ArticleFrontiers in oncology2021
Novel Prognostic Biomarkers in Gastric Cancer: CGB5, MKNK2, and PAPPA2.
Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- A prognostic model for gastric cancer constructed by multiple machine learning algorithms.Journal of molecular histology · 2025Article
- Article
- A prognostic model for stomach adenocarcinoma based on hypoxia- and immune-related genes.Archives of medical science : AMS · 2025Article
- Cancer-associated MDM2 W329G mutant attenuates ribosomal stress-mediated p53 responses to promote cell survival and glycolysis.American journal of cancer research · 2024Article
- Unveiling DNA damage repair-based molecular subtypes, tumor microenvironment and pharmacogenomic landscape in gastric cancer.Frontiers in genetics · 2023Article
- Identification and characterization of a novel molecular classification incorporating oxidative stress and metabolism-related genes for stomach adenocarcinoma in the framework of predictive, preventive, and personalized medicine.Frontiers in endocrinology · 2023Article
- ACAN, MDFI, and CHST1 as Candidate Genes in Gastric Cancer: A Comprehensive Insilco Analysis.Asian Pacific journal of cancer prevention : APJCP · 2022Article
- A novel necroptosis-related gene index for predicting prognosis and a cold tumor immune microenvironment in stomach adenocarcinoma.Frontiers in immunology · 2022Review
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7 authors.
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Abstract
introductionGastric cancer is one of the most common malignant tumors of the digestive tract. However, there are no adequate prognostic markers available for this disease. The present study used bioinformatics to identify prognostic markers for gastric cancer that would guide the clinical diagnosis and treatment of this disease. MATERIALS AND
methodsGene expression data and clinical information of gastric cancer patients along with the gene expression data of 30 healthy samples were downloaded from the TCGA database. The initial screening was performed using the WGCNA method combined with the analysis of differentially expressed genes, which was followed by univariate analysis, multivariate COX regression analysis, and Lasso regression analysis for screening the candidate genes and constructing a prognostic model for gastric cancer. Subsequently, immune cell typing was performed using CIBERSORT to analyze the expression of immune cells in each sample. Finally, we performed laboratory validation of the results of our analyses using immunohistochemical analysis.
resultsAfter five screenings, it was revealed that only three genes fulfilled all the screening requirements. The survival curves generated by the prognostic model revealed that the survival rate of the patients in the high-risk group was significantly lower compared to the patients in the low-risk group (P-value < 0.001). The immune cell component analysis revealed that the three genes were differentially associated with the corresponding immune cells (P-value < 0.05). The results of immunohistochemistry also support our analysis.
conclusionCGB5, MKNK2, and PAPPA2 may be used as novel prognostic biomarkers for gastric cancer.
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