Dataset Information

INKA, an integrative data analysis pipeline for phosphoproteomic inference of active kinases.

ABSTRACT: Identifying hyperactive kinases in cancer is crucial for individualized treatment with specific inhibitors. Kinase activity can be discerned from global protein phosphorylation profiles obtained with mass spectrometry-based phosphoproteomics. A major challenge is to relate such profiles to specific hyperactive kinases fueling growth/progression of individual tumors. Hitherto, the focus has been on phosphorylation of either kinases or their substrates. Here, we combined label-free kinase-centric and substrate-centric information in an Integrative Inferred Kinase Activity (INKA) analysis. This multipronged, stringent analysis enables ranking of kinase activity and visualization of kinase-substrate networks in a single biological sample. To demonstrate utility, we analyzed (i) cancer cell lines with known oncogenes, (ii) cell lines in a differential setting (wild-type versus mutant, +/- drug), (iii) pre- and on-treatment tumor needle biopsies, (iv) cancer cell panel with available drug sensitivity data, and (v) patient-derived tumor xenografts with INKA-guided drug selection and testing. These analyses show superior performance of INKA over its components and substrate-based single-sample tool KARP, and underscore target potential of high-ranking kinases, encouraging further exploration of INKA's functional and clinical value.

SUBMITTER: Beekhof R

PROVIDER: S-EPMC6461034 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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INKA, an integrative data analysis pipeline for phosphoproteomic inference of active kinases.

Beekhof Robin R van Alphen Carolien C Henneman Alex A AA Knol Jaco C JC Pham Thang V TV Rolfs Frank F Labots Mariette M Henneberry Evan E Le Large Tessa Ys TY de Haas Richard R RR Piersma Sander R SR Vurchio Valentina V Bertotti Andrea A Trusolino Livio L Verheul Henk Mw HM Jimenez Connie R CR

Molecular systems biology 20190412 4

Identifying hyperactive kinases in cancer is crucial for individualized treatment with specific inhibitors. Kinase activity can be discerned from global protein phosphorylation profiles obtained with mass spectrometry-based phosphoproteomics. A major challenge is to relate such profiles to specific hyperactive kinases fueling growth/progression of <i>individual</i> tumors. Hitherto, the focus has been on phosphorylation of either kinases or their substrates. Here, we combined label-free kinase-c ...[more]

PMID: 30979792

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Project description:BackgroundA major goal in the discovery of cellular signaling networks is to identify regulated phosphorylation sites ("phosphosites") and map them to the responsible protein kinases. The V2 vasopressin receptor is a G-protein coupled receptor (GPCR) that is responsible for regulation of renal water excretion through control of aquaporin-2-mediated osmotic water transport in kidney collecting duct cells. Genome editing experiments have demonstrated that virtually all vasopressin-triggered phosphorylation changes are dependent on protein kinase A (PKA), but events downstream from PKA are still obscure.MethodsHere, we used: 1) Tandem mass tag-based quantitative phosphoproteomics to experimentally track phosphorylation changes over time in native collecting ducts isolated from rat kidneys; 2) a clustering algorithm to classify time course data based on abundance changes and the amino acid sequences surrounding the phosphosites; and 3) Bayes' Theorem to integrate the dynamic phosphorylation data with multiple prior "omic" data sets covering expression, subcellular location, known kinase activity, and characteristic surrounding sequences to identify a set of protein kinases that are regulated secondary to PKA activation.ResultsPhosphoproteomic studies revealed 185 phosphosites regulated by vasopressin over 15 min. The resulting groups from the cluster algorithm were integrated with Bayes' Theorem to produce corresponding ranked lists of kinases likely responsible for each group. The top kinases establish three PKA-dependent protein kinase modules whose regulation mediate the physiological effects of vasopressin at a cellular level. The three modules are 1) a pathway involving several Rho/Rac/Cdc42-dependent protein kinases that control actin cytoskeleton dynamics; 2) mitogen-activated protein kinase and cyclin-dependent kinase pathways that control cell proliferation; and 3) calcium/calmodulin-dependent signaling.ConclusionsOur findings identify a novel set of downstream small GTPase effectors and calcium/calmodulin-dependent kinases with potential roles in the regulation of water permeability through actin cytoskeleton rearrangement and aquaporin-2 trafficking. The proposed signaling network provides a stronger hypothesis for the kinases mediating V2 vasopressin receptor responses, encouraging future targeted examination via reductionist approaches. Furthermore, the Bayesian analysis described here provides a template for investigating signaling via other biological systems and GPCRs. Video abstract.

Dataset Information

INKA, an integrative data analysis pipeline for phosphoproteomic inference of active kinases.

Publications

INKA, an integrative data analysis pipeline for phosphoproteomic inference of active kinases.

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