Self-assembled patient-derived tumor-like cell clusters for personalized drug testing in diverse sarcomas.

Abstract

11569 Background: Soft tissue sarcomas (STS) are rare malignancies with over 100 distinct histological subtypes. Their rarity and heterogeneity pose significant challenges to identifying effective therapies, and approved regimens show varied responses. Several patient-derived tumor models have emerged recently. However, STS present a challenge in developing preclinical drug-testing models due to their non-epithelial and complex nature. Methods: Here we report a model termed patient-derived tumor-like cell clusters (PTCs) derived from STS patients. PTCs result from the self-assembly and proliferation of mesenchymal stem cells (MSCs), epithelial cells, and immune cells, faithfully recapitulating the morphology and function of the original tumors. This is an trial to assess the feasibility and predictive value of a standardized PTC-based test to differentiate efficacy of the patients' clinical drug regimens. The study was conducted at Peking University Cancer Hospital and was approved by the local ethical review board. The patients and corresponding PTCs were divided into three sets: characterization and storage set, assay set and validation set. The characterization and storage set were used to characterize PTCs in comparison with original tumor samples or stored for future study. The assay set was separated into two groups to determine the drug efficacy concentration of a targeted therapy or chemotherapy due to their different action mechanisms. The validation set was used to compare the consistency between PTC drug assays and clinical outcome. We then conducted comparative analyses between PTCs and tumor spheres, as well as between PTCs and paired tumor samples. Results: From 2019 to the 2025, we obtained 254 samples (155 surgical, 98 puncture, and 1 ascites sample) to generate PTCs, covering tens of sarcoma classifications, with an overall success ratio of 94.9%, ranging from 85.7% to 100%. A total of 3,740 differentially expressed genes (DEGs) were identified between PTCs and tumor spheres, while 1,222 DEGs were identified between PTCs and tumor samples. Through standardized culture and drug-response assessment protocols, PTCs facilitate personalized drug testing, evaluating hundreds of therapies within two weeks. PTCs demonstrate an overall predictive accuracy of 78.3% for all clinical outcomes and 100% accuracy distinguishing CR/PR from PD, could serve as a valuable tool for personalized medicine. Conclusions: These findings revealed that PTCs as a tool to better understand the biology of individual tumors and characterize the landscape of drug resistance and sensitivity in sarcoma. These results underscore the potential of PTCs for prospective use in clinical decision-making therapy selection.