Description: Purpose: Most non–small cell lung cancers (NSCLC) are now diagnosed from small specimens, and classification using standard pathology methods can be difficult. This is of clinical relevance as many therapy regimens and clinical trials are histology dependent. The purpose of this study was to develop an mRNA expression signature as an adjunct test for routine histopathologic classification of NSCLCs. Experimental Design: A microarray dataset of resected adenocarcinomas (ADC) and squamous cell carcinomas (SCC) was used as the learning set for an ADC-SCC signature. The Cancer Genome Atlas (TCGA) lung RNAseq dataset was used for validation. Another microarray dataset of ADCs and matched nonmalignant lung was used as the learning set for a tumor versus nonmalignant signature. The classifiers were selected as the most differentially expressed genes and sample classification was determined by a nearest distance approach. Results: We developed a 62-gene expression signature that contained many genes used in immunostains for NSCLC typing. It includes 42 genes that distinguish ADC from SCC and 20 genes differentiating nonmalignant lung from lung cancer. Testing of the TCGA and other public datasets resulted in high prediction accuracies (93%–95%). In addition, a prediction score was derived that correlates both with histologic grading and prognosis. We developed a practical version of the Classifier using the HTG EdgeSeq nuclease protection–based technology in combination with next-generation sequencing that can be applied to formalin-fixed paraffin-embedded (FFPE) tissues and small biopsies. Conclusions: Our RNA classifier provides an objective, quantitative method to aid in the pathologic diagnosis of lung cancer. Clin Cancer Res; 22(19); 4880–9. ©2016 AACR .

Description: Objective American Indians (AI) have a high prevalence of electronic nicotine delivery system (ENDS) use. However, little information exists on (ENDS) use, either alone or in combination with cigarettes (dual use), among AI. The objective of this small-scaled study was to examine use behaviours and dependence among exclusive ENDS users and dual users of AI descent. Exclusive smokers were included for comparison purposes. Setting Oklahoma, USA. Participants Adults of AI descent who reported being exclusive ENDS users (n=27), dual users (n=28) or exclusive cigarette smokers (n=27). Measures Participants completed a detailed questionnaire on use behaviours. The Hooked on Nicotine Checklist (HONC) was used to assess loss of autonomy over cigarettes and was reworded for ENDS. Dual users completed the HONC twice. Sum of endorsed items indicated severity of diminished autonomy. Comparisons were made with non-parametric methods and statistical significance was defined as P〈0.05. Results Median duration of ENDS use was 2 years among ENDS users and 1 year among dual users. Most ENDS and dual users reported 〈20 vape sessions per day (72.0% vs 72.0%) with ≤10 puffs per vape session (70.4% vs 69.2%). Severity of diminished autonomy over ENDS was similar among ENDS and dual users (medians: 4 vs 3; P=0.6865). Among dual users, severity of diminished autonomy was lower for ENDS than cigarettes (medians: 3 vs 9; P=〈0.0001). Comparing ENDS users with smokers, ENDS users had a lower severity of diminished autonomy (4 vs 8; P=0.0077). Comparing dual users with smokers, median severity of diminished autonomy over cigarettes did not differ (P=0.6865). Conclusions Severity of diminished autonomy was lower for ENDS than cigarettes in this small sample of AI. Future, adequately powered studies should be conducted to fully understand ENDS use patterns and dependence levels in this population.