ArticlePeerJ2020
A transcriptional co-expression network-based approach to identify prognostic biomarkers in gastric carcinoma.
Article in PeerJ, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 20 citations in OpenAlex.
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- MicroRNA-210-3p Regulates Endometriotic Lesion Development by Targeting IGFBP3 in Baboons and Women with Endometriosis.Reproductive sciences (Thousand Oaks, Calif.) · 2023Article
- Cannabinoid Receptor Interacting Protein 1a (CRIP1a) in Health and Disease.Biomolecules · 2020Review
- Clinical value and potential mechanisms of COL8A1 upregulation in breast cancer: a comprehensive analysis.Cancer cell international · 2020Article
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Authors and funding
3 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGastric carcinoma is a very diverse disease. The progression of gastric carcinoma is influenced by complicated gene networks. This study aims to investigate the actual and potential prognostic biomarkers related to survival in gastric carcinoma patients to further our understanding of tumor biology.
methodsA weighted gene co-expression network analysis was performed with a transcriptome dataset to identify networks and hub genes relevant to gastric carcinoma prognosis. Data was obtained from 300 primary gastric carcinomas (GSE62254). A validation dataset (GSE34942 and GSE15459) and TCGA dataset confirmed the results. Gene ontology, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and gene set enrichment analysis (GSEA) were performed to identify the clusters responsible for the biological processes and pathways of this disease.
resultsA brown transcriptional module enriched in the organizational process of the extracellular matrix was significantly correlated with overall survival (HR = 1.586,
conclusionA transcriptional co-expression network-based approach was used to identify prognostic biomarkers in gastric carcinoma. This method may have potential for use in personalized therapies, however, large-scale randomized controlled clinical trials and replication experiments are needed before these key biomarkers can be applied clinically.
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