Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 1,767

The DOI matches its Crossref record; 173 of the 173 references it cites were found in a registry or an index.

Myeloid-derived suppressor cells coming of age

Open access
Veglia, Filippo, Perego, Michela, Gabrilovich, Dmitry·2018·Nature Immunology

Abstract

Myeloid-derived suppressor cells (MDSCs) are a heterogeneous population of cells generated during a large array of pathologic conditions ranging from cancer to obesity. These cells represent a pathologic state of activation of monocytes and relatively immature neutrophils. MDSCs are characterized by a distinct set of genomic and biochemical features, and can, on the basis of recent findings, be distinguished by specific surface molecules. The salient feature of these cells is their ability to inhibit T cell function and thus contribute to the pathogenesis of various diseases. In this Review, we discuss the origin and nature of these cells; their distinctive features; and their biological roles in cancer, infectious diseases, autoimmunity, obesity and pregnancy. Gabrilovich and colleagues review the origin and nature of myeloid-derived suppressor cells, as well as their distinctive features and biological roles in cancer, infectious diseases, autoimmunity, obesity and pregnancy.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1038/s41590-017-0022-x

Cites

173 of 173 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 173 references

Cited by

See all 1,767

Metadata

Authors
Veglia, F., Perego, M., & Gabrilovich, D.
Venue
Nature Immunology
Published
2018-01-18
Volume
19
Issue
2
Pages
108-119
ISSN
  • 1529-2908 (ISSN-L)
  • 1529-2916
OpenAlex
W2782485041
Cited by
1,767
References
173
FWCI
69.85
Type
journal article
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Myeloid-derived suppressor cells coming of age. https://app.cochat.ai/papers/10.1038/s41590-017-0022-x
The paper
Veglia, F., Perego, M., & Gabrilovich, D. (2018). Myeloid-derived suppressor cells coming of age. Nature Immunology. https://doi.org/10.1038/s41590-017-0022-x

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.