Pilot study of a micro-organosphere drug screen platform to lead care in advanced breast cancer (MODEL-ABC).

Authors

null

David Graham

Xilis, Durham, NC

David Graham , Gabrielle Rupprecht , Wylie Watlington , Jaycee Cushman , Angelica Montalvo , Samantha Womack , Caroline Morales , Samantha M. Thomas , Steven Metzger , Xiling Shen , Jeremy Meyer Force

Organizations

Xilis, Durham, NC, Duke University Medical Center, Durham, NC, Duke University, Durham, NC, Department of Biostatistics and Bioinformatics, Duke Cancer Institute, Duke University Medical Center, Durham, NC, Xilis, Inc., Durham, NC, Department of Medicine, Duke Cancer Institute, Duke Consortium for IBC, Duke University Medical Center, Durham, NC

Research Funding

Pharmaceutical/Biotech Company
Xilis

Background: ASCO guidelines suggest using single agent chemotherapy for patients with advanced breast cancer (ABC). Single agent chemotherapy provides modest response rates in ABC, causing patients to be exposed to unnecessary toxicity without benefit. Thus, there is an unmet clinical need to develop a clinically applicable assay to guide treatment. We recently reported the use of MicroOrganoSpheres (MOS), which are gel droplets that encapsulate tumor cells creating miniature avatars of a patient’s tumor and are amenable to high throughput dispensing and drug studies. In our current study, we evaluated the feasibility of generating and dosing MOS from ABC samples as a novel drug screen platform that led to the development and enrollment of a precision oncology trial, known as MODEL-ABC. Methods: We first performed a proof-of-concept study on 21 samples from patients with ABC and generated MOS. Drug screens were then performed on these MOS across 7 standard of care (SOC) chemotherapies commonly prescribed for ABC. These data resulted in a platform for the MODEL-ABC study that enrolled patients with ABC of any ER, PR, or HER2 subtype who were eligible for single agent chemotherapy to determine the feasibility of using MOS to predict response to therapy. In this study, biopsies from lesions ≥ 2 cm were obtained as part of SOC to generate MOS and perform drug screens. The patient subsequently received single agent chemotherapy per physicians’ choice with either carboplatin, capecitabine, paclitaxel, eribulin, liposomal doxorubicin, gemcitabine, or vinorelbine. MOSwere treated using the same chemotherapy as the patient along with 1-3 alternative single agent chemotherapies. Results: We generated MOS from 19/21 samples (90% success rate) across several breast cancer subtypes. Dose response curves of MOSwere successfully generated across the 7 chemotherapies with a mean turnaround time of 21±7 days validating the clinical applicability of MOS and leading to the MODEL-ABC trial. As of February 14, 2023, 4 of 15 patients have enrolled onto MODEL-ABC. All biopsies provided sufficient tissue for MOS generation, and drug screens were performed in 14-28 days across 2-4 chemotherapies. Two patients received capecitabine, one patient received eribulin, and one patient received paclitaxel. Full results of MODEL-ABC including correlation between MOS drug response and patient outcomes will be reported at the meeting. Conclusions: Our platform enables efficient establishment of MOS from ABC patient samples and allows for drug dosing studies to be performed in a clinically meaningful timeframe. Our preliminary data suggests it is feasible to obtain biopsies for MOS development and perform drug screens within 14 days. These findings provided the foundation for evaluating this technology as a potential ABC diagnostic tool and warrants further clinical development in ABC. Clinical trial information: NCT04655573.

Disclaimer

This material on this page is ©2024 American Society of Clinical Oncology, all rights reserved. Licensing available upon request. For more information, please contact licensing@asco.org

Abstract Details

Meeting

2023 ASCO Annual Meeting

Session Type

Poster Session

Session Title

Breast Cancer—Metastatic

Track

Breast Cancer

Sub Track

Other Breast Cancer Subtypes

Clinical Trial Registration Number

NCT04655573

Citation

J Clin Oncol 41, 2023 (suppl 16; abstr 1107)

DOI

10.1200/JCO.2023.41.16_suppl.1107

Abstract #

1107

Poster Bd #

328

Abstract Disclosures