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Supplementary Data, Figures 1-2 from Human Tumor Antigens Tn and Sialyl Tn Arise from Mutations in Cosmc

Neoplastic lesions typically express specific carbohydrate antigens on glycolipids, mucins, and other glycoproteins. Such antigens are often under epigenetic control and are subject to reversion and loss upon therapeutic selective pressure. We report here that two of the most common tumor-associated carbohydrate antigens, Tn and sialyl Tn (STn), result from somatic mutations in the gene Cosmc that encodes a molecular chaperone required for formation of the active T-synthase. Diverse neoplastic lesions, including colon cancer and melanoma-derived cells lines, expressed both Tn and STn antigen due to loss-of-function mutations in Cosmc. In addition, two human cervical cancer specimens that showed expression of the Tn/STn antigens were also found to have mutations in Cosmc and loss of heterozygosity for the cross-linked Cosmc locus. This is the first example of somatic mutations in multiple types of cancers that cause global alterations in cell surface carbohydrate antigen expression. [Cancer Res 2008;68(6):1636–46]

Introduction The tobacco-specific nitrosamines (TSNAs) are an important group of carcinogens found in tobacco and tobacco smoke. To describe and characterize the levels of TSNAs in the Population Assessment of Tobacco and Health (PATH) Study Wave 1 (2013–2014), we present four biomarkers of TSNA exposure: N′-nitrosonornicotine, N′-nitrosoanabasine, N′-nitrosoanatabine, and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) which is the primary urinary metabolite of 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone. Methods We measured total TSNAs in 11 522 adults who provided urine using automated solid-phase extraction coupled to isotope dilution liquid chromatography–tandem mass spectrometry. After exclusions in this current analysis, we selected 11 004 NNAL results, 10 753 N′-nitrosonornicotine results, 10 919 N′-nitrosoanatabine results, and 10 996 N′-nitrosoanabasine results for data analysis. Geometric means and correlations were calculated using SAS and SUDAAN. Results TSNA concentrations were associated with choice of tobacco product and frequency of use. Among established, every day, exclusive tobacco product users, the geometric mean urinary NNAL concentration was highest for smokeless tobacco users (993.3; 95% confidence interval [CI: 839.2, 1147.3] ng/g creatinine), followed by all types of combustible tobacco product users (285.4; 95% CI: [267.9, 303.0] ng/g creatinine), poly tobacco users (278.6; 95% CI: [254.9, 302.2] ng/g creatinine), and e-cigarette product users (6.3; 95% CI: [4.7, 7.9] ng/g creatinine). TSNA concentrations were higher in every day users than in intermittent users for all the tobacco product groups. Among single product users, exposure to TSNAs differed by sex, age, race/ethnicity, and education. Urinary TSNAs and nicotine metabolite biomarkers were also highly correlated. Conclusions We have provided PATH Study estimates of TSNA exposure among US adult users of a variety of tobacco products. These data can inform future tobacco product and human exposure evaluations and related regulatory activities.

Oxidative stress (OS) plays a major role in the pathogenesis of various diseases in humans. OS is a result of an imbalance between reactive oxygen species (ROS) and the biologically available antioxidants that prevent or repair damage that ROS inflict on the host cells. ROS are naturally generated during normal mitochondrial respiration and by oxidative burst during the immune response. Many factors may influence OS, including genetics, diet, exercise, and exposure to environmental toxicants (e.g., tobacco smoke). A nonenzymatic peroxidation product of arachidonic acid (AA), 8-iso-PGF2α (8-isoprostane), is a validated biomarker of OS that is present in urine as both glucuronide conjugate and free acid. Previous studies report that the conjugated forms of 8-isoprostane can vary between 30 and 80% of the total 8-isoprostane levels. By hydrolyzing the conjugated forms, it is possible to obtain a total (free + conjugated) measurement of 8-isoprostane in urine samples. Here, we describe a robust, automated, and high-throughput method for measuring total urinary 8-isoprostane using a polymeric weak anion-exchange solid-phase extraction (SPE) and isotope-dilution ultrahigh performance liquid chromatography electrospray ionization-tandem mass spectrometry (UHPLC-MS/MS). This method, using a 96-well plate platform, showed good sensitivity (8.8 pg/mL LOD) and used only 400 μL of the sample volume with a cycle time of 11 min. The inter- and intraday precision, calculated from 20 repeated measurements of two quality control pools, varied from 4 to 10%. Accuracy, calculated from the recovery percentage at three spiking levels, ranged from 92.7 to 106.7%. We modified this method to allow for the exclusive measurement of free 8-isoprostane by removing the hydrolysis step. We measured both free and total 8-isoprostane in urine collected from 30 cigarette smokers (free: 460 ± 78.8 pg/mL; total: 704 ± 108 pg/mL) and 30 nonusers of tobacco products (free: 110 ± 24.2 pg/mL; total: 161 ± 38.7 pg/mL). This method is robust, accurate, and easily adaptable for large population studies.

Background: Heterocyclic aromatic amines (HAA) are a group of hazardous substances produced during combustion of tobacco or high-temperature cooking of meats. 2-Amino-9H-pyrido[2,3-b]indole (AαC) is a major carcinogenic HAA in tobacco smoke. Methods: Urinary AαC, used as a marker of AαC exposure, was analyzed on spot urine samples from adult participants of the 2013–2014 cycle of the National Health and Nutrition Examination Survey (N = 1,792). AαC was measured using isotope-dilution liquid chromatography–tandem mass spectrometry. Exclusive combusted tobacco smokers were differentiated from nonusers of tobacco products through both self-report and serum cotinine data. Results: Among exclusive smokers, sample-weighted median urinary AαC was 40 times higher than nonusers. Sample-weighted regression models showed that urinary AαC increased significantly with serum cotinine among both exclusive tobacco users and nonusers with secondhand smoke exposure. Among nonusers, eating beef cooked at high temperature was associated with a significant increase in urinary AαC, whereas consuming vegetables was associated with decreased AαC. In addition, smoking one-half pack of cigarettes per day was associated with a significant increase of 23.6 pg AαC/mL calculated at geometric mean of AαC, controlling for potential confounders. In comparison, increase in AαC attributable to consuming the 99th percentile of beef cooked at high temperature was 0.99 pg AαC/mL. Conclusions: Both exclusive smokers and nonusers of tobacco in the general U.S. population are exposed to AαC from tobacco smoke, with additional, lesser contributions from certain dietary components. Impact: AαC is an important biomarker that is associated with tobacco smoke exposure.

Background Electronic cigarette (e-cigarette) conventions regularly bring together thousands of users around the world. In these environments, secondhand exposures to high concentrations of e-cigarette emissions are prevalent. Some biomarkers for tobacco smoke exposure may be used to characterize secondhand e-cigarette exposures in such an environment. Methods Participants who did not use any tobacco product attended four separate e-cigarette events for approximately six hours. Urine and saliva samples were collected from participants prior to the event, immediately after the event, 4-h after the event, and the next morning (first void). Urine samples from 34 participants were analyzed for cotinine, trans-3′-hydroxycotinine, S-(3-hydroxypropyl)-N-acetylcysteine (3-HPMA), S-carboxyethyl-N-acetylcysteine (CEMA), select tobacco-specific nitrosamines (TSNAs), and 8-isoprostane. Saliva samples were analyzed for cotinine and trans-3′-hydroxycotinine. Results Data from 28 of 34 participants were used in the data analysis. Creatinine-adjusted urinary cotinine concentrations increased up to 13-fold and peaked 4-h after completed exposure (range of adjusted geometric means [AGMs] = 0.352–2.31 μg/g creatinine). Salivary cotinine concentrations were also the highest 4-h after completed exposure (range of AGMs = 0.0373–0.167 ng/mL). Salivary cotinine and creatinine-corrected concentrations of urinary cotinine, trans-3′-hydroxycotinine, CEMA, and 3-HPMA varied significantly across sampling times. Urinary and salivary cotinine, urinary trans-3′-hydroxycotinine, and urinary 3-HPMA concentrations also varied significantly across events. Conclusion Secondhand e-cigarette exposures lasting six hours resulted in significant changes in exposure biomarker concentrations of both nicotine and acrolein but did not change exposure to tobacco-specific nitrosamines. Additional research is needed to understand the relationship between biomarker concentrations and environmental concentrations of toxicants in e-cigarette emissions.

Biomarkers of tobacco exposure are known to be associated with disease risk but previous studies are limited in number and restricted to certain regions. We conducted a nested case–control study examining baseline levels and subsequent lung cancer incidence among current male exclusive cigarette smokers in the Golestan Cohort Study in Iran. We calculated geometric mean biomarker concentrations for 28 matched cases and 52 controls for the correlation of biomarker levels among controls and for adjusted odds’ ratios (ORs) for lung cancer incidence by biomarker concentration, accounting for demographic characteristics, smoking quantity and duration, and opium use. Lung cancer cases had higher average levels of most biomarkers including total nicotine equivalents (TNE-2), 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL), and 3-hydroxyfluorene (3-FLU). Many biomarkers correlated highly with one another including TNE-2 with NNAL and N-Acetyl-S-(2-cyanoethyl)-L-cysteine (2CYEMA), and N-Acetyl-S-(4-hydroxy-2-buten-1-yl)-L-cysteine (t4HBEMA) with N-Acetyl-S-(3-hydroxypropyl-1-methyl)-L-cysteine (3HMPMA) and N-Acetyl-S-(4-hydroxy-2-methyl-2-buten-1-yl)-L-cysteine (4HMBEMA). Lung cancer risk increased with concentration for several biomarkers, including TNE-2 (OR = 2.22, 95% CI = 1.03, 4.78) and NNN (OR = 2.44, 95% CI = 1.13, 5.27), and estimates were significant after further adjustment for demographic and smoking characteristics for 2CYEMA (OR = 2.17, 95% CI = 1.03, 4.55), N-Acetyl-S-(2-carbamoylethyl)-L-cysteine (2CAEMA) (OR = 2.14, 95% CI = 1.01, 4.55), and N-Acetyl-S-(2-hydroxypropyl)-L-cysteine (2HPMA) (OR = 2.85, 95% CI = 1.04, 7.81). Estimates were not significant with adjustment for opium use. Concentrations of many biomarkers were higher at the baseline for participants who subsequently developed lung cancer than among the matched controls. Odds of lung cancer were higher for several biomarkers including with adjustment for smoking exposure for some but not with adjustment for opium use.

Background: Accumulating evidence suggests that non-daily smokers have higher disease and mortality risks than never smokers. Yet, the accuracy of self-reported non-daily cigarette smoking is poorly understood. Methods: We examined the concordance between self-reported non-daily smoking and serum cotinine in 18,835 adult participants (20 years or older) of the 2007 to 2014 National Health and Nutrition Examination Surveys, in comparison with daily smokers and nonsmokers. We also analyzed concentrations of the urinary biomarker 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) by smoking status. Results: In the study sample, 77.8% (14,660) reported currently not smoking (nonsmokers), 18.3% (3,446) smoked every day (daily smokers), and 3.9% (729) smoked on some days of the past month (non-daily smokers). Just 2.1% of nonsmokers had cotinine concentrations in the active smoking range (>10 ng/mL), compared with 70.4% of non-daily and 98.8% of daily smokers. Non-daily smokers reported smoking a median of 24 cigarettes per month [interquartile range (IQR) = 9–60] and had substantially higher concentrations of NNAL (median = 72.5; IQR = 14.8–211.0 pg/mL) than nonsmokers (median = 0.4; IQR = 0.4–2.1 pg/mL), although lower than daily smokers (median = 294.0; IQR = 148.0–542.0 pg/mL). Among non-daily smokers, concentrations of cotinine and NNAL were positively correlated with days and cigarettes smoked per month (P < 0.001). Conclusions: We observed excellent concordance between self-reported non-daily cigarette smoking and concentrations of serum cotinine. Impact: These results provide evidence for the validity of self-reported non-daily smoking and indicate that non-daily smokers are exposed to substantial concentrations of carcinogenic nitrosamines regardless of the low number of cigarettes they smoke per month.

The United States experienced an outbreak of e-cigarette, or vaping, product use-associated lung injury (EVALI) that began in August 2019. Patient diagnosis and treatment sometimes involved bronchoscopy and collection of the bronchoalveolar lavage (BAL) fluid. Although this matrix has been useful for understanding some chemical exposures in the lungs, no methods existed for measuring the nicotine content. Therefore, we developed a simple and sensitive method for measuring nicotine in the BAL fluid. Nicotine was extracted from the BAL fluid using acetone precipitation in a 96-well plate format to increase the sample throughput (200 samples/day). We optimized liquid chromatography column conditions (e.g., mobile phase, column temperature) and mass spectrometry parameters to improve the signal-to-noise ratio and lower limits of detection (LOD) for measuring nicotine in the BAL fluid. The LOD for nicotine in the BAL fluid was 0.050 ng/mL at a sample volume of 40 μL of the BAL fluid. The within-day and between-day imprecision and bias were less than 10%. This method detected nicotine in 15 of 43 BAL fluids from EVALI case patients. This method is useful for understanding recent inhalational exposure to nicotine as part of characterizing EVALI or similar illnesses.

Hookah smoking has become common in the USA, especially among young adults. This study measured biomarkers of exposure to known tobacco product toxicants in a population-based sample of exclusive, established hookah users. Urinary biomarker data from 1753 adults in Wave 1 of the Population Assessment of Tobacco and Health (PATH) Study were used to compare geometric mean concentrations of biomarkers of exposure in exclusive, established past 30-day hookah users to never users of tobacco. Geometric mean ratios were calculated comparing hookah user groups with never users adjusting for age, sex, race/ethnicity, education, past 30-day marijuana use, secondhand smoke exposure and creatinine. Past 30-day hookah users (n = 98) had 10.6 times the urinary cotinine level of never tobacco users. Compared to never tobacco users, past 30-day hookah users had 2.3 times the level of the carcinogen 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL), a metabolite of the tobacco-specific nitrosamine (TSNA) 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK), 1.3 times higher polycyclic aromatic hydrocarbons (PAHs) 3-hydroxyfluorene and 1-hydroxypyrene, 1.8 times higher levels of acrylonitrile, 1.3 times higher levels of acrylamide, and 1.2 times higher levels of acrolein exposure. These data indicate that hookah use is a significant source of exposure to nicotine, carcinogens, and respiratory toxicants.

Background: How carcinogen exposure varies across users of different, particularly noncigarette, tobacco products remains poorly understood. Methods: We randomly selected 165 participants of the Golestan Cohort Study from northeastern Iran: 60 never users of any tobacco, 35 exclusive cigarette, 40 exclusive (78% daily) waterpipe, and 30 exclusive smokeless tobacco (nass) users. We measured concentrations of 39 biomarkers of exposure in 4 chemical classes in baseline urine samples: tobacco alkaloids, tobacco-specific nitrosamines (TSNA), polycyclic aromatic hydrocarbons (PAH), and volatile organic compounds (VOC). We also quantified the same biomarkers in a second urine sample, obtained 5 years later, among continuing cigarette smokers and never tobacco users. Results: Nass users had the highest concentrations of tobacco alkaloids. All tobacco users had elevated TSNA concentrations, which correlated with nicotine dose. In both cigarette and waterpipe smokers, PAH and VOC biomarkers were higher than never tobacco users and nass users, and highly correlated with nicotine dose. PAH biomarkers of phenanthrene and pyrene and two VOC metabolites (phenylmercapturic acid and phenylglyoxylic acid) were higher in waterpipe smokers than in all other groups. PAH biomarkers among Golestan never tobacco users were comparable to those in U.S. cigarette smokers. All biomarkers had moderate to good correlations over 5 years, particularly in continuing cigarette smokers. Conclusions: We observed two patterns of exposure biomarkers that differentiated the use of the combustible products (cigarettes and waterpipe) from the smokeless product. Environmental exposure from nontobacco sources appeared to contribute to the presence of high levels of PAH metabolites in the Golestan Cohort. Impact: Most of these biomarkers would be useful for exposure assessment in a longitudinal study.

BACKGROUND: Over 19.5 million people worldwide abuse natural opiates, such as opium-derived products common in Central Asia and Middle East, and many of them also smoke cigarettes. However, there is little information on human exposure to carcinogens and other toxicants related to opiate use, alone or in combination with tobacco use. METHODS: Based on self-reported information, we randomly selected four groups of participants of the Golestan Cohort Study in Northeast Iran: 60 never users of either opiates or tobacco, 35 exclusive current cigarette smokers, 30 exclusive current opiate users, and 30 current opiate users who also smoked cigarettes (dual users; 21 smoked opiates and 9 took them by mouth). We quantified urinary concentrations of 39 exposure biomarkers in four chemical classes: tobacco alkaloids, tobacco specific nitrosamines (TSNAs), polycyclic aromatic hydrocarbons (PAHs), and volatile organic compounds (VOCs). Total nicotine equivalent (TNE) was used as a measure of nicotine dose. We used Oaxaca-Blinder decomposition to parse out the share of the biomarker concentrations explained by opiate use and nicotine dose. RESULTS: Exclusive opiate users and exclusive cigarette smokers had substantially higher concentrations of PAH and VOC biomarkers than never users of either product, but dual users had the highest concentrations. Decomposition analysis showed that opiate use contributed a larger part of the PAH concentrations than nicotine dose, and the sum of 2- and 3-hydroxyphenanthrene (∑(2,3)-phe) resulted almost completely (92%) from opiate use. Concentrations of most VOC biomarkers were explained by both nicotine dose and opiate use, but nicotine dose contributed more. Two acrylamide metabolites (AAMA: 90%, GAMA: 91%), the 1,3-butadiene metabolite (DHBM: 73%), and the dimethylformamide metabolite (AMCA: 72%) were more strongly explained by opiate use. Acrylamide metabolites and ∑(2,3)-phe were significantly higher in opiate smokers than opiate eaters; other biomarkers did not vary by the route of opiate intake. CONCLUSION: Both opiate users and cigarette smokers are exposed to several toxicants and carcinogens. Most biomarkers in opiate users were independent of exposure route, but a few were higher among opiate smokers than eaters. As opiates are widely used worldwide, exposure to some of these toxicants, including PAHs and VOCs, may have substantial global public health impact.

Background: Monitoring population-level toxicant exposures from smokeless tobacco (SLT) use is important for assessing population health risks due to product use. In this study, we assessed tobacco biomarkers of exposure (BOE) among SLT users from the Wave 1 (2013–2014) of the Population Assessment of Tobacco and Health (PATH) Study. Methods: Urinary biospecimens were collected from adults ages 18 and older. Biomarkers of nicotine, tobacco-specific nitrosamines (TSNA), polycyclic aromatic hydrocarbons (PAH), volatile organic compounds (VOC), metals, and inorganic arsenic were analyzed and reported among exclusive current established SLT users in comparison with exclusive current established cigarette smokers, dual SLT and cigarette users, and never tobacco users. Results: In general, SLT users (n = 448) have significantly higher concentrations of BOE to nicotine, TSNAs, and PAHs compared with never tobacco users; significant dose–response relationships between frequency of SLT use and biomarker concentrations were also reported among exclusive SLT daily users. Exclusive SLT daily users have higher geometric mean concentrations of total nicotine equivalent-2 (TNE2) and TSNAs than exclusive cigarette daily smokers. In contrast, geometric mean concentrations of PAHs and VOCs were substantially lower among exclusive SLT daily users than exclusive cigarette daily smokers. Conclusions: Our study produced a comprehensive assessment of SLT product use and 52 biomarkers of tobacco exposure. Compared with cigarette smokers, SLT users experience greater concentrations of some tobacco toxicants, including nicotine and TSNAs. Impact: Our data add information on the risk assessment of exposure to SLT-related toxicants. High levels of harmful constituents in SLT remain a health concern.

Background: 25-Hydroxyvitamin D (25(OH)D) deficiency is the most common complication of kidney disease. Previous studies have suggested that 25(OH)D deficiency is involved in the pathogenesis of anemia in kidney disease subjects not requiring dialysis. However, these associations have not been investigated in peritoneal dialysis (PD) patients. Objectives: The aim of this study was to elucidate the prospective relationship between 25-Hydroxyvitamin D insufficiency and anemia in PD Patients.Materials and Methods: In a cross-sectional study, 80 PD participants were included. Participants were divided into two groups based on baseline 25(OH)D3 concentrations: group 1, 25(OH)D3 levels

Heterocyclic aromatic amines (HCAA) are listed by the US Food and Drug Administration (FDA) as harmful or potentially harmful constituents of tobacco smoke. However, quantifying HCAA exposure is challenging. In this study, we developed a sensitive, precise, and accurate isotope dilution, liquid chromatography-tandem mass spectrometry (LC-MS/MS) method to quantify urinary HCAAs in smokers and nonsmokers. The high-throughput robotic sample preparation system could handle a throughput of over 300 samples per day, while maintaining intra-day and inter-day imprecision and bias ≤10 %. The limits of detection of carcinogenic HCAAs ranged from 0.31 to 0.83 pg/mL. The validated method was applied to measure HCAAs in urine collected from smokers and non-smokers. This sensitive and efficient analytical method is ideal to support large-scale biomonitoring studies of HCAA exposure. Graphical Abstract LC/MS/MS and robotic sample preparation system for urinary HCAA analysis.

BACKGROUND Primary deficiencies in mannosylation of N-glycans are seen in a majority of patients with congenital disorders of glycosylation (CDG). We report the discovery of a series of novel N-glycans in sera, plasma, and cultured skin fibroblasts from patients with CDG having deficient mannosylation. METHOD We used LC-MS/MS and MALDI-TOF-MS analysis to identify and quantify a novel N-linked tetrasaccharide linked to the protein core, an N-tetrasaccharide (Neu5Acα2,6Galβ1,4-GlcNAcβ1,4GlcNAc) in plasma, serum glycoproteins, and a fibroblast lysate from patients with CDG caused by ALG1 [ALG1 (asparagine-linked glycosylation protein 1), chitobiosyldiphosphodolichol β-mannosyltransferase], PMM2 (phosphomannomutase 2), and MPI (mannose phosphate isomerase). RESULTS Glycoproteins in sera, plasma, or cell lysate from ALG1-CDG, PMM2-CDG, and MPI-CDG patients had substantially more N-tetrasaccharide than unaffected controls. We observed a >80% decline in relative concentrations of the N-tetrasaccharide in MPI-CDG plasma after mannose therapy in 1 patient and in ALG1-CDG fibroblasts in vitro supplemented with mannose. CONCLUSIONS This novel N-tetrasaccharide could serve as a diagnostic marker of ALG1-, PMM2-, or MPI-CDG for screening of these 3 common CDG subtypes that comprise >70% of CDG type I patients. Its quantification by LC-MS/MS may be useful for monitoring therapeutic efficacy of mannose. The discovery of these small N-glycans also indicates the presence of an alternative pathway in N-glycosylation not recognized previously, but its biological significance remains to be studied.