Accelerated epigenetic age, inflammation, and gene expression in lung: comparisons of smokers and vapers with non-smokers

BACKGROUND

Cigarette smoking and aging are the main risk factors for pulmonary diseases, including cancer. Epigenetic aging may explain the relationship between smoking, electronic cigarette vaping, and pulmonary health. No study has examined smoking and vaping-related epigenetic aging in relation to lung biomarkers.

METHODS

Lung epigenetic aging measured by DNA methylation (mAge) and its acceleration (mAA) was assessed in young (age 21-30) electronic cigarette vapers (EC, n = 14, including 3 never-smoking EC), smokers (SM, n = 16), and non-EC/non-SM (NS, n = 39). We investigated relationships of mAge estimates with chronological age (Horvath-mAge), lifespan/mortality (Grim-mAge), telomere length (TL-mAge), smoking/EC history, urinary biomarkers, lung cytokines, and transcriptome.

RESULTS

Compared to NS, EC and SM had significantly older Grim-mAge, shorter TL-mAge, significantly accelerated Grim-mAge and decelerated TL-mAge. Among SM, Grim-mAA was associated with nicotine intake and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL). For EC, Horvath-mAA was significantly correlated with puffs per day. Overall, cytokines (IL-1β, IL-6, and IL-8) and 759 transcripts (651 unique genes) were significantly associated with Grim-mAA. Grim-mAA-associated genes were highly enriched in immune-related pathways and genes that play a role in the morphology and structures of cells/tissues.

CONCLUSIONS

Faster lung mAge for SM is consistent with prior studies of blood. Faster lung mAge for EC compared to NS indicates possible adverse pulmonary effects of EC on biological aging. Our findings support further research, particularly on epigenetic markers, on effects of smoking and vaping on pulmonary health. Given that most EC are former smokers, further study is needed to understand unique effects of electronic cigarettes on biological aging.

Untargeted Metabolomics and Body Mass in Adolescents: A Cross-Sectional and Longitudinal Analysis

Obesity in children and adolescents has increased globally. Increased body mass index (BMI) during adolescence carries significant long-term adverse health outcomes, including chronic diseases such as cardiovascular disease, stroke, diabetes, and cancer. Little is known about the metabolic consequences of changes in BMI in adolescents outside of typical clinical parameters. Here, we used untargeted metabolomics to assess changing BMI in male adolescents. Untargeted metabolomic profiling was performed on urine samples from 360 adolescents using UPLC-QTOF-MS. The study includes a baseline of 235 subjects in a discovery set and 125 subjects in a validation set. Of them, a follow-up of 81 subjects (1 year later) as a replication set was studied. Linear regression analysis models were used to estimate the associations of metabolic features with BMI z-score in the discovery and validation sets, after adjusting for age, race, and total energy intake (kcal) at false-discovery-rate correction (FDR) ≤ 0.1. We identified 221 and 16 significant metabolic features in the discovery and in the validation set, respectively. The metabolites associated with BMI z-score in validation sets are glycylproline, citrulline, 4-vinylsyringol, 3'-sialyllactose, estrone sulfate, carnosine, formiminoglutamic acid, 4-hydroxyproline, hydroxyprolyl-asparagine, 2-hexenoylcarnitine, L-glutamine, inosine, N-(2-Hydroxyphenyl) acetamide glucuronide, and galactosylhydroxylysine. Of those 16 features, 9 significant metabolic features were associated with a positive change in BMI in the replication set 1 year later. Histidine and arginine metabolism were the most affected metabolic pathways. Our findings suggest that obesity and its metabolic outcomes in the urine metabolome of children are linked to altered amino acids, lipid, and carbohydrate metabolism. These identified metabolites may serve as biomarkers and aid in the investigation of obesity's underlying pathological mechanisms. Whether these features are associated with the development of obesity, or a consequence of changing BMI, requires further study.

A Pilot Cross-Sectional Study of Immunological and Microbiome Profiling Reveals Distinct Inflammatory Profiles for Smokers, Electronic Cigarette Users, and Never-Smokers

Smokers (SM) have increased lung immune cell counts and inflammatory gene expression compared to electronic cigarette (EC) users and never-smokers (NS). The objective of this study is to further assess associations for SM and EC lung microbiomes with immune cell subtypes and inflammatory gene expression in samples obtained by bronchoscopy and bronchoalveolar lavage (n = 28). RNASeq with the CIBERSORT computational algorithm were used to determine immune cell subtypes, along with inflammatory gene expression and microbiome metatranscriptomics. Macrophage subtypes revealed a two-fold increase in M0 (undifferentiated) macrophages for SM and EC users relative to NS, with a concordant decrease in M2 (anti-inflammatory) macrophages. There were 68, 19, and 1 significantly differentially expressed inflammatory genes (DEG) between SM/NS, SM/EC users, and EC users/NS, respectively. CSF-1 and GATA3 expression correlated positively and inversely with M0 and M2 macrophages, respectively. Correlation profiling for DEG showed distinct lung profiles for each participant group. There were three bacteria genera-DEG correlations and three bacteria genera-macrophage subtype correlations. In this pilot study, SM and EC use were associated with an increase in undifferentiated M0 macrophages, but SM differed from EC users and NS for inflammatory gene expression. The data support the hypothesis that SM and EC have toxic lung effects influencing inflammatory responses, but this may not be via changes in the microbiome.

Lung mitochondrial DNA copy number, inflammatory biomarkers, gene transcription and gene methylation in vapers and smokers

BACKGROUND

Mitochondrial DNA copy number (mtCN) maintains cellular function and homeostasis, and is linked to nuclear DNA methylation and gene expression. Increased mtCN in the blood is associated with smoking and respiratory disease, but has received little attention for target organ effects for smoking or electronic cigarette (EC) use.

METHODS

Bronchoscopy biospecimens from healthy EC users, smokers (SM), and never-smokers (NS) were assessed for associations of mtCN with mtDNA point mutations, immune responses, nuclear DNA methylation and gene expression using linear regression. Ingenuity pathway analysis was used for enriched pathways. GEO and TCGA respiratory disease datasets were used to explore the involvement of mtCN-associated signatures.

FINDINGS

mtCN was higher in SM than NS, but EC was not statistically different from either. Overall there was a negative association of mtCN with a point mutation in the D-loop but no difference within groups. Positive associations of mtCN with IL-2 and IL-4 were found in EC only. mtCN was significantly associated with 71,487 CpGs and 321 transcripts. 263 CpGs were correlated with nearby transcripts for genes enriched in the immune system. EC-specific mtCN-associated-CpGs and genes were differentially expressed in respiratory diseases compared to controls, including genes involved in cellular movement, inflammation, metabolism, and airway hyperresponsiveness.

INTERPRETATION

Smoking may elicit a lung toxic effect through mtCN. While the impact of EC is less clear, EC-specific associations of mtCN with nuclear biomarkers suggest exposure may not be harmless. Further research is needed to understand the role of smoking and EC-related mtCN on lung disease risks.

FUNDING

The National Cancer Institute, the National Heart, Lung, and Blood Institute, the Food and Drug Administration Center for Tobacco Products, the National Center For Advancing Translational Sciences, and Pelotonia Intramural Research Funds.

Saliva and Lung Microbiome Associations with Electronic Cigarette Use and Smoking

The microbiome has increasingly been linked to cancer. Little is known about the lung and oral cavity microbiomes in smokers, and even less for electronic cigarette (EC) users, compared with never-smokers. In a cross-sectional study (n = 28) of smokers, EC users, and never-smokers, bronchoalveolar lavage and saliva samples underwent metatranscriptome profiling to examine associations with lung and oral microbiomes. Pairwise comparisons assessed differentially abundant bacteria species. Total bacterial load was similar between groups, with no differences in bacterial diversity across lung microbiomes. In lungs, 44 bacteria species differed significantly (FDR < 0.1) between smokers/never-smokers, with most decreased in smokers. Twelve species differed between smokers/EC users, all decreased in smokers of which Neisseria sp. KEM232 and Curvibacter sp. AEP1-3 were observed. Among the top five decreased species in both comparisons, Neisseria elongata, Neisseria sicca, and Haemophilus parainfluenzae were observed. In the oral microbiome, 152 species were differentially abundant for smokers/never-smokers, and 17 between smokers/electronic cigarette users, but only 21 species were differentially abundant in both the lung and oral cavity. EC use is not associated with changes in the lung microbiome compared with never-smokers, indicating EC toxicity does not affect microbiota. Statistically different bacteria in smokers compared with EC users and never-smokers were almost all decreased, potentially due to toxic effects of cigarette smoke. The low numbers of overlapping oral and lung microbes suggest that the oral microbiome is not a surrogate for analyzing smoking-related effects in the lung.

PREVENTION RELEVANCE

The microbiome affects cancer and other disease risk. The effects of e-cig usage on the lung microbiome are essentially unknown. Given the importance of lung microbiome dysbiosis populated by oral species which have been observed to drive lung cancer progression, it is important to study effects of e-cig use on microbiome.

Abstract 751: Lung mitochondrial DNA copy number variations: E-cig users, smokers, and never-smokers

Background: Electronic cigarettes (e-cigs) are one of the most popular tobacco products in the US. Little is known regarding their pulmonary effects. E-cigs induce similar oxidant reactivity as cigarette smoke and promote oxidative damage/inflammation in airway cells. Given that mtDNA is more prone to oxidative stress than nuclear DNA because of a less effective proofreading system, mtDNA alterations may be important indicators of e-cigs' toxic effects. Clinically, mitochondrial DNA alteration is an emerging biomarker of respiratory diseases.

Methods: We compared mtDNA copy number (mtDNA-CN) from lung brushings in a cross-sectional bronchoscopy study of healthy young adults, e-cig users (EC)(n=15), non-smokers, non-EC users (NS)(n=43), and smokers (SM)(n=26). We examined associations of mtDNA-CN with immune response (differential cell counts and cytokines in bronchoalveolar lavage), DNA methylation and gene expression brushings. Associations for: 1) EC vs NS vs SM, and 2) tobacco product users (EC+SM) vs NS for MtDNA-CN with immune response, methylation, and expression were made using linear regression. Further, significant features by group interactions were followed up by within-group tests. False Discovery Rate (FDR) at 0.1 was considered significant. Ingenuity pathway analysis was used to identify the most significantly enriched pathways/molecular functions/diseases.

Results: MtDNA-CN was not significantly different among the three groups (P=0.06). MtDNA-CN was higher in SM than NS (P=0.02), and in tobacco product users than NS (P=0.02); EC mtDNA-CN tended to be intermediate between the 2 other groups. There were significantly positive associations of IL-2 and IL-4 with mtDNA-CN in EC, but not in SM or NS (Interaction FDR=0.06 for both). We found 147 transcripts (60 genes) and 1,153 CpGs (713 genes) to be significantly associated with mtDNA-CN in all three groups. The most common canonical pathway of the signatures for both expression and methylation were immune responses. The top molecular and cellular functions for both included cell death and survival. Ten transcripts (LINC01184, SNU13, RPL35A, COLCA1, HLA-DRB1, LOC105379655, TRIM9, TCIRG1, CLPB, MIR2114) and 3,929 CpGs (top: ULK4, STARD13, HLCS, FLT1, TMEM91, CYP2J2) were associated with mtDNA-CN in E-cig users only. Some of these genes are known to play a role in lung diseases, including cancer. For the signatures associated in all groups, we found many more significant signatures (236 vs 147 transcripts and 40,830 vs 1,153 CpGs) in the two group vs. three group comparisons, respectively.

Conclusion: While the sample size was small, this study is the first to suggest that mtDNA-CN is a site of pulmonary toxic effects. We found associations of mtDNA-CN with inflammatory markers among EC users, and with a number of biological signatures, particularly genes related to immune response, in the lungs of EC, SM, and NS, but differently by groups for some.

Citation Format: Kellie M. Mori, Joseph P. McElroy, Daniel Y. Weng, Sangwoon Chung, Sarah A. Reisinger, Kevin L. Ying, Quentin A. Nickerson, Theodore M. Brasky, Mark D. Wewers, Jo L. Freudenheim, Peter G. Shields, Min-Ae Song. Lung mitochondrial DNA copy number variations: E-cig users, smokers, and never-smokers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 751.

Lipid laden macrophages and electronic cigarettes in healthy adults

Background

An outbreak of E-cigarette or Vaping Product Use-Associated Lung Injury (EVALI) with significant morbidity and mortality was reported in 2019. While most patients with EVALI report vaping tetrahydrocannabinol (THC) oils contaminated with vitamin E acetate, a subset report only vaping with nicotine-containing electronic cigarettes (e-cigs). Whether or not e-cigs cause EVALI, the outbreak highlights the need for identifying long term health effects of e-cigs. EVALI pathology includes alveolar damage, pneumonitis and/or organizing pneumonia, often with lipid-laden macrophages (LLM). We assessed LLM in the lungs of healthy smokers, e-cig users, and never-smokers as a potential marker of e-cig toxicity and EVALI.

Methods

A cross-sectional study using bronchoscopy was conducted in healthy smokers, e-cig users, and never-smokers (n = 64). LLM, inflammatory cell counts, and cytokines were determined in bronchial alveolar fluids (BAL). E-cig users included both never-smokers and former light smokers.

Findings

High LLM was found in the lungs of almost all smokers and half of the e-cig users, but not those of never-smokers. LLM were not related to THC exposure or smoking history. LLM were significantly associated with inflammatory cytokines IL-4 and IL-10 in e-cig users, but not smoking-related cytokines.

Interpretation

This is the first report of lung LLM comparing apparently healthy smokers, e-cig users, and never-smokers. LLM are not a specific marker for EVALI given the frequent positivity in smokers; whether LLMs are a marker of lung inflammation in some e-cig users requires further study.

Funding

The National Cancer Institute, the National Heart, Lung, and Blood Institute, the Food and Drug Administration Center for Tobacco Products, the National Center For Advancing Translational Sciences, and Pelotonia Intramural Research Funds

Abstract 1163: Lung and salivary microbiome in electronic cigarette users, never-smokers, and smokers: A pilot cross-sectional study

Background: Little is known about the microbiomes of the lung and oral cavity with electronic cigarette (e-cig) use and how they compare to those of smokers and never-smokers. E-cigs have been promoted as a safe alternative to smoking cigarettes. Given the recent outbreak of E-cigarette or Vaping product use Associated Lung Injury (EVALI) there is an urgent need for understanding the biological effects of e-cig use on the lung and oral cavity, including effects on the microbiome. Previous studies have been limited to 16S-rRNA sequencing which were used to detect bacteria genera. In this study, we used metatranscriptome profiling to study differentially abundant bacteria species in the oral and lung microbiome of never-smokers, smokers, and e-cig users.

Methods: A cross-sectional study of 10 never-smokers, 8 cigarette smokers, and 10 e-cig users was conducted, with saliva and bronchoalveolar lavage (BAL) collected for each study participant. RNA was extracted from saliva and BAL samples for total transcriptome RNA-seq analysis. Sequences were aligned with bowtie2 v.2.2.8 to the human genome (hg19) and non-aligned reads were aligned and annotated using NCBI metagenomes database and Kraken v.1. Differences in the microbiome by smoking status were determined by pairwise comparisons using limma-voom with FDR q-value cutoffs &lt;0.2.

Results: The distribution of richness and evenness of bacterial communities measured by Shannon diversity in our metatranscriptome data did not significantly differ between the three smoking status groups. When comparing levels of bacteria species between groups in the saliva, 234 were differentially abundant between smokers and never-smokers, and 39 were differentially abundant between smokers and e-cig users. In the lung, 87 bacterial species were differentially abundant between smokers and never-smokers and 36 were differentially abundant between smokers and e-cig users. Notably, no bacteria species were differentially abundant when comparing e-cig users and never-smokers in both the saliva and lung samples. There are 50 bacterial species found to be differentially abundant in both the lung and saliva samples, 47 of which are decreased in smokers. These 47 bacteria species included common commensal oral microbiome species such as Haemophilus parainfluenzae, Capnocytophaga gingivalis and Neisseria species. The 3 species that were increased in smokers were Lactobacillus species.

Conclusion: Our findings suggests that smoking cigarettes may alter populations of common commensal species in both the oral and lung microbiome. The lack of differentially abundant bacterial species between electronic cigarette users and never-smokers indicates that e-cigs may alter bacterial species to a lesser extent than smoking.

Citation Format: Kevin L. Ying, Min-Ae Song, Daniel Y. Weng, Quentin A. Nickerson, Joseph P. McElory, Theodore M. Brasky, Noah B. Whiteman, Mark D. Wewers, Jo L. Freudenheim, Ewy A. Mathé, Peter G. Shields. Lung and salivary microbiome in electronic cigarette users, never-smokers, and smokers: A pilot cross-sectional study [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1163.

Abstract LB-159: The association of alveolar lipid laden macrophages with inflammatory cytokines in electronic cigarette users

Introduction: Lipid laden macrophages (LLM) from lung bronchoscopies have been identified as characteristic for some patients with e-cigarette (e-cig) or vaping product use associated lung injury (EVALI). While vaping with THC oils containing vitamin E acetate is thought to have caused the outbreak, there is a subset of the EVALI cases who reported vaping only with nicotine-containing e-cigs. A recent animal study showed that propylene glycol (PG) and vegetable glycerin altered lipid homeostasis and induced LLM. In addition to the associations with EVALI, understanding the health effects of vaping with e-cigs in general needs additional investigation. Objective: We examined alterations in alveolar lipid homeostasis comparing e-cig users to cigarette smokers and never-smokers. Further, we determined the association of LLM with inflammatory cytokines. Methods: LLMs, inflammatory cell counts, and cytokines were determined in bronchial alveolar fluids (BAL) from a cross-sectional study of 62 volunteer subjects, age 21-45. Participants who were e-cig users were either never-smokers or former smokers. Cigarette smoking and e-cig use were confirmed by biomarkers of exposure, including lung and urine cotinine and 3-hydroxycotinine and urine anatabine, nicotelline, and PG. Results: High LLM counts were found in the lungs of almost all smokers and about half of the e-cig users, but not in any never-smokers (P&lt;0.001). LLMs were significantly correlated with the inflammatory cytokines IL-4 and IL-10 in e-cig users (P=0.01). Smoking history, including cigarettes per day and biomarkers of exposure, e-cig use history, and gender were not associated with LLMs (all P&gt;0.05). LLMs were not related to THC exposure. Discussion: This is the first report comparing LLMs in the lungs of e-cig users with smokers and never-smokers. LLMs were found in lungs of both smokers and a portion of e-cig users. Given their presence among smokers, they are not likely to be useful as a marker identifying those with EVALI. However, LLMs may be one of the markers for specific disease risks associated with e-cig usage, but not smoking.

Citation Format: Min-Ae Song, Peter G. Shields, Jo L. Freudenheim, Theodore M. Brasky, Joseph P. McElroy, Joseph P. McElroy, Sarah A. Reisinger, Daniel Y. Weng, Rongqin Ren, Thomas Eissenberg, Mark D. Wewers, Konstantin Shilo. The association of alveolar lipid laden macrophages with inflammatory cytokines in electronic cigarette users [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr LB-159.

Abstract A34: Lung and salivary microbiome in electronic cigarette users, never-smokers, and smokers: A pilot cross-sectional study

Background: Little is known about the microbiomes of the lung and oral cavity with electronic cigarette (e-cig) use and how they compare to those of smokers and never-smokers. E-cigs have been promoted as a safe alternative to smoking cigarettes. Given the recent outbreak of E-cigarette or Vaping product use Associated Lung Injury (EVALI), there is an urgent need for understanding the biologic effects of e-cig use on the lung and oral cavity, including effects on the microbiome. Previous studies have been limited to 16S-rRNA sequencing, which was used to detect bacteria genera. In this study, we used metatranscriptome profiling to study differentially abundant bacteria species in the oral and lung microbiome of never-smokers, smokers, and e-cig users.

Methods: A cross-sectional study of 10 never-smokers, 8 cigarette smokers, and 10 e-cig users was conducted, with saliva and bronchoalveolar lavage (BAL) collected for each study participant. RNA was extracted from saliva and BAL samples for total transcriptome RNA-seq analysis. Sequences were aligned with bowtie2 v.2.2.8 to the human genome (hg19) and nonaligned reads were aligned and annotated using NCBI metagenomes database and Kraken v.1. Differences in the microbiome by smoking status were determined by pairwise comparisons using limma-voom with FDR q-value cutoffs &lt;0.2.

Results: The distribution of richness and evenness of bacterial communities measured by Shannon diversity in our metatranscriptome data did not significantly differ between the three smoking status groups. When comparing levels of bacteria species between groups in the saliva, 234 were differentially abundant between smokers and never-smokers, and 39 were differentially abundant between smokers and e-cig users. In the lung, 87 bacterial species were differentially abundant between smokers and never-smokers and 36 were differentially abundant between smokers and e-cig users. Notably, no bacteria species were differentially abundant when comparing e-cig users and never-smokers in both the saliva and lung samples. There are 50 bacterial species found to be differentially abundant in both the lung and saliva samples, 47 of which are decreased in smokers. These 47 bacteria species included common commensal oral microbiome species such as Haemophilus parainfluenzae, Capnocytophaga gingivalis, and Neisseria species. The 3 species that were increased in smokers were Lactobacillus species.

Conclusion: Our findings suggests that smoking cigarettes may alter populations of common commensal species in both the oral and lung microbiome. The lack of differentially abundant bacterial species between electronic cigarette users and never-smokers indicates that e-cigs may alter bacterial species to a lesser extent than smoking.

Citation Format: Kevin L. Ying, Min-Ae Song, Daniel Y. Weng, Quentin A. Nickerson, Joseph P. McElroy, Theodore M. Brasky, Noah B. Whiteman, Mark D. Wewers, Jo L. Freudenheim, Ewy A. Mathe, Peter G. Shields. Lung and salivary microbiome in electronic cigarette users, never-smokers, and smokers: A pilot cross-sectional study [abstract]. In: Proceedings of the AACR Special Conference on the Microbiome, Viruses, and Cancer; 2020 Feb 21-24; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2020;80(8 Suppl):Abstract nr A34.

Biomarkers of Exposure and Effect in the Lungs of Smokers, Nonsmokers, and Electronic Cigarette Users

BACKGROUND

Nicotine-containing electronic cigarette (e-cig) use has become widespread. However, understanding the biological impact of e-cigs compared with smoking on the lung is needed. There are major gaps in knowledge for chronic effects and for an etiology to recent acute lung toxicity leading to death among vapers.

METHODS

We conducted bronchoscopies in a cross-sectional study of 73 subjects (42 never-smokers, 15 e-cig users, and 16 smokers). Using bronchoalveolar lavage and brushings, we examined lung inflammation by cell counts, cytokines, genome-wide gene expression, and DNA methylation.

RESULTS

There were statistically significant differences among never-smokers, e-cig users, and smokers for inflammatory cell counts and cytokines (FDR q < 0.1). The e-cig users had values intermediate between smokers and never-smokers, with levels for most of the biomarkers more similar to never-smokers. For differential gene expression and DNA methylation, e-cig users also more like never-smokers; many of these genes corresponded to smoking-related pathways, including those for xenobiotic metabolism, aryl hydrocarbon receptor signaling, and oxidative stress. Differentially methylated genes were correlated with changes in gene expression, providing evidence for biological effects of the methylation associations.

CONCLUSIONS

These data indicate that e-cigs are associated with less toxicity than cigarettes for smoking-related pathways. What is unknown may be unique effects for e-cigs not measured herein, and a comparison of smokers completely switching to e-cigs compared with former smokers. Clinical trials for smokers switching to e-cigs who undergo serial bronchoscopy and larger cross-sectional studies of former smokers with and without e-cig use, and for e-cigs who relapse back to smoking, are needed.

IMPACT

These data can be used for product regulation and for informing tobacco users considering or using e-cigs. What is unknown may be unique effects for e-cigs not measured herein, and clinical trials with serial bronchoscopy underway can demonstrate a direct relationship for changes in lung biomarkers.

Effects of Electronic Cigarette Constituents on the Human Lung: A Pilot Clinical Trial

Electronic cigarette (e-cig) use is continuing to increase, particularly among youth never-smokers, and is used by some smokers to quit. The acute and chronic toxicity of e-cig use is unclear generally in the context of increasing reports of inflammatory-type pneumonia in some e-cig users. To assess lung effects of e-cigs without nicotine or flavors, we conducted a pilot study with serial bronchoscopies over 4 weeks in 30 never-smokers, randomized either to a 4-week intervention with the use of e-cigs containing only 50% propylene glycol (PG) and 50% vegetable glycerine or to a no-use control group. Compliance to the e-cig intervention was assessed by participants sending daily puff counts and by urinary PG. Inflammatory cell counts and cytokines were determined in bronchoalveolar lavage (BAL) fluids. Genome-wide expression, miRNA, and mRNA were determined from bronchial epithelial cells. There were no significant differences in changes of BAL inflammatory cell counts or cytokines between baseline and follow-up, comparing the control and e-cig groups. However, in the intervention but not the control group, change in urinary PG as a marker of e-cig use and inhalation was significantly correlated with change in cell counts (cell concentrations, macrophages, and lymphocytes) and cytokines (IL8, IL13, and TNFα), although the absolute magnitude of changes was small. There were no significant changes in mRNA or miRNA gene expression. Although limited by study size and duration, this is the first experimental demonstration of an impact of e-cig use on inflammation in the human lung among never-smokers.

Abstract 664: Microbial and inflammatory response to electronic cigarette and cigarette use

Background: As electronic cigarette (e-cig) use increases in the US, investigation of their effects are critical. Alteration of the lung microbiome, oral microbiome, and inflammation are well established effects of cigarettes; however the effects of e-cigs are yet unknown. Individuals with smoking-related lung disease have alterations in their lung microbiome compared to healthy individuals and their lung microbiomes appear more similar to their oral microbiomes when compared to healthy individuals. To our knowledge, only one study has examined smoking tobacco’s concurrent effects in the oral and lung microbiome and none have examined e-cig use. Further, none have studied e-cigs’ effect on the lung microbiome and inflammation. We hypothesized that e-cig use would affect the lung microbiome, and that the effects are different from smokers and never-smokers; alteration of the lung microbiome will also affect inflammatory gene expression in the lungs.

Methods: A cross-sectional study of bronchoscopy with bronchoalveolar lavage (BAL) of 10 never-smokers, 8 cigarette smokers, and 10 e-cig users was conducted. RNA was extracted from BAL samples for total transcriptome RNA-seq analysis, allowing measurement of the microbiome and human gene expression. Differences in the microbiome by smoking status were determined by the Kruskal-Wallis test. Pairwise Wilcoxon rank sum tests with Holm correction was used. Effect size (fold change &gt;1.5) and adjusted P-value cutoffs (&lt;0.05) were used to identify microbes of potential interest. The limma-voom package in R was used to determine associations with human gene expression.

Results: We identified 53 differentially-abundant bacterial species in BAL samples by smoking group. Among them, the majority were less abundant in the lung of smokers and ~20 are normally found in the oral microbiome. While there were significant differences in differentially-abundant microbes between e-cig users and smokers and between smokers and never-smokers, the microbiome of e-cig users did not differ from that of never-smokers. In preliminary analyses of gene expression, there were 2,400 differentially-expressed human genes among the three groups, of which 58 are inflammatory pathway genes.

Conclusion: The majority of differentially-abundant microbes observed by smoking group are largely due to smokers. The microbiome of e-cig users is more similar to that of never-smokers. Interestingly, nearly half of microbes that are altered in the lung microbiome due to smoking use are bacterial species normally found in the oral microbiome. These findings suggest that the alterations in the oral microbiome associated with smoking cigarettes may also be reflected in the lung microbiome.

Citation Format: Kevin L. Ying, Min-Ae Song, Daniel Y. Weng, Quentin A. Nickerson, Joseph P. McElroy, Theodore M. Brasky, Mark D. Wewers, Ewy Mathé, Jo L. Freudenheim, Peter G. Shields. Microbial and inflammatory response to electronic cigarette and cigarette use [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 664.

Abstract 3237: Electronic cigarettes and inflammation in the human lung

Background: The use of electronic cigarettes (e-cigs) is increasing rapidly among both adults and youth, including among both smokers and never-smokers, and is thought to be less harmful than cigarettes. However, biological changes including inflammation have not been studied in target organs such as the lung, particularly for e-cigs; further, it is not known if changes are reversible in smokers who switch to e-cigs.

Methods: We conducted a cross-sectional bronchoscopy study of e-cig users (n=13), cigarette smokers (n=16), and never-smokers (n=40), age 21-30, to assess inflammatory cell counts and cytokines in bronchoalveolar lavages (BAL) fluids. BAL total cell counts were measured using the Countess Automated Cell Counter. Differential cells were performed on stained cytospins by a blinded clinical histopathologist. Smoking-associated inflammatory cytokines were measured using a V-PLEX Plus Pro-inflammatory Panel. Non-parametric Mann-Whitney and Kruskal-Wallis tests were used for cell counts. Log10 transformed cytokines were used for 1-way ANOVA.

Results: Smokers averaged 16 cigarettes/day (SD: 4.7) for 7 years (SD: 4.1). E-cig users vaped an average e-liquid nicotine content of 12 mg/ml (SD: 7.6) and 8 ml/day (SD: 3.9), for an average of 3 years (SD: 0.9); mean time since smoking among e-cig users was 24 months (SD: 16) (2 were never-smokers). Smokers compared to never-smokers had significantly increased total cell counts, macrophages and neutrophils, and decreased lymphocytes (7.15E-05&lt;P&lt;0.05). Total cell concentration for the e-cig users were 35% lower than the smokers and 30% higher than the never smokers (overall P=0.0005). Total and differential cell counts were borderline or significantly different for the smokers compared to e-cig users, and followed the same trends for never-smokers compared to e-cig users. Inflammatory cytokines IL-1β, IL-6, and IL-8 were significantly higher for smokers compared to never-smokers, and were lower for IL-2 and IFN-γ (all P's &lt;0.002). Levels of these cytokines in e-cig users were corroborated by patterns of differences for the cell counts, where overall differences were highly significantly different; e-cig users were intermediate. IL-4, IL-10, IL-12p70, IL-13, and TNF-α did not differ across the groups. Time since last cigarette and cigarettes/day among e-cig users was not significantly correlated with any of the cell counts or cytokine levels.

Discussion: Inflammation differed for never-smokers and smokers, with markers of inflammation intermediate for e-cig users, consistent with the hypothesis that e-cigs are less harmful. Study of whether e-cig use is more harmful than never-use and never-smoking is warranted. Because this cross-sectional study provides only indirect evidence of causation, additional observation studies and randomized trials are needed to understand changes in inflammation for e-cig users, both former- never-smokers.

Citation Format: Min-Ae Song, Theodore M. Brasky, Jo L. Freudenheim, Joseph P. McElroy, Daniel Y. Weng, Kevin L. Ying, Quentin A. Nickerson, Sarah A. Reisinger, Mark D. Wewers, Peter G. Shields. Electronic cigarettes and inflammation in the human lung [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3237.

Abstract 3233: The effects of electronic cigarette exposure on genome-wide expression in human bronchial epithelium

Background: Although smoking rates continue to decline in US adults, the number of electronic cigarette (e-cig) users is rapidly growing, especially among youth. Exposure to cigarette smoke is known to result in lung cancer and chronic obstructive pulmonary disease, is associated with inflammatory and immune responses generally, and effects gene expression related these and other pathways. However, the effects of e-cigs on the gene expression and inflammation in the bronchial epithelium are largely unknown. We conducted a cross-sectional study to evaluate the effects of e-cig use on gene expression in the bronchial epithelium, in comparison to effects on never smokers and cigarette smokers.

Methods: Epithelia brushings were obtained by bronchoscopy from never smokers (n=42), e-cig users (n=14), and current smokers (n=16) (overall, age 21-30, 78% European-American, 54% male). RNA was extracted and profiled for the whole genome transcriptome (Affymetrix Human Transcriptome Array 2.0). Between group differences were determined with the t-test. False Discovery Rate (FDR) &lt; 0.05 was considered significant. Functional and network analyses were performed using Ingenuity Pathway Analysis (IPA) software.

Results: The average number of cigarettes smoked per day in the smoker group was 16, ranging from 10 to 20 cigarettes/day. In the e-cig user group, the average number of puffs inhaled per day was 173, ranging from 20 to 600, and the average volume of e-liquid per day was 8 ml, ranging from 2 to 20 ml. Of the 14 e-cig users, eleven identified themselves as former smokers (average 24 months since last cigarette), while three were never-smokers. In microarray analysis, comparing never smoker and smoker groups, there were 2,536 differentially expressed genes (DEGs; 1,235 up-regulated genes, 1,301 down-regulated genes in smokers) and 69 DEGs comparing never smoker and e-cig user groups (59 up-regulated genes, 10 down-regulated genes in e-cig users). In addition, there were 108 DEGs between e-cig user and smoker groups (83 up-regulated genes, 25 down-regulated genes in smokers). Several well-known smoking-related genes such as CYP1B1, AKR1B10, ALDH3A1, CYP2A13, and CX3CL1 were significantly decreased in their expression for e-cig users compared to smokers. Unsupervised hierarchical clustering revealed that the expression profiles of never smokers and e-cig users are more similar to each other compared to profiles of smokers. Pathway analysis of smoking-related genes revealed that NRF2-mediated oxidative stress was the most significant canonical pathway (P = 7.88E-11).

Conclusions: Consistent with the hypothesis that e-cigs are less harmful than smoking, bronchial epithelium gene expression profiles of never smokers and e-cig users are more similar, while smokers exhibit distinct profiles. Associations of different nicotine products are apparent in gene expression profiles.

Citation Format: Daniel Y. Weng, Min-Ae Song, Theodore M. Brasky, Joseph P. McElroy, Ewy Mathe, Jo L. Freudenheim, Mark D. Wewers, Peter G. Shields. The effects of electronic cigarette exposure on genome-wide expression in human bronchial epithelium [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3233.

Abstract 3236: Lung epithelium DNA methylation: Electronic cigarette users, smokers, and never-smokers

Background: The use of electronic cigarettes (e-cigs) among smokers and never-smokers is increasing, and is considered to be less harmful than cigarettes. However, this has not been studied in target organs for smoking-related diseases, especially the lung. Altered DNA methylation is seen in smokers and contributes to lung carcinogenesis. However, it is not known how e-cigs affect methylation in the lung or whether smoking-induced DNA methylation changes can be reversed in former smokers who switch to e-cigs.

Methods: We conducted a cross-sectional bronchoscopy study of e-cig users (n=12), cigarette smokers (n=10), and never-smokers (n=10) (age 21-30, 84% European-American, 66% male). Bisulfite-converted DNA extracted from lung epithelium collected by bronchial brushing was analyzed for 865,859 CpGs with the llumina Infinium Methylation EPIC Chip in a single batch. Probes were filtered out if on sex chromosomes, cross-reactive, or SNP associated, leaving 735,317 CpGs for analysis. One-way analysis of covariance using M-values was used to identify CpGs differentially methylated for the three groups. False Discovery Rate (FDR) of q&lt;0.1 was considered significant. Ingenuity pathway analysis (IPA) was used for potential biologic implications of identified CpGs.

Results: Smokers averaged 18 cigarettes/day (SD: 4.2) and 6 years of smoking (SD: 4.5). E-cig users vaped an average e-liquid nicotine content of 10 mg/mL (SD: 11) and 8 mL/day (SD: 4), for an average of three years (SD: 1). Mean time since smoking among the e-cig users was 31 months (SD: 15); 3 were never-smokers. We identified 517 differentially methylated CpGs among the three groups (FDR q&lt;0.1). Of them, 128 (25%) were in enhancers, 165 (47%) in promoters, and 162 (31%) in CpG islands/surroundings. For e-cig users, methylation of most differentially methylated CpGs (n=505) was between those for smokers and never-smokers. For smoking- and/or lung cancer-related genes: AHRR, ALDH3A1, ALPK3, CYP1B1, and OXCT1, CpGs were less methylated in smokers than in never-smokers; e-cig users were intermediate. There were 330 unique genes with differentially methylated CpGs; 319 were included in an IPA analysis. The most significantly associated disease was cancer (n=283) and biologic function was drug metabolism (n=10). The top canonical pathways included xenobiotic metabolism signaling (n=13) and wnt/β-catenin signaling (n=9).

Discussion: DNA methylation differed for never-smokers and smokers, with e-cig users' methylation intermediate, consistent with the hypothesis that e-cigs are less harmful than smoking; whether e-cig use is more harmful than never-smoking needs to be studied. Because this study is cross-sectional, association, and not causation, is indicated. Additional observational studies and randomized trials are warranted to understand biologic changes in the lung for smokers and never-smokers using e-cigs.

Citation Format: Min-Ae Song, Dominic J. Smiraglia, Theodore M. Brasky, Daniel Y. Weng, Joseph P. McElroy, Sarah A. Reisinger, Kevin L. Ying, Quentin A. Nickerson, Mark D. Wewers, Peter G. Shields, Jo L. Freudenheim. Lung epithelium DNA methylation: Electronic cigarette users, smokers, and never-smokers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3236.

Abstract 1231: Using oral and lung microbiome to assess microbial dysbiosis and inflammatory response to electronic cigarettes and to cigarettes

Background: Alteration of the oral microbiome (microbial dysbiosis) with cigarette smoking is well established. However, the effect of electronic cigarettes (e-cigs) use on the oral microbiome is unknown, although there are emerging data that e-cigs induce microbial changes similar to smoking. In smoking-related diseases, such as chronic obstructive pulmonary disease, there are changes in the oral microbiome and in the expression of genes involved in inflammatory pathways. Similar to the oral microbiome, it is feasible that smoking tobacco and e-cig use could also affect the lung microbiome. To the best of our knowledge, there is only one published study investigating smoking tobacco effects on the oral and lung microbiome. No published studies have evaluated concurrent effects of e-cigs in the oral and lung microbiome.

Aims: We hypothesize that microbial dysbiosis and expression of inflammatory cytokines in the oral cavity and lung will differ between smokers and nonsmokers, and that e-cig users will have microbial dysbiosis more similar to smokers. To accomplish this, we propose 1) to examine the association of oral and lung microbiome in nonsmokers, smokers and e-cig users, 2) to determine if the oral microbiome and the lung microbiome differ among these groups, and 3) to determine correlation of the microbiota with host expression of inflammation-related genes.

Methods: A cross-sectional study using bronchoscopy and oral rinse collection of 10 never-smokers, 8 cigarette smokers, and 10 e-cig users was conducted. For each study participant, RNA was extracted from saliva and bronchoalveolar lavage (BAL) samples for total transcriptome analysis using RNA-seq; facilitating this approach allows measurement of bacterial communities and human inflammatory cytokine expression in the same assay. To determine microbial dysbiosis by smoking status, the Mann Whitney U-test and Kruskal-Wallis H-test were used with Bonferroni correction for multiple comparisons. Both effect size (fold change &gt;1.5) and adjusted p-value cutoffs (&lt;0.05) were used to identify statistical significance.

Results: In preliminary analyses we identified 2,257 bacterial strains in saliva samples and 1592 in BAL samples. We found a lack of concordance of highly abundant bacteria in the oral cavity and lungs. The top twenty expressed human genes were associated with RNA splicing, RNA elongation and miRNAs. Comparisons of microbial dysbiosis by smoking status are currently under way.

Conclusion: The composition of the microbiome for saliva is different from that of BAL. Comparison of the metatranscriptome and transcriptome between the lung and oral cavity, as well as between smokers, nonsmokers and e-cigarette users, will allow us to observe how e-cig use compares with cigarette smoking and never smoking in terms of microbial dysbiosis and inflammatory cytokines.

Citation Format: Kevin L. Ying, Min-Ae Song, Daniel Y. Weng, Quentin A. Nickerson, Joseph P. McElroy, David Frankhouser, Pearlly S. Yan, Ralf Bundschuh, Theodore M. Brasky, Mark D. Wewers, Ewy Mathé, Jo L. Freudenheim, Peter G. Shields. Using oral and lung microbiome to assess microbial dysbiosis and inflammatory response to electronic cigarettes and to cigarettes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1231.

Discovery and replication of microRNAs for breast cancer risk using genome-wide profiling

Background

Genome-wide miRNA expression may be useful for predicting breast cancer risk and/or for the early detection of breast cancer.

Results

A 41-miRNA model distinguished breast cancer risk in the discovery study (accuracy of 83.3%), which was replicated in the independent study (accuracy = 63.4%, P=0.09). Among the 41 miRNA, 20 miRNAs were detectable in serum, and predicted breast cancer occurrence within 18 months of blood draw (accuracy 53%, P=0.06). These risk-related miRNAs were enriched for HER-2 and estrogen-dependent breast cancer signaling.

Materials and Methods

MiRNAs were assessed in two cross-sectional studies of women without breast cancer and a nested case-control study of breast cancer. Using breast tissues, a multivariate analysis was used to model women with high and low breast cancer risk (based upon Gail risk model) in a discovery study of women without breast cancer (n=90), and applied to an independent replication study (n=71). The model was then assessed using serum samples from the nested case-control study (n=410).

Conclusions

Studying breast tissues of women without breast cancer revealed miRNAs correlated with breast cancer risk, which were then found to be altered in the serum of women who later developed breast cancer. These results serve as proof-of-principle that miRNAs in women without breast cancer may be useful for predicting breast cancer risk and/or as an adjunct for breast cancer early detection. The miRNAs identified herein may be involved in breast carcinogenic pathways because they were first identified in the breast tissues of healthy women.

Landscape of genome-wide age-related DNA methylation in breast tissue

Despite known age-related DNA methylation (aDNAm) changes in breast tumors, little is known about aDNAm in normal breast tissues. Breast tissues from a cross-sectional study of 121 cancer-free women, were assayed for genome-wide DNA methylation. mRNA expression was assayed by microarray technology. Analysis of covariance was used to identify aDNAm’s. Altered methylation was correlated with expression of the corresponding gene and with DNA methyltransferase protein DNMT3A, assayed by immunohistochemistry. Publically-available TCGA-BRCA data were used for replication. 1,214 aDNAm’s were identified; 97% with increased methylation, and all on autosomes. Sites with increased methylation were predominantly in CpG lslands and non-enhancers. aDNAm’s with decreased methylation were generally located in intergenic regions, non-CpG Islands, and enhancers. Of the aDNAm’s identified, 650 are known to be involved in cancer, including ESR1 and beta-estradiol responsive genes. Expression of DNMT3A was positively associated with age. Two aDNAm’s showed borderline significant associations with DNMT3A expression; KRR1 (OR 6.57, 95% CI: 2.51–17.23) and DHRS12 (OR 6.08, 95% CI: 2.33–15.86). A subset of aDNAm’s co-localized within vulnerable regions for somatic mutations in cancers including breast cancer. Expression of C19orf48 was inversely and significantly correlated with its methylation level. In the TCGA dataset, 84% and 64% of the previously identified aDNAm’s were correlated with age in both normal-adjacent and tumor breast tissues, with differential associations by histological subtype. Given the similarity of findings in the breast tissues of healthy women and breast tumors, aDNAm’s may be one pathway for increased breast cancer risk with age.

Abstract 246: Assessing microbial dysbiosis of electronic cigarettes and cigarette smokers using oral and lung microbiome

The link between smoking tobacco and changes in the oral microbiome in response to tobacco smoking are well established. It is not known if there are changes in response to electronic cigarettes (e-cig). These changes in the microbiome are associated with increased numbers of disease causing pathogens. Currently there are no published studies that have investigated the relationship of smoking tobacco on both the oral and lung microbiome. There is insufficient evidence showing whether changes in oral cavity and lung microbiome are also seen in e-cig users. We will study the oral cavity and lung of non-smokers, smokers and e-cig users to examine concordance between oral cavity and the lungs as well as comparing the three groups, examining the microbiomes and expression of inflammatory markers. We hypothesize that microbial dysbiosis and expression of inflammatory cytokines will differ for smokers and non-smokers; and that e-cig users will have microbial dysbiosis similar to cigarette smokers. A cross-sectional study is being conducted on three groups, 1) never-smokers, 2) cigarette smokers, and 3) e-cig users. For each study participant, saliva and bronchoalveolar lavage (BAL) are being collected to measure microbiome. RNA is extracted from saliva and BAL samples for total transcriptome analysis using RNA-seq. This analysis will detect human and bacterial reads thereby allowing observations of bacterial communities as well as human inflammatory cytokine response to bacterial presence. 85% to 98% of BAL sample reads aligned to the human genome compared to less than 50% from saliva samples. The alignment results allow us to deduce that the majority of reads from BAL samples are human and that the majority of the reads in saliva samples are bacterial.

Preliminary results show detection of human RNA expression and of bacterial reads are present in both saliva and BAL samples. More samples are being processed and the comparison of BAL and saliva samples between the three groups will be discussed.

Citation Format: Kevin Ying, Min-Ae Song, Daniel Y. Weng, Quentin Nickerson, David Frankhouser, Pearlly S. Yan, Ralf Bundschuh, Mark D. Wewers, Ewy Mathé, Jo L. Freudenheim, Peter G. Shields. Assessing microbial dysbiosis of electronic cigarettes and cigarette smokers using oral and lung microbiome [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 246. doi:10.1158/1538-7445.AM2017-246

Abstract 4361: An integrated genome-wide methylation analysis with gene expression in normal breast tissues identifies differentially methylated CpG loci associated with obesity

Introduction: Obesity is a risk factor for breast cancer, but the underlying mechanisms for this are only partially understood, and there has been only limited study of breast tissues molecularly before cancer develops.

Methods: Breast tissues from healthy women undergoing reduction mammoplasty and epidemiologic interviews (n=121) were profiled for the whole genome transcriptome (Affymetrix Human Transcriptome Arrays) and genome-wide DNA methylation (Infinium HumanMethylation 450 BeadChip array).

Results: After adjusting for confounding by age and race, 12,210 CpG dinucleotides with altered methylation levels correlated with body mass index (BMI) (10,808 positive correlations and1,402 negative correlations, FDR&lt;0.05). Among them 4,170 BMI-associated hypermethylated CpG dinucleotides (-1.5 kb from transcription start site, 1st Exon, and 5’UTR) and 443 BMI-associated hypomethylated CpG dinucleotides were located in promoter regions. By integrating DNA methylation and mRNA expression data, we identified 310 methylated genes that correlated with gene expression (FDR&lt;0.05). Of these, 242 genes had higher methylation status showing concurrent down-regulation in obese women, and 68 genes had lower methylation status showing concurrent up-regulation in obese women. Among the affected genes involved in diseases and disorders for inflammatory response, hereditary disorder, and immunological disease.

Conclusions: This study provides evidence that obesity epigenetically deregulates genes potentially involved in breast cancer that have functional relationships to gene expression.

Citation Format: Daniel Y. Weng, Min-Ae Song, Theodore M. Brasky, Catalin Marian, Renny S. Lan, Adana A. Llanos, Scott L. Spear, Bhaskar V. Kallakury, Jo L. Freudenheim, Peter G. Shields. An integrated genome-wide methylation analysis with gene expression in normal breast tissues identifies differentially methylated CpG loci associated with obesity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4361. doi:10.1158/1538-7445.AM2017-4361

Racial differences in genome-wide methylation profiling and gene expression in breast tissues from healthy women

Breast cancer is more common in European Americans (EAs) than in African Americans (AAs) but mortality from breast cancer is higher among AAs. While there are racial differences in DNA methylation and gene expression in breast tumors, little is known whether such racial differences exist in breast tissues of healthy women. Genome-wide DNA methylation and gene expression profiling was performed in histologically normal breast tissues of healthy women. Linear regression models were used to identify differentially-methylated CpG sites (CpGs) between EAs (n = 61) and AAs (n = 22). Correlations for methylation and expression were assessed. Biological functions of the differentially-methylated genes were assigned using the Ingenuity Pathway Analysis. Among 485 differentially-methylated CpGs by race, 203 were hypermethylated in EAs, and 282 were hypermethylated in AAs. Promoter-related differentially-methylated CpGs were more frequently hypermethylated in EAs (52%) than AAs (27%) while gene body and intergenic CpGs were more frequently hypermethylated in AAs. The differentially-methylated CpGs were enriched for cancer-associated genes with roles in cell death and survival, cellular development, and cell-to-cell signaling. In a separate analysis for correlation in EAs and AAs, different patterns of correlation were found between EAs and AAs. The correlated genes showed different biological networks between EAs and AAs; networks were connected by Ubiquitin C. To our knowledge, this is the first comprehensive genome-wide study to identify differences in methylation and gene expression between EAs and AAs in breast tissues from healthy women. These findings may provide further insights regarding the contribution of epigenetic differences to racial disparities in breast cancer.

Persistent alterations of gene expression profiling of human peripheral blood mononuclear cells from smokers

The number of validated biomarkers of tobacco smoke exposure is limited, and none exist for tobacco-related cancer. Additional biomarkers for smoke, effects on cellular systems in vivo are needed to improve early detection of lung cancer, and to assist the Food and Drug Administration in regulating exposures to tobacco products. We assessed the effects of smoking on the gene expression using human cell cultures and blood from a cross-sectional study. We profiled global transcriptional changes in cultured smokers' peripheral blood mononuclear cells (PBMCs) treated with cigarette smoke condensate (CSC) in vitro (n = 7) and from well-characterized smokers' blood (n = 36). ANOVA with adjustment for covariates and Pearson correlation were used for statistical analysis in this study. CSC in vitro altered the expression of 1 178 genes (177 genes with > 1.5-fold-change) at P < 0.05. In vivo, PBMCs of heavy and light smokers differed for 614 genes (29 with > 1.5-fold-change) at P < 0.05 (309 remaining significant after adjustment for age, race, and gender). Forty-one genes were persistently altered both in vitro and in vivo, 22 having the same expression pattern reported for non-small cell lung cancer. Our data provides evidence that persistent alterations of gene expression in vitro and in vivo may relate to carcinogenic effects of cigarette smoke, and the identified genes may serve as potential biomarkers for cancer. The use of an in vitro model to corroborate results from human studies provides a novel way to understand human exposure and effect. © 2015 Wiley Periodicals, Inc.

Abstract 2777: One-carbon metabolism genetic variant and genome-wide DNA methylation in breast tissues from healthy women

Altered DNA methylation is an early event in carcinogenesis. Little is known about the mechanism of altered methylation in breast tissue; possible factors include diet such as alcohol and folate intake, and genetic variation for enzymes in one carbon metabolism. Examination of the association of these factors with methylation in breast tissues from healthy women provides insight into these changes. Blood and glandular breast tissues from 81 women with no history of cancer and who underwent reduction mammoplasty were assayed. The 96-plex Illumina BeadXpress® or TaqMan® SNP Genotyping assays assessed SNPs, genome-wide DNA methylation profiling was performed using the Illumina Infinium HumanMethylation450 BeadChip.The Affymetrix GeneChip Human Trascriptome Array 2.0 was used to compare gene expression level with methylation change in fresh frozen breast tissues. Biological networks of differentially-methylated (DM) genes were assigned using the Ingenuity Pathway Analysis (IPA). Fifty-seven CpG sites were DM in comparisons of genotype for eight SNPs in FTHFD, MTHFD1, MTHFR, MTR, MTRR, and TYMS (P&lt;5.0 × 10-5 for each). SNPs in FTHFD were associated with 56% of the DM CpGs. SNPs in FTHFD and MTR were associated with DM CpG sites in their own genes. Six methylation and gene expression pairs were modestly to weakly correlated (P&lt;0.05), five positively correlated (HCN4, FRMD4A, FTHFD, SLC39A7, and LOC63930) and one negatively correlated (ADAMTS14). Four DM CpGs identified by SNPs in MTRR, MTHFR, and FTHFD were significantly associated with alcohol consumption and/or breast folate. Forty-five DM genes were available in the IPA database. IPA revealed enrichment for genes (91%) involved in cancers. The top-scoring network was “Energy Production, Molecular Transportation, Nucleic Acid Metabolism” (score = 32). The top molecular and cellular functions were Amino Acid Metabolism (ALDH1L1, MTR, and PTPRN2), Cell-to-Cell Signaling (DLG3, GRN, HLA-DQB1, PTPRN2, and SLC6A3), Cellular Function and Maintenance (ADAMTS14, ADMTS2, CRIPT, DCL1, DLG3, GRN, KAG2, PTPRN2, and RXRB). High concordance of methylation levels for all DM loci analyzed was found between HM450 and pyrosequencing on 75 technically validated samples (Spearman correlation r = 0.98, P&lt;1.0×10-47). This is the first comprehensive study of the association between variation in one-carbon metabolism genes and genome-wide DNA methylation in histologically normal breast tissues. These SNPs, particularly FTHFD, as well as alcohol intake and folate exposure appear to affect DNA methylation in the breast of healthy women. The finding that SNPs in FTHFD and MTR are associated with their own methylation is also novel and highlights a role for these SNPs as methylation quantitative trait loci. Understanding of the role of one carbon metabolism in altered DNA methylation could provide insight into prevention of breast tumors.

Citation Format: Min-Ae Song, Theodore M. Brasky, Catalin Marian, Daniel Y. Weng, Cenny Taslim, Adana A. Llanos, Ramona G. Dumitrescu, Zhenhua Liu, Joel B. Mason, Bhaskar V. Kallakury, Jo L. Freudenheim, Peter G. Shields. One-carbon metabolism genetic variant and genome-wide DNA methylation in breast tissues from healthy women. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2777.

DNA methylation and breast tumor clinicopathological features: The Western New York Exposures and Breast Cancer (WEB) study

We evaluated the association between methylation of 9 genes, SCGB3A1, GSTP1, RARB, SYK, FHIT, CDKN2A, CCND2, BRCA1, and SFN in tumor samples from 720 breast cancer cases with clinicopathological features of the tumors and survival. Logistic regression was used to estimate odds ratios (OR) of methylation and Cox proportional hazards models to estimate hazard ratios (HR) between methylation and breast cancer related mortality. Estrogen receptor (ER) and progesterone receptor (PR) positivity were associated with increased SCGB3A1 methylation among pre- and post-menopausal cases. Among premenopausal women, compared with Stage 0 cases, cases of invasive cancer were more likely to have increased methylation of RARB (Stage I OR = 4.7, 95% CI: 1.1-19.0; Stage IIA/IIB OR = 9.7, 95% CI: 2.4-39.9; Stage III/IV OR = 5.6, 95% CI: 1.1-29.4) and lower methylation of FHIT (Stage I OR = 0.2, 95% CI: 0.1-0.9; Stage IIA/IIB OR = 0.2, 95% CI: 0.1-0.8; Stage III/IV OR = 0.6, 95% CI: 0.1-3.4). Among postmenopausal women, methylation of SYK was associated with increased tumor size (OR = 1.7, 95% CI: 1.0-2.7) and higher nuclear grade (OR = 2.0, 95% CI 1.2-3.6). Associations between methylation and breast cancer related mortality were observed among pre- but not post-menopausal women. Methylation of SCGB3A1 was associated with reduced risk of death from breast cancer (HR = 0.41, 95% CI: 0.17-0.99) as was BRCA1 (HR = 0.41, 95% CI: 0.16-0.97). CCND2 methylation was associated with increased risk of breast cancer mortality (HR = 3.4, 95% CI: 1.1-10.5). We observed differences in methylation associated with tumor characteristics; methylation of these genes was also associated with breast cancer survival among premenopausal cases. Understanding of the associations of DNA methylation with other clinicopathological features may have implications for prevention and treatment.

Genetic variation in one-carbon metabolism in relation to genome-wide DNA methylation in breast tissue from heathy women

Single nucleotide polymorphisms (SNPs) in one-carbon metabolism genes and lifestyle factors (alcohol drinking and breast folate) may be determinants of whole-genome methylation in the breast. DNA methylation profiling was performed using the Illumina Infinium HumanMethylation450 BeadChip in 81 normal breast tissues from women undergoing reduction mammoplasty and no history of cancer. ANCOVA, adjusting for age, race and BMI, was used to identify differentially-methylated (DM) CpGs. Gene expression, by the Affymetrix GeneChip Human Transcriptome Array 2.0, was correlated with DM. Biological networks of DM genes were assigned using Ingenuity Pathway Analysis. Fifty-seven CpG sites were DM in association with eight SNPs in FTHFD, MTHFD1, MTHFR, MTR, MTRR, and TYMS (P <5.0 x 10^-5); 56% of the DM CpGs were associated with FTHFD SNPs, including DM within FTHFD. Gene expression was negatively correlated with FTHFD methylation (r=-0.25, P=0.017). Four DM CpGs identified by SNPs in MTRR, MTHFR, and FTHFD were significantly associated with alcohol consumption and/or breast folate. The top biological network of DM CpGs was associated with Energy Production, Molecular Transportation, and Nucleic Acid Metabolism. This is the first comprehensive study of the association between SNPs in one-carbon metabolism genes and genome-wide DNA methylation in normal breast tissues. These SNPs, especially FTHFD, as well as alcohol intake and folate exposure, appear to affect DM in breast tissues of healthy women. The finding that SNPs in FTHFD and MTR are associated with their own methylation is novel and highlights a role for these SNPs as cis-methylation quantitative trait loci.

Abstract 833: Persistent alterations of gene expression profiling of human peripheral blood mononuclear cells from smokers

The number of validated biomarkers of tobacco smoke exposure is limited, and none exist for tobacco-related cancer. Additional biomarkers for smoke effects on cellular systems in vivo are needed to improve early detection of lung cancer, and to assist the Food and Drug Administration in regulating exposures to tobacco products. We assessed the effects of smoking on the gene expression in vitro and in vivo using human cell cultures and blood from a cross-sectional study. We profiled global transcriptional changes in cultured smokers’ peripheral blood mononuclear cells (PBMCs) treated with cigarette smoke condensate (CSC) in vitro and from well-characterized smokers’ blood (n = 36). ANOVA and linear regression with adjustment for covariates were used for statistical analysis. CSC in vitro altered the expression of 1178 genes (177 genes with &gt; 1.5 fold-change) at P &lt; 0.05. Phase I and II metabolizing enzyme genes were up-regulated, cytokines and chemokines were down-regulated. Nine putative oncogenes and 5 tumor suppressor genes were dysregulated. In vivo, PBMCs of heavy and light smokers differed for 614 genes (29 with &gt; 1.5 fold-change) at P &lt; 0.05 (309 remaining significant after adjustment for age, race and gender). Seventy eight genes had a significant linear correlation (P &lt; 0.01) with cigarettes per day and 28 genes were linearly correlated with cumulative pack-year smoking. Forty-one genes were persistently altered both in vitro and in vivo, 22 having the same expression pattern reported for non-small cell lung cancer. Our data provides evidence that persistent alterations of gene expression in vitro and in vivo may relate to carcinogenic effects of cigarette smoke, and the identified genes may serve as potential biomarkers for cancer. The use of an in vitro model to corroborate results from human studies provides direct evidence for a cause and effect.

Citation Format: Daniel Y. Weng, Jinguo Chen, Cenny Taslim, Ping-Ching Hsu, Catalin Marian, Sean P. David, Christopher A. Loffredo, Peter G. Shields. Persistent alterations of gene expression profiling of human peripheral blood mononuclear cells from smokers. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 833. doi:10.1158/1538-7445.AM2015-833

Abstract 3971: Genome-wide tissue-based microRNA signature in healthy women predicting breast cancer risk

Introduction: Small non-coding microRNAs (miRNAs) play important roles in both normal breast development and breast carcinogenesis. The goal of this study is to identify miRNAs in normal breast tissues which are related to breast cancer risk.

Materials and Methods: We used a high-throughput digital counting of miRNAs without amplification (Nanostring®) to examine miRNA expression in 161 reduction mammoplasty (RM) tissues from two independent studies. A multivariate model was used to identify miRNAs associated with breast cancer risk (based upon Gail risk scores) in a training study (n = 90) then the model was validated in a replication study (n = 71). Risk-related microRNAs were then evaluated in serum for associations with real breast cancer cases using publically available prospective cohort (Sister Study, n = 410).

Results: We identified a 41-miRNA signature in healthy women distinguishing high risk from low risk women with a prediction accuracy of 82% (95% CI = 80% to 87%) in the training study. Predictive accuracy was 69% (95% CI = 65% to 73%) in the replication study. 34 of 41 serum miRNAs that mapped to public data predicted women who developed breast cancer within 18 months after blood draw from those who remained cancer free with accuracy of 59% (95% CI = 57% to 61%). We have also shown that these accuracies were significantly higher than random chance (P &lt; 0.0001). IPA canonical pathway analysis revealed that the risk-related microRNAs targets were significantly enriched for HER-2 signaling in breast cancer, and estrogen-dependent breast cancer signaling, and other important cancer pathways such as molecular mechanisms of cancer, PI3K/AKT signaling, PTEN signaling, and TGF-beta signaling.

Conclusion: Our results indicate that miRNA profiling from breast tissue of healthy patients may identify clinically useful predictors of breast cancer risk and these miRNAs may also work as non-invasive biomarker for early breast cancer prediction.

Citation Format: Cenny Taslim, Daniel Y. Weng, Theodore M. Brasky, Ramona G. Dumitrescu, Kun Huang, Bhaskar V. s. Kallakury, Shiva Krishnan, Adana A. Llanos, Catalin Marian, Sallie S. Schneider, Scott L. Spear, Melissa A. Troester, Jo L. Freudenheim, Susan Geyer, Peter G. Shields. Genome-wide tissue-based microRNA signature in healthy women predicting breast cancer risk. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 3971. doi:10.1158/1538-7445.AM2015-3971

Abstract 3639: DNA methylation in SYK, GSTP1, & FHIT genes: associations with parity and time since birth

Introduction: Breast cancer risk is transiently increased following pregnancy; these tumors, referred to as pregnancy associated breast cancer (PABC) have poorer prognosis. As more women delay pregnancy until older age this increase in risk following pregnancy is projected to mean increased numbers of PABCs. Epigenetic events are important in the development and progression of cancer. Methylation status of specific genes may potentially be useful as screening targets in clinical practice. We examined DNA methylation for three genes of interest, Spleen tyrosine kinase (SYK), a non-receptor protein tyrosine kinase expressed in hematopoietic and non-hematopoietic breast epithelial cells, exhibiting tumor suppressor qualities, Fragile histadine triad (FHIT), encoding a protein involved in cell differentiation and apoptosis, and Glutathione S-transferase P1 (GSTP1), a phase II detoxification enzyme in most cell types acting on carcinogens, environmental pollutants, and drugs. We compared DNA methylation in these genes in breast tissues from healthy premenopausal women by parity status and time since last birth (nulliparous, &lt;5 years, &gt;10 years) to understand changes in methylation associated with recent pregnancy.

Methods: DNA samples were obtained from fresh frozen tissues of 81 premenopausal women undergoing reduction mammoplasty with no prior history of cancer except non-melanoma skin cancer. Genomic DNA was modified using EZ DNA Methylation Gold Kit and sequenced using Pyro Q-CpGTM Software. Two-sample t-tests and 1-way Analysis of Variance were used to examine differences in mean methylation in the three genes by parity status and time since last birth. Generalized linear regression models were used to compare mean methylation levels adjusted for age, race, menopausal status, and family history of breast cancer.

Results: Parous healthy premenopausal women had a higher adjusted mean methylation in all three genes than their nulliparous counterparts. Mean percent methylation of SYK (0.98 vs. 0.87; P=0.56) and FHIT (2.08 vs. 1.85, P=0.50) were 12% higher in parous versus nulliparous women. Methylation of GSTP1 was 7% higher among parous versus nulliparous women (0.70 vs. 0.65; P=0.82); however, differences were not statistically significant. For GSTP1, there was a suggestion of higher mean percent methylation among women who gave birth more recently (&lt;5 years: 0.93) versus births in the more distant past (&gt;10 years: 0.64) or nulliparous women (0.69; P=0.64). There were no clear differences by recency of birth for FHIT or SYK.

Conclusions: Mean percent methylation of SYK, GSTP1, and FHIT may be suggestive of changes in methylation among parous women, and for GSTP1, particularly higher DNA methylation among women who gave birth more recently. Given the small sample size, these findings are preliminary, and additional studies are needed to better understand methylation in PABC risk.

Citation Format: Ruth N. Kagwima, Adana A. LLanos, Theodore M. Brasky, Daniel Y. Weng, Jo L. Freudenheim, Peter G. Shields. DNA methylation in SYK, GSTP1, & FHIT genes: associations with parity and time since birth. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 3639. doi:10.1158/1538-7445.AM2013-3639

Promiscuous recombination of LoxP alleles during gametogenesis in cornea Cre driver mice

PURPOSE

To examine whether promiscuous Cre/LoxP recombination happens during gametogenesis in double transgenic mice carrying LoxP modified alleles and Cre transgene driven by tissue-specific promoter outside the gonads of adult mice.

METHODS

Cre driver mice were crossbred with reporter mouse lines (e.g., ZEG and Rosa26R) to obtain Cre/ZEG and Cre/Rosa26R double transgenic mice. The frequency of promiscuous LoxP/Cre recombination was determined by the expression of second reporter genes in the offspring of double transgenic mice.

RESULTS

The frequency of promiscuous LoxP/Cre recombination varied in different lines of Cre driver mice and in the sex of the same driver mice with higher penetrance in male than in female double transgenic mice. Polymerase chain reaction (PCR) and recombination analysis demonstrate that the recombination of floxed allele occurs during the transition from spermatogonia (diploid) to primary spermatocyte (tetraploid) in the testis. Thereby, target-floxed allele(s) may be ubiquitously ablated in experimental animals intended for tissue-specific gene deletion.

CONCLUSIONS

Gametogenesis-associated recombination should always be examined in tissue-specific gene ablation studies.