Highlights from the American Association for Cancer Research (AACR) 2025 Meeting
Introduction
Organoids have emerged as transformative three-dimensional (3D) culture systems that faithfully mimic the architecture, functionality, and genetic diversity of native tissues. In the past decade, their use in oncology has grown significantly, helping to bridge key gaps between traditional two-dimensional (2D) cell cultures, animal models, and patient-derived xenografts (PDXs). Presentations at the American Association for Cancer Research (AACR) 2025 meeting underscore how organoid technology has advanced from a specialized tool to a widely adopted preclinical platform accelerating innovation in drug discovery and development.
Diverse Types of Organoids and Their Applications
A prominent trend across the abstracts is the remarkable diversity of organoid systems now being employed. Patient-derived organoids (PDOs) remain the core, representing various solid tumors including pancreatic ductal adenocarcinoma, colorectal cancer, gastric cancer, lung cancer, ovarian clear cell carcinoma, bladder cancer, and rare subtypes such as neuroendocrine prostate cancer and hormone receptor-positive breast cancer. Researchers have extended this platform to PDX-derived organoids, which are are three-dimensional (3D) cell culture models grown from patient-derived xenografts (PDXs),canine and feline organoids, engineered organoids with gene knockouts or reporter constructs, and even two-dimensional organoids (2DOs) to study tumor-stroma co-culture (Table 1).
This diversity demonstrates the adaptability of organoids to model inter- and intra-tumoral heterogeneity, metastatic behavior, and treatment resistance mechanisms that are difficult to capture in conventional models. For example, several abstracts detailed the establishment of drug-resistant organoid lines, such as enfortumab vedotin-resistant urothelial organoids, illustrating their value in modeling acquired resistance and guiding next-line therapy development.
Moreover, veterinary oncology models, notably cat breast cancer organoids and canine bladder cancer organoids, underscore the expanding recognition of spontaneous animal cancers as valuable comparative models for human disease.
Table 1: Organoid types and their applications in cancer research and drug discovery.
| Organoid Type | Method of Production | Use/Application |
| Two-Dimensional Organoid (2DO) | Cancer cells derived from patient tumors, cultured as specialized 2D monolayers that preserve key tumor features and enable co-culture with stromal or immune cells. | Study of tumor-stroma interactions, circulating tumor cell (CTC) models, treatment-resistant subpopulations. |
| Bladder organoid | Derived from bladder epithelial cells or tumor tissues, often from human or canine samples. | Model bladder cancer progression, drug screening, resistance mechanisms. |
| Breast cancer organoid | Isolated from breast cancer tissue, embedded in Matrigel or hydrogels for 3D culture. | Study hormone receptor-positive or triple-negative breast cancer, drug sensitivity, resistance. |
| Colon organoid | Generated from normal or tumor colon tissue; may include engineered gene knockouts. | Understand colorectal cancer development, early tumorigenesis, drug screening. |
| Engineered organoid | Genetically modified using lentiviral transduction or CRISPR, often expressing markers or mutations. | Mechanistic studies, pathway targeting, co-culture visualization, in vivo tracking. |
| General organoid | Any organoid derived from patient tumor cells or tissues, grown in 3D culture conditions. | Broad drug screening, model tumor heterogeneity, preclinical testing. |
| Intestinal organoid | Isolated from intestinal epithelial cells, often with genetic modifications for cancer studies. | Study stem cell behavior, early tumorigenesis, Wnt pathway studies. |
| Lung organoid | Developed from lung cancer biopsies or patient-derived xenograft (PDX), tumors cultured in Matrigel or hydrogel droplets. | Model NSCLC, test combinatorial therapies, metabolic pathway vulnerability. |
| Normal organoid | Derived from healthy tissue, used as control or baseline for comparative studies. | Compare normal vs. tumorigenic pathways, biomarker discovery. |
| PDO (Patient-Derived Organoid) | Patient-derived tumor tissue embedded in 3D ECM matrices like Matrigel. | Personalized drug screening, predictive response modeling. |
| Patient-derived xenografts (PDX)-derived organoid | Tumor cells harvested from patient-derived xenograft grown in mice, then cultured as organoids. | Combine in vivo and in vitro models, drug resistance studies. |
| Prostate organoid | Established from prostate cancer biopsies or resistant tumor subtypes, grown in 3D matrices. | Target NEPC (Neuroendocrine Prostate Cancer), CRPC (Castration-Resistant Prostate Cancer); study androgen resistance. |
| Tumor organoid | General tumor-derived organoids from diverse cancers grown in 3D culture. | Model tumor behavior, screen therapies, study microenvironment. |
| Xenograft-derived organoid | Harvested from xenografted tumors and transitioned into 3D culture. | Study drug response, validate xenograft findings in vitro. |
Innovative Methods and Technological Integration of Organoids
Researchers demonstrated remarkable ingenuity in adapting and expanding organoid technologies for cancer drug discovery through high-content imaging, multi-omics profiling, and cutting-edge bioengineering approaches.
Hydrogel-based platforms: Multiple groups highlighted the use of hydrogel-based platforms, such as customized hydrogels designed to replicate patient-specific extracellular matrices, which improve organoid viability and mimic in vivo tumor environments more accurately, a notable example being work by investigators from North Dakota State University, who engineered esophageal adenocarcinoma models using hydrogel encapsulation strategies. Similarly, hydrogel-based microwell chips, as reported by teams at National Cheng Kung University, Taiwan, offer standardized high-throughput organoid formation and drug screening with consistent size and morphology.
Microfluidic 3D culture: Microfluidic devices emerged as another significant innovation, allowing precise control of nutrient and drug delivery while facilitating dynamic co-culture conditions; research teams from institutions like the Dana-Farber Cancer Institute described using microfluidic 3D culture systems to recreate tumor–stroma and immune interactions, enhancing the predictive value of drug response assays.
Co-culture with immune cells: The integration of co-culture platforms, particularly those involving patient-derived peripheral blood mononuclear cells (PBMCs) or tumor-infiltrating lymphocytes (TILs), is a growing theme, enabling functional evaluation of immunotherapies within autologous microenvironments, with groups such as Shanghai Medicilon Inc. advancing these approaches for testing checkpoint blockade combinations.
Digital pathology and deep learning: Several abstracts showcased the application of digital pathology and deep learning for organoid analysis, including the use of AI-assisted image classification and single-cell segmentation to quantify treatment responses and histologic changes; for example, a team from the University of Chicago Medicine applied deep learning models to automate tumor region identification and phenotype scoring in patient-derived colorectal organoids.
Single-cell and multi-omics profiling: Single-cell and multi-omics profiling were frequently integrated to uncover treatment-induced clonal evolution and epigenetic reprogramming, with research from UC Davis Comprehensive Cancer Center and collaborative consortia employing RNA-seq, ATAC-seq, and other multi-layered assays to unravel therapeutic vulnerabilities.
High-throughput assay platforms: High-throughput assay integration, enabled by robotics and chip-based bioreactors, is another clear trend, supporting systematic drug combination testing and large-scale synergy screens, as highlighted by groups working on KRAS-mutant pancreatic ductal adenocarcinoma and neuroendocrine prostate cancer models.
Collectively, these innovative methods signal a transformative shift toward more physiologically relevant, scalable, and data-rich organoid platforms that close the gap between in vitro assays and patient outcomes. By coupling bioengineering advances with computational tools and high-throughput capabilities, these research groups — spanning academic medical centers, contract research organizations, and biotech startups worldwide — are laying the groundwork for next-generation precision oncology pipelines driven by organoid science.
Organoids in Assay Development and Therapeutic Drug Screening
Across these abstracts, researchers have employed an array of advanced assays to optimize drug screening in organoid systems, underscoring how robust analytical platforms enhance the predictive power of preclinical models. One of the most widely adopted methods is the CellTiter-Glo® viability assay, which quantifies ATP to measure cell proliferation and cytotoxicity in 3D organoid cultures; this assay was used by groups at institutions like Shanghai Medicilon Inc. to evaluate single agents and drug combinations for bladder cancer and PDX-derived models. Similarly, the LDH release assay is used to detect cytotoxicity by measuring lactate dehydrogenase enzyme leakage from damaged cells, supporting validation of drug-induced cell death in multiple tumor organoid systems.
Live-cell imaging, enabled by platforms such as Incucyte, has emerged as another cornerstone, allowing researchers at centers like the University of Chicago Medicine and Dana-Farber Cancer Institute to dynamically monitor organoid growth, apoptosis, and morphological changes in response to treatment over time. These live-readout systems often combine fluorescent viability staining, confocal microscopy, and automated high-content image analysis to provide multiparametric data on drug efficacy. Flow cytometry and immunocytochemistry were frequently integrated to profile surface markers and intracellular signaling pathways before and after drug exposure, improving mechanistic understanding and identifying resistant subpopulations.
Several groups coupled histological approaches, such as Hematoxylin and Eosin (H&E) staining and immunohistochemistry (IHC), with digital pathology to confirm treatment-induced tissue remodeling within organoid xenografts or hydrogel-embedded cultures. Furthermore, multi-omics strategies, including whole exome sequencing (WES), RNA-seq, ATAC-seq, and single-cell transcriptomics , were used extensively for drug response biomarker discovery, especially by research teams from the UC Davis Comprehensive Cancer Center and various translational consortia. Some abstracts also described drug synergy scoring pipelines, which combine viability and omics data to map combination effects in complex tumor models, such as KRAS-mutant pancreatic ductal adenocarcinoma and resistant prostate cancer.
Together, these assays form an integrated pipeline that spans high-throughput compound screening, real-time efficacy monitoring, single-cell resolution profiling, and histological validation, solidifying the role of organoid systems as sophisticated testbeds for next-generation cancer therapeutics across leading academic medical centers and industry collaborators worldwide.
Organoids in Developing Potency, Pharmacodynamic (PD), and Pharmacokinetic (PK) Assays for Cancer Drugs
Several abstracts describe how organoid models are increasingly leveraged to support the development of potency assays, pharmacodynamic (PD) assays, and pharmacokinetic (PK) evaluations that more faithfully predict clinical outcomes. For instance, teams at institutions such as the Dana-Farber Cancer Institute report using colorectal and pancreatic cancer organoids to validate PD endpoints, linking molecular pathway inhibition to functional readouts like cell viability and apoptosis. This allows more precise measurement of drug mechanism of action in a 3D tumor microenvironment that better mimics patient tumors than traditional 2D cell lines.
In parallel, several research groups at translational cancer centers and biotech industry labs highlight how organoid platforms are integrated with pharmacokinetic analyses to assess the bioavailability, tissue penetration, and metabolic stability of novel compounds. By embedding organoids in microfluidic systems or hydrogel-based matrices, these studies simulate real-tissue barriers and diffusion properties, producing PK data that complement in vivo animal studies.
Moreover, potency assays within organoid systems are increasingly being deployed as robust screening tools to rank drug candidates before they advance to preclinical or early clinical phases. This is particularly evident in abstracts that combine high-throughput viability assays, LDH release tests, and single-cell omics to verify whether a compound’s potency aligns with its molecular target engagement, ensuring only the most promising leads move forward. Such workflows, as developed by multidisciplinary teams at centers including Dana-Farber and UC Davis Comprehensive Cancer Center, underscore how organoids are filling a critical gap between in vitro and in vivo testing by providing a more human-relevant platform for PK/PD and potency characterization.
Cancer Organoids (Tumoroids): Trends and Future Directions
Cancer Organoids (Tumoroids) are three-dimensional (3D) miniaturized tumor models created from patient-derived cancer cells that self-organize in culture to closely replicate the architecture, cellular diversity, and genetic characteristics of the original tumor. Looking forward, several emerging trends are set to shape the future of organoid-based cancer research. The expansion of living biobanks that link organoids with matched genomic and clinical data will advance personalized therapy by enabling individualized treatment design and real-time drug sensitivity testing. High-throughput automation, driven by the integration of microfluidics and robotics, will help overcome scalability challenges and facilitate large-scale drug screening and functional genomics studies. More sophisticated co-culture systems that include vasculature, stromal components, and immune cells will better recreate the tumor microenvironment, strengthening the relevance of organoids for immunotherapy and tumor–host interaction research. At the same time, artificial intelligence and digital pathology will boost the speed and accuracy of organoid classification, phenotyping, and biomarker discovery through automated, deep-learning-powered analysis for high-content screening. Finally, comparative oncology approaches that employ cross-species organoid models, such as those derived from canine and feline cancers, will continue to expand, offering fresh insights into tumor evolution and opening new pathways for therapeutic innovation.
Conclusion
Organoids have progressed from proof-of-concept tools to essential platforms in preclinical oncology. By accurately modeling tumor heterogeneity, genetic complexity, and treatment responses, organoid systems are helping to close the translational gap that has long limited the predictive power of conventional in vitro and in vivo models. The continued integration of organoids with bioengineering, multi-omics approaches, and computational technologies is poised to further enhance their role in drug discovery and development. As challenges related to standardization, scalability, and regulatory acceptance are addressed, organoid technologies are expected to play an increasingly important role not only in preclinical research but also in clinical decision-making and personalized cancer treatment.
Reference
Related blog
Organoids in the Development of Pharmacokinetics, Pharmacodynamics, and Potency Assays.
Disclaimer: This blog post is intended solely for educational and scientific informational purposes. Any mention of therapeutic drug names, including FDA-approved medications, is for the purpose of accurate reporting and discussion of biomedical research and does not constitute medical advice, endorsement, or promotion. Readers should not interpret the content as a recommendation for any specific treatment. Always consult a qualified healthcare professional for medical advice or treatment decisions.
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