ArticleAsian Pacific journal of cancer prevention : APJCP2022
ACAN, MDFI, and CHST1 as Candidate Genes in Gastric Cancer: A Comprehensive Insilco Analysis.
Article in Asian Pacific journal of cancer prevention : APJCP, 2022. 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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10 citing papers in PubMed, 10 citations in OpenAlex.
- Diagnostic and prognostic values of differentially expressed genes in canine mammary carcinoma: An integrated bioinformatics analysis.PloS one · 2026Article
- Comprehensive bioinformatic analysis reveals sorafenib response-related prognostic signature in hepatocellular carcinoma.Journal of gastrointestinal oncology · 2025Article
- CHST1 as a prognostic-related biomarker in gastric cancer correlating with immune infiltration.Heliyon · 2025Article
- MDFI promotes the proliferation and tolerance to chemotherapy of colorectal cancer cells by binding ITGB4/LAMB3 to activate the AKT signaling pathway.Cancer biology & therapy · 2024Article
- Integrating Bulk RNA and Single-Cell RNA Sequencing Identifies and Validates Lactylation-Related Signatures for Intervertebral Disc Degeneration.Journal of cellular and molecular medicine · 2024Article
- Comprehensive analysis of prognostic and immunological role of basement membrane-related genes in soft tissue sarcoma.Immunity, inflammation and disease · 2024Article
- Identification of diagnostic markers for moyamoya disease by combining bulk RNA-sequencing analysis and machine learning.Scientific reports · 2024Article
- Systems biology approach to identify biomarkers and therapeutic targets for colorectal cancer.Biochemistry and biophysics reports · 2024Article
- Co-Expression Network Analysis and Molecular Docking Demonstrate That Diosgenin Inhibits Gastric Cancer Progression via SLC1A5/mTORC1 Pathway.Drug design, development and therapy · 2024Article
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4 authors at 2 institutions in 1 country.
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Abstract
backgroundGastric cancer (GC) is a complex disorder with an inadequate response to treatment. Although many efforts have been made to clarify the development of GC, the exact etiology and molecular mechanisms of this malignancy remain unclear. This study was designed to identify and characterize essential associated genes with GC to construct a prognostic model.
methodsIn this Insilco study, the gene expression microarray dataset GSE122401 was downloaded from the Gene Expression Omnibus (GEO). The raw data were processed and quantile-normalized with the edgeR package of R ver.3.5.3. The module-trait relationship and hub-genes associated with GC were analyzed with Weighted Gene Co-expression Network Analysis (WGCNA). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed by Cluepedia and Enrichr Database. Finally, hub-genes were screened and validated by GEPIA online database.
resultsAccording to the WGCNA results, the blue module was found to be strongly correlated with the GC (r=0.91, p-value=1e-57). DEGs analysis was performed by edgeR package of R and indicated a total of 47 genes as hub-genes. Verifying the hub-genes expression using GEPIA online database showed a significantly increased level of ACAN gene expression in primary cancer cell line compared to metastatic cell line. On the other hand, the expression of MDFI and CHST1 genes in primary cell lines were lower compared to metastatic cancer cell lines.
conclusionsThis study provides a framework of the co-expression gene modules ACAN, MDFI, and CHST1 as hub-genes. These hub-genes might offer candidate biomarkers to targeted therapy against GC. Further experiment validation and animal models are needed to reveal the exact mechanism of the above-mentioned genes in the pathogenesis and prognoses of GC.
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