INKA, an integrative data analysis pipeline for phosphoproteomic inference of active kinases. Issue 4 (12th April 2019)

• Record Type: Journal Article
• Authors: Beekhof, Robin; van Alphen, Carolien; Henneman, Alex A; Knol, Jaco C; Pham, Thang V; Rolfs, Frank; Labots, Mariette; Henneberry, Evan; Le Large, Tessa YS; de Haas, Richard R; Piersma, Sander R; Vurchio, Valentina; Bertotti, Andrea; Trusolino, Livio; Verheul, Henk MW; Jimenez, Connie R
• Is Part Of: Molecular systems biology. Volume 15:Issue 4(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-04-12
• Subjects: cancer -- computational tool -- drug selection -- kinase–substrate phosphorylation network -- single‐sample analysis; Molecular biology -- Periodicals; Systems biology -- Periodicals; 572.8
• DOI: 10.15252/msb.20188250
• Languages: English
• ISSNs: 1744-4292

Abstract

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. Synopsis: INKA (Integrative Inferred Kinase Activity) is an integrative data analysis approach ranking kinase activities in mass spectrometry‐based phosphoproteome data derived from single samples. INKA reveals oncogenes, differential kinase activity and drug targets. INKA combines kinase‐centric and substrate‐centric information and enables ranking kinase activities and visualizing kinase‐substrate networks in a single biological sample. INKA shows superior performance over its four components. INKA can be applied to both label‐free count and intensity data and was modified to accommodate labeling data. INKA can be used both for single‐sample and differential analysis and provides a versatile tool that can condense complex phosphoproteome data to actionable results. Abstract : INKA (Integrative Inferred Kinase Activity) is an integrative data analysis approach ranking kinase activities in mass spectrometry‐based phosphoproteome data derived from single samples. INKA reveals oncogenes, differential kinase activity and drug targets.