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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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Execution

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:36950431
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2026-11-01T19:01:35Z
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2026-11-01T22:51:33Z
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title
Role of the antineoplastic drug bleomycin based on toxicogenomic-DNA damage inducing (TGx-DDI) genomic biomarkers data: A meta-analysis.
doi
10.12669/pjms.39.2.7321
pmid
36950431
authors array · 4 items
[0]
Peter Natesan Pushparaj
[1]
Mahmood Rasool
[2]
Muhammad Imran Naseer
[3]
Kalamegam Gauthaman
journal
Pakistan journal of medical sciences
year
2023
abstract
Objectives: Accurately identifying the cellular, biomolecular, and toxicological functions of anticancer drugs help to decipher the potential risk of genotoxicity and other side effects. Here, we examined bleomycin for cellular, molecular and toxicological mechanisms using next-generation knowledge discovery (NGKD) tools. Methods: 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). Results: 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. Conclusion: 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.
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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.
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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.
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This study was conducted using publicly available gene expression data from the Gene Expression Omnibus (GEO).8
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Bleomycin differently regulates the p53 pathway, transcriptional dysregulation in cancer, FOXO pathway, viral carcinogenesis, and cancer pathways.
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Bleomycin differently regulates the p53 pathway, transcriptional dysregulation in cancer, FOXO pathway, viral carcinogenesis, and cancer pathways.
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Bleomycin differently regulates the p53 pathway, transcriptional dysregulation in cancer, FOXO pathway, viral carcinogenesis, and cancer pathways.
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Toxicity Testing in the 21st Century: An Integrated Approach to Genetic Safety Testing using the TGx-DDI Genomic Biomarker and High-Throughput CometChip® [NanoString]
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Toxicity Testing in the 21st Century: An Integrated Approach to Genetic Safety Testing using the TGx-DDI Genomic Biomarker and High-Throughput CometChip®
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activity-read-36950431
type
extraction
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[0]
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agent
agent:minimax-reader
[2] object · 4 fields
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activity-resolve-GSE196369
type
accession_resolution
used array · 1 item
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data:geo:GSE196369
agent
agent:corpus-assay-engine
agents array · 2 items
[0] object · 3 fields
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agent:corpus-assay-engine
type
software
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[1] object · 3 fields
id
agent:minimax-reader
type
software
label
MiniMax literature reader
source_run_id
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dsl_catalogue_fingerprint
343fb30756ba6ec3
capability_table_fingerprint
2cb3e42f047d2ecf
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ba34b49490d9bfaf
lineage object · 4 fields
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pmid:36950431
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sha256:52817a1a297a63ebcb73243722f14a1be1517cb4dd2748b6fca14842b97f8329
fork_of
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gaps array · 8 items
[0]
asset:data:geo:GSE196369 licence not read
[1]
asset:data:geo:GSE196369 not downloaded
[2]
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[3]
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[4]
execution.not_run
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review.human_critique
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review.independent_reader
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review.machine_critique
assays array · 2 items
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definition_version
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required_operations array · 0 items
support_state
partial
source_hashes object · 1 field
assay_lexicon
99e1195c7d6f
confidence
0.99
evidence array · 2 items
[0]
he GEO2R tool based on the Linear Models for Microarray Analysis (limma) R packages to derive the di
[1]
based on the GEOquery and Linear Models for Microarray Analysis (limma) R packages obtained from th
order_basis
paper_text_order:848
id
assay:1
[1] object · 11 fields
role
analysis
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differential_expression
definition_version
f2132e96ae6c7a4e
required_operations array · 3 items
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normalise_counts
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source_hashes object · 1 field
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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.
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36950431", "kind": "science-record", "revision": 4, "content_hash": "sha256:7fe89ae352892cf07008c965f72a4b3586b519903dc93886ed4b4934dc005f2b", "created_at": "2026-11-01T19:01:35Z", "updated_at": "2026-11-01T22:51:33Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Role of the antineoplastic drug bleomycin based on toxicogenomic-DNA damage inducing (TGx-DDI) genomic biomarkers data: A meta-analysis.", "doi": "10.12669/pjms.39.2.7321", "pmid": "36950431", "authors": ["Peter Natesan Pushparaj", "Mahmood Rasool", "Muhammad Imran Naseer", "Kalamegam Gauthaman"], "journal": "Pakistan journal of medical sciences", "year": 2023, "abstract": "Objectives: Accurately identifying the cellular, biomolecular, and toxicological functions of anticancer drugs help to decipher the potential risk of genotoxicity and other side effects. 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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