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Abstract For detecting field carcinogenesis non-invasively, early technical development and case–control testing of exhaled breath condensate microRNAs was performed. In design, human lung tissue microRNA-seq discovery was reconciled with TCGA and published tumor-discriminant microRNAs, yielding a panel of 24 upregulated microRNAs. The airway origin of exhaled microRNAs was topographically “fingerprinted”, using paired EBC, upper and lower airway donor sample sets. A clinic-based case–control study (166 NSCLC cases, 185 controls) was interrogated with the microRNA panel by qualitative RT-PCR. Data were analyzed by logistic regression (LR), and by random-forest (RF) models. Feasibility testing of exhaled microRNA detection, including optimized whole EBC extraction, and RT and qualitative PCR method evaluation, was performed. For sensitivity in this low template setting, intercalating dye-based URT-PCR was superior to fluorescent probe-based PCR (TaqMan). In application, adjusted logistic regression models identified exhaled miR-21, 33b, 212 as overall case–control discriminant. RF analysis of combined clinical + microRNA models showed modest added discrimination capacity (1.1–2.5%) beyond clinical models alone: all subjects 1.1% (p = 8.7e−04)); former smokers 2.5% (p = 3.6e−05); early stage 1.2% (p = 9.0e−03), yielding combined ROC AUC ranging from 0.74 to 0.83. We conclude that exhaled microRNAs are qualitatively measureable, reflect in part lower airway signatures; and when further refined/quantitated, can potentially help to improve lung cancer risk assessment.

Gene regulatory analysis of highly diverse human tissues in vivo is essentially constrained by the challenge of performing genome-wide, integrated epigenetic and transcriptomic analysis in small selected groups of specific cell types. Here we performed genome-wide bisulfite sequencing and RNA-seq from the same small groups of bronchial and alveolar cells isolated by laser capture microdissection from flash-frozen lung tissue of 12 donors and their peripheral blood T cells. Methylation and transcriptome patterns differed between alveolar and bronchial cells, while each of these epithelia showed more differences from mesodermally-derived T cells. Differentially methylated regions (DMRs) between alveolar and bronchial cells tended to locate at regulatory regions affecting promoters of 4,350 genes. A large number of pathways enriched for these DMRs including GTPase signal transduction, cell death, and skeletal muscle. Similar patterns of transcriptome differences were observed: 4,108 differentially expressed genes (DEGs) enriched in GTPase signal transduction, inflammation, cilium assembly, and others. Prioritizing using DMR-DEG regulatory network, we highlighted genes, e.g., ETS1, PPARG, and RXRG, at prominent alveolar vs. bronchial cell discriminant nodes. Our results show that multi-omic analysis of small, highly specific cells is feasible and yields unique physiologic loci distinguishing human lung cell types in situ.

Aberrant cytosine 5-methylation underlies many deregulated elements of cancer. Among paired non-small cell lung cancers (NSCLC), we sought to profile DNA 5-methyl-cytosine features which may underlie genome-wide deregulation. In one of the more dense interrogations of the methylome, we sampled 1.2 million CpG sites from twenty-four NSCLC tumor (T)-non-tumor (NT) pairs using a methylation-sensitive restriction enzyme- based HELP-microarray assay. We found 225,350 differentially methylated (DM) sites in adenocarcinomas versus adjacent non-tumor tissue that vary in frequency across genomic compartment, particularly notable in gene bodies (GB; p