iTReX: Interactive exploration of mono- and combination therapy dose response profiling data

High throughput screening methods, measuring the sensitivity and resistance of tumor cells to drug treatments have been rapidly evolving. Not only do these screens allow correlating response profiles to tumor genomic features for developing novel predictors of treatment response, but they can also add evidence for therapy decision making in precision oncology. Recent analysis methods developed for either assessing single agents or combination drug efficacies enable quantification of dose-response curves with restricted symmetric fit settings. Here, we introduce iTReX, a user-friendly and interactive Shiny/R application, for both the analysis of mono- and combination therapy responses. The application features an extended version of the drug sensitivity score (DSS) based on the integral of an advanced five-parameter dose-response curve model and a differential DSS for combination therapy profiling. Additionally, iTReX includes modules that visualize drug target interaction networks and support the detection of matches between top therapy hits and the sample omics features to enable the identification of druggable targets and biomarkers. iTReX enables the analysis of various quantitative drug or therapy response readouts (e.g. luminescence, fluorescence microscopy) and multiple treatment strategies (drug treatments, radiation). Using iTReX we validate a cost-effective drug combination screening approach and reveal the application’s ability to identify potential sample-specific biomarkers based on drug target interaction networks. The iTReX web application is accessible at (https://itrex.kitz-heidelberg.de).Peer reviewe

MYCN mediates cysteine addiction and sensitizes neuroblastoma to ferroptosis

Aberrant expression of MYC transcription factor family members predicts poor clinical outcome in many human cancers. Oncogenic MYC profoundly alters metabolism and mediates an antioxidant response to maintain redox balance. Here we show that MYCN induces massive lipid peroxidation on depletion of cysteine, the rate-limiting amino acid for glutathione (GSH) biosynthesis, and sensitizes cells to ferroptosis, an oxidative, non-apoptotic and iron-dependent type of cell death. The high cysteine demand of MYCN-amplified childhood neuroblastoma is met by uptake and transsulfuration. When uptake is limited, cysteine usage for protein synthesis is maintained at the expense of GSH triggering ferroptosis and potentially contributing to spontaneous tumor regression in low-risk neuroblastomas. Pharmacological inhibition of both cystine uptake and transsulfuration combined with GPX4 inactivation resulted in tumor remission in an orthotopic MYCN-amplified neuroblastoma model. These findings provide a proof of concept of combining multiple ferroptosis targets as a promising therapeutic strategy for aggressive MYCN-amplified tumors

iTReX: Interactive exploration of mono- and combination therapy dose response profiling data

High throughput screening methods, measuring the sensitivity and resistance of tumor cells to drug treatments have been rapidly evolving. Not only do these screens allow correlating response profiles to tumor genomic features for developing novel predictors of treatment response, but they can also add evidence for therapy decision making in precision oncology. Recent analysis methods developed for either assessing single agents or combination drug efficacies enable quantification of dose-response curves with restricted symmetric fit settings. Here, we introduce iTReX, a user-friendly and interactive Shiny/R application, for both the analysis of mono- and combination therapy responses. The application features an extended version of the drug sensitivity score (DSS) based on the integral of an advanced five-parameter dose-response curve model and a differential DSS for combination therapy profiling. Additionally, iTReX includes modules that visualize drug target interaction networks and support the detection of matches between top therapy hits and the sample omics features to enable the identification of druggable targets and biomarkers. iTReX enables the analysis of various quantitative drug or therapy response readouts (e.g. luminescence, fluorescence microscopy) and multiple treatment strategies (drug treatments, radiation). Using iTReX we validate a cost-effective drug combination screening approach and reveal the application’s ability to identify potential sample-specific biomarkers based on drug target interaction networks. The iTReX web application is accessible at (https://itrex.kitz-heidelberg.de).Peer reviewe

Combining APR-246 and HDAC-Inhibitors: A Novel Targeted Treatment Option for Neuroblastoma

APR-246 (Eprenetapopt/PRIMA-1Met) is a very potent anti-cancer drug in clinical trials and was initially developed as a p53 refolding agent. As an alternative mode of action, the elevation of reactive oxygen species (ROS) has been proposed. Through an in silico analysis, we investigated the responses of approximately 800 cancer cell lines (50 entities; Cancer Therapeutics Response Portal, CTRP) to APR-246 treatment. In particular, neuroblastoma, lymphoma and acute lymphocytic leukemia cells were highly responsive. With gene expression data from the Cancer Cell Line Encyclopedia (CCLE; n = 883) and patient samples (n = 1643) from the INFORM registry study, we confirmed that these entities express low levels of SLC7A11, a previously described predictive biomarker for APR-246 responsiveness. Combining the CTRP drug response data with the respective CCLE gene expression profiles, we defined a novel gene signature, predicting the effectiveness of APR-246 treatment with a sensitivity of 90% and a specificity of 94%. We confirmed the predicted APR-246 sensitivity in 8/10 cell lines and in ex vivo cultures of patient samples. Moreover, the combination of ROS detoxification-impeding APR-246 with approved HDAC-inhibitors, known to elevate ROS, substantially increased APR-246 sensitivity in cell cultures and in vivo in two zebrafish neuroblastoma xenograft models. These data provide evidence that APR-246, in combination with HDAC-inhibitors, displays a novel potent targeted treatment option for neuroblastoma patients

Functional Therapeutic Target Validation Using Pediatric Zebrafish Xenograft Models

The survival rate among children with relapsed tumors remains poor, due to tumor heterogeneity, lack of directly actionable tumor drivers and multidrug resistance. Novel personalized medicine approaches tailored to each tumor are urgently needed to improve cancer treatment. Current pediatric precision oncology platforms, such as the INFORM (INdividualized Therapy FOr Relapsed Malignancies in Childhood) study, reveal that molecular profiling of tumor tissue identifies targets associated with clinical benefit in a subgroup of patients only and should be complemented with functional drug testing. In such an approach, patient-derived tumor cells are exposed to a library of approved oncological drugs in a physiological setting, e.g., in the form of animal avatars injected with patient tumor cells. We used molecularly fully characterized tumor samples from the INFORM study to compare drug screen results of individual patient-derived cell models in functional assays: (i) patient-derived spheroid cultures within a few days after tumor dissociation; (ii) tumor cells reisolated from the corresponding mouse PDX; (iii) corresponding long-term organoid-like cultures and (iv) drug evaluation with the corresponding zebrafish PDX (zPDX) model. Each model had its advantage and complemented the others for drug hit and drug combination selection. Our results provide evidence that in vivo zPDX drug screening is a promising add-on to current functional drug screening in precision medicine platforms

Super enhancers define regulatory subtypes and cell identity in neuroblastoma

Half of the children diagnosed with neuroblastoma (NB) have high-risk disease, disproportionately contributing to overall childhood cancer-related deaths. In addition to recurrent gene mutations, there is increasing evidence supporting the role of epigenetic deregulation in disease pathogenesis. Yet, comprehensive cis-regulatory network descriptions from NB are lacking. Here, using genome-wide H3K27ac profiles across 60 NBs, covering the different clinical and molecular subtypes, we identified four major super-enhancer-driven epigenetic subtypes and their underlying master regulatory networks. Three of these subtypes recapitulated known clinical groups; namely, MYCN-amplified, MYCN non-amplified high-risk and MYCN non-amplified low-risk NBs. The fourth subtype, exhibiting mesenchymal characteristics, shared cellular identity with multipotent Schwann cell precursors, was induced by RAS activation and was enriched in relapsed disease. Notably, CCND1, an essential gene in NB, was regulated by both mesenchymal and adrenergic regulatory networks converging on distinct super-enhancer modules. Overall, this study reveals subtype-specific super-enhancer regulation in NBs