Cross-species transcriptomic signatures predict response to MK2 inhibition in mouse models of chronic inflammation

Lucia Suarez-Lopez; Bing Shui; Douglas K Brubaker; Marza Hill; Alexander Bergendorf; Paul S Changelian; Aisha Laguna; Alina Starchenko; Douglas A Lauffenburger; Kevin M Haigis

doi:10.1016/j.isci.2021.103406

Cross-species transcriptomic signatures predict response to MK2 inhibition in mouse models of chronic inflammation

iScience. 2021 Nov 7;24(12):103406. doi: 10.1016/j.isci.2021.103406. eCollection 2021 Dec 17.

Authors

Lucia Suarez-Lopez^{1

2}, Bing Shui^{1

2}, Douglas K Brubaker^{3

4

5}, Marza Hill¹, Alexander Bergendorf⁴, Paul S Changelian⁶, Aisha Laguna¹, Alina Starchenko³, Douglas A Lauffenburger³, Kevin M Haigis^{1

2}

Affiliations

¹ Department of Cancer Biology, Dana Farber Cancer Institute, Boston, MA 02215, USA.
² Department of Medicine, Brigham & Women's Hospital and Harvard Medical School, Boston, MA 02215, USA.
³ Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
⁴ Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN 47906, USA.
⁵ Regenstrief Center for Healthcare Engineering, Purdue University, West Lafayette, IN 47906, USA.
⁶ Aclaris Therapeutics, Inc., 4320 Forest Park Avenue, St. Louis, MO 63108, USA.

Abstract

Inflammatory bowel diseases (IBDs) are genetically complex and exhibit significant inter-patient heterogeneity in disease presentation and therapeutic response. Here, we show that mouse models of IBD exhibit variable responses to inhibition of MK2, a pro-inflammatory serine/threonine kinase, and that MK2 inhibition suppresses inflammation by targeting inflammatory monocytes and neutrophils in murine models. Using a computational approach (TransComp-R) that allows for cross-species comparison of transcriptomic features, we identified an IBD patient subgroup that is predicted to respond to MK2 inhibition, and an independent preclinical model of chronic intestinal inflammation predicted to be non-responsive, which we validated experimentally. Thus, cross-species mouse-human translation approaches can help to identify patient subpopulations in which to deploy new therapies.

Keywords: Computational bioinformatics; Immunology; Systems biology; Transcriptomics.