Evidence map›Paper›PMID 36741363›Full record

ArticleFrontiers in immunology2022

A 31-plex panel for high-dimensional single-cell analysis of murine preclinical models of solid tumors by imaging mass cytometry.

Yaël Glasson, Laure-Agnès Chépeaux, Anne-Sophie Dumé, Philippe Jay, Nelly Pirot, Nathalie Bonnefoy, Henri-Alexandre Michaud

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.2field-weighted citation impact, top 21% 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

6 citing papers in PubMed, 8 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

7 authors at 5 institutions in 1 country.

Yaël GlassonInstitut de Recherche en Cancérologie de Montpellier (IRCM), Univ Montpellier, Inserm, Institut régional du Cancer de Montpellier (ICM), Plateforme de Cytométrie et d'Imagerie de Masse, Montpellier, France.
Laure-Agnès ChépeauxInstitut de Recherche en Cancérologie de Montpellier (IRCM), Univ Montpellier, Inserm, Institut régional du Cancer de Montpellier (ICM), Plateforme de Cytométrie et d'Imagerie de Masse, Montpellier, France.
Anne-Sophie DuméInstitut de Recherche en Cancérologie de Montpellier (IRCM), Univ Montpellier, Inserm, Institut régional du Cancer de Montpellier (ICM), Plateforme de Cytométrie et d'Imagerie de Masse, Montpellier, France.
Philippe JayInstitut de Génomique Fonctionnelle (IGF), University of Montpellier, Centre national de la recherche scientifique (CNRS), Inserm, Montpellier, France.
Nelly PirotInstitut de Recherche en Cancérologie de Montpellier (IRCM), Univ Montpellier, Inserm, Institut régional du Cancer de Montpellier (ICM), Montpellier, France.
Nathalie BonnefoyInstitut de Recherche en Cancérologie de Montpellier (IRCM), Univ Montpellier, Inserm, Institut régional du Cancer de Montpellier (ICM), Plateforme de Cytométrie et d'Imagerie de Masse, Montpellier, France.
Henri-Alexandre MichaudInstitut de Recherche en Cancérologie de Montpellier (IRCM), Univ Montpellier, Inserm, Institut régional du Cancer de Montpellier (ICM), Plateforme de Cytométrie et d'Imagerie de Masse, Montpellier, France.
Institut de Recherche en Cancérologie de Montpellier · FRUniversité de Montpellier · FRCentre National de la Recherche Scientifique · FRHôpital Saint Eloi · FRInserm · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Currently, the study of resistance mechanisms and disease progression in cancer relies on the capacity to analyze tumors as a complex ecosystem of healthy and malignant cells. Therefore, one of the current challenges is to decipher the intra-tumor heterogeneity and especially the spatial distribution and interactions of the different cellular actors within the tumor. Preclinical mouse models are widely used to extend our understanding of the tumor microenvironment (TME). Such models are becoming more sophisticated and allow investigating questions that cannot be addressed in clinical studies. Indeed, besides studying the tumor cell interactions within their environment, mouse models allow evaluating the efficacy of new drugs and delivery approaches, treatment posology, and toxicity. Spatially resolved analyses of the intra-tumor heterogeneity require global approaches to identify and localize a large number of different cell types. For this purpose, imaging mass cytometry (IMC) is a major asset in the field of human immuno-oncology. However, the paucity of validated IMC panels to study TME in pre-clinical mouse models remains a critical obstacle to translational or basic research in oncology. Here, we validated a panel of 31 markers for studying at the single-cell level the TME and the immune landscape for discovering/characterizing cells with complex phenotypes and the interactions shaping the tumor ecosystem in mouse models.

Indexed as

EcosystemNeoplasmsAnimalsDisease Models, AnimalHumansImage CytometryMiceTumor Microenvironmentcellular networkhigh dimensional multiplexingImaging mass cytometryimmune signaturepreclinical mouse modeltumor microenvironment

Identifiers

PMID36741363
PMCPMC9893499
OpenAlexW4317425767

What OpenQuestion holds

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LicenceCC BY
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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.