INTERNATIONAL CONGRESS OF
CancerGenetics
Integrative Bioinformatics-Based Identification of TOP2A as a Candidate Therapeutic Target and In Silico Drug Discovery in Colorectal Cancer
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Asal Zargham Pour ,1 Fatemeh Ebrahimi Tarki,2,*
1. Islamic Azad University, Central Tehran Branch, Tehran, Iran
2. Islamic Azad University, Central Tehran Branch, Tehran, Iran
- Introduction: Colorectal cancer is one of the most common and deadly cancers. Therefore, identifying disease-related genes as a diagnostic biomarker, as well as examining and analyzing transcriptomic data and molecular networks to discover new therapeutic targets, are of great importance. The aim of this study is to identify candidate genes associated with colorectal cancer using bioinformatics WORKFLOW and evaluate the identified candidate gene as a candidate therapeutic target, followed by in silico drug discovery and identification of potential binding compounds to its protein.
- Methods: The study was conducted on the GSE44076 dataset, which included 98 samples of normal distant colon mucosa cells and 98 samples of primary colon adenocarcinoma cells, and the initial analysis was performed with GEO2R. Then, differentially expressed genes were selected using filtration and for further analysis, their protein interaction network was identified using STRING. In the next step, Candidate hub genes were prioritized using Cytoscape based on MCC, degree, and betweenness centrality. Using survival analyses and associations with tumor and tumor stage, the TOP2A gene was finally selected as a candidate. Then, its protein structure was examined for the drug discovery stage, and candidate compounds were identified from pharmaceutical and chemical databases, and their interaction with the TOP2A protein was evaluated using molecular docking. F.Ebrahimitarki@alzahra.ac.ir
- Results: The analysis revealed 2095 differentially expressed genes between tumor and healthy samples. A set of genes associated with key cancer processes and central network genes were also identified. Among the classified genes, TOP2A was identified as a candidate gene for further study due to its significantly increased expression in tumor tissue, its association with cell proliferation-related processes, and its central position in the protein interaction network. Expression and patient survival studies also supported the potential clinical relevance of TOP2A in colorectal cancer. In the drug discovery phase, known TOP2A-targeting compounds, including etoposide, doxorubicin, epirubicin, and mitoxantrone, were selected as candidate compounds and reference compounds for structural evaluation. This set provided a basis for structural screening and investigation of TOP2A ligand-protein interaction
- Conclusion: This study identified TOP2A as a potential therapeutic target in colorectal cancer through an integrative bioinformatics workflow combining differential gene expression analysis, protein–protein interaction network analysis, hub gene prioritization, and clinical relevance assessment. The significant upregulation of TOP2A in tumor tissues, its central role in the interaction network, and its association with tumor-related processes and patient survival support its potential importance in colorectal cancer progression. Furthermore, the selection of known TOP2A-targeting compounds, including etoposide, doxorubicin, epirubicin, and mitoxantrone, provided a foundation for investigating protein–ligand interactions through molecular docking. Overall, these findings highlight the potential of integrating transcriptomic and structural bioinformatics approaches to identify candidate therapeutic targets and evaluate compounds for colorectal cancer treatment. However, further experimental validation and comprehensive evaluation of compound binding affinity, selectivity, and safety are required to confirm the therapeutic potential of TOP2A and the identified compounds.
- Keywords: Colorectal cancer, Drug discovery, Bioinformatics, Molecular docking, TOP2A
