicting the chemotherapeutic outcomes of capecitabine and oxaliplatin in patients with gastric cancer.Oncology letters · 2020Article
- A Prognostic Nomogram Model Based on mRNA Expression of DNA Methylation-Driven Genes for Gastric Cancer.Frontiers in oncology · 2020Article
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8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesMolecular prognostic biomarkers for gastric cancer (GC) are still limited. We aimed to identify potential messenger RNAs (mRNAs) associated with GC prognosis and further establish an mRNA signature to predict the survival of GC based on the publicly accessible databases.
methodsDiscovery of potential mRNAs associated with GC survival was undertaken for 441 patients with GC based on the Cancer Genome Atlas (TCGA), with information on clinical characteristics and vital status. Gene ontology functional enrichment analysis and pathway enrichment analysis were conducted to interrogate the possible biological functions. We narrowed down the list of mRNAs for validation study based on a significance level of 1.00 × 10, also integrating the information from the methylation analysis and constructing the protein-protein interaction network for elucidating biological processes. A total of 54 mRNAs were further studied in the validation stage, using the Gene Expression Omnibus (GEO) database (GSE84437, n = 433). The validated mRNAs were used to construct a risk score model predicting the prognosis of GC.
resultsA total of 13 mRNAs were significantly associated with survival of GC, after the validation stage, including DCLK1, FLRT2, MCC, PRICKLE1, RIMS1, SLC25A15, SLCO2A1, CDO1, GHR, CD109, SELP, UPK1B, and CD36. Except CD36, DCLK1, and SLCO2A1, other mRNAs are newly reported to be associated with GC survival. The 13 mRNA-based risk score had good performance on distinguishing GC prognosis, with a higher score indicating worse survival in both TCGA and GEO datasets.
conclusionsWe established a 13-mRNA signature to potentially predict the prognosis of patients with GC, which might be useful in clinical practice for informing patient stratification.
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