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pmid:36950431
Role of the antineoplastic drug bleomycin based on toxicogenomic-DNA damage inducing (TGx-DDI) genomic biomarkers data: A meta-analysis.
Peter Natesan Pushparaj · Mahmood Rasool · Muhammad Imran Naseer · Kalamegam Gauthaman
Pakistan journal of medical sciences · 2023 doi:10.12669/pjms.39.2.7321
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Experiment
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Data
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Analysis
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Complete file
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Here, we examined bleomycin for cellular, molecular and toxicological mechanisms using next-generation knowledge discovery (NGKD) tools.\nMethods: This study was conducted at the Faculty of Applied Medical Sciences, King Abdulaziz University (KAU), Jeddah, Saudi Arabia in October 2022. We first analyzed the raw Toxicogenomic and DNA damage-inducing (TGx-DDI) gene expression data from Gene Expression Omnibus (GEO) (GSE196373) of TK6 cells treated with 10 µM bleomycin and TK6 cells treated with DMSO for four hours using the GEO2R tool based on the Linear Models for Microarray Analysis (limma) R packages to derive the differentially expressed genes (DEGs). Then, iPathwayGuide was used to determine differentially regulated signaling pathways, biological processes, cellular, molecular functions and upstream regulators (genes and miRNAs).\nResults: Bleomycin differently regulates the p53 pathway, transcriptional dysregulation in cancer, FOXO pathway, viral carcinogenesis, and cancer pathways. The biological processes such as p53 class mediator signaling, intrinsic apoptotic signaling, DNA damage response, and DNA damage-induced intrinsic apoptotic signaling and molecular functions like ubiquitin protein transferase and p53 binding were differentially regulated by bleomycin. iPathwayGuide analysis showed that the p53 and its regulatory gene and microRNA networks induced by bleomycin.\nConclusion: Analysis of TGx-DDI data of bleomycin using NGKD tools provided information about toxicogenomics and other mechanisms. Integration of all \"omics\" based approaches is crucial for the development of translatable biomarkers for evaluating anticancer drugs for safety and efficacy.", "claims": [{"id": "claim-method", "statement": "The DEGs were identified using the limma R package using a log2 fold change (Log2FC) cut-off of 2 and p value cut off of 0.05.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36950431", "locator": "sections[5] \"GEO2R Analysis of NanoString nCounter® Data:\" paragraph 2", "quote": "The DEGs were identified using the limma R package using a log2 fold change (Log2FC) cut-off of 2 and p value cut off of 0.05."}], "state": "complete"}, {"id": "claim-data-access", "statement": "This study was conducted using publicly available gene expression data from the Gene Expression Omnibus (GEO).8", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36950431", "locator": "sections[4] \"Ethical Statement:\" paragraph 2", "quote": "This study was conducted using publicly available gene expression data from the Gene Expression Omnibus (GEO).8"}], "state": "complete"}, {"id": "claim-target-result", "statement": "Bleomycin differently regulates the p53 pathway, transcriptional dysregulation in cancer, FOXO pathway, viral carcinogenesis, and cancer pathways.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36950431", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Bleomycin differently regulates the p53 pathway, transcriptional dysregulation in cancer, FOXO pathway, viral carcinogenesis, and cancer pathways."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Bleomycin differently regulates the p53 pathway, transcriptional dysregulation in cancer, FOXO pathway, viral carcinogenesis, and cancer pathways.", "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:36950431"], "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:GSE196369"], "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:GSE196369"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36950431", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.12669/pjms.39.2.7321", "sha256": 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