Abstract
Neuroblastoma cell lines are an important and cost-effective model used to study oncogenic drivers of the disease. While many of these cell lines have been previously characterized with SNP, methylation, and/or mRNA expression microarrays, there has not been an effort to comprehensively sequence these cell lines. Here, we present raw whole transcriptome data generated by RNA sequencing of 39 commonly-used neuroblastoma cell lines. These data can be used to perform differential expression analysis based on a genetic aberration or phenotype in neuroblastoma (e.g., MYCN amplification status, ALK mutation status, chromosome arm 1p, 11q and/or 17q status, sensitivity to pharmacologic perturbation). Additionally, we designed this experiment to enable structural variant and/or long-noncoding RNA analysis across these cell lines. Finally, as more DNase/ATAC and histone/transcription factor ChIP sequencing is performed in these cell lines, our RNA-Seq data will be an important complement to inform transcriptional targets as well as regulatory (enhancer or repressor) elements in neuroblastoma.
Highlights
Background & SummaryAn estimated 15,780 children were diagnosed with cancer in 2014 In the United States, and per year globally, this number is nearly 250,000
We focus on neuroblastoma, the most common extracranial solid tumor in children
We provide a processed file of gene-level mRNA abundances for each sample. We anticipate this data being a valuable tool for the neuroblastoma research community as we continue investigation into oncogenomic mechanisms of this disease
Summary
An estimated 15,780 children were diagnosed with cancer in 2014 In the United States, and per year globally, this number is nearly 250,000 (ref. 1). Utilizing a panel of cell lines which harbor a mixture of these characteristics enables differential expression analyses on the basis of a genetic lesion, mutation of interest, or expression of a gene of interest These data have reuse value to inform selection of cell lines for experimental investigation of putative neuroblastoma oncogenes and/or tumor suppressors. Choice of knock-down or overexpression studies require a priori knowledge of basal expression of the gene of interest for rational experimental design These data allow the experimenter to quickly determine which cell lines are high, mid, or low expressers of a gene of interest without requiring tedious quantitative, real-time PCR analysis or western blotting of multiple cell lines prior to initiating a gene over-expression or knockdown experiment. We anticipate this data being a valuable tool for the neuroblastoma research community as we continue investigation into oncogenomic mechanisms of this disease
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