Abstract 225: Integration of patient-derived tumor organoids and patient clinical multimodal data to investigate the role of organoids in predicting treatment response
Authors: Burke Kathleen A. , Larsen Brian , Tan Yi-Hung Carol , Barbeau Jessica , Brinkman Curtis , Moore Elle , Callamaras Nick , Dry Jonathan R. , Huerga Iker , Sasser Kate , Borgia Jeffrey A. 
Published: March 2024

Introduction: Patient-derived organoids (PDOs) enable the ex vivo study of tumor heterogeneity and its effect on response to treatment. Our previous work demonstrated that our robust pan-cancer organoid platform shows genetic and transcriptomic concordance with clinical tumor samples and can be deployed for high-throughput drug response screening. Here, we ran a standard of care (SOC) panel on PDOs with paired de-identified clinically curated data to enable a comparison of patient response to the same drugs ex vivo and exploration of potentially more effective treatment alternatives.

Methods: Patient tumor samples were cultivated into tumor PDOs in extracellular matrix + chemically defined media. PDOs underwent pathological review to ensure development of malignant tissue. PDOs were identified by clusters of Hoechst-positive cells and live and dead cell counts for each PDO were determined using fluorescent stains. The median number of cells per PDO in the well was calculated, excluding PDOs with &lt;3 cells and the top 1% of PDOs by area. Drug screens were run with 6 doses of the compound and the inverse area under the curve of ToPro3 live cell measurements was calculated to quantify response. Tempus xT DNA-seq and xR whole-transcriptome assays were used to perform NGS on organoids and patient samples where available. Data was processed through our standard pipeline to identify targetable mutations, neoantigens, copy number variants (CNVs) and fusions.

Results: We analyzed 38 PDOs with paired patient data across 9 different cancer types comprising mostly lung (n=14) and colorectal (n=12); 17 PDOs had responses associated with treatment given close to the biopsy collection date. Across the full PDO cohort, we observed a range of responses to SOC compounds, providing a platform to better understand biomarkers and mechanisms of response. Treatment response in PDOs correlated with patient response in many cases. In the 3 patients with progression-free survival &gt;1 year and outcomes of either complete response or stable disease, all showed strong responses to the corresponding drugs in the SOC panel. For most patients with progressive disease recorded after treatment the corresponding PDO cluster showed limited response to treatment. The SOC panel includes several targeted therapies that provide insight into how patients respond to treatment beyond chemotherapy. For two patients with limited response to treatment in both patient and PDO, we identified targeted therapies relevant to their clinico-genomic landscape. One patient showed improved clinical outcomes to a later line of therapy with a similar mechanism of action to the drug that showed response in the organoid.

Conclusion: These results suggest that PDOs may serve as a powerful tool for predicting patient response to treatment and aid the development of new therapies.

Citation Format: Kathleen A. Burke, Brian Larsen, Yi-Hung Carol Tan, Jessica Barbeau, Curtis Brinkman, Elle Moore, Nick Callamaras, Jonathan R. Dry, Iker Huerga, Kate Sasser, Jeffrey A. Borgia. Integration of patient-derived tumor organoids and patient clinical multimodal data to investigate the role of organoids in predicting treatment response [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 225.