Prediction of novel target genes and pathways involved in bevacizumab-resistant colorectal cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:29342159", "kind": "science-record", "revision": 7, "content_hash": "sha256:d979748b511334c67856e5b03c7901a872204c2073b37403fe8f2b916bc05c14", "created_at": "2026-11-01T15:40:31Z", "updated_at": "2026-11-01T21:59:40Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Prediction of novel target genes and pathways involved in bevacizumab-resistant colorectal cancer.", "doi": "10.1371/journal.pone.0189582", "pmid": "29342159", "authors": ["Precious Takondwa Makondi", "Chia-Hwa Lee", "Chien-Yu Huang", "Chi-Ming Chu", "Yu-Jia Chang", "Po-Li Wei"], "journal": "PloS one", "year": 2018, "abstract": "Bevacizumab combined with cytotoxic chemotherapy is the backbone of metastatic colorectal cancer (mCRC) therapy; however, its treatment efficacy is hampered by therapeutic resistance. Therefore, understanding the mechanisms underlying bevacizumab resistance is crucial to increasing the therapeutic efficacy of bevacizumab. The Gene Expression Omnibus (GEO) database (dataset, GSE86525) was used to identify the key genes and pathways involved in bevacizumab-resistant mCRC. The GEO2R web tool was used to identify differentially expressed genes (DEGs). Functional and pathway enrichment analyses of the DEGs were performed using the Database for Annotation, Visualization, and Integrated Discovery(DAVID). Protein-protein interaction (PPI) networks were established using the Search Tool for the Retrieval of Interacting Genes/Proteins database(STRING) and visualized using Cytoscape software. A total of 124 DEGs were obtained, 57 of which upregulated and 67 were downregulated. PPI network analysis showed that seven upregulated genes and nine downregulated genes exhibited high PPI degrees. In the functional enrichment, the DEGs were mainly enriched in negative regulation of phosphate metabolic process and positive regulation of cell cycle process gene ontologies (GOs); the enriched pathways were the phosphoinositide 3-kinase-serine/threonine kinase signaling pathway, bladder cancer, and microRNAs in cancer. Cyclin-dependent kinase inhibitor 1A(CDKN1A), toll-like receptor 4 (TLR4), CD19 molecule (CD19), breast cancer 1, early onset (BRCA1), platelet-derived growth factor subunit A (PDGFA), and matrix metallopeptidase 1 (MMP1) were the DEGs involved in the pathways and the PPIs. The clinical validation of the DEGs in mCRC (TNM clinical stages 3 and 4) revealed that high PDGFA expression levels were associated with poor overall survival, whereas high BRCA1 and MMP1 expression levels were associated with favorable progress free survival(PFS). The identified genes and pathways can be potential targets and predictors of therapeutic resistance and prognosis in bevacizumab-treated patients with mCRC.", "claims": [{"id": "claim-method", "statement": "The expression data were further analyzed using GeneSpring GX software (version 11.0, Agilent Technologies), and the differentially expressed genes (DEGs) between the bevacizumab-resistant HT29 tumors vs untreated control were compared using the Fisher exact test, followed by multiple corrections using the Benjamini and Hochberg false discovery rate (FDR) method [22].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:29342159", "locator": "sections[3] \"Microarray data\" paragraph 2", "quote": "The expression data were further analyzed using GeneSpring GX software (version 11.0, Agilent Technologies), and the differentially expressed genes (DEGs) between the bevacizumab-resistant HT29 tumors vs untreated control were compared using the Fisher exact test, followed by multiple corrections using the Benjamini and Hochberg false discovery rate (FDR) method [22]."}], "state": "complete"}, {"id": "claim-data-access", "statement": "All relevant data are within the paper and its Supporting Information files.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:29342159", "locator": "sections[18] \"Data Availability\" paragraph 2", "quote": "All relevant data are within the paper and its Supporting Information files."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Using the GEO dataset GSE86525 and the GEO2R web tool, the study identified 124 DEGs associated with bevacizumab resistance, including 57 upregulated and 67 downregulated genes.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:29342159", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "The Gene Expression Omnibus (GEO) database (dataset, GSE86525) was used to identify the key genes and pathways involved in bevacizumab-resistant mCRC."}, {"asset": "source:pmid:29342159", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "The GEO2R web tool was used to identify differentially expressed genes (DEGs)."}, {"asset": "source:pmid:29342159", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "A total of 124 DEGs were obtained, 57 of which upregulated and 67 were downregulated."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Using the GEO dataset GSE86525 and the GEO2R web tool, the study identified 124 DEGs associated with bevacizumab resistance, including 57 upregulated and 67 downregulated genes.", "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:29342159"], "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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