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

Robin Beekhof, Carolien van Alphen, Alex A. Henneman, Jaco C. Knol, Thang V. Pham, Frank Rolfs, Mariette Labots, Evan Henneberry, Tessa Ys le Large, Richard R. de Haas, Sander R. Piersma, Valentina Vurchio, Andrea Bertotti, Livio Trusolino, Henk Mw Verheul, Connie R. Jimenez

Research output: Contribution to journalArticleAcademicpeer-review

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.
Original languageEnglish
Pages (from-to)e8250
JournalMolecular Systems Biology
Volume15
Issue number4
DOIs
Publication statusPublished - 2019

Cite this

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. / INKA, an integrative data analysis pipeline for phosphoproteomic inference of active kinases. In: Molecular Systems Biology. 2019 ; Vol. 15, No. 4. pp. e8250.
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title = "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.",
author = "Robin Beekhof and {van Alphen}, Carolien and Henneman, {Alex A.} and Knol, {Jaco C.} and Pham, {Thang V.} and Frank Rolfs and Mariette Labots and Evan Henneberry and {le Large}, {Tessa Ys} and {de Haas}, {Richard R.} and Piersma, {Sander R.} and Valentina Vurchio and Andrea Bertotti and Livio Trusolino and Verheul, {Henk Mw} and Jimenez, {Connie R.}",
year = "2019",
doi = "10.15252/msb.20188250",
language = "English",
volume = "15",
pages = "e8250",
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Beekhof, R, van Alphen, C, Henneman, AA, Knol, JC, Pham, TV, Rolfs, F, Labots, M, Henneberry, E, le Large, TY, de Haas, RR, Piersma, SR, Vurchio, V, Bertotti, A, Trusolino, L, Verheul, HM & Jimenez, CR 2019, 'INKA, an integrative data analysis pipeline for phosphoproteomic inference of active kinases' Molecular Systems Biology, vol. 15, no. 4, pp. e8250. https://doi.org/10.15252/msb.20188250

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

In: Molecular Systems Biology, Vol. 15, No. 4, 2019, p. e8250.

Research output: Contribution to journalArticleAcademicpeer-review

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T1 - INKA, an integrative data analysis pipeline for phosphoproteomic inference of active kinases

AU - Beekhof, Robin

AU - van Alphen, Carolien

AU - Henneman, Alex A.

AU - Knol, Jaco C.

AU - Pham, Thang V.

AU - Rolfs, Frank

AU - Labots, Mariette

AU - Henneberry, Evan

AU - le Large, Tessa Ys

AU - de Haas, Richard R.

AU - Piersma, Sander R.

AU - Vurchio, Valentina

AU - Bertotti, Andrea

AU - Trusolino, Livio

AU - Verheul, Henk Mw

AU - Jimenez, Connie R.

PY - 2019

Y1 - 2019

N2 - 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.

AB - 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.

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UR - https://www.ncbi.nlm.nih.gov/pubmed/30979792

U2 - 10.15252/msb.20188250

DO - 10.15252/msb.20188250

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