Evidence map›Paper›PMID 34849469›Full record

ArticleiScience2021

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

Open access · goldAbstract read
In one paragraph

Article in iScience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
0.3field-weighted citation impact, top 49% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 17 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 5 institutions in 1 country.

Lucia Suarez-LopezDepartment of Cancer Biology, Dana Farber Cancer Institute, Boston, MA 02215, USA.
Bing ShuiDepartment of Cancer Biology, Dana Farber Cancer Institute, Boston, MA 02215, USA.
Douglas K BrubakerDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Marza HillDepartment of Cancer Biology, Dana Farber Cancer Institute, Boston, MA 02215, USA.
Alexander BergendorfWeldon School of Biomedical Engineering, Purdue University, West Lafayette, IN 47906, USA.
Paul S ChangelianAclaris Therapeutics, Inc., 4320 Forest Park Avenue, St. Louis, MO 63108, USA.
Aisha LagunaDepartment of Cancer Biology, Dana Farber Cancer Institute, Boston, MA 02215, USA.
Alina StarchenkoDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Douglas A LauffenburgerDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Kevin M HaigisDepartment of Cancer Biology, Dana Farber Cancer Institute, Boston, MA 02215, USA.
Brigham and Women's Hospital · USDana-Farber Cancer Institute · USMassachusetts Institute of Technology · USPurdue University West Lafayette · USAclaris Therapeutics (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Computational bioinformaticsImmunologySystems biologyTranscriptomics

Identifiers

PMID34849469
PMCPMC8609096
OpenAlexW3212138897

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.