Patient derived tumoroids of high grade neuroendocrine neoplasms for more personalized therapies

Purpose: Advanced high-grade gastroenteropancreatic neuroendocrine neoplasm (GEP-NEN) are highly aggressive and heterogeneous epithelial malignancies with poor clinical outcomes. No therapeutic predictive biomarkers exist and representative preclinical models to study their biology are missing. Patient-derived (PD) tumoroids may enable fast ex vivo pharmacotyping and provide subsidiary biological information for more personalized therapy strategies in individual patients. Experimental Design: PD tumoroids were established from rare biobanked surgical resections of advanced high-grade GEP-NEN patients. Using targeted in vitro pharmacotyping and next-generation sequencing of patient samples and matching PD tumoroids, we profiled individual patients and compared treatment-induced molecular stress response and in vitro drug sensitivity to the clinical therapy response. Results: We demonstrate high success rates in culturing PD tumoroids of high-grade GEP-NENs within clinically meaningful timespans. PD tumoroids recapitulate biological key features of high-grade GEP-NEN and mimic clinical response to cisplatin and temozolomide in vitro. Moreover, investigating treatment-induced molecular stress responses in PD tumoroids in silico, we discovered and functionally validated Lysine demethylase 5A (KDM5A) and interferon-beta (IFNB1) as two vulnerabilities that act synergistically in combination with cisplatin and may present novel therapeutic options in high-grade GEP-NENs. Conclusion: Patient-derived tumoroids from high-grade GEP-NENs represent a relevant model to screen drug sensitivities of individual patients within clinically relevant timespans and provide novel functional insights into drug-induced stress responses. Clinical patient response to standard-of-care chemotherapeutics matches with drug sensitivities of PD tumoroids. Together, our findings provide a functional precision oncology approach for gathering patient-centered subsidiary treatment information that will potentially increase therapeutic opportunities in the framework of personalized medicine.