Investigator

Alexander T. H. Wu

Taipei Medical University

ATHAlexander T. H. Wu
Papers(2)
In-Silico Evaluation …Computer-aided drug d…
Collaborators(10)
Hsu-Shan HuangHarshita Nivrutti Khe…Lung-Ching ChenMaryam Rachmawati Sum…Ntlotlang MokgautsiSheng-Liang HuangSung-Ling TangVijesh Kumar YadavBashir LawalYu-Cheng Kuo
Institutions(4)
Taipei Medical Univer…Shin Kong WHS Memoria…Unknown InstitutionNational Defense Medi…

Papers

In-Silico Evaluation of Genetic Alterations in Ovarian Carcinoma and Therapeutic Efficacy of NSC777201, as a Novel Multi-Target Agent for TTK, NEK2, and CDK1

Ovarian cancer is often detected at the advanced stages at the time of initial diagnosis. Early-stage diagnosis is difficult due to its asymptomatic nature, where less than 30% of 5-year survival has been noticed. The underlying molecular events associated with the disease’s pathogenesis have yet to be fully elucidated. Thus, the identification of prognostic biomarkers as well as developing novel therapeutic agents for targeting these markers become relevant. Herein, we identified 264 differentially expressed genes (DEGs) common in four ovarian cancer datasets (GSE14407, GSE18520, GSE26712, GSE54388), respectively. We constructed a protein-protein interaction (PPI) interaction network with the overexpressed genes (72 genes) and performed gene enrichment analysis. In the PPI networks, three proteins; TTK Protein Kinase (TTK), NIMA Related Kinase 2 (NEK2), and cyclin-dependent kinase (CDK1) with higher node degrees were further evaluated as therapeutic targets for our novel multi-target small molecule NSC777201. We found that the upregulated DEGs were enriched in KEGG and gene ontologies associated with ovarian cancer progression, female gamete association, otic vesicle development, regulation of chromosome segregation, and therapeutic failure. In addition to the PPI network, ingenuity pathway analysis also implicate TTK, NEK2, and CDK1 in the elevated salvage pyrimidine and pyridoxal pathways in ovarian cancer. The TTK, NEK2, and CDK1 are over-expressed, demonstrating a high frequency of genetic alterations, and are associated with poor prognosis of ovarian cancer cohorts. Interestingly, NSC777201 demonstrated anti-proliferative and cytotoxic activities (GI50 = 1.6 µM~1.82 µM and TGI50 = 3.5 µM~3.63 µM) against the NCI panels of ovarian cancer cell lines and exhibited a robust interaction with stronger affinities for TTK, NEK2, and CDK1, than do the standard drug, paclitaxel. NSC777201 displayed desirable properties of a drug-like candidate and thus could be considered as a novel small molecule for treating ovarian carcinoma.

Computer-aided drug discovery of a dual-target inhibitor for ovarian cancer: therapeutic intervention targeting CDK1/TTK signaling pathway and structural insights in the NCI-60

Ovarian cancer remains the third most prevalent and deadliest gynecologic malignancy worldwide, with most patients eventually developing resistance to platinum-based chemotherapy. This highlights a critical unmet need for innovative multitargeted therapies to address current treatment challenges. In this study, we identified 35 differentially expressed genes (DEGs) through integrated analysis of four GEO ovarian cancer datasets, with validation using TCGA data. Gene Ontology (GO) and KEGG enrichment analyses highlighted key tumor-associated pathways, and protein-protein interaction (PPI) network modeling prioritized CDK1 and TTK as high-value therapeutic targets. We evaluated the association between molecular genomic features and drug responses across the NCI-60 ovarian cancer cell line panel (IGROV1, OVCAR-3, OVCAR-4, OVCAR-5, OVCAR-8, NCI/ADR-RES, and SK-OV-3), using a series of salicylanilide-derived compounds and four FDA-approved drugs (cabozantinib, paclitaxel, rapamycin, and niclosamide) from the NCI Developmental Therapeutics Program (DTP). Among these, NSC765690 (MCC22) emerged as the most promising candidate. It demonstrated potent antiproliferative activity, high target selectivity, and strong binding affinity to both CDK1 and TTK. Multi-omics integration, combined with AI-driven network modeling, further elucidated NSC765690's mechanism of action and its relevance to ovarian cancer pathogenesis. Additionally, ADMET and pharmacokinetic profiling confirmed its favorable drug-like properties and low predicted toxicity. Collectively, these findings establish NSC765690 as a potent dual-target inhibitor and exemplify a rational, data-driven drug discovery pipeline for overcoming chemotherapy resistance in ovarian cancer.

2Papers
10Collaborators
Country

TW

Keywords
Cancer BiologyImmunotherapyCaner stem and stem cell biologyTumor microenvironmentDrug resistanceCellular metabolism and Aging
Links & IDs
0000-0002-0178-6530

Scopus: 24777511600