Abstract 1292: Innovative 3D ecm platforms for tumoroid development, drug screening, and personalized treatment
Abstract New advances in cancer research require robust in vitro and in vivo models that mimic the complexity of human tumors. Traditional 2D cell cultures lack the complexity of the tumor microenvironment (TME), leading to unreliable prediction of drug efficacy. Animal models are costly, time-intensive, and fail to fully replicate human tumor biology due to interspecies differences. To overcome these limitations, we present an innovative approach that involves TME-mimetic extracellular matrix (ECM)-based 3D platforms and co-culture systems for the development of tumoroids, circulating tumor cell (CTC) expansion, and PDX models. These 3D systems provide a physiologically relevant TME by mimicking the native cellular and extracellular interactions that drive tumor growth and progression. Tumoroids established through co-culturing a pool of primary cells dissociated from human solid tumors using a solid micro extracellular matrix (smECM) exhibited pathohistological properties, biomarker expression, and tissue architecture closely resembling the original tumors. Incorporating human foreskin fibroblasts (HFFs) in co-culture further enhanced tumor growth and stromal support, making these 3D models highly effective for drug screening and functional studies. Additionally, the use of smECM provided an innovative solution for expanding rare CTCs ex vivo. Unlike traditional methods, the 3D smECM platform supported the sustained viability and proliferation of CTCs, preserving their heterogeneity and allowing for rapid generation of CTC-seeded PDX models. These models demonstrated a high degree of clinical relevance by maintaining genomic profiles and chemoresistance characteristics of the original patient tumors. By integrating these advanced 3D platforms, we offer a powerful tool to develop versatile models for cancer research. Citation Format: Navneet Kaur, Dazhi Yang, Jamel Ali. Innovative 3D ecm platforms for tumoroid development, drug screening, and personalized 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 1292.
Authors
- Dazhi Yang (ORCID: https://orcid.org/0000-0003-0316-8346)
- Jamel Ali
- Navneet Kaur
Institutions
- Florida State University (US)
Publication Details
- Journal
- Cancer Research
- Published
- 2025-04-21
- DOI
- https://doi.org/10.1158/1538-7445.am2025-1292
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00