The use of phosphoproteomic data to identify altered kinases and signaling pathways in cancer

Abstract

Altered kinase signaling is one of the hallmarks of cancer that has previously been studied at the genomic and transcriptomic level. However, phosphoproteomic data are an increasingly popular way to study global cell signaling and can be used as a readout of kinase activity. This thesis provides a review of the tools and best practices used to analyze phosphoproteomic data. These resources include knowledge bases of enzymes, phosphorylation sites, mutations, and kinase inhibitors, and tools for prediction, visualization, and analysis. Furthermore, phosphoproteomic data were used to identify altered kinases in breast cancer, validate mutation-identified driver subnetworks in breast cancer subtypes, and identify altered signaling pathways in colon cancer. The DNA damage response pathway was predicted to be overactive in basal-like breast cancer based on phosphorylation. Furthermore, hyper-phosphorylated retinoblastoma-associated protein (RB1) was shown to promote colon cancer survival through both activation of proliferation and inhibition of apoptosis. Ultimately, phosphoproteomic data provided both complementary and contradictory information to genomic and transcriptomic data.