Our goal is to integrate mouse and human multi-omics data to identify oncogenic events in pediatric brain tumors. In our recent study (Wang et al. Nat. Comm. 2019), we profiled transcriptome, whole proteome and phosphoproteome in two glioma mouse models driven by mutated RTK oncogenes, PDGFRA and NTRK1. Systems biology approaches identified numerous some master regulators, including 41 kinases and 23 transcription factors. However, considering enormous complexity and diversity in human patient samples, mapping the altered omics changes in mouse models back to human is an effective approach to pinpoint oncogenic events in patients. We thus propose to use brain cancer genome data from Children's Brain Tumor Network (CBTN), to perform our cross-species omics comparison by validating the identified oncogenic signaling networks.
What are the goals of this project?
We plan to use whole genome sequence and RNAseq data of pediatric brain cancer tissues and perform a cross-species comparisons with mouse data that we collected. To compare the expression levels, with a focus on RTKs and other identified master regulators, mouse RNA-seq data will be aligned to the human dataset, and the expression changes will be traced back to genomic mutations. The expression changes will be further validated by the mouse proteomic data.