Evidence map›Paper›PMID 33193376›Full record

ArticleFrontiers in immunology2020

Method for the Analysis of the Tumor Microenvironment by Mass Cytometry: Application to Chronic Lymphocytic Leukemia.

Susanne Gonder, Iria Fernandez Botana, Marina Wierz, Giulia Pagano, Ernesto Gargiulo, Antonio Cosma, Etienne Moussay, Jerome Paggetti, Anne Largeot

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2020. 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
1.7field-weighted citation impact, top 15% 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, 20 citations in OpenAlex.

  1. Review
  2. Article
  3. Deciphering the aging process through single-cell cytometric technologies.Cytometry. Part A : the journal of the International Society for Analytical Cytology · 2024
    Review
  4. Article
  5. Article
  6. Review
  7. CyTOFFrontiers in immunology · 2022
    Review
  8. Article
  9. Review
  10. Article
  11. Article
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

9 authors at 2 institutions in 1 country.

Susanne GonderTumor Stroma Interactions, Department of Oncology, Luxembourg Institute of Health, Luxembourg, Luxembourg.
Iria Fernandez BotanaTumor Stroma Interactions, Department of Oncology, Luxembourg Institute of Health, Luxembourg, Luxembourg.
Marina WierzTumor Stroma Interactions, Department of Oncology, Luxembourg Institute of Health, Luxembourg, Luxembourg.
Giulia PaganoTumor Stroma Interactions, Department of Oncology, Luxembourg Institute of Health, Luxembourg, Luxembourg.
Ernesto GargiuloTumor Stroma Interactions, Department of Oncology, Luxembourg Institute of Health, Luxembourg, Luxembourg.
Antonio CosmaNational Cytometry Platform, Quantitative Biology Unit, Transversal Activities, Luxembourg Institute of Health, Luxembourg, Luxembourg.
Etienne MoussayTumor Stroma Interactions, Department of Oncology, Luxembourg Institute of Health, Luxembourg, Luxembourg.
Jerome PaggettiTumor Stroma Interactions, Department of Oncology, Luxembourg Institute of Health, Luxembourg, Luxembourg.
Anne LargeotTumor Stroma Interactions, Department of Oncology, Luxembourg Institute of Health, Luxembourg, Luxembourg.
Luxembourg Institute of Health · LUUniversity of Luxembourg · LU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the past 20 years, the interest for the tumor microenvironment (TME) has exponentially increased. Indeed, it is now commonly admitted that the TME plays a crucial role in cancer development, maintenance, immune escape and resistance to therapy. This stands true for hematological malignancies as well. A considerable amount of newly developed therapies are directed against the cancer-supporting TME instead of targeting tumor cells themselves. However, the TME is often not clearly defined. In addition, the unique phenotype of each tumor and the variability among patients limit the success of such therapies. Recently, our group took advantage of the mass cytometry technology to unveil the specific TME in the context of chronic lymphocytic leukemia (CLL) in mice. We found the enrichment of LAG3 and PD1, two immune checkpoints. We tested an antibody-based immunotherapy, targeting these two molecules. This combination of antibodies was successful in the treatment of murine CLL. In this methods article, we provide a detailed protocol for the staining of CLL TME cells aiming at their characterization using mass cytometry. We include panel design and validation, sample preparation and acquisition, machine set-up, quality control, and analysis. Additionally, we discuss different advantages and pitfalls of this technique.

Indexed as

Flow CytometryTumor MicroenvironmentAnimalsAntigens, CDBiomarkers, TumorImmune Checkpoint InhibitorsImmunotherapyLeukemia, Lymphocytic, Chronic, B-CellLymphocyte Activation Gene 3 ProteinMiceProgrammed Cell Death 1 ReceptorAntigens, CDBiomarkers, TumorImmune Checkpoint InhibitorsLag3 protein, mouseLymphocyte Activation Gene 3 ProteinPdcd1 protein, mouseProgrammed Cell Death 1 Receptorchronic lymphocytic leukemiaimmunosuppressionlymphomamass cytometrymicroenvironment

Identifiers

PMID33193376
PMCPMC7606286
OpenAlexW3094159156

What Socratic 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 Socratic graph.