Abstract 521: Drug repurposing via ultra-high throughput 3D spheroids screening in rare cancer treatment
Spinal cord gliomas (SCG) are rare cancers, and relevant pharmaceutical research and treatments are limited. While drug repurposing of FDA-approved compounds has shown promise for orphan diseases, its potential for SCG remains uncertain. Our research team has recently developed an SCG model in minipigs, offering anatomical, immunological, developmental, and genetic similarities to humans, which makes it an ideal model for translational precision medicine. In this study, we used a novel drug repurposing strategy using 3D spheroids from our recently established large animal SCG model as a case study. First, we established a miniaturized 3D cell culture platform for ultra-high-throughput screening (uHTS). After screening the FDA-approved and Bioactive compound library with minipig SCG 3D spheroids, Clofoctol, showed potential as a glioma treatment by targeting genes in the p53 pathway. Evaluation in a xenograft model demonstrated Clofoctol's ability to suppress tumor growth over a 10-day treatment period, followed by immunohistochemistry and RNA-seq. These findings suggested Clofoctol is a promising therapeutic for glioma treatment. Thus, our study shows the feasibility of 3D spheroids uHTS to expedite orphan disease research, providing a strategy for future drug repurposing for rare cancer patients. Citation Format: Marybeth G. Yonk, Muhibullah S. Tora, Megan A. Lim, Thais Federici, Haian Fu, Yuhong Du, Bing Yao, Nicholas Boulis, Kecheng Lei. Drug repurposing via ultra-high throughput 3D spheroids screening in rare cancer treatment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 521.
Authors
- Thais Federici
- Kecheng Lei (ORCID: https://orcid.org/0000-0002-2607-8960)
- Bing Yao (ORCID: https://orcid.org/0000-0002-6657-2760)
- Nicholas M. Boulis (ORCID: https://orcid.org/0000-0002-7271-3953)
- Muhibullah S. Tora (ORCID: https://orcid.org/0000-0002-3300-6367)
- Haian Fu (ORCID: https://orcid.org/0000-0002-2362-7979)
- Marybeth Yonk
- Yuhong Du
- Megan Amber Lim
Institutions
- Emory University (US)
Publication Details
- Journal
- Cancer Research
- Published
- 2025-04-21
- DOI
- https://doi.org/10.1158/1538-7445.am2025-521
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00