Capmatinib is an effective treatment for MET-fusion driven pediatric high-grade glioma and synergizes with radiotherapy.

BACKGROUND: Pediatric-type diffuse high-grade glioma (pHGG) is the most frequent malignant brain tumor in children and can be subclassified into multiple entities. Fusion genes activating the MET receptor tyrosine kinase often occur in infant-type hemispheric glioma (IHG) but also in other pHGG and are associated with devastating morbidity and mortality. METHODS: To identify new treatment options, we established and characterized two novel orthotopic mouse models harboring distinct MET fusions. These included an immunocompetent, murine allograft model and patient-derived orthotopic xenografts (PDOX) from a MET-fusion IHG patient who failed conventional therapy and targeted therapy with cabozantinib. With these models, we analyzed the efficacy and pharmacokinetic properties of three MET inhibitors, capmatinib, crizotinib and cabozantinib, alone or combined with radiotherapy. RESULTS: Capmatinib showed superior brain pharmacokinetic properties and greater in vitro and in vivo efficacy than cabozantinib or crizotinib in both models. The PDOX models recapitulated the poor efficacy of cabozantinib experienced by the patient. In contrast, capmatinib extended survival and induced long-term progression-free survival when combined with radiotherapy in two complementary mouse models. Capmatinib treatment increased radiation-induced DNA double-strand breaks and delayed their repair. CONCLUSIONS: We comprehensively investigated the combination of MET inhibition and radiotherapy as a novel treatment option for MET-driven pHGG. Our seminal preclinical data package includes pharmacokinetic characterization, recapitulation of clinical outcomes, coinciding results from multiple complementing in vivo studies, and insights into molecular mechanism underlying increased efficacy. Taken together, we demonstrate the groundbreaking efficacy of capmatinib and radiation as a highly promising concept for future clinical trials.

A high-throughput quality control method for assessing the serial dilution performance of dose-response plates with acoustic ejection mass spectrometry.

This study aimed to develop a streamlined method for evaluating the dilution ratio of drug dose-response plates created by automated liquid handlers in the early stages of drug discovery. The quantitative techniques commonly used for this purpose have restrictions due to their limited linear dynamic range and inaccuracies in assessing serial dilution performance. To address this challenge, we describe a method based on acoustic ejection mass spectrometry (AEMS). The method involves using standard compounds and an internal standard to evaluate each dilution point in quality control (QC) plates. The samples are transferred to a chromatography-free tandem mass spectrometry system through an acoustic source, enabling the analysis of one sample per three seconds from a microtiter plate. This approach provides precise, accurate, label-free, and rapid data acquisition to support high-throughput screening efforts.

ATM inhibition enhances the efficacy of radiation across distinct molecular subgroups of pediatric high-grade glioma.

BACKGROUND: Pediatric high-grade glioma (pHGG) is largely incurable and accounts for most brain tumor-related deaths in children. Radiation is a standard therapy, yet the benefit from this treatment modality is transient, and most children succumb to disease within 2 years. Recent large-scale genomic studies suggest that pHGG has alterations in DNA damage response (DDR) pathways that induce resistance to DNA damaging agents. The aim of this study was to evaluate the therapeutic potential and molecular consequences of combining radiation with selective DDR inhibition in pHGG. METHODS: We conducted an unbiased screen in pHGG cells that combined radiation with clinical candidates targeting the DDR and identified the ATM inhibitor AZD1390. Subsequently, we profiled AZD1390 + radiation in an extensive panel of early passage pHGG cell lines, mechanistically characterized response to the combination in vitro in sensitive and resistant cells and evaluated the combination in vivo using TP53 wild-type and TP53 mutant orthotopic xenografts. RESULTS: AZD1390 significantly potentiated radiation across molecular subgroups of pHGG by increasing mutagenic nonhomologous end joining and augmenting genomic instability. In contrast to previous reports, ATM inhibition significantly improved the efficacy of radiation in both TP53 wild-type and TP53 mutant isogenic cell lines and distinct orthotopic xenograft models. Furthermore, we identified a novel mechanism of resistance to AZD1390 + radiation that was marked by an attenuated ATM pathway response which dampened sensitivity to ATM inhibition and induced synthetic lethality with ATR inhibition. CONCLUSIONS: Our study supports the clinical evaluation of AZD1390 in combination with radiation in pediatric patients with HGG.

Proteasome inhibition targets the KMT2A transcriptional complex in acute lymphoblastic leukemia.

Rearrangments in Histone-lysine-N-methyltransferase 2A (KMT2Ar) are associated with pediatric, adult and therapy-induced acute leukemias. Infants with KMT2Ar acute lymphoblastic leukemia (ALL) have a poor prognosis with an event-free-survival of 38%. Herein we evaluate 1116 FDA approved compounds in primary KMT2Ar infant ALL specimens and identify a sensitivity to proteasome inhibition. Upon exposure to this class of agents, cells demonstrate a depletion of histone H2B monoubiquitination (H2Bub1) and histone H3 lysine 79 dimethylation (H3K79me2) at KMT2A target genes in addition to a downregulation of the KMT2A gene expression signature, providing evidence that it targets the KMT2A transcriptional complex and alters the epigenome. A cohort of relapsed/refractory KMT2Ar patients treated with this approach on a compassionate basis had an overall response rate of 90%. In conclusion, we report on a high throughput drug screen in primary pediatric leukemia specimens whose results translate into clinically meaningful responses. This innovative treatment approach is now being evaluated in a multi-institutional upfront trial for infants with newly diagnosed ALL.

Data vignettes for the application of response surface models in drug combination analysis.

This data set contains the data used in Twarog et al. (2021) to examine the robustness and utility of response surface models in drug combination analysis. It includes simulated experimental data for the evaluation of traditional index methods, as well as a processed library of interaction metrics evaluated on the Merck OncoPolyPharmacology Screen (O'Neil et al., 2016), the scripts used to implement those metrics on all tested combinations in that screen, and scripts to evaluate the performance of those metrics in comparison with real-world mechanistic classifications. Finally, the data set includes data from several published and unpublished drug combination experiments, and scripts which allow the analyses of those experiments to be replicated and applied to new data.

SLFN11 is Widely Expressed in Pediatric Sarcoma and Induces Variable Sensitization to Replicative Stress Caused By DNA-Damaging Agents.

Pediatric sarcomas represent a heterogeneous group of malignancies that exhibit variable response to DNA-damaging chemotherapy. Schlafen family member 11 protein (SLFN11) increases sensitivity to replicative stress and has been implicated as a potential biomarker to predict sensitivity to DNA-damaging agents (DDA). SLFN11 expression was quantified in 220 children with solid tumors using IHC. Sensitivity to the PARP inhibitor talazoparib (TAL) and the topoisomerase I inhibitor irinotecan (IRN) was assessed in sarcoma cell lines, including SLFN11 knock-out (KO) and overexpression models, and a patient-derived orthotopic xenograft model (PDOX). SLFN11 was expressed in 69% of pediatric sarcoma sampled, including 90% and 100% of Ewing sarcoma and desmoplastic small round-cell tumors, respectively, although the magnitude of expression varied widely. In sarcoma cell lines, protein expression strongly correlated with response to TAL and IRN, with SLFN11 KO resulting in significant loss of sensitivity in vitro and in vivo Surprisingly, retrospective analysis of children with sarcoma found no association between SLFN11 levels and favorable outcome. Subsequently, high SLFN11 expression was confirmed in a PDOX model derived from a patient with recurrent Ewing sarcoma who failed to respond to treatment with TAL + IRN. Selective inhibition of BCL-xL increased sensitivity to TAL + IRN in SLFN11-positive resistant tumor cells. Although SLFN11 appears to drive sensitivity to replicative stress in pediatric sarcomas, its potential to act as a biomarker may be limited to certain tumor backgrounds or contexts. Impaired apoptotic response may be one mechanism of resistance to DDA-induced replicative stress.

Patient-derived models recapitulate heterogeneity of molecular signatures and drug response in pediatric high-grade glioma.

Pediatric high-grade glioma (pHGG) is a major contributor to cancer-related death in children. In vitro and in vivo disease models reflecting the intimate connection between developmental context and pathogenesis of pHGG are essential to advance understanding and identify therapeutic vulnerabilities. Here we report establishment of 21 patient-derived pHGG orthotopic xenograft (PDOX) models and eight matched cell lines from diverse groups of pHGG. These models recapitulate histopathology, DNA methylation signatures, mutations and gene expression patterns of the patient tumors from which they were derived, and include rare subgroups not well-represented by existing models. We deploy 16 new and existing cell lines for high-throughput screening (HTS). In vitro HTS results predict variable in vivo response to PI3K/mTOR and MEK pathway inhibitors. These unique new models and an online interactive data portal for exploration of associated detailed molecular characterization and HTS chemical sensitivity data provide a rich resource for pediatric brain tumor research.

Using response surface models to analyze drug combinations.

Quantitative evaluation of how drugs combine to elicit a biological response is crucial for drug development. Evaluations of drug combinations are often performed using index-based methods, which are known to be biased and unstable. We examine how these methods can produce misleadingly structured patterns of bias, leading to erroneous judgments of synergy or antagonism. By contrast, response surface models are less prone to these defects and can be applied to a wide range of data that have appeared in recent literature, including the measurement of combination therapeutic windows and the analysis of discrete experimental measures, three-way drug combinations, and atypical response behaviors.

A critical evaluation of methods to interpret drug combinations.

Combination therapy is increasingly central to modern medicine. Yet reliable analysis of combination studies remains an open challenge. Previous work suggests that common methods of combination analysis are too susceptible to noise to support robust scientific conclusions. In this paper, we use simulated and real-world combination datasets to demonstrate that traditional index methods are unstable and biased by pharmacological and experimental conditions, whereas response-surface approaches such as the BRAID method are more consistent and unbiased. Using a publicly-available data set, we show that BRAID more accurately captures variations in compound mechanism of action, and is therefore better able to discriminate between synergistic, antagonistic, and additive interactions. Finally, we applied BRAID analysis to identify a clear pattern of consistently enhanced AKT sensitivity in a subset of cancer cell lines, and a far richer array of PARP inhibitor combination therapies for BRCA1-deficient cancers than would be identified by traditional synergy analysis.

Erratum: BRAID: A Unifying Paradigm for the Analysis of Combined Drug Action.

This corrects the article DOI: 10.1038/srep25523.

Orthotopic patient-derived xenografts of paediatric solid tumours.

Paediatric solid tumours arise from endodermal, ectodermal, or mesodermal lineages. Although the overall survival of children with solid tumours is 75%, that of children with recurrent disease is below 30%. To capture the complexity and diversity of paediatric solid tumours and establish new models of recurrent disease, here we develop a protocol to produce orthotopic patient-derived xenografts at diagnosis, recurrence, and autopsy. Tumour specimens were received from 168 patients, and 67 orthotopic patient-derived xenografts were established for 12 types of cancer. The origins of the patient-derived xenograft tumours were reflected in their gene-expression profiles and epigenomes. Genomic profiling of the tumours, including detailed clonal analysis, was performed to determine whether the clonal population in the xenograft recapitulated the patient's tumour. We identified several drug vulnerabilities and showed that the combination of a WEE1 inhibitor (AZD1775), irinotecan, and vincristine can lead to complete response in multiple rhabdomyosarcoma orthotopic patient-derived xenografts tumours in vivo.

Diversity-oriented natural product platform identifies plant constituents targeting Plasmodium falciparum.

BACKGROUND: A diverse library of pre-fractionated plant extracts, generated by an automated high-throughput system, was tested using an in vitro anti-malarial screening platform to identify known or new natural products for lead development. The platform identifies hits on the basis of in vitro growth inhibition of Plasmodium falciparum and counter-screens for cytotoxicity to human foreskin fibroblast or embryonic kidney cell lines. The physical library was supplemented by early-stage collection of analytical data for each fraction to aid rapid identification of the active components within each screening hit. RESULTS: A total of 16,177 fractions from 1300 plants were screened, identifying several P. falciparum inhibitory fractions from 35 plants. Although individual fractions were screened for bioactivity to ensure adequate signal in the analytical characterizations, fractions containing less than 2.0 mg of dry weight were combined to produce combined fractions (COMBIs). Fractions of active COMBIs had EC50 values of 0.21-50.28 and 0.08-20.04 µg/mL against chloroquine-sensitive and -resistant strains, respectively. In Berberis thunbergii, eight known alkaloids were dereplicated quickly from its COMBIs, but berberine was the most-active constituent against P. falciparum. The triterpenoids α-betulinic acid and ß-betulinic acid of Eugenia rigida were also isolated as hits. Validation of the anti-malarial discovery platform was confirmed by these scaled isolations from B. thunbergii and E. rigida. CONCLUSIONS: These results demonstrate the value of curating and exploring a library of natural products for small molecule drug discovery. Attention given to the diversity of plant species represented in the library, focus on practical analytical data collection, and the use of counter-screens all facilitate the identification of anti-malarial compounds for lead development or new tools for chemical biology.

BRAID: A Unifying Paradigm for the Analysis of Combined Drug Action.

With combination therapies becoming increasingly vital to understanding and combatting disease, a reliable method for analyzing combined dose response is essential. The importance of combination studies both in basic and translational research necessitates a method that can be applied to a wide range of experimental and analytical conditions. However, despite increasing demand, no such unified method has materialized. Here we introduce the Bivariate Response to Additive Interacting Doses (BRAID) model, a response surface model that combines the simplicity and intuitiveness needed for basic interaction classifications with the versatility and depth needed to analyze a combined response in the context of pharmacological and toxicological constraints. We evaluate the model in a series of simulated combination experiments, a public combination dataset, and several experiments on Ewing's Sarcoma. The resulting interaction classifications are more consistent than those produced by traditional index methods, and show a strong relationship between compound mechanisms and nature of interaction. Furthermore, analysis of fitted response surfaces in the context of pharmacological constraints yields a more concrete prediction of combination efficacy that better agrees with in vivo evaluations.

Robust Classification of Small-Molecule Mechanism of Action Using a Minimalist High-Content Microscopy Screen and Multidimensional Phenotypic Trajectory Analysis.

Phenotypic screening through high-content automated microscopy is a powerful tool for evaluating the mechanism of action of candidate therapeutics. Despite more than a decade of development, however, high content assays have yielded mixed results, identifying robust phenotypes in only a small subset of compound classes. This has led to a combinatorial explosion of assay techniques, analyzing cellular phenotypes across dozens of assays with hundreds of measurements. Here, using a minimalist three-stain assay and only 23 basic cellular measurements, we developed an analytical approach that leverages informative dimensions extracted by linear discriminant analysis to evaluate similarity between the phenotypic trajectories of different compounds in response to a range of doses. This method enabled us to visualize biologically-interpretable phenotypic tracks populated by compounds of similar mechanism of action, cluster compounds according to phenotypic similarity, and classify novel compounds by comparing them to phenotypically active exemplars. Hierarchical clustering applied to 154 compounds from over a dozen different mechanistic classes demonstrated tight agreement with published compound mechanism classification. Using 11 phenotypically active mechanism classes, classification was performed on all 154 compounds: 78% were correctly identified as belonging to one of the 11 exemplar classes or to a different unspecified class, with accuracy increasing to 89% when less phenotypically active compounds were excluded. Importantly, several apparent clustering and classification failures, including rigosertib and 5-fluoro-2'-deoxycytidine, instead revealed more complex mechanisms or off-target effects verified by more recent publications. These results show that a simple, easily replicated, minimalist high-content assay can reveal subtle variations in the cellular phenotype induced by compounds and can correctly predict mechanism of action, as long as the appropriate analytical tools are used.

Targeting the DNA repair pathway in Ewing sarcoma.

Ewing sarcoma (EWS) is a tumor of the bone and soft tissue that primarily affects adolescents and young adults. With current therapies, 70% of patients with localized disease survive, but patients with metastatic or recurrent disease have a poor outcome. We found that EWS cell lines are defective in DNA break repair and are sensitive to PARP inhibitors (PARPis). PARPi-induced cytotoxicity in EWS cells was 10- to 1,000-fold higher after administration of the DNA-damaging agents irinotecan or temozolomide. We developed an orthotopic EWS mouse model and performed pharmacokinetic and pharmacodynamic studies using three different PARPis that are in clinical development for pediatric cancer. Irinotecan administered on a low-dose, protracted schedule previously optimized for pediatric patients was an effective DNA-damaging agent when combined with PARPis; it was also better tolerated than combinations with temozolomide. Combining PARPis with irinotecan and temozolomide gave complete and durable responses in more than 80% of the mice.