Identification of Key Genes in Colorectal Cancer Regulated by miR-34a.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:29197895", "kind": "science-record", "revision": 9, "content_hash": "sha256:b9d58085496861f3a8b72d860afe6af48920a76196e1ba927c10daaed0cbd96a", "created_at": "2026-11-01T15:40:29Z", "updated_at": "2026-11-01T22:43:10Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of Key Genes in Colorectal Cancer Regulated by miR-34a.", "doi": "10.12659/msm.904937", "pmid": "29197895", "authors": ["Tao Wang", "Haihe Xu", "Xianglong Liu", "Shuo Chen", "Yi Zhou", "Xipeng Zhang"], "journal": "Medical science monitor : international medical journal of experimental and clinical research", "year": 2017, "abstract": "BACKGROUND The aim of this study was to screen the molecular targets of miR-34a in colorectal cancer (CRC) and construct the regulatory network, to gain more insights to the pathogenesis of CRC. MATERIAL AND METHODS The microarray data of CRC samples and normal samples (GSE4988), as well as CRC samples transformed with miR-34a and non-transfected CRC samples (GSE7754), were downloaded from the Gene Expression Omnibus (GEO) database. The differently expressed genes (DEGs) were identified via the LIMMA package in R language. The Database for Annotation, Visualization and Integrated Discovery (DAVID) was used to identify significant Gene Ontology (GO) terms and pathways in DEGs. The targets of miR-34a were obtained via the miRWalk database, and then the overlaps between them were selected out to construct the regulatory network of miR-34a in CRC using the Cytoscape software. RESULTS A total of 392 DEGs were identified in CRC samples compared with normal samples, including 239 upregulated genes and 153 downregulated ones. These DEGs were enriched in 75 GO terms and one Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. At the same time, 332 DEGs (188 upregulated and 144 downregulated) were screened out between miR-34a transformed CRC and miR-34a non-transfected CRC samples and they were enriched in 20 GO terms and eight KEGG pathways. Six overlapped genes were identified in two DEGs groups. There were 1,668 targets of miR-34a obtained via the miRWalk database, among which 21 were identified differently expressed in miR-34a transformed CRC samples compared with miR-34a non-transfected CRC samples. Two regulatory networks of miR-34a in CRC within these two groups of overlapped genes were constructed respectively. CONCLUSIONS Pathways related to cell cycle, DNA replication, oocyte meiosis, and pyrimidine metabolism might play critical roles in the progression of CRC. Several genes such as SERPINE1, KLF4, SEMA4B, PPARG, CDC45, and KIAA0101 might be the targets of miR-34a and the potential therapeutic targets of CRC.", "claims": [{"id": "claim-method", "statement": "LIMMA package in R language was used to analyze the DEGs in CRC samples compared to normal samples (regarded as DEGs-1), as well as CRC samples transformed with miR-34a compared to non-transfected CRC samples (regarded as DEGs-2).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:29197895", "locator": "sections[4] \"Data preprocessing and identification of DEGs\" paragraph 2", "quote": "LIMMA package in R language was used to analyze the DEGs in CRC samples compared to normal samples (regarded as DEGs-1), as well as CRC samples transformed with miR-34a compared to non-transfected CRC samples (regarded as DEGs-2)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Microarray data set GSE4988 and GSE7754 were downloaded from the GEO (http://www.ncbi.nlm.nih.gov/geo/) database. The GSE4988 data set contained 20 samples: 12 CRC samples and eight normal samples. These microarray data were analyzed using the GPL3014 (ResGenHs15K_DIO) platform.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:29197895", "locator": "sections[3] \"Microarray data\" paragraph 2", "quote": "Microarray data set GSE4988 and GSE7754 were downloaded from the GEO (http://www.ncbi.nlm.nih.gov/geo/) database. The GSE4988 data set contained 20 samples: 12 CRC samples and eight normal samples. These microarray data were analyzed using the GPL3014 (ResGenHs15K_DIO) platform."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Using the GEO datasets GSE4988 and GSE7754, preprocessed with RMA and analyzed with the LIMMA package in R, the study identified 392 DEGs in CRC versus normal samples and 332 DEGs in miR-34a-transformed versus non-transfected CRC samples.", "kind": "quantitative", "target": {"value": 0.05, "unit": "p-value", "tolerance": null, "source": "DEGs were obtained according to the criteria: adjusted p<0.05 and |log(fold change)| >1."}, "evidence": [{"asset": "source:pmid:29197895", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "The microarray data of CRC samples and normal samples (GSE4988), as well as CRC samples transformed with miR-34a and non-transfected CRC samples (GSE7754), were downloaded from the Gene Expression Omnibus (GEO) database."}, {"asset": "source:pmid:29197895", "locator": "sections[4] \"Data preprocessing and identification of DEGs\" paragraph 2", "quote": "The raw data was background corrected, log2 transformed, and quantile normalized using Robust Multi-array Average (RMA)."}, {"asset": "source:pmid:29197895", "locator": "sections[4] \"Data preprocessing and identification of DEGs\" paragraph 2", "quote": "LIMMA package in R language was used to analyze the DEGs in CRC samples compared to normal samples (regarded as DEGs-1), as well as CRC samples transformed with miR-34a compared to non-transfected CRC samples (regarded as DEGs-2)."}, {"asset": "source:pmid:29197895", "locator": "sections[4] \"Data preprocessing and identification of DEGs\" paragraph 2", "quote": "DEGs were obtained according to the criteria: adjusted p<0.05 and |log(fold change)| >1."}, {"asset": "source:pmid:29197895", "locator": "sections[10] \"Identification of DEGs\" paragraph 2", "quote": "After data preprocessing, a total of 392 DEGs were identified in DEGs-1."}, {"asset": "source:pmid:29197895", "locator": "sections[10] \"Identification of DEGs\" paragraph 2", "quote": "At the same time, the DEGs-2 set contained 332 DEGs (188 upregulated and 144 downregulated), and the top 20 DEGs of are shown in Figure 1B."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Using the GEO datasets GSE4988 and GSE7754, preprocessed with RMA and analyzed with the LIMMA package in R, the study identified 392 DEGs in CRC versus normal samples and 332 DEGs in miR-34a-transformed versus non-transfected CRC samples.", "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:29197895"], "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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MATERIAL AND METHODS The microarray data of CRC samples and normal samples (GSE4"], "order_basis": "paper_text_order:246", "id": "assay:1"}, {"role": "data_generation", "definition_id": "transfection", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["CRC samples transformed with miR-34a and non-transfected CRC samples (GSE7754), were downloaded from", "ween miR-34a transformed CRC and miR-34a non-transfected CRC samples and they were enriched in 20 GO", "formed CRC samples compared with miR-34a non-transfected CRC samples. Two regulatory networks of miR-"], "order_basis": "paper_text_order:363", "id": "assay:2"}, {"role": "analysis", "definition_id": "differential_expression", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["LIMMA package in R language was used to analyze the DEGs in CRC samples compared to normal samples (regarded as DEGs-1), as well as CRC samples transformed with miR-34a compared to non-transfected CRC samples (regarded as DEGs-2)."], "order_basis": "consumes_earlier_output", "id": "assay:3"}]}