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Cited by 717

The DOI matches its Crossref record; 192 of the 192 references it cites were found in a registry or an index.

Gasotransmitters in cancer: from pathophysiology to experimental therapy

Open access
Szabo, Csaba·2016·Nature Reviews Drug Discovery

Abstract

The three endogenous gaseous transmitters — nitric oxide (NO), carbon monoxide (CO) and hydrogen sulfide (H2S) — regulate a number of key biological functions. Emerging data have revealed several new mechanisms for each of these three gasotransmitters in tumour biology. It is now appreciated that they show bimodal pharmacological character in cancer, in that not only the inhibition of their biosynthesis but also elevation of their concentration beyond a certain threshold can exert anticancer effects. This Review discusses the role of each gasotransmitter in cancer and the effects of pharmacological agents — some of which are in early-stage clinical studies — that modulate the levels of each gasotransmitter. A clearer understanding of the pharmacological character of these three gases and the mechanisms underlying their biological effects is expected to guide further clinical translation.

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Crossref · 10.1038/nrd.2015.1

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Metadata

Authors
Szabo, C.
Venue
Nature Reviews Drug Discovery
Published
2015-12-18
Volume
15
Issue
3
Pages
185-203
ISSN
  • 1474-1776 (ISSN-L)
  • 1474-1784
OpenAlex
W2197175751
Cited by
717
References
192
FWCI
1.79
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Gasotransmitters in cancer: from pathophysiology to experimental therapy. https://app.cochat.ai/papers/10.1038/nrd.2015.1
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Szabo, C. (2016). Gasotransmitters in cancer: from pathophysiology to experimental therapy. Nature Reviews Drug Discovery. https://doi.org/10.1038/nrd.2015.1

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.