ACAN, MDFI, and CHST1 as Candidate Genes in Gastric Cancer: A Comprehensive Insilco Analysis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35225482", "kind": "science-record", "revision": 5, "content_hash": "sha256:8e621957d929ea0f42b80031677e08888c15cda452858b5ef20a2e09276d0492", "created_at": "2026-11-01T17:36:59Z", "updated_at": "2026-11-01T22:06:00Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "ACAN, MDFI, and CHST1 as Candidate Genes in Gastric Cancer: A Comprehensive Insilco Analysis.", "doi": "10.31557/APJCP.2022.23.2.683", "pmid": "35225482", "authors": ["Farzane Vafaeie", "Samira Nomiri", "Javad Ranjbaran", "Hossein Safarpour"], "journal": "Asian Pacific journal of cancer prevention : APJCP", "year": 2022, "abstract": "BACKGROUND: Gastric 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.\nMETHODS: In 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.\nRESULTS: According 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.\nCONCLUSIONS: This 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.", "claims": [{"id": "claim-method", "statement": "We used WGCNA for reconstructing the co-expression network of GC genes.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35225482", "locator": "sections[2] \"Materials and Methods\" paragraph 7", "quote": "We used WGCNA for reconstructing the co-expression network of GC genes."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The gene expression dataset GSE122401 was downloaded from the Gene Expression Omnibus (GEO; https://www.ncbi.nlm.nih.gov/geo/) database, which is based on Illumina HiSeq 2500 GPL16791 platform. Notably, this dataset provides a raw read count of 160 human GC samples and normal adjacent specimens (Mun et al., 2019).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35225482", "locator": "sections[2] \"Materials and Methods\" paragraph 5", "quote": "The gene expression dataset GSE122401 was downloaded from the Gene Expression Omnibus (GEO; https://www.ncbi.nlm.nih.gov/geo/) database, which is based on Illumina HiSeq 2500 GPL16791 platform. Notably, this dataset provides a raw read count of 160 human GC samples and normal adjacent specimens (Mun et al., 2019)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The blue WGCNA module was strongly correlated with gastric cancer (r=0.91, p-value=1e-57).", "kind": "quantitative", "target": {"value": 0.91, "unit": "correlation coefficient", "tolerance": null, "source": "Accordingly, the blue module was found to be strongly correlated with the GC (r=0.91, p-value=1e-57) (Table 1 and Figure 5a)."}, "evidence": [{"asset": "source:pmid:35225482", "locator": "sections[3] \"Results\" paragraph 11", "quote": "Accordingly, the blue module was found to be strongly correlated with the GC (r=0.91, p-value=1e-57) (Table 1 and Figure 5a)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The blue WGCNA module was strongly correlated with gastric cancer (r=0.91, p-value=1e-57).", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:35225482"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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