Project description:Osteosarcoma (OS) and Ewing’s sarcoma (EW) are the two most common pediatric solid tumors, after brain tumors. Multimodal treatments have significantly improved prognosis in localized disease but outcome is still poor in metastatic patients, for whom therapeutic options are often inadequate. Preclinical drug testing to identify promising treatment options that match the molecular make-up of these tumors is hampered by the lack of appropriate and molecularly well-characterized patient-derived models. To address this need, a panel of patient-derived xenografts (PDX) was established by subcutaneous implantation of fresh, surgically resected OS and EW tumors in NSG mice. Tumors were re-transplanted to next mice generations and fragments were collected for histopathological and molecular characterization. A model was considered established after observing stable histological and molecular features for at least three passages. To evaluate the similarity of the model with primary tumor, we performed a global gene expression profiling and tissue microarrays (TMA), to assess tumor specific biomarkers on tissues from OS/EW tumors and their PDXs (1st and 3rd passage). Moreover, we verified the feasibility of these models for preclinical drug testing. We implanted 61 OS and 29 EW samples: 14/38 (37%) primary OS and 9/23 (39%) OS lung metastases successfully engrafted; while among EW, 5/26 (19%) primary samples and 1/3 (33%) metastases were established. Comparison between patient samples and PDXs, highlighted that histology and genetic characteristics of PDXs were stable and maintained over passages. In particular, correlative analysis between OS and EW samples and their PDXs was extremely high (Pearson’s r range r=0.94-0.96), while patient-derived primary cultures displayed reduced correlation with human samples (r=0.90-0.93), indicating that in vitro adaptation superimpose molecular alterations that create genetic diversion from original tumors. No significant differentially expressed gene profile was observed from the comparison between EW samples and PDXs (fold change > 2, adjusted p <0.05 at paired t-test). In OS, the comparison between OS patient-derived tumors and PDX indicated differences in 397 genes, mostly belonging to immune system functional category. This is in line with the idea that human immune cells are gradually replaced by murine counterparts upon engraftment in the mouse. As proof-of concept, two EW PDX and one OS PDX have been treated with conventional and innovated drugs to test their value in terms of drug-sensitivity prediction. Overall, our study indicated that PDX models maintained the histological and genetic markers of the tumor samples and represent reliable models to test sensitivity to novel drug associations.

Project description:Pediatric liver tumors with high-risk features pose therapeutic challenges, necessitating the development of more targeted and effective treatment strategies. Computational modeling of virtual patients and in silico drug response simulations, based on properly trained mechanistic models, is a powerful strategy to predict new treatment options. We aimed to leverage patient-specific mechanistic cell models to identify therapeutic alternatives for pediatric patients with high-risk liver tumors. We generated digital twins of high-risk pediatric liver tumor patients by integrating clinical, genetic, and transcriptomic data and performed computational drug response simulations using mechanistic models. We validated the therapeutic potential of ceritinib in patient-derived xenograft models both in vitro and in vivo and used fluorescence microscopy-based imaging for functional analyses. Mechanistic models trained with digital twins of high-risk pediatric liver tumor patients identified ceritinib as the most effective treatment option through iterated in silico drug response simulations. Validation on a comprehensive drug-testing platform demonstrated that ceritinib, unlike other ALK receptor tyrosine kinase inhibitors with lower prediction scores, inhibited tumor growth by targeting non-canonical kinases. Mechanistically, ceritinib suppressed expression of nucleoporins, essential components of the nuclear pore complex overexpressed in pediatric liver tumors, consequently leading to the disruption of nuclear membrane integrity, perinuclear accumulation of mitochondria, production of reactive oxygen species, and induction of apoptosis. In patient-derived xenograft mouse models, ceritinib reduced tumor burden and extended survival by promoting cell death. This study demonstrates the successful application of mechanistic models on virtual patients to position ceritinib as a promising therapeutic agent for high-risk pediatric liver tumors, highlighting its impact on key kinases implicated in tumor aggressiveness and its ability to compromise nuclear integrity.

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