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BackgroundStandardized Nucleic Acid Quantification for SEQuencing (SNAQ-SEQ) is a novel method that utilizes synthetic DNA internal standards spiked into each sample prior to next generation sequencing (NGS) library preparation. This method was applied to analysis of normal appearing airway epithelial cells (AEC) obtained by bronchoscopy in an effort to define a somatic mutation field effect associated with lung cancer risk. There is a need for biomarkers that reliably detect those at highest lung cancer risk, thereby enabling more effective screening by annual low dose CT. The purpose of this study was to test the hypothesis that lung cancer risk is characterized by increased prevalence of low variant allele frequency (VAF) somatic mutations in lung cancer driver genes in AEC.MethodsSynthetic DNA internal standards (IS) were prepared for 11 lung cancer driver genes and mixed with each AEC genomic (g) DNA specimen prior to competitive multiplex PCR amplicon NGS library preparation. A custom Perl script was developed to separate IS reads and respective specimen gDNA reads from each target into separate files for parallel variant frequency analysis. This approach identified nucleotide-specific sequencing error and enabled reliable detection of specimen mutations with VAF as low as 5 × 10− 4(0.05%). This method was applied in a retrospective case-control study of AEC specimens collected by bronchoscopic brush biopsy from the normal airways of 19 subjects, including eleven lung cancer cases and eight non-cancer controls, and the association of lung cancer risk with AEC driver gene mutations was tested.ResultsTP53 mutations with 0.05–1.0% VAF were more prevalent (p ConclusionsApplication of SNAQ-SEQ to measure mutations in the 0.05–1.0% VAF range enabled identification of an AEC somatic mutation field of injury associated with lung cancer risk. A biomarker comprising TP53, PIK3CA, and BRAF somatic mutations may better stratify individuals for optimal lung cancer screening and prevention outcomes.

Background Annual low dose CT (LDCT) screening of individuals at high demographic risk reduces lung cancer mortality by more than 20%. However, subjects selected for screening based on demographic criteria typically have less than a 10% lifetime risk for lung cancer. Thus, there is need for a biomarker that better stratifies subjects for LDCT screening. Toward this goal, we previously reported a lung cancer risk test (LCRT) biomarker comprising 14 genome-maintenance (GM) pathway genes measured in normal bronchial epithelial cells (NBEC) that accurately classified cancer (CA) from non-cancer (NC) subjects. The primary goal of the studies reported here was to optimize the LCRT biomarker for high specificity and ease of clinical implementation. Methods Targeted competitive multiplex PCR amplicon libraries were prepared for next generation sequencing (NGS) analysis of transcript abundance at 68 sites among 33 GM target genes in NBEC specimens collected from a retrospective cohort of 120 subjects, including 61 CA cases and 59 NC controls. Genes were selected for analysis based on contribution to the previously reported LCRT biomarker and/or prior evidence for association with lung cancer risk. Linear discriminant analysis was used to identify the most accurate classifier suitable to stratify subjects for screening. Results After cross-validation, a model comprising expression values from 12 genes (CDKN1A, E2F1, ERCC1, ERCC4, ERCC5, GPX1, GSTP1, KEAP1, RB1, TP53, TP63, and XRCC1) and demographic factors age, gender, and pack-years smoking, had Receiver Operator Characteristic area under the curve (ROC AUC) of 0.975 (95% CI: 0.96–0.99). The overall classification accuracy was 93% (95% CI 88%–98%) with sensitivity 93.1%, specificity 92.9%, positive predictive value 93.1% and negative predictive value 93%. The ROC AUC for this classifier was significantly better (p

Background Cigarette smoking is the primary cause of bronchogenic carcinoma (BC), yet only 10–15% of heavy smokers develop BC and it is likely that this variation in risk is, in part, genetically determined. We previously reported a set of antioxidant genes for which transcript abundance was lower in normal bronchial epithelial cells (NBEC) of BC individuals compared to non-BC individuals. In unpublished studies of the same NBEC samples, transcript abundance values for several DNA repair genes were correlated with these antioxidant genes. From these data, we hypothesized that antioxidant and DNA repair genes are co-regulated by one or more transcription factors and that inter-individual variation in expression and/or function of one or more of these transcription factors is responsible for inter-individual variation in risk for BC. Methods The putative transcription factor recognition sites common to six of the antioxidant genes were identified through in silico DNA sequence analysis. The transcript abundance values of these transcription factors (n = 6) and an expanded group of antioxidant and DNA repair genes (n = 16) were measured simultaneously by quantitative PCR in NBEC of 24 non-BC and 25 BC individuals. Results CEBPG transcription factor was significantly (p < 0.01) correlated with eight of the antioxidant or DNA repair genes in non-BC individuals but not in BC individuals. In BC individuals the correlation with CEBPG was significantly (p < 0.01) lower than that of non-BC individuals for four of the genes (XRCC1, ERCC5, GSTP1, and SOD1) and the difference was nearly significant for GPX1. The only other transcription factor correlated with any of these five target genes in non-BC individuals was E2F1. E2F1 was correlated with GSTP1 among non-BC individuals, but in contrast to CEBPG, there was no significant difference in this correlation in non-BC individuals compared to BC individuals. Conclusion We conclude that CEBPG is the transcription factor primarily responsible for regulating transcription of key antioxidant and DNA repair genes in non-BC individuals. Further, we conclude that the heavy smokers selected for development of BC are those who have sub-optimal regulation of antioxidant and DNA repair genes by CEBPG.