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pmid:29844680
Identifying miRNA and gene modules of colon cancer associated with pathological stage by weighted gene co-expression network analysis.
Xian-Guo Zhou · Xiao-Liang Huang · Si-Yuan Liang · Shao-Mei Tang · Si-Kao Wu · Tong-Tong Huang · Zeng-Nan Mo · Qiu-Yan Wang
OncoTargets and therapy · 2018 doi:10.2147/OTT.S163891
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Complete file
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The tumor, node, metastasis (TNM) stage remains the standard for CRC prognostication. Identification of meaningful microRNA (miRNA) and gene modules or representative biomarkers related to the pathological stage of colon cancer helps to predict prognosis and reveal the mechanisms behind cancer progression.\nMATERIALS AND METHODS: We applied a systems biology approach by combining differential expression analysis and weighted gene co-expression network analysis (WGCNA) to detect the pathological stage-related miRNA and gene modules and construct a miRNA-gene network. The Cancer Genome Atlas (TCGA) colon adenocarcinoma (CAC) RNA-sequencing data and miRNA-sequencing data were subjected to WGCNA analysis, and the GSE29623, GSE35602 and GSE39396 were utilized to validate and characterize the results of WGCNA.\nRESULTS: Two gene modules (Gmagenta and Ggreen) and one miRNA module were associated with the pathological stage. Six hub genes (COL1A2, THBS2, BGN, COL1A1, TAGLN and DACT3) were related to prognosis and validated to be associated with the pathological stage. Five hub miRNAs were identified to be related to prognosis (hsa-miR-125b-5p, hsa-miR-145-5p, hsa-let-7c-5p, hsa-miR-218-5p and hsa-miR-125b-2-3p). A total of 18 hub genes and seven hub miRNAs were predominantly expressed in tumor stroma. Proteoglycans in cancer, focal adhesion, extracellular matrix (ECM)-receptor interaction and so on were common pathways of the three modules. Hsa-let-7c-5p was located at the core of miRNA-gene network.\nCONCLUSION: These findings help to advance the understanding of tumor stroma in the progression of CAC and provide prognostic biomarkers as well as therapeutic targets.", "claims": [{"id": "claim-method", "statement": "The gene co-expression networks and miRNA co-expression networks were constructed by the WGCNA package based on DEGs and DEMs.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:29844680", "locator": "sections[5] \"Weighted gene co-expression network construction and module detection\" paragraph 2", "quote": "The gene co-expression networks and miRNA co-expression networks were constructed by the WGCNA package based on DEGs and DEMs."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The level three RNA-sequencing data (RNA-Seq-HTSeq) and level three miRNA isoform expression quantification data (miRNA-Seq-BCGSC miRNA Profiling) of CAC patients were downloaded from The Cancer Genome Atlas (TCGA; http://cancergenome.nih.gov/) on October 5, 2017.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:29844680", "locator": "sections[3] \"Data collection and preprocessing\" paragraph 2", "quote": "The level three RNA-sequencing data (RNA-Seq-HTSeq) and level three miRNA isoform expression quantification data (miRNA-Seq-BCGSC miRNA Profiling) of CAC patients were downloaded from The Cancer Genome Atlas (TCGA; http://cancergenome.nih.gov/) on October 5, 2017."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The study combined differential expression analysis with weighted gene co-expression network analysis (WGCNA), using TCGA colon adenocarcinoma RNA-sequencing and miRNA-sequencing data and validating the results with the GEO datasets GSE29623, GSE35602 and GSE39396.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:29844680", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "We applied a systems biology approach by combining differential expression analysis and weighted gene co-expression network analysis (WGCNA) to detect the pathological stage-related miRNA and gene modules and construct a miRNA–gene network."}, {"asset": "source:pmid:29844680", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "The Cancer Genome Atlas (TCGA) colon adenocarcinoma (CAC) RNA-sequencing data and miRNA-sequencing data were subjected to WGCNA analysis, and the GSE29623, GSE35602 and GSE39396 were utilized to validate and characterize the results of WGCNA."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The study combined differential expression analysis with weighted gene co-expression network analysis (WGCNA), using TCGA colon adenocarcinoma RNA-sequencing and miRNA-sequencing data and validating the results with the GEO datasets GSE29623, GSE35602 and GSE39396.", "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:29844680"], "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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