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Updated: Jul 21, 2025

Evaluating the Effectiveness of Cancer Drug Sensitization In Vitro and In Vivo
Published on: February 6, 2015
Exploration of potential molecular mechanisms and genotoxicity of anti-cancer drugs using next generation knowledge
Peter Natesan Pushparaj1, Mahmood Rasool2, Muhammad Imran Naseer3
1Peter Natesan Pushparaj, PhD Associate Professor Center of Excellence in Genomic Medicine Research, Department of Medical Laboratory Technology, Faculty of Applied Medical Sciences King Abdulaziz University, Jeddah, Saudi Arabia.
Background & Objectives:
Accurate identification of molecular and toxicological functions of potential drug candidates is crucial for drug discovery and development. This may aid in the evaluation of the risks of genotoxicity and carcinogenesis. In addition, in silico characterization of existing and new drugs might offer clues for future investigations and aid in the development of anticancer treatments. Using next-generation knowledge discovery (NGKD) methodology, we endeavored to establish a risk assessment of anticancer drugs for their molecular mechanism(s) and genotoxicity.
Methods:
This study was performed at the Faculty of Applied Medical Sciences, King Abdulaziz University (KAU), Jeddah, Saudi Arabia, in November 2022. Using innovative in silico model systems, we assessed the molecular mechanism of action and toxicity of around 20 distinct substances such as Deguelin, Etoposide, Camptothecin, Cytarabine (Ara-C), Cisplatin, Hydroxyurea, Trichostain A, Antimycin, Colchicine, 2-deoxyglucose, Tunicamycin, Thapsigargin, Vinblastin, Docetaxel, Oxaliplatin, Methotrexate, 5-flurouracil, Bleomycin, Taxol (Paclitaxel), and Apicidin. Using the Ingenuity Pathway Analysis (IPA) knowledge base, the number of targets for each compound was determined in silico. Subsequently, they were examined using Fisher's exact test and Benjamini Hochberg Multiple Testing Correction (P<0.05) and submitted to core analysis with IPA to decode the biological and toxicological activities differently controlled by these drugs. In addition, a multiple comparison module in IPA was used to compare the core analyses of each molecule. In addition, we obtained the top 100 protein targets of Etoposide, Camptothecin, and Ara-C using SwissTargetPrediction, as well as the key pathways and gene ontologies affected by these drugs and disease associations using the WebGestalt tool.
Results:
We identified distinct toxicological signatures and canonical signaling pathways in tumor cell lines regulated by these 20 anticancer drugs. These signaling pathways included cell death and apoptosis in addition to molecular processes, p53 signaling, and aryl hydrocarbon receptor signaling. The TP53 signaling pathway is utilized by these agents to effectively trigger cell death and apoptosis, and p53 functions as a master regulator in a variety of cellular stress responses, including genotoxic stress.
Conclusion:
Our research has laid the groundwork for the discovery of additional biomarkers that assess both the safety and effectiveness of treatment. Our mechanism based "NGKD" tools have more relevance for the identification of safer therapies and has the potential to lead to the rational screening of drug candidates targeting specific molecular networks and canonical pathways implicated in cancer and genotoxicity. In addition, the combination of protein, microRNA and metabolome profiles may be essential for the development of translatable biomarkers for the safety and efficacy of pharmacotherapeutic agents.Our research has laid the groundwork for the discovery of additional biomarkers that assess both the safety and the effectiveness of a treatment.
Insights
This study used in silico methods to assess anticancer drug toxicity and molecular mechanisms, identifying pathways like TP53 signaling involved in cell death and genotoxicity for safer drug development.
Area of Science:
- Computational toxicology
- Pharmacology
- Bioinformatics
Background:
- Accurate identification of molecular and toxicological functions is crucial for drug discovery and development.
- In silico characterization of drugs aids in evaluating genotoxicity and carcinogenesis risks.
- Understanding drug mechanisms can inform anticancer treatment development.
Purpose of the Study:
- To establish a risk assessment of anticancer drugs for their molecular mechanisms and genotoxicity using next-generation knowledge discovery (NGKD).
- To identify distinct toxicological signatures and signaling pathways regulated by anticancer drugs.
- To explore potential biomarkers for assessing treatment safety and efficacy.
Main Methods:
- Utilized in silico model systems to assess molecular mechanisms and toxicity of 20 anticancer drugs.
- Employed Ingenuity Pathway Analysis (IPA) to determine drug targets and analyze biological/toxicological activities.
- Used SwissTargetPrediction and WebGestalt for target identification, pathway analysis, and gene ontology mapping.
Main Results:
- Identified distinct toxicological signatures and canonical signaling pathways, including cell death, apoptosis, p53 signaling, and aryl hydrocarbon receptor signaling.
- Confirmed that the TP53 signaling pathway is utilized by anticancer agents to induce cell death and apoptosis.
- p53 was identified as a master regulator in cellular stress responses, including genotoxic stress.
Conclusions:
- The study provides a foundation for discovering biomarkers to assess treatment safety and effectiveness.
- NGKD tools are relevant for identifying safer therapies and rationally screening drug candidates.
- Combining molecular profiles may be essential for developing translatable biomarkers for drug safety and efficacy.
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