2018_TSRC74_Makena.pdf Urinary Leukotriene E4 And 2,3-dinor Thromboxane B2: Potential Biomarkers of Effect for Tobacco Product Evaluations Patrudu Makena, Gang Liu, Peter Chen, and G.L. Prasad RAI Services Company, Winston-Salem, NC 27101 72nd Tobacco Science Research Conference 16-19 September 2018 - Memphis, Tennessee USA 1 TSRC2018(72) - Document not peer-reviewed 2018_TSRC74_Makena.pdf Biomarkers of Tobacco Effect/Potential Harm (BioEff) • What are biomarkers of effect? – Biological indicators of the body’s response to exposure – Indicate early sub-clinical changes, which if sustained, may contribute to pathological consequences • Why do we need biomarkers of effect? – BioEff enable the assessment of the biological response when consumers switch from combustible cigarettes to potential reduced exposure products – BioEff could be useful for modified risk tobacco product evaluations1 • Several BioEff have been described1 – For Example: Forced Expiratory Volume in 1 second (FEV1), White Blood Cell (WBC) count – However, some challenges still remain 1Hatsukami et al., Nicotine Tob Res, 2006. 8(4): p. 600-22 2 TSRC2018(72) - Document not peer-reviewed 2018_TSRC74_Makena.pdf Need for Short-term Biomarkers of Effect (BioEff) Short-term BioEff Long-term BioEff . Early biochemical changes . Not responsive to short-term changes . Relationship between Biomarkers of Exposure . Need long-term clinical studies (BioExp) and BioEff . Subject noncompliance to study protocol . Better compliance to clinical study protocol . Resource intensive . Cost-effective compared to long-term studies Smoking Cessation 2 weeks Day 1 ≥ 1 year . Short-term BioEff can be valuable tools for evaluation in tobacco product-switching studies . Biological responses potentially leading to pathophysiological changes associated with tobacco use 3 TSRC2018(72) - Document not peer-reviewed 2018_TSRC74_Makena.pdf RAIS Biomarker Development Studies • Investigated Arachidonic Acid (AA) metabolites – Metabolomics – Cross sectional studies – Published literature • AA metabolites biologically and pharmacologically important 4 TSRC2018(72) - Document not peer-reviewed Metabolites of Arachidonic Acid in Smokers (SMK) and 2018_TSRC74_Makena.pdf Moist Snuff Consumers (MSC) • Arachidonic acid is a key precursor molecule in inflammatory pathways • Several metabolites of arachidonic acid were measured under GLP conditions and the results are presented in this “spider plot”2. • Although SMK exhibit a distinct inflammatory status pattern across multiple analytes, MSC and non-tobacco consumers (NTC) exhibit similar patterns, indicating overall similarity in the inflammatory status in the non- smoking (MSC and NTC) cohorts 2Prasad et al., Clin Chem Lab Med 2016. 54(4):p. 633–642 5 TSRC2018(72) - Document not peer-reviewed Arachidonic Acid Pathway 2018_TSRC74_Makena.pdf Cell membrane phospholipids Several AA metabolites are impacted by smoking (internal and published literature)3 3Harizi et al., Trends Mol Med, 2008.14(10):p. 461-9. 6 TSRC2018(72) - Document not peer-reviewed 2018_TSRC74_Makena.pdf Study Approach • Biological samples derived from three internal short-term confinement studies 1. Smoking abstinence (Study I) 2. Product switching from combustible to smokeless tobacco products (Study II) 3. Product switching from combustible to ENDS products (Study III) • Methodology – LC-MS/MS at ABF GmbH (Munich, Germany) • Select arachidonic acid markers: nine metabolites – PGF2α, 8-i-PGF2α, 2,3-d-8-i-PGF2α, t-PGDM, t-PGEM (prostaglandins) – 2,3-d-TXB2, 11-d-TXB2 (thromboxanes) –LTE4 (leukotrienes) – 12(S)-HETE (hydroxyeicosatetraenoic acid) 7 TSRC2018(72) - Document not peer-reviewed 2018_TSRC74_Makena.pdf Samples, Studies and Biomarker Development Process Biomarker Phase Discovery Qualification Utilization Study I: CPDR Study Study II: STP Study Study III: ENDS Exposure Study Not a brand-specific study Snus, Sticks, Strips and Orbs Two ENDS products 5-day (confinement) 5-day (confinement) 5-day (confinement) Smokers reduced # cigarettes / quit Smokers switched to products / quit Smokers switched to ENDS products . AA metabolites are important regulators of diverse physiological activities. A select panel of AA metabolites was analyzed in 24h urine samples collected in the above three studies in a phased approach. 8 TSRC2018(72) - Document not peer-reviewed 2018_TSRC74_Makena.pdf Study I: Cigarette Per Day Reduction (CPDR) study • CPDR study4 – A single-center, randomized, controlled, open-label, parallel group study designed to evaluate the dose-effect relationships between CPDR and BioExp • Study Group (n) – Tobacco abstinence (30) • Sample Analysis – 24 hour urine samples from smokers switched from 19-25 CPD to abstinence (“0 CPD”) 4Theophilus et al. (2015). Regul Toxicol Pharmacol. 71(2): p. 225-34 9 TSRC2018(72) - Document not peer-reviewed 2018_TSRC74_Makena.pdf Study I: Leukotriene E4 (LTE4) 20 CPD 0 CPD • LTE4 is significantly different in smokers switched to abstinence for 5 days 10 TSRC2018(72) - Document not peer-reviewed 2018_TSRC74_Makena.pdf Study II: Smokeless Tobacco Product (STP) Study • STP Study5 – A multi-center, open-label, randomized, parallel cohort, forced-switching study designed to evaluate changes in tobacco product use behavior and levels of selected BioExp • Study Groups (n) – Tobacco abstinence (24) – Exclusive Snus use (27) – Exclusive Sticks use (28) – Exclusive Strips use (24) – Exclusive Orbs (28) – Dual use of usual brand (UB) cigarettes and snus (25) • Sample Analysis – 24 hour urine samples from smokers switched to STP, dual use or abstinence for 5 days 5Krautter et al. (2015) Regul Toxicol Pharmacol. 71(2): p.186-97 11 TSRC2018(72) - Document not peer-reviewed Study II: Leukotriene E4 (LTE4) 2018_TSRC74_Makena.pdf Tobacco Abstinence Snus Orbs Sticks Before After Before After Before After Before After Switch Switch Switch Switch Switch Switch Switch Switch Strips Dual Use (UB+Snus) • LTE4 levels significantly decreased in all groups except in Dual Use. Before After Before After Switch Switch Switch Switch 12 TSRC2018(72) - Document not peer-reviewed Study II: 2,3-dinor Thromboxane B2 (2,3 d-TXB2) 2018_TSRC74_Makena.pdf Tobacco Abstinence Snus Orbs Sticks Before After Before After Before After Before After Switch Switch Switch Switch Switch Switch Switch Switch Strips Dual Use (UB+Snus) • 2,3 d-TXB2 levels significantly decreased in all groups. Before After Before After Switch Switch Switch Switch 13 TSRC2018(72) - Document not peer-reviewed 2018_TSRC74_Makena.pdf Study III: Electronic Nicotine Delivery Systems (ENDS) Study • ENDS Study6 – A single-center, randomized, controlled, open-label, parallel cohort switching study designed to evaluate changes in BioExp of smokers switched to ENDS • Study Groups (n) – ENDS Vuse Solo Original variant (38) – ENDS Vuse Solo Menthol variant (40) • Sample Analysis – 24 hour urine samples from smokers switched from usual brand cigarettes to ENDS-Original or ENDS-Menthol for 5 days 6Round et al. (2018) Nicotine Tob Res, 2018: doi:10.1093/ntr/nty140 14 TSRC2018(72) - Document not peer-reviewed 2018_TSRC74_Makena.pdf Study III: Leukotriene E4 (LTE4) ENDS-Original ENDS-Menthol Before After Before After Switch Switch Switch Switch . LTE4 in ENDS-Original and -Menthol variant groups was not statistically different . Possibly due to one outlier from each group 15 TSRC2018(72) - Document not peer-reviewed 2018_TSRC74_Makena.pdf Study III: 2,3-dinor Thromboxane B2 (2,3 d-TXB2) ENDS-Original ENDS-Menthol Before After Before After Switch Switch Switch Switch . 2,3 d-TXB2 in ENDS-Original and -Menthol groups were statistically different after 5-day product switch 16 TSRC2018(72) - Document not peer-reviewed Summary of 2,3-d-TXB2 and LTE4: Percent Change 2018_TSRC74_Makena.pdf After a 5-Day Product Switching Outliers Excluded % Change % Change % Change Study # Products use 2,3-d-TXB2 LTE4 LTE4 Study I: CPD Abstinence -16.1 -39.5 Abstinence -48.3 -39.2 Orbs -42.6 -38.2 Snus -39.3 -43.3 Study II: STP Sticks -24.3 -26.0 Strips -44.5 -34.3 Dual Use -34.5 -5.0 ENDS-Menthol -44.2 -17.5 -32 (p<0.001) Study III: ENDS ENDS-Original -43.8 -20.3 -33 (p<0.001) 17 TSRC2018(72) - Document not peer-reviewed 2018_TSRC74_Makena.pdf Biomarker Performance • A Biomarker-based Machine Learning Model – Constructed to differentiate the changes upon product switching – Used to evaluate the performance of selected biomarkers • The performance is defined as the classifier’s ability to identify the groups correctly • A Classification Model for Evaluation of ENDS – ENDS-Original data in Study III were used to: • build, train, and cross-validate the model – Independent validation using: • ENDS-Menthol data in Study III • Smoking Abstinence data in Study I and II 18 TSRC2018(72) - Document not peer-reviewed Receiver Operator Characteristic (ROC) curve 2018_TSRC74_Makena.pdf ROC curve7 TPR=1; FPR=0 False Positive Rate (FPR) Ideal model Total number of False Positive/Total number of Actual (NO) True Positive Rate (TPR) Rate Positive True Total number of True Positive/Total number of Actual (YES) Binary classification model False Positive Rate . The area under the ROC curve (AUC) summarizes the predictive power of a binary classification model. 7https://ifordata.wordpress.com/category/predictions-in-r/ 19 TSRC2018(72) - Document not peer-reviewed 2018_TSRC74_Makena.pdf Classification Model: Result • Biomarker-based classification model works well in differentiating cigarette smoking or ENDS use ENDS-Original (AUC=0.88) ENDS-Menthol (AUC=0.82) Smoking