Patient- and xenograft-derived organoids recapitulate pediatric brain tumor features and patient treatments.

Brain tumors are the leading cause of cancer-related death in children. Experimental in vitro models that faithfully capture the hallmarks and tumor heterogeneity of pediatric brain cancers are limited and hard to establish. We present a protocol that enables efficient generation, expansion, and biobanking of pediatric brain cancer organoids. Utilizing our protocol, we have established patient-derived organoids (PDOs) from ependymomas, medulloblastomas, low-grade glial tumors, and patient-derived xenograft organoids (PDXOs) from medulloblastoma xenografts. PDOs and PDXOs recapitulate histological features, DNA methylation profiles, and intratumor heterogeneity of the tumors from which they were derived. We also showed that PDOs can be xenografted. Most interestingly, when subjected to the same routinely applied therapeutic regimens, PDOs respond similarly to the patients. Taken together, our study highlights the potential of PDOs and PDXOs for research and translational applications for personalized medicine.

Predictive modeling of resistance to SMO inhibition in a patient-derived orthotopic xenograft model of SHH medulloblastoma.

Background: Inhibition of the sonic hedgehog (SHH) pathway with Smoothened (SMO) inhibitors is a promising treatment strategy in SHH-activated medulloblastoma, especially in adult patients. However, the problem is that tumors frequently acquire resistance to the treatment. To understand the underlying resistance mechanisms and to find ways to overcome the resistance, preclinical models that became resistant to SMO inhibition are needed. Methods: To induce SMO inhibitor resistant tumors, we have treated a patient-derived xenograft (PDX) model of SHH medulloblastoma, sensitive to SMO inhibition, with 20 mg/kg Sonidegib using an intermitted treatment schedule. Vehicle-treated and resistant models were subjected to whole-genome and RNA sequencing for molecular characterization and target engagement. In vitro drug screens (76 drugs) were performed using Sonidegib-sensitive and -resistant lines to find other drugs to target the resistant lines. One of the top hits was then validated in vivo. Results: Nine independent Sonidegib-resistant PDX lines were generated. Molecular characterization of the resistant models showed that eight models developed missense mutations in SMO and one gained an inactivating point mutation in MEGF8, which acts downstream of SMO as a repressor in the SHH pathway. The in vitro drug screen with Sonidegib-sensitive and -resistant lines identified good efficacy for Selinexor in the resistant line. Indeed, in vivo treatment with Selinexor revealed that it is more effective in resistant than in sensitive models. Conclusions: We report the first human SMO inhibitor resistant medulloblastoma PDX models, which can be used for further preclinical experiments to develop the best strategies to overcome the resistance to SMO inhibitors in patients.

A biobank of patient-derived pediatric brain tumor models.

Brain tumors are the leading cause of cancer-related death in children. Genomic studies have provided insights into molecular subgroups and oncogenic drivers of pediatric brain tumors that may lead to novel therapeutic strategies. To evaluate new treatments, better preclinical models adequately reflecting the biological heterogeneity are needed. Through the Children's Oncology Group ACNS02B3 study, we have generated and comprehensively characterized 30 patient-derived orthotopic xenograft models and seven cell lines representing 14 molecular subgroups of pediatric brain tumors. Patient-derived orthotopic xenograft models were found to be representative of the human tumors they were derived from in terms of histology, immunohistochemistry, gene expression, DNA methylation, copy number, and mutational profiles. In vivo drug sensitivity of targeted therapeutics was associated with distinct molecular tumor subgroups and specific genetic alterations. These models and their molecular characterization provide an unprecedented resource for the cancer community to study key oncogenic drivers and to evaluate novel treatment strategies.