Abstract

3592 Background: Patient-derived models of cancer, such as cell lines, patient-derived organoids, and patient-derived xenografts, are useful models of patient response in the clinic. However, these models are often not clinically applicable within the time periods necessary to inform clinical decision making, as they can take weeks to months to develop. An ideal platform using patient-derived models would be generated from a core biopsy with a subsequent drug screen within 10-14 days to minimize delay in therapy. We recently reported the development of MicroOrganoSpheres (MOS) that can be used in drug screens within 14 days of obtaining a biopsy. In the current study, we use this MOS system as precision oncology platform in colorectal cancer (CRC) to identify new therapies and predict response to therapy. Methods: CRC patient tissue samples were collected under a Duke Institutional Review Board approved protocol (Pro00089222). Resections or biopsies were mechanically and enzymatically digested to obtain a single cell suspension. Cells were then plated in Matrigel at a ratio of 20,000 cells:5 µL Matrigel to establish “mini-bulk” organoid cultures. After establishment for 5-7 days, cultures were harvested with subsequent generation of MOS at a ratio of 50 cells per MOS. After growing for 3-4 days, MOS were used for dose-response curves using oxaliplatin, SN38, and 5-Fluorouracil (5-FU) as well as high-throughput drug screens with the NCI Approved Oncology Drugs Set VI library. Results: We developed and optimized a MOS pipeline on over 50 CRC specimens, including 9 primary rectal, 35 primary CRC, 12 CRC liver metastasis, and 1 CRC lung metastasis lines with a success rate of 80% and an average of 10-21days from biopsy to MOS generation. The high success of generating CRC MOS in a clinically applicable time frame led to the next phase of the project where a total of 10 CRC MOS were tested against standard of care chemotherapy agents used in CRC (oxaliplatin, irinotecan and 5-FU) as well as the NCI Approved Oncology Drugs Set VI within 14-21days of establishment. We noted a range of sensitivity of approximately 100-fold for standard of care agents. The most sensitive drugs found in the high-throughput screen were Bortezomib, Carfilzomib, and Panobinostat and the most resistant were Gefitinib, Chlorambucil, and Procarbazine hydrochloride. Conclusions: These results demonstrate that our MOS pipeline can be used as a precision oncology platform within a clinically applicable time frame to potentially guide therapy. We are now in the process of correlating drug response in MOS to patient outcome data and these findings will be presented at the annual meeting.

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