Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 781

The DOI matches its Crossref record; 241 of the 241 references it cites were found in a registry or an index.

Interleukins in cancer: from biology to therapy

Open access
Briukhovetska, Daria, Dörr, Janina, Endres, Stefan, Libby, Peter, Dinarello, Charles A., Kobold, Sebastian·2021·Nature Reviews Cancer

Abstract

Interleukins and associated cytokines serve as the means of communication for innate and adaptive immune cells as well as non-immune cells and tissues. Thus, interleukins have a critical role in cancer development, progression and control. Interleukins can nurture an environment enabling and favouring cancer growth while simultaneously being essential for a productive tumour-directed immune response. These properties of interleukins can be exploited to improve immunotherapies to promote effectiveness as well as to limit side effects. This Review aims to unravel some of these complex interactions. This Review provides an update of interleukins in tumour biology, covering the milestones of the latest discoveries of interleukin-related mechanisms in cancer, together with their application in clinical practice. It includes an overview of current clinical trials and breakthrough preclinical concepts.

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/s41568-021-00363-z

Cites

241 of 241 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 241 references

Cited by

See all 781

Metadata

Authors
Briukhovetska, D., Dörr, J., Endres, S., Libby, P., Dinarello, C. A., & Kobold, S.
Venue
Nature Reviews Cancer
Published
2021-06-03
Volume
21
Issue
8
Pages
481-499
ISSN
  • 1474-175X (ISSN-L)
  • 1474-1768
OpenAlex
W3165585845
Cited by
781
References
241
FWCI
19.30
Type
journal article
Language
en
Open access
bronze

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: Interleukins in cancer: from biology to therapy. https://app.cochat.ai/papers/10.1038/s41568-021-00363-z
The paper
Briukhovetska, D., Dörr, J., Endres, S., Libby, P., Dinarello, C. A., & Kobold, S. (2021). Interleukins in cancer: from biology to therapy. Nature Reviews Cancer. https://doi.org/10.1038/s41568-021-00363-z

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.