Litcius/Paper detail

A highly multiplexed quantitative phosphosite assay for biology and preclinical studies

Hasmik Keshishian, E. Robert McDonald, Filip Mundt, Randy Melanson, Karsten Krug, Dale Porter, Luke Wallace, Dominique Forestier, Bokang Rabasha, Sara Marlow, Judit Jané‐Valbuena, Ellen Todres, Harrison Specht, Margaret Lea Robinson, Pierre M. Jean Beltran, Özgün Babur, Meagan E. Olive, Javad Golji, Eric Kuhn, Michael Burgess, Melanie A. MacMullan, Tomáš Rejtar, Karen Wang, DR Mani, Shankha Satpathy, Michael A. Gillette, William R. Sellers, Steven A. Carr

2021Molecular Systems Biology23 citationsDOIOpen Access PDF

Abstract

Reliable methods to quantify dynamic signaling changes across diverse pathways are needed to better understand the effects of disease and drug treatment in cells and tissues but are presently lacking. Here, we present SigPath, a targeted mass spectrometry (MS) assay that measures 284 phosphosites in 200 phosphoproteins of biological interest. SigPath probes a broad swath of signaling biology with high throughput and quantitative precision. We applied the assay to investigate changes in phospho-signaling in drug-treated cancer cell lines, breast cancer preclinical models, and human medulloblastoma tumors. In addition to validating previous findings, SigPath detected and quantified a large number of differentially regulated phosphosites newly associated with disease models and human tumors at baseline or with drug perturbation. Our results highlight the potential of SigPath to monitor phosphoproteomic signaling events and to nominate mechanistic hypotheses regarding oncogenesis, response, and resistance to therapy.

Topics & Concepts

BiologyComputational biologyPhosphoproteomicsSystems biologySignal transductionBiological pathwayDrug discoveryCarcinogenesisDrug resistanceBioinformaticsCancer researchCancerCell biologyPhosphorylationGeneticsProtein phosphorylationGeneProtein kinase AGene expressionAdvanced Proteomics Techniques and ApplicationsProtein Kinase Regulation and GTPase SignalingBioinformatics and Genomic Networks