Abstract PO5-14-06: Transcriptomics-based drug screening in 3D ex vivo patient-drived breast cancer model and patient biopsy for personalized therapy

Abstract

Abstract Breast cancer is a leading cause of cancer-related mortality for women worldwide. Hormone receptor-positive (HR+) breast tumors, which represent 70% of all breast cancer cases, are treated with endocrine therapy. However, not all patients benefit from this treatment regimen because of patient-to-patient variation. Therefore, high throughput drug screening system is warranted to enable personalized medicine. Patient-derived organoids, which serve as a screening platform, lose their hormone receptors and response upon ex vivo culturing, and may not be adequate models for HR+ breast tumors. Moreover, unidentified biological components in the widely-used basement membrane matrix, Matrigel, result in high batch-to-batch variations and poor reproducibility in organoid cultures. Here, we propose a hydrogel-based 3D ex vivo model with defined structural and chemical properties to test hormone and drug sensitivity of HR+ breast tumors from patient-derived xenografts (PDXs) and patient tumor biopsies using microfluidics. Our data demonstrate the feasibility of this model to preserve cell proliferation and hormone receptor expression over 7 days. We also demonstrate that responses to hormones and FDA-approved drugs are faithfully maintained in this model. Finally, to establish a high throughput hormone and drug testing workflow with transcriptomic readout, we multiplexed barcoded- and drug-treated tumor samples in a single experiment with bulk RNA-sequencing. Our preliminary data demonstrate patient-specific responses to hormones and drugs that correspond to patient genetic mutation profiles, treatment history, disease stages and subtypes. This platform also enables testing of drugs in clinical trials that shows promising therapeutic outcomes for breast cancer, such as CDK4/6i, AKTi, PARPi, mTORi and their combination with endocrine therapy, thanks to the high throughput of the screening system and the low consumption of patient-derived or patient tissue. Given the capability of combining this physiologically-relevant 3D ex vivo model with RNA-seq for HR+ breast tumors, this platform holds potential for high throughput compound testing and transcriptomic profiling of patient biopsies for personalized medicine. Citation Format: Yueyun Zhang, Carlos Henrique Venturi Ronchi, Giovanna Ambrosini, Yuanlong Liu, Patrick Aouad, Daria Matvienko, Christoph Merten, Cathrin Brisken. Transcriptomics-based drug screening in 3D ex vivo patient-drived breast cancer model and patient biopsy for personalized therapy [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-14-06.