Although most lung cancers are a result of smoking, approximately 25% of lung cancer cases worldwide are not attributable to tobacco use, accounting for over 300,000 deaths each year. Striking differences in the epidemiological, clinical and molecular characteristics of lung cancers arising in never smokers versus smokers have been identified, suggesting that they are separate entities. This Review summarizes our current knowledge of this unique and poorly understood disease.

Lung cancer in never smokers — a different disease

Previous studies have suggested that the frequency of chromosomal aberrations (CAs), but not of sister chromatid exchanges (SCEs), predicts cancer risk. We have further examined this relationship in European cohorts comprising altogether almost 22,000 subjects, in the framework of a European collaborative project (CancerRiskBiomarkers). The present paper gives an overview of some of the results of the project, especially as regards CAs and SCEs. The results confirm that a high level of CAs is associated with an increased risk of cancer and indicate that this association does not depend on the time between CA analysis and cancer detection, i.e., is obviously not explained by undetected cancer. The present evidence indicates that both chromatid-type and chromosome-type CAs predict cancer, even though some data suggest that chromosome-type CAs may have a more pronounced predictive value than chromatid-type CAs. CA frequency appears to predict cancers at various sites, although there seems to be a particular association with gastrointestinal cancers. SCE frequency does not appear to have cancer predictive value, at least partly due to uncontrollable technical variation. A number of genetic polymorphisms of xenobiotic metabolism, DNA repair, and folate metabolism affect the level of CAs and might collectively contribute to the cancer predictivity of CAs. Other factors that may influence the association between CAs and cancer include, e.g., exposure to genotoxic carcinogens and internal generation of genotoxic species. Although the association between CA level and cancer is seen at the group level, an association probably also exists for the individual, although it is not known if an individual approach could be feasible. However, group level evidence should be enough to support the use of CA analysis as a tool in screening programs and prevention policies in occupational and environmental health.

Chromosomal aberrations and SCEs as biomarkers of cancer risk

Lung cancer is the leading cause of cancer mortality worldwide. There have been only slight improvements in early diagnosis and survival, reflecting limited advances in screening and treatment for lung cancer. The identification of host differences in susceptibility to lung carcinogens, in particular to cigarette smoke, is essential in predicting who is at highest risk. Susceptibility differences in the form of rare, high-penetrance genes are suggested from studies of familial aggregation of lung cancer and a linkage study. Studies focused on more common, low-penetrance genes in the tobacco smoke metabolism pathways (phase I and phase II enzymes) and DNA repair pathways are reviewed, as are inflammation and cell cycle-related genes and DNA adducts as intermediate biomarkers. Also reviewed are studies of epigenetic mechanisms, such as methylation, as alternative sources of variation in host susceptibility. Studies of molecular epidemiology in lung cancer survival are discussed briefly. In the future, studies that focus on complex interactions between multiple genes and environmental exposures within pertinent pathways are needed. New technological advances in genotyping will help move the field forward.

/pdf/the-molecular-epidemiology-of-lung-cancer-4t5fjfwwkb.pdf

The molecular epidemiology of lung cancer

Lung cancer is predominantly associated with cigarette smoking; however, a substantial minority of patients with the disease have never smoked. In the US it is estimated there are 17,000-26,000 annual deaths from lung cancer in never smokers, which as a separate entity would be the seventh leading cause of cancer mortality. Controversy surrounds the question of whether or not the incidence of lung cancer in never-smokers is increasing, with more data to support this observation in Asia. There are several factors associated with an increased risk of developing lung cancer in never smokers including second hand smoke, indoor air pollution, occupational exposures, and genetic susceptibility among others. Adenocarcinoma is the most common histology of lung cancer in never smokers and in comparison to lung cancer in smokers appears less complex with a higher likelihood to have targetable driver mutations.

Lung Cancer in Never Smokers

Cytochrome P450 (CYP) enzymes, involved in metabolism of tobacco carcinogens, are also involved in estrogen metabolism and many are regulated by estrogens. These genes may thus be of relevance to gender-specific differences in lung cancer risk, particularly in early-onset lung cancer, where a high proportion of women is observed. We conducted a case-control study to investigate genetic polymorphisms in cytochromes that might modify the risk of developing early-onset lung cancer. In total, 638 Caucasian patients under the age of 51 with primary lung cancer and 1300 cancer-free control individuals, matched by age and sex, were included in this analysis. Thirteen polymorphisms in the CYP1A1, CYP1B1, CYP2A13, CYP3A4 and CYP3A5 genes were analyzed. No significant association was found for any of the analyzed polymorphisms and lung cancer risk overall. However, among women, a significantly increased risk of early-onset lung cancer was observed for carriers of the minor allele of CYP1B1 SNP rs1056836 [odds ratio (OR) 1.97; 95% confidence interval (CI) 1.32-2.94; P < 0.001]. Also, a non-significant increase in lung cancer risk was observed in the group of women carriers of the minor allele of CYP2A13 SNP rs1709084 (OR 1.64; 95% CI 1.00-2.70; P = 0.05). The effect of these two polymorphisms was shown to be modified by smoking. Haplotype analysis was performed for CYP1B1 and CYP2A13. No differences between cases and controls were observed for both genes (P = 0.63 and P = 0.42 for CYP1B1 and CYP2A13, respectively). Our results suggest that the CYP1B1 and the CYP2A13 genotypes may contribute to individual susceptibility to early-onset lung cancer in women.

CYP450 polymorphisms as risk factors for early-onset lung cancer: gender-specific differences

Background Since genetic factors may play an important role in lung cancer development at low dose carcinogen exposure, non-smokers are a good model to study genetic susceptibility and its interaction with environmental factors. Materials and methods We evaluated the role of the metabolic gene polymorphisms CYP1A1MspI, CYP1A1Ile462Val, GSTM1, and GSTT1 in non-smoker lung cancer patients from the International Collaborative Study on Genetic Susceptibility to Environmental Carcinogens (GSEC). Non-smokers (defined as subjects who never smoked on a regular basis) were selected from the GSEC database. We pooled the raw data from 21 case-control studies for a total of 2764 Caucasians (555 cases and 2209 controls) and 383 Asians (113 cases and 270 controls). Tests of heterogeneity and of inclusion bias were performed. Results A significant association between lung cancer and CYP1A1Ile462Val polymorphism was observed in Caucasians (adjusted OR = 2.04, 95% CI 1.17–3.54). GSTT1 deletion seems to be a risk factor for lung cancer in Caucasian non smokers only when the analysis was restricted to studies including healthy controls (adjusted OR = 1.66, 95% CI 1.12–2.46). A protective effect on lung cancer was observed with the combination of CYP1A1 wild type, GSTM1 null, and GSTT1 non-null genotypes. None of the analysed polymorphisms were associated with lung cancer in Asian non-smokers. Discussion Our analysis confirms previous findings that CYP1A1Ile462Val polymorphism may play a role in lung carcinogenesis in Caucasian non-smokers.

Metabolic gene polymorphisms and lung cancer risk in non-smokers. An update of the GSEC study.

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Andre Gsur

Author Tools

Chat about Author

Papers

Metabolic gene polymorphisms and lung cancer risk in non-smokers. An update of the GSEC study.