Single-cell or nucleus RNAseq of neuroblastoma patient-derived xenografts
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus Homo sapiens
PROVIDER: GSE228957 | GEO | 2024/05/15
REPOSITORIES: GEO
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Project description:Single-cell or nucleus RNAseq of neuroblastoma patient-derived xenografts
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Project description:Neuroblastoma is the most common solid tumour in childhood and prognosis remains poor for high-risk cases despite the use of multimodal treatment. Analysis of public drug sensitivity data showed neuroblastoma lines to be particularlysensitive to indisulam, a molecular glue that selectively targets the RNA splicing factor RBM39 for proteosomal degradation via DCAF15-E3-ubiquitin ligase. In neuroblastoma models indisulam induced rapid loss of RBM39, accumulation of splicing errors and growth inhibition in a DCAF15-dependent manner. Integrative analysis of RNAseq and proteomics data highlighted a particular disruption to cell cycle and metabolism. Metabolic profiling demonstrated metabolome perturbations and mitochondrial dysfunction resulting from indisulam. Complete tumour without relapse was observed in both xenografts and the Th-MYCN transgenic model of neuroblastoma after indisulam treatment, with RBM39 loss confirmed in vivo. Our data imply that dual targeting of metabolism and RNA splicing with anti-cancer sulfonamides such as indisulam is promising therapeutic approach for high-risk neuroblastoma.
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Project description:Prediction of the antimalarial potential of small molecules. This model is an ensemble of smaller QSAR models trained on proprietary data from various sources, up to a total of >7M compounds. The training sets belong to Evotec, Johns Hopkins, MRCT, MMV - St. Jude, AZ, GSK, and St. Jude Vendor Library. The code and training data are not released, using this model posts predictions to the MAIP online server. The Ersilia Model Hub also offers MAIP-surrogate as a downloadable package for IP-sensitive queries.
Model Type: Predictive machine learning model.
Model Relevance: Predicts antimalarial activity.
Model Encoded by: Amna Ali (Ersilia)
Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam
Implementation of this model code by Ersilia is available here:
https://github.com/ersilia-os/eos4zfy
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Project description:Neurotrophic receptor tyrosine kinases, also known as Tropomyosin receptor kinases (TrkA, TrkB and TrkC), despite their homology, contribute to the clinical heterogeneity of childhood cancer neuroblastoma. TrkA expression is associated with low-stage disease and is often seen with spontaneous tumour regression. Conversely, TrkB is present in unfavourable neuroblastomas that often harbour amplification of the MYCN oncogene. The role of TrkC is less clearly defined, although some studies suggest its association with a favourable outcome. Understanding the differences in the activity of Trk receptors that drive divergent clinical phenotypes as well as the influence of MYCN amplification on downstream Trk receptor signalling remain poorly understood. Here, we present a comprehensive label-free mass spectrometry-based total proteomics and phosphoproteomics dataset where we identified and quantified 4,907 proteins, 16,744 phosphosites and 5,084 phosphoproteins, derived from NGF/BDNF/NT-3 treated TrkA/B/C-overexpressing neuroblastoma cells with differential MYCN status. Analysing our dataset offers valuable insights into TrkA/B/C receptor signalling in neuroblastoma and its modulation by MYCN status; and holds potential for advancing therapeutic strategies in this challenging childhood cancer.
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