General scientific questions:

Can we identify features of MRIs to diagnose specific tumor types or predict progression? Can we improve upon current segmentation algorithms?  

MRI Imaging Dataset:

2 image stacks (STIR and T1) from 50 NF1 NF2, and schwannomatosis patients using whole body magnetic resonance imaging (WB MRI). We'll also provide matching structured clinical data (diagnosis, tumor burden, etc) to facilitate phenotypic analysis of the imaging data.


General scientific questions:

Can we use the data from pre-clinical systems of NF1 and NF2 associated tumors to identify validated and druggable targets that modulate disease? 

Pre-Clinical Drug Modeling Dataset:

Harmonized plexiform neurofibroma, malignant peripheral nerve sheath tumor, meningioma, schwannoma drug screening data from cell lines with single-dose % viability measurements and summary dose-response curve metrics. At present, the summary dataset contains dose-response metrics from 38 cell lines and approximately 2000 drug-like small molecule representative of >1.2 million single-compound and combination dose-response measurements.


General scientific questions:

What genomic/transcriptomic features are most closely associated with the different NF tumor types? Can we use these features to identify novel drug targets?

RNASeq and Gene Variant Dataset:

Harmonized pNF, cNF, MPNST, meningioma, schwannoma RNASeq and gene variant datasets from patient samples as well as human and mouse cell lines.