Pre-clinical validation of an RNA-based precision oncology platform for patient-therapy alignment in a diverse set of human malignancies resistant to standard treatments

We use a Master Regular-based precision cancer medicine framework to perform joint analysis of transcriptomic profiles from patients with distinct treatment refractory cancer and drug perturbation transcriptional profiles in cognate cell lines, to predict drug sensitivity. Validation of predictions was performed in patient-derived xenograft (PDX) mice. Pharmacodynamic samples were obtained from PDX mice after the third dose for RNASeq and downstream analysis. Overall design: RNASeq profiles of patient tumors and their respective xenografts for which drugs were predicted using the PCM tools OncoTarget and OncoTreat; RNASeq profiles of cognate cell line models; drug perturbational (DMSO controls and post-perturbation) profiles in these cell lines; RNASeq of on-treatment pharmacodynamic PDX samples; RNAseq profiles of 103 meningioma patient tumors sequenced at Columbia University Irving Medical Center and used to derive a meningioma gene regulatory network (interactome).