Evidence map›Paper›PMID 33526920›Full record

ReviewNature reviews. Immunology2021

Myeloid-derived suppressor cells in the era of increasing myeloid cell diversity.

Filippo Veglia, Emilio Sanseviero, Dmitry I Gabrilovich

Open access · bronzeAbstract readReview
In one paragraph

Review in Nature reviews. Immunology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1,226 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1,226citing papers in PubMed, 2 pooled it
100.8field-weighted citation impact, top 1% 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

1,226 citing papers in PubMed, 2 syntheses or guidelines pooled it, 1,724 citations in OpenAlex.

  1. Association between the systemic inflammation response index and prognosis in lung cancer: a systematic review and meta-analysis.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
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  18. Macrophage Trogocytosis of Tumor Cells Drives the Immunosuppression of Tumor Microenvironment.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
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1,166 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

3 authors at 3 institutions in 4 countries.

Filippo Veglia *H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.
Emilio Sanseviero *Wistar Institute, Philadelphia, PA, USA.
Dmitry I GabrilovichAstraZeneca, Gaithersburg, MD, USA. dmitry.gabrilovich@astrazeneca.com.ORCID http://orcid.org/0000-0001-9913-6407
AstraZeneca (Netherlands) · NLMoffitt Cancer Center · USThe Wistar Institute · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Myeloid-derived suppressor cells (MDSCs) are pathologically activated neutrophils and monocytes with potent immunosuppressive activity. They are implicated in the regulation of immune responses in many pathological conditions and are closely associated with poor clinical outcomes in cancer. Recent studies have indicated key distinctions between MDSCs and classical neutrophils and monocytes, and, in this Review, we discuss new data on the major genomic and metabolic characteristics of MDSCs. We explain how these characteristics shape MDSC function and could facilitate therapeutic targeting of these cells, particularly in cancer and in autoimmune diseases. Additionally, we briefly discuss emerging data on MDSC involvement in pregnancy, neonatal biology and COVID-19.

Indexed as

Autoimmune DiseasesCOVID-19CytokinesHumansMonocytesMyeloid CellsMyeloid-Derived Suppressor CellsNeoplasmsNeutrophilsSARS-CoV-2Cytokines

Identifiers

PMID33526920
PMCPMC7849958
OpenAlexW3127051356

What OpenQuestion holds

Textmetadata
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.