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Integrative discovery of treatments for high-risk neuroblastoma

ABSTRACT: Neuroblastoma (NB) cells exhibit a complex spectrum of pathway changes associated with oncogene activation, chromosome events, tumor micro-environment and super-enhancer states. So far, elucidating which pharmaceutical compounds could modulate the activation level of each known pathway in NB cells has not been feasible. We treated 2 patient-derived xenograft (PDX) NB cell lines with different chemical compounds, at 3 different doses (IC50, IC20, and IC10) and 2 time-points (6 and 24h). The whole-transcriptome of the treated cells was analyzed by a cost-effective DRUG-Seq method. Using factor analysis and supervised machine learning, the data was used to build a model that predicts the NB-specific outcome of 19,000+ drugs studied in other (non-NB) cell lines in several drug profiling databases (LINCS, CMap, DepMap).

ORGANISM(S): Homo sapiens

PROVIDER: GSE120920 | GEO | 2019/11/02

REPOSITORIES: GEO

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