The e-liquids used in electronic cigarettes (E-cigs) consist of propylene glycol (PG), vegetable glycerin (VG), nicotine, and chemical additives for flavoring. There are currently over 7,700 e-liquid flavors available, and while some have been tested for toxicity in the laboratory, most have not. Here, we developed a 3-phase, 384-well, plate-based, high-throughput screening (HTS) assay to rapidly triage and validate the toxicity of multiple e-liquids. Our data demonstrated that the PG/VG vehicle adversely affected cell viability and that a large number of e-liquids were more toxic than PG/VG. We also performed gas chromatography–mass spectrometry (GC-MS) analysis on all tested e-liquids. Subsequent nonmetric multidimensional scaling (NMDS) analysis revealed that e-liquids are an extremely heterogeneous group. Furthermore, these data indicated that (i) the more chemicals contained in an e-liquid, the more toxic it was likely to be and (ii) the presence of vanillin was associated with higher toxicity values. Further analysis of common constituents by electron ionization revealed that the concentration of cinnamaldehyde and vanillin, but not triacetin, correlated with toxicity. We have also developed a publicly available searchable website (www.eliquidinfo.org). Given the large numbers of available e-liquids, this website will serve as a resource to facilitate dissemination of this information. Our data suggest that an HTS approach to evaluate the toxicity of multiple e-liquids is feasible. Such an approach may serve as a roadmap to enable bodies such as the Food and Drug Administration (FDA) to better regulate e-liquid composition.

Motivation Splice variant neoantigens are a potential source of tumor-specific antigen (TSA) that are shared between patients in a variety of cancers, including acute myeloid leukemia (AML). Current tools for genomic prediction of splice variant neoantigens demonstrate promise. However, many tools have not been well validated with simulated and/or wet lab approaches, with no studies published that have presented a targeted immunopeptidome mass spectrometry approach designed specifically for identification of predicted splice variant neoantigens. Results In this study, we describe NeoSplice, a novel computational method for splice variant neoantigen prediction based on 1) prediction of tumor-specific k-mers from RNA-seq data, 2) alignment of differentially expressed k-mers to the splice graph, and 3) inference of the variant transcript with MHC binding prediction. NeoSplice demonstrates high sensitivity and precision (>80% on average across all splice variant classes) through in silico simulated RNA-seq data. Through mass spectrometry analysis of the immunopeptidome of the K562.A2 cell line compared against a synthetic peptide reference of predicted splice variant neoantigens, we validated four of 37 predicted antigens corresponding to three of 17 unique splice junctions. Lastly, we provide a comparison of NeoSplice against other splice variant prediction tools described in the literature. NeoSplice provides a well-validated platform for prediction of TSA vaccine targets for future cancer antigen vaccine studies to evaluate the clinical efficacy of splice variant neoantigens. Availability https://github.com/Benjamin-Vincent-Lab/NeoSplice Supplementary information Supplementary data are available at Bioinformatics Advances online.

Nicotine is the primary psychoactive chemical in both traditional and electronic cigarettes (e-cigarettes). Nicotine levels in both traditional cigarettes and e-cigarettes are an important concern for public health. Nicotine exposure due to e-cigarette use is of importance primarily due to the addictive potential of nicotine, but there is also concern for nicotine poisoning in e-cigarette users. Nicotine concentrations in e-liquids vary widely. Additionally, there is significant genetic variability in the rate of metabolism of nicotine due to polymorphisms of CYP2A6, the enzyme responsible for the metabolism of approximately 80% of nicotine. Recent studies have shown CYP2A6 activity is also reduced by aromatic aldehydes such as those added to e-liquids as flavoring agents, which may increase nicotine serum concentrations. However, the impacts of flavored e-liquids on CYP2A6 activity are unknown. In this study, we investigated the impact of three flavored e-liquids on microsomal recombinant CYP2A6. Microsomal recombinant CYP2A6 was challenged at e-liquid concentrations ranging up to 0.125% (v/v) and monitored for metabolic activity using a probe molecule approach. Two e-liquids exhibited dose-dependent inhibition of CYP2A6 activity. Mass spectrometry was conducted to identify flavoring agents in flavored e-liquids that inhibited CYP2A6. Microsomal recombinant CYP2A6 was subsequently exposed to flavoring agents at concentrations ranging from 0.03 μM to 500 μM. Cinnamaldehyde and benzaldehyde were found to be the most potent inhibitors of microsomal CYP2A6 of the flavoring agents tested, with identified IC50 values of 1.1 μM and 3.0 μM, respectively. These data indicate certain aromatic aldehyde flavoring agents are potent inhibitors of CYP2A6, which may reduce nicotine metabolism in vivo. These findings indicate an urgent need to evaluate the effects of flavoring agents in e-cigarette liquids on the pharmacokinetics of nicotine in vivo.

Certain e-liquids and aromatic aldehyde flavoring agents were previously identified as inhibitors of microsomal recombinant CYP2A6, the primary nicotine-metabolizing enzyme. However, due to their reactive nature, aldehydes may react with cellular components before reaching CYP2A6 in the endoplasmic reticulum. To determine whether e-liquid flavoring agents inhibited CYP2A6 in a cellular system, we investigated their effects on CYP2A6 using BEAS-2B cells transduced to overexpress CYP2A6. We demonstrated that two e-liquids and three aldehyde flavoring agents (cinnamaldehyde, benzaldehyde, and ethyl vanillin) exhibited dose-dependent inhibition of cellular CYP2A6.