(P 184) PAN-SARCOMA ORGANOID SCREENING PIPELINE

Objective: Bone and soft tissue sarcomas are a rare and diverse family of malignancies. Given the scarcity of efficient tumor models for bone and soft tissue sarcomas, studying the underlying molecular biology and identifying effective therapies remain difficult. In vitro cell line drug screening has limited benefit in confirmation of ineffective drugs. Patient-derived tumor organoids (PDTOs) are representative of the native physiology of tumors across an array of malignancies, including sarcoma (Phan et al, 2019; Al Shihabi et al, 2021). Our goal is to leverage PDTOs to create physiologically relevant sarcoma models across an array of bone and soft tissue subtypes, and to develop a pipeline for high-throughput screening of clinically relevant drugs to identify unique sensitivities of individual tumors.

Methods: We procured n=189 sarcoma specimens from biopsies and resections from n=128 patients. We successfully generated organoids from over 100 samples originating from primary, recurrent, and metastatic lesions of bone sarcomas (osteosarcoma, chondrosarcoma, Ewing sarcoma, etc.) and soft-tissue sarcomas (liposarcoma, leiomyosarcoma, undifferentiated pleomorphic sarcoma, etc.). In addition to molecular and histologic characterization, we monitored organoid growth using a machine learning-based segmentation algorithm. Finally, we screened organoids to generate functional drug sensitivity profiles of 500 single-agent drugs, 42 two-drug combination and 9 three-drug combination regimens in total.

Results: Samples procured represent over 30 distinct subtypes of bone and soft tissue sarcomas. We show how sarcoma PDTOs developed from clinical specimens closely resemble the tumor of origin in their histology and molecular features. Quantification of brightfield images of sarcoma organoids captures the diverse growth patterns of different sarcoma subtypes. Functional screening of chemotherapies, targeted agents, and combination therapies yields results within one week from surgery. We observe tumor-specific susceptibilities with high heterogeneity both across and within sarcoma subtypes. These organoids show drug response profiles that cannot be predicted by patient characteristics and diagnosis alone, underscoring the need for novel approaches to facilitate clinical selection of therapies individualized to each patient. We discuss the patterns of response with respect to prior treatment, patient age, lesion type and disease trajectory. We highlight specific cases where application of functional screening can mirror treatment outcome or facilitate clinical decisions.

Conclusion: We have established a pipeline to effectively generate patient-specific sarcoma models for downstream characterization and high-throughput screening. Drug response profiling of PDTOs derived from clinical specimens can provide timely, actionable information for functional precision medicine approaches.