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Cited by 480

The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.

Lung carcinogenesis by tobacco smoke

Open access
Hecht, Stephen S.·2012·International Journal of Cancer

Abstract

Cigarette smoke is a complex mixture of chemicals including multiple genotoxic lung carcinogens. The classic mechanisms of carcinogen metabolic activation to DNA adducts, leading to miscoding and mutations in critical growth control genes, applies to this mixture but some aspects are difficult to establish because of the complexity of the exposure. This article discusses certain features of this mechanism including the role of nicotine and its receptors; lung carcinogens, co‐carcinogens and related substances in cigarette smoke; structurally characterized DNA adducts in the lungs of smokers; the mutational consequences of DNA adduct formation in smokers' lungs; and biomarkers of nicotine and carcinogen uptake as related to lung cancer. While there are still uncertainties which may never be fully resolved, the general mechanisms by which cigarette smoking causes lung cancer are well understood and provide insights relevant to prevention of lung cancer, the number one cancer killer in the world, causing 1.37 million deaths per year.

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Metadata

Authors
Hecht, S. S.
Venue
International Journal of Cancer
Publisher
Wiley
Published
2012-10-03
Volume
131
Issue
12
Pages
2724-2732
ISSN
  • 0020-7136 (ISSN-L)
  • 1097-0215
OpenAlex
W2083832226
Cited by
480
References
8
FWCI
10.09
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Lung carcinogenesis by tobacco smoke. https://app.cochat.ai/papers/10.1002/ijc.27816
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Hecht, S. S. (2012). Lung carcinogenesis by tobacco smoke. International Journal of Cancer. https://doi.org/10.1002/ijc.27816

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.