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Perturbation-response genes reveal signaling footprints in cancer gene expression

Author

Listed:
  • Michael Schubert

    (Wellcome Genome Campus)

  • Bertram Klinger

    (Charité Universitätsmedizin Berlin
    Humboldt University Berlin)

  • Martina Klünemann

    (Charité Universitätsmedizin Berlin
    Humboldt University Berlin)

  • Anja Sieber

    (Charité Universitätsmedizin Berlin
    Humboldt University Berlin)

  • Florian Uhlitz

    (Charité Universitätsmedizin Berlin
    Humboldt University Berlin)

  • Sascha Sauer

    (Berlin Institute for Medical Systems Biology/Berlin Institute of Health)

  • Mathew J. Garnett

    (Wellcome Genome Campus)

  • Nils Blüthgen

    (Charité Universitätsmedizin Berlin
    Humboldt University Berlin)

  • Julio Saez-Rodriguez

    (Wellcome Genome Campus
    RWTH Aachen University, Faculty of Medicine, Joint Research Centre for Computational Biomedicine)

Abstract

Aberrant cell signaling can cause cancer and other diseases and is a focal point of drug research. A common approach is to infer signaling activity of pathways from gene expression. However, mapping gene expression to pathway components disregards the effect of post-translational modifications, and downstream signatures represent very specific experimental conditions. Here we present PROGENy, a method that overcomes both limitations by leveraging a large compendium of publicly available perturbation experiments to yield a common core of Pathway RespOnsive GENes. Unlike pathway mapping methods, PROGENy can (i) recover the effect of known driver mutations, (ii) provide or improve strong markers for drug indications, and (iii) distinguish between oncogenic and tumor suppressor pathways for patient survival. Collectively, these results show that PROGENy accurately infers pathway activity from gene expression in a wide range of conditions.

Suggested Citation

  • Michael Schubert & Bertram Klinger & Martina Klünemann & Anja Sieber & Florian Uhlitz & Sascha Sauer & Mathew J. Garnett & Nils Blüthgen & Julio Saez-Rodriguez, 2018. "Perturbation-response genes reveal signaling footprints in cancer gene expression," Nature Communications, Nature, vol. 9(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-017-02391-6
    DOI: 10.1038/s41467-017-02391-6
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    7. L. Mathur & B. Szalai & N. H. Du & R. Utharala & M. Ballinger & J. J. M. Landry & M. Ryckelynck & V. Benes & J. Saez-Rodriguez & C. A. Merten, 2022. "Combi-seq for multiplexed transcriptome-based profiling of drug combinations using deterministic barcoding in single-cell droplets," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    8. Erick Armingol & Hratch M. Baghdassarian & Cameron Martino & Araceli Perez-Lopez & Caitlin Aamodt & Rob Knight & Nathan E. Lewis, 2022. "Context-aware deconvolution of cell–cell communication with Tensor-cell2cell," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
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    10. Yoshiharu Muto & Eryn E. Dixon & Yasuhiro Yoshimura & Haojia Wu & Kohei Omachi & Nicolas Ledru & Parker C. Wilson & Andrew J. King & N. Eric Olson & Marvin G. Gunawan & Jay J. Kuo & Jennifer H. Cox & , 2022. "Defining cellular complexity in human autosomal dominant polycystic kidney disease by multimodal single cell analysis," Nature Communications, Nature, vol. 13(1), pages 1-19, December.
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