Identification of the circRNA-miRNA-mRNA regulatory network and its prognostic effect in colorectal cancer.

{"sci_version": "1.0", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34222420", "kind": "science-record", "revision": 3, "content_hash": "sha256:ed629d64a2ae9a56473d0314b94a8ab29ad4cdc62796fdf9479022291341a273", "created_at": "2026-11-01T15:41:42Z", "updated_at": "2026-11-01T18:56:00Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of the circRNA-miRNA-mRNA regulatory network and its prognostic effect in colorectal cancer.", "doi": "10.12998/wjcc.v9.i18.4520", "pmid": "34222420", "authors": ["Teng-Fei Yin", "Dong-Yan Zhao", "Yuan-Chen Zhou", "Qian-Qian Wang", "Shu-Kun Yao"], "journal": "World journal of clinical cases", "year": 2021, "abstract": "BACKGROUND: The high morbidity and mortality of colorectal cancer (CRC) have posed great threats to human health. Circular RNA (CircRNA) and microRNA (miRNA), acting as competing endogenous RNAs (ceRNAs), have been found to play vital roles in carcinogenesis. However, the biological function of ceRNAs in CRC pathogenesis and prognosis remains largely unexplored.\nAIM: To identify the CRC-specific circRNA-miRNA-mRNA regulatory network and uncover the subnetwork associated with its prognosis.\nMETHODS: CircRNAs, miRNAs and mRNAs differentially expressed (DE) in CRC tissues were selected by expression file analysis in the Gene Expression Omnibus (GEO) database, and the downstream target molecules of circRNAs and miRNAs were predicted. Then, the intersection of differentially expressed RNA molecules with the predicted targets was determined to obtain a ceRNA network. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were conducted to elucidate the possible mechanism of pathogenesis. A survival analysis using the gene profiles and clinical information in The Cancer Genome Atlas (TCGA) database was performed to identify the mRNAs associated with the clinical outcome of CRC patients and construct a prognostic subnetwork.\nRESULTS: We downloaded three datasets (GSE126095, GSE41655 and GSE41657) of large-scale CRC samples from the GEO database. There were 55 DEcircRNAs, 114 DEmiRNAs and 267 DEmRNAs in CRC tissues compared with normal tissues. After intersecting these molecules with predicted targets, 19 circRNAs, 13 miRNAs and 28 mRNAs were chosen to develop a circRNA-miRNA-mRNA network. GO and KEGG functional enrichment analyses indicated that the retinol metabolic process, leukocyte chemotaxis, extracellular matrix remodeling, endoplasmic reticulum stress, alcohol dehydrogenase activity, gastric acid secretion, nitrogen metabolism and NOD-like receptor signaling pathway might participate in the tumorigenesis of CRC. After verifying the identified mRNA effect in the TCGA database, we finally recognized 3 mRNAs (CA2, ITLN1 and LRRC19) that were significantly associated with the overall survival of CRC patients and constructed a ceRNA subnetwork including 5 circRNAs (hsa_circ_0080210, hsa_circ_0007158, hsa_circ_0000375, hsa_circ_0018909 and hsa_circ_0011536) and 3 miRNAs (hsa-miR-601, hsa-miR-671-5p and hsa-miR-765), which could contain innovative and noninvasive indicators for the early screening and prognostic prediction of CRC.\nCONCLUSION: We proposed a circRNA-miRNA-mRNA regulatory network closely associated with the progression and clinical outcome of CRC that might include promising biomarkers for carcinogenesis and therapeutic targets.", "claims": [{"id": "claim-data-access", "statement": "No additional data are available.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34222420", "locator": "sections[27] \"Data sharing statement\" paragraph 2", "quote": "No additional data are available."}], "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:34222420"], "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. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE126095"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE126095"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:34222420", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.12998/wjcc.v9.i18.4520", "sha256": 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