Glioblastoma multiforme (
GBM
) is a highly malignant form of cancer that lacks effective treatment options or well‐defined strategies for personalized cancer therapy. The disease has been stratified into distinct molecular subtypes; however, the underlying regulatory circuitry that gives rise to such heterogeneity and its implications for therapy remain unclear. We developed a modular computational pipeline, Integrative Modeling of Transcription Regulatory Interactions for Systematic Inference of Susceptibility in Cancer (in
TRINS
iC), to dissect subtype‐specific regulatory programs and predict genetic dependencies in individual patient tumors. Using a multilayer network consisting of 518 transcription factors (
TF
s), 10,733 target genes, and a signaling layer of 3,132 proteins, we were able to accurately identify differential regulatory activity of
TF
s that shape subtype‐specific expression landscapes. Our models also allowed inference of mechanisms for altered
TF
behavior in different
GBM
subtypes. Most importantly, we were able to use the multilayer models to perform an
in silico
perturbation analysis to infer differential genetic vulnerabilities across
GBM
subtypes and pinpoint the
MYB
family member
MYBL
2 as a drug target specific for the Proneural subtype.