Akademik Veri Yönetim Sistemi
ESMO Rare Cancers, cilt.5, ss.40, 2026 (Düzenli olarak gerçekleştirilen hakemli kongrenin bildiri kitabı)
Background
Sarcomas are heterogeneous mesenchymal tumours with limited systemic options and few predictive biomarkers. Responses to chemotherapy remain unpredictable, and molecular profiling seldom identifies actionable targets. This therapeutic uncertainty highlights the need for complementary approaches such as functional precision oncology. Our laboratory has established a high-fidelity patient-derived organoid/tumoroid screening platform across multiple solid tumours. Using this system, we present preliminary data from three sarcoma cases to illustrate how ex vivo 3D drug sensitivity profiling may uncover clinically relevant vulnerabilities not evident from routine pathology or genomics.Methods
Fresh tumour samples from leiomyosarcoma (LMS), intimal sarcoma (IS) and chondrosarcoma (CS) were processed into 3D tumoroids. Morphologic, genotypic and phenotypic comparisons with matched tumours confirmed model fidelity. A broad drug panel was tested in 3D, and Day-6 viability was measured using CellTiter-Glo to classify agents as Sensitive, Low Sensitive or Not Sensitive.Results
Tumoroid generation was successful for all cases, showing high concordance with primary tumours. Despite a shared pattern of global chemoresistance to standard sarcoma agents, each tumour demonstrated a distinct profile. LMS showed unexpected susceptibility to EGFR-pathway inhibitors and selected platinums. IS exhibited a narrow yet reproducible vulnerability to gemcitabine, vinorelbine, ramucirumab and sorafenib, while most agents showed no activity. CS, typically chemoresistant, displayed selective sensitivity to alkylators, with minimal response to other classes. These findings reveal substantial functional divergence across sarcoma subtypes.Conclusions
This validated organoid platform identified subtype-specific therapeutic vulnerabilities in three sarcomas, supporting the integration of ex vivo drug sensitivity testing into individualized treatment planning and clinical trial prioritization.