Evidence map›Paper›PMID 33023656›Full record

ArticleGenome medicine2020

The murine Microenvironment Cell Population counter method to estimate abundance of tissue-infiltrating immune and stromal cell populations in murine samples using gene expression.

Florent Petitprez, Sacha Levy, Cheng-Ming Sun, Maxime Meylan, Christophe Linhard, Etienne Becht, Nabila Elarouci, David Tavel, Lubka T Roumenina, Mira Ayadi and 3 more

Abstract read
In one paragraph

Article in Genome medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 95 papers.

0numbers the graph read from it
0cells of the map it votes in
95citing papers in PubMed
–field-weighted citation impact
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

95 citing papers in PubMed.

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  19. The Myeloid BiomarkerInternational journal of molecular sciences · 2025
    Article
  20. Article

35 more citing papers are in PubMed but not listed here.

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

13 authors.

Florent PetitprezCentre de Recherche des Cordeliers, INSERM, Sorbonne Université, Université de Paris, Team Inflammation, Complement and Cancer, F-75006, Paris, France. florent.petitprez@ligue-cancer.net.ORCID 0000-0002-5117-6466
Sacha LevyCentre de Recherche des Cordeliers, INSERM, Sorbonne Université, Université de Paris, Team Inflammation, Complement and Cancer, F-75006, Paris, France.
Cheng-Ming SunCentre de Recherche des Cordeliers, INSERM, Sorbonne Université, Université de Paris, Team Inflammation, Complement and Cancer, F-75006, Paris, France.
Maxime MeylanCentre de Recherche des Cordeliers, INSERM, Sorbonne Université, Université de Paris, Team Inflammation, Complement and Cancer, F-75006, Paris, France.
Christophe LinhardCentre de Recherche des Cordeliers, INSERM, Sorbonne Université, Université de Paris, Team Inflammation, Complement and Cancer, F-75006, Paris, France.
Etienne BechtFred Hutchinson Cancer Research Center, Seattle, WA, USA.
Nabila ElarouciProgramme Cartes d'Identité des Tumeurs, Ligue Nationale contre le Cancer, F-75013, Paris, France.
David TavelProgramme Cartes d'Identité des Tumeurs, Ligue Nationale contre le Cancer, F-75013, Paris, France.
Lubka T RoumeninaCentre de Recherche des Cordeliers, INSERM, Sorbonne Université, Université de Paris, Team Inflammation, Complement and Cancer, F-75006, Paris, France.
Mira AyadiProgramme Cartes d'Identité des Tumeurs, Ligue Nationale contre le Cancer, F-75013, Paris, France.
Catherine Sautès-FridmanCentre de Recherche des Cordeliers, INSERM, Sorbonne Université, Université de Paris, Team Inflammation, Complement and Cancer, F-75006, Paris, France.
Wolf H FridmanCentre de Recherche des Cordeliers, INSERM, Sorbonne Université, Université de Paris, Team Inflammation, Complement and Cancer, F-75006, Paris, France.
Aurélien de ReynièsProgramme Cartes d'Identité des Tumeurs, Ligue Nationale contre le Cancer, F-75013, Paris, France. reyniesa@ligue-cancer.net.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Quantifying tissue-infiltrating immune and stromal cells provides clinically relevant information for various diseases. While numerous methods can quantify immune or stromal cells in human tissue samples from transcriptomic data, few are available for mouse studies. We introduce murine Microenvironment Cell Population counter (mMCP-counter), a method based on highly specific transcriptomic markers that accurately quantify 16 immune and stromal murine cell populations. We validated mMCP-counter with flow cytometry data and showed that mMCP-counter outperforms existing methods. We showed that mMCP-counter scores are predictive of response to immune checkpoint blockade in cancer mouse models and identify early immune impacts of Alzheimer's disease.

Indexed as

TranscriptomeAlzheimer DiseaseAnimalsBiomarkersCellular MicroenvironmentComputational BiologyDatabases, GeneticFemaleGene Expression ProfilingHigh-Throughput Nucleotide SequencingImmune Checkpoint InhibitorsImmune Checkpoint ProteinsLeukocytesMiceROC CurveSingle-Cell AnalysisBiomarkersImmune Checkpoint InhibitorsImmune Checkpoint ProteinsAlzheimer’s diseaseHeterogeneous tissueImmune checkpoint blockadeImmune compositionTumor microenvironment

Identifiers

PMID33023656
PMCPMC7541325

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.