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Transcription profiling of human lung adenocarcinoma and non-tumors from former, current and never smoking individuals

ABSTRACT: Tobacco smoking is responsible for over 90% of lung cancer cases, and yet the precise molecular alterations induced by smoking in lung that develop into cancer and impact survival have remained obscure. We performed gene expression analysis using HG-U133A Affymetrix chips on 135 fresh frozen tissue samples of adenocarcinoma and paired noninvolved lung tissue from current, former and never smokers, with biochemically validated smoking information. ANOVA analysis adjusted for potential confounders, multiple testing procedure, Gene Set Enrichment Analysis, and GO-functional classification were conducted for gene selection. Results were confirmed in independent adenocarcinoma and non-tumor tissues from two studies. We identified a gene expression signature characteristic of smoking that includes cell cycle genes, particularly those involved in the mitotic spindle formation (e.g., NEK2, TTK, PRC1). Expression of these genes strongly differentiated both smokers from non-smokers in lung tumors and early stage tumor tissue from non-tumor tissue (p<0.001 and fold-change>1.5, for each comparison), consistent with an important role for this pathway in lung carcinogenesis induced by smoking. These changes persisted many years after smoking cessation. NEK2 (p<0.001) and TTK (p=0.002) expression in the noninvolved lung tissue was also associated with a 3-fold increased risk of mortality from lung adenocarcinoma in smokers. Our work provides insight into the smoking-related mechanisms of lung neoplasia, and shows that the very mitotic genes known to be involved in cancer development are induced by smoking and affect survival. These genes are candidate targets for chemoprevention and treatment of lung cancer in smokers. Experiment Overall Design: Overall, 180 adenocarcinoma and non-tumor tissue samples were selected for the analyses, including duplicate or triplicate samples from 14 subjects for quality control. From the original 180 samples, 148 provided sufficient quantity of high-quality RNA for microarray analyses; 13 additional samples were excluded because of problematic assays. Normalization was conducted on the remaining 135 microarrays. After normalization, 13 samples were excluded because of low percentage of tumor cells in the tumor tissues. This report is based on 122 samples, of which 15 duplicates were averaged, resulting in 107 final expression values from 58 tumor and 49 non-tumor tissues from 20 never smokers, 26 former smokers, and 28 current smokers.

ORGANISM(S): Homo sapiens

SUBMITTER: Liu Huaitian

PROVIDER: S-ECPF-GEOD-10072 | biostudies-other |

REPOSITORIES: biostudies-other

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Project description:Tobacco smoking is responsible for over 90% of lung cancer cases, and yet the precise molecular alterations induced by smoking in lung that develop into cancer and impact survival have remained obscure. We performed gene expression analysis using HG-U133A Affymetrix chips on 135 fresh frozen tissue samples of adenocarcinoma and paired noninvolved lung tissue from current, former and never smokers, with biochemically validated smoking information. ANOVA analysis adjusted for potential confounders, multiple testing procedure, Gene Set Enrichment Analysis, and GO-functional classification were conducted for gene selection. Results were confirmed in independent adenocarcinoma and non-tumor tissues from two studies. We identified a gene expression signature characteristic of smoking that includes cell cycle genes, particularly those involved in the mitotic spindle formation (e.g., NEK2, TTK, PRC1). Expression of these genes strongly differentiated both smokers from non-smokers in lung tumors and early stage tumor tissue from non-tumor tissue (p<0.001 and fold-change>1.5, for each comparison), consistent with an important role for this pathway in lung carcinogenesis induced by smoking. These changes persisted many years after smoking cessation. NEK2 (p<0.001) and TTK (p=0.002) expression in the noninvolved lung tissue was also associated with a 3-fold increased risk of mortality from lung adenocarcinoma in smokers. Our work provides insight into the smoking-related mechanisms of lung neoplasia, and shows that the very mitotic genes known to be involved in cancer development are induced by smoking and affect survival. These genes are candidate targets for chemoprevention and treatment of lung cancer in smokers. Experiment Overall Design: Overall, 180 adenocarcinoma and non-tumor tissue samples were selected for the analyses, including duplicate or triplicate samples from 14 subjects for quality control. From the original 180 samples, 148 provided sufficient quantity of high-quality RNA for microarray analyses; 13 additional samples were excluded because of problematic assays. Normalization was conducted on the remaining 135 microarrays. After normalization, 13 samples were excluded because of low percentage of tumor cells in the tumor tissues. This report is based on 122 samples, of which 15 duplicates were averaged, resulting in 107 final expression values from 58 tumor and 49 non-tumor tissues from 20 never smokers, 26 former smokers, and 28 current smokers.

Project description:Background DNA methylation (DNAm) performs excellently in the discrimination of current and former smokers from never smokers, where AUCs > 0.9 are regularly reported using a single CpG site (cg05575921; AHRR). However, there is a paucity of DNAm models which attempt to distinguish current, former and never smokers as individual classes. Derivation of a robust DNAm model that accurately distinguishes between current, former and never smokers would be particularly valuable to epidemiological research (as a more accurate smoking definition vs. self-report) and could potentially translate to clinical settings. Therefore, we appraise 4 DNAm models of ternary smoking status (that is, current, former and never smokers): methylation at cg05575921 (AHRR model), weighted scores from 13 CpGs created by Maas et al. (Maas model), weighted scores from a LASSO model of candidate smoking CpGs from the literature (candidate CpG LASSO model), and weighted scores from a LASSO model supplied with genome-wide 450K data (agnostic LASSO model). Discrimination is assessed by AUC, whilst classification accuracy is assessed by accuracy and kappa, derived from confusion matrices. Results We find that DNAm can classify ternary smoking status with reasonable accuracy, including when applied to external data. Ternary classification using only DNAm far exceeds the classification accuracy of simply assigning all classes as the most prevalent class (63.7% vs. 36.4%). Further, we develop a DNAm classifier which performs well in discriminating current from former smokers (agnostic LASSO model AUC in external validation data: 0.744). Finally, across our DNAm models, we show evidence of enrichment for biological pathways and human phenotype ontologies relevant to smoking, such as haemostasis, molybdenum cofactor synthesis, body fatness and social behaviours, providing evidence of the generalisability of our classifiers. Conclusions Our findings suggest that DNAm can classify ternary smoking status with close to 65% accuracy. Both the ternary smoking status classifiers and current versus former smoking status classifiers address the present lack of former smoker classification in epigenetic literature; essential if DNAm classifiers are to adequately relate to real-world populations. To improve performance further, additional focus on improving discrimination of current from former smokers is necessary. Supplementary Information The online version contains supplementary material available at 10.1186/s13148-021-01191-6.

Project description:Although obesity has been directly linked to the development of many cancers, many epidemiological studies have found that body mass index (BMI)--a surrogate marker of obesity--is inversely associated with the risk of lung cancer. These studies are difficult to interpret because of potential confounding by cigarette smoking, a major risk factor for lung cancer that is associated with lower BMI.We prospectively examined the association between BMI and the risk of lung cancer among 448?732 men and women aged 50-71 years who were recruited during 1995-1996 for the National Institutes of Health-AARP Diet and Health Study. BMI was calculated based on the participant's self-reported height and weight on the baseline questionnaire. We identified 9437 incident lung carcinomas (including 415 in never smokers) during a mean follow-up of 9.7 years through 2006. Multivariable Cox proportional hazards regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) with adjustment for lung cancer risk factors, including smoking status. To address potential bias due to preexisting undiagnosed disease, we excluded potentially unhealthy participants in sensitivity analyses. All statistical tests were two-sided.The crude incidence rate of lung cancer over the study follow-up period was 233 per 100?000 person-years among men and 192 per 100?000 person-years among women. BMI was inversely associated with the risk of lung cancer among both men and women (BMI ?35 vs 22.5-24.99 kg/m(2): HR = 0.81, 95% CI = 0.70 to 0.94 and HR = 0.73, 95% CI = 0.61 to 0.87, respectively). The inverse association was restricted to current and former smokers and was stronger after adjustment for smoking. Among smokers, the inverse association persisted even after finely stratifying on smoking status, time since quitting smoking, and number of cigarettes smoked per day. Sensitivity analyses did not support the possibility that the inverse association was due to prevalent undiagnosed disease.Our results suggest that a higher BMI is associated with a reduced risk of lung cancer in current and former smokers. Our inability to attribute the inverse association between BMI and the risk of lung cancer to residual confounding by smoking or to bias suggests the need for considering other explanations.

Project description:Alcohol consumption among individuals who experience a flushing response (reddening of the face, nausea, dizziness, headache, anxiety, and increased heartbeat) can result in serious health problems. However, studies on reasons for drinking among flushers, especially in the college context, are limited. Thus, this study investigated the association between primary reason for drinking and alcohol use among a nationally representative sample of current, former, and never flushing college students. The aim was to measure whether college students with current or former experience of facial flushing have different primary reasons for drinking compared to students with no experience of facial flushing. We surveyed and analyzed the data of 4590 students in a nationally representative sample of 82 colleges in South Korea. Multiple regression analysis was used to identify the association between primary reason for drinking and alcohol intake. Alcohol intake was measured using the Alcohol Use Disorders Identification Test (AUDIT). Among 1537 current (33.5%), 152 former (3.3%), and 2901 (63.2%) never flushers, mean AUDIT scores were 7.715 ± 5.434, 11.039 ± 6.405, and 10.465 ± 5.779, respectively. Current flushers had significantly higher AUDIT scores when drinking for pleasure (β = 2.696, p < 0.0001) or stress/depression (β = 2.578, p < 0.0001). Primary reasons for drinking were not associated with alcohol intake for former flushers. Never flushers had significantly higher AUDIT scores when drinking for pleasure (β = 2.696, p < 0.0001), stress/depression (β = 2.578, p < 0.0001), or boredom (β = 0.740, p = 0.029) than peer pressure. Our results suggest that former and never flushers consume higher amounts of alcohol on average than never flushers. For current flushers, drinking for pleasure or stress/depression may increase alcohol intake, while for never flushers, drinking for pleasure, stress/depression, as well as boredom may have the same effect.

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Transcription profiling of human lung adenocarcinoma and non-tumors from former, current and never smoking individuals

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