ABSTRACT
CRLF2 overexpression in B-ALL patients with an IGH-CRLF2 translocation activates JAK-STAT, PI3K and ERK/MAPK signaling pathways. Although inhibitors of these pathways are available, investigating alternate targets could reduce treatment-associated toxicities. Comparing RNA-seq from IGH-CRLF2 and non-translocated patients we defined a translocation gene signature. Next, we assembled a B-ALL cancer-specific regulatory network using 529 B-ALL patient samples from the NCI TARGET database coupled with priors generated from ATAC-seq peak TF-motif analysis. The network was used to infer differential changes in TF activities predicted to control IGH-CRLF2 deregulated genes, thereby enabling identification of translocation-associated pathways and potential new therapeutic targets.