Integrated Analysis of Oncogenic Networks in Colorectal Cancer Identifies GUCA2A as a Molecular Marker.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:31467713", "kind": "science-record", "revision": 8, "content_hash": "sha256:7ae0e03da4b165ef769efecad2a271f79c1d9d0d89a8d32d4665635e2703fce5", "created_at": "2026-11-01T15:40:49Z", "updated_at": "2026-11-01T22:44:10Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Integrated Analysis of Oncogenic Networks in Colorectal Cancer Identifies GUCA2A as a Molecular Marker.", "doi": "10.1155/2019/6469420", "pmid": "31467713", "authors": ["Hui Zhang", "Yuanyuan Du", "Zhuo Wang", "Rui Lou", "Jianzhong Wu", "Jifeng Feng"], "journal": "Biochemistry research international", "year": 2019, "abstract": "Colorectal cancer (CRC) is one of the most common and deadly malignancies in the world. In China, the morbidity rate of CRC has increased during the period 2000 to 2011. Biomarker detection for early CRC diagnosis can effectively reduce the mortality of patients with CRC. To explore the underlying mechanisms of effective biomarkers and identify more of them, we performed weighted correlation network analysis (WGCNA) on a GSE68468 dataset generated from 378 CRC tissue samples. We screened the gene set (module), which was significantly associated with CRC histology, and analyzed the hub genes. The key genes were identified by obtaining six colorectal raw data (i.e., GSE25070, GSE44076, GSE44861, GSE21510, GSE9348, and GSE21815) from the GEO database (https://www.ncbi.nlm.nih.gov/geo). The robust differentially expressed genes (DEGs) in all six datasets were calculated and obtained using the library \"RobustRankAggreg\" package in R 3.5.1. An integrated analysis of CRC based on the top 50 downregulated DEGs and hub genes in the red module from WGCNA was conducted, and the intersecting genes were screened. The Kaplan-Meier plot was further analyzed, and the genes associated with CRC prognosis based on patients from the TCGA database were determined. Finally, we validated the candidate gene in our clinical CRC specimens. We postulated that the candidate genes screened from the database and verified by our clinical pathological data may contribute to understanding the molecular mechanisms of tumorigenesis and may serve as potential biomarkers for CRC diagnosis and treatment.", "claims": [{"id": "claim-method", "statement": "Then, we further evaluated the diagnostic value of GUCA2A for CRC tissues and normal counterparts using ROC curve analyses.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:31467713", "locator": "sections[7] \"2.5. Human Tissue Samples and Quantitative Real-Time PCR\" paragraph 2", "quote": "Then, we further evaluated the diagnostic value of GUCA2A for CRC tissues and normal counterparts using ROC curve analyses."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The data used to support the findings of this study are available from the corresponding author upon request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:31467713", "locator": "sections[18] \"Data Availability\" paragraph 2", "quote": "The data used to support the findings of this study are available from the corresponding author upon request."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "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:31467713"], "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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The PCR reactant mix co", "2.5. Human Tissue Samples and Quantitative Real-Time PCR We performed real-time PCR to examine the le", "and Quantitative Real-Time PCR We performed real-time PCR to examine the levels of GUCA2A in 31 paired", "s 4.5. 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