Abstract 231: Live cell painting of drug responses in high grade serous cancer organoids
Authors: Andrews David W. , Li Betty , Schormann Wiebke , Buzina Alla , Gien Lilian , MacKay Helen 
Published: March 2024

While most patients with high grade serous ovarian cancer (HGSC) respond to platinum-based chemotherapy, the response is rarely durable and recurrence almost inevitable. A characteristic of HGSC is defective DNA repair. A class of drugs called PARP inhibitors (PARPi) exploit this vulnerability and have proven useful in delaying recurrence. However, resistance is inevitable. In models of HGSC a protein that frequently confers resistance is called Bcl-xL, a member of the Bcl-2 family of proteins that prevent apoptosis. If treating the patients with a PARPi makes cancer cells dependent on Bcl-xL then adding an inhibitor of Bcl-xL to their treatment would be sufficient to cause the cancer cells to die. To test this, we have initiated companion studies for a clinical trial in which patients that have had a recurrence after receiving platinum-based therapy will first be treated with the PARPi Olaparib and then, an inhibitor of Bcl-xL, Navitoclax, will be added to their course of treatment. The idea is that for some women this will provide the one-two-punch needed to eliminate the cancer or at least dramatically prolong response. However, Bcl-xL is only one of the five known inhibitors of apoptosis. To identify which women will benefit most from adding Navitoclax to their treatment we need a biomarker(s). An ideal biomarker would also let us determine for other women which inhibitor of Bcl-2 proteins would be best combined with a PARPi.

Our hypothesis is that patient derived organoids can be used as a pragmatic way to identify for individual patients which Bcl-2 protein inhibitor will synergize with a PARPi to optimize treatment.

We are using organoids to develop biomarkers for High Grade Serous Cancer (HGSC) treatment response. Organoids generated from biopsy samples acquired prior to treatment for HGSC promise to be efficient and reliable experimental models that recapitulate in vitro patient tumors faithfully enough to facilitate translation to therapeutic decisions for patients. By adapting the relatively new technique of conditional reprogramming and combining it with novel methods for cell aggregation and hydrogel based synthetic ECM supports we can reproducibly generate HGSC patient-specific tumor organoids models in weeks with greater than 90% success. Organoids grown 384 well format are stained with novel non-toxic dyes enabling live cell painting of chemoresponses to drugs alone and in combination with drugs targeting anti-apoptotic proteins. Our data suggest that this approach captures the inherent heterogeneity of the disease, albeit local to the sampled site. We are now employing deep learning AI algorithms to enable automated analyses of 3D confocal image stacks of organoids to infer drug responses that will be compared to patient responses in ongoing clinical trials.

Citation Format: David W. Andrews, Betty Li, Wiebke Schormann, Alla Buzina, Lilian Gien, Helen MacKay. Live cell painting of drug responses in high grade serous cancer organoids [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 231.