Faculty Bibliography

In lung cancer, enrichment of the lower airway microbiota with oral commensals commonly occurs and ex vivo models support that some of these bacteria can trigger host transcriptomic signatures associated with carcinogenesis. Here, we show that this lower airway dysbiotic signature was more prevalent in group IIIB-IV TNM stage lung cancer and is associated with poor prognosis, as shown by decreased survival among subjects with early stage disease (I-IIIA) and worse tumor progression as measured by RECIST scores among subjects with IIIB-IV stage disease. In addition, this lower airway microbiota signature was associated with upregulation of IL-17, PI3K, MAPK and ERK pathways in airway transcriptome, and we identified Veillonella parvula as the most abundant taxon driving this association. In a KP lung cancer model, lower airway dysbiosis with V. parvula led to decreased survival, increased tumor burden, IL-17 inflammatory phenotype and activation of checkpoint inhibitor markers.

BACKGROUND:Emphysema in asymptomatic heavy smokers can be detected during CT-scan screening for lung cancer. Metalloproteinases (MMPs) have been found to play a role in the pathogenesis of chronic obstructive pulmonary disease and to possibly serve as biomarkers for emphysema. METHODS:The NYU Lung Cancer Biomarker Center enrolled study subjects over 50 years of age with lung cancer risk factors from January 1, 2010, to December 31, 2015. These subjects received chest multi-detector computed tomography, spirometry, and provided serum for immunoassays for metalloproteinases (MMP) -1, -2, -7, -9, -10 and tissue inhibitor of metalloproteinases (TIMP) -1 and -2. RESULTS:/FVC percent compared to smokers without emphysema (68 ± 11 (mean ± sd) versus 75 ± 8; p < 0.0001). Increased age and pack-years of smoking were associated with increased odds of emphysema. None of the metalloproteinases or tissue inhibitors of metalloproteinases were useful to predict the presence of emphysema in smokers. CONCLUSION/CONCLUSIONS:/FVC ratio).

: Low-dose CT (LDCT) is widely accepted as the preferred method for detecting pulmonary nodules. However, the determination of whether a nodule is benign or malignant involves either repeated scans or invasive procedures that sample the lung tissue. Noninvasive methods to assess these nodules are needed to reduce unnecessary invasive tests. In this study, we have developed a pulmonary nodule classifier (PNC) using RNA from whole blood collected in RNA-stabilizing PAXgene tubes that addresses this need. Samples were prospectively collected from high-risk and incidental subjects with a positive lung CT scan. A total of 821 samples from 5 clinical sites were analyzed. Malignant samples were predominantly stage 1 by pathologic diagnosis and 97% of the benign samples were confirmed by 4 years of follow-up. A panel of diagnostic biomarkers was selected from a subset of the samples assayed on Illumina microarrays that achieved a ROC-AUC of 0.847 on independent validation. The microarray data were then used to design a biomarker panel of 559 gene probes to be validated on the clinically tested NanoString nCounter platform. RNA from 583 patients was used to assess and refine the NanoString PNC (nPNC), which was then validated on 158 independent samples (ROC-AUC = 0.825). The nPNC outperformed three clinical algorithms in discriminating malignant from benign pulmonary nodules ranging from 6-20 mm using just 41 diagnostic biomarkers. Overall, this platform provides an accurate, noninvasive method for the diagnosis of pulmonary nodules in patients with non-small cell lung cancer. SIGNIFICANCE: These findings describe a minimally invasive and clinically practical pulmonary nodule classifier that has good diagnostic ability at distinguishing benign from malignant pulmonary nodules.

BACKGROUND:In lung cancer, upregulation of the PI3K pathway is an early event that contributes to cell proliferation, survival, and tissue invasion. Upregulation of this pathway was recently described as associated with enrichment of the lower airways with bacteria identified as oral commensals. We hypothesize that host-microbe interactions in the lower airways of subjects with lung cancer affect known cancer pathways. METHODS:Airway brushes were collected prospectively from subjects with lung nodules at time of diagnostic bronchoscopy, including 39 subjects with final lung cancer diagnoses and 36 subjects with non-cancer diagnosis. Additionally, samples from 10 healthy control subjects were included. 16S rRNA gene amplicon sequencing and paired transcriptome sequencing (RNAseq) were performed on all airway samples. In addition, an in vitro model with airway epithelial cells exposed to bacteria/bacterial products was performed. RESULTS:The composition of the lower airway transcriptome in the cancer patients was significantly different from the controls, which included upregulation of ERK and PI3K signaling pathways. The lower airways of lung cancer patients were enriched for oral taxa (Streptococcus and Veillonella), which was associated with upregulation of the ERK and PI3K signaling pathways. In vitro exposure of airway epithelial cells to Veillonella, Prevotella, and Streptococcus led to upregulation of these same signaling pathways. CONCLUSIONS:The data presented here shows that several transcriptomic signatures previously identified as relevant to lung cancer pathogenesis are associated with enrichment of the lower airway microbiota with oral commensals.

It remains unclear whether PAX6 acts as a crucial transcription factor for lung cancer stem cell (CSC) traits. We demonstrate that PAX6 acts as an oncogene responsible for induction of cancer stemness properties in lung adenocarcinoma (LUAD). Mechanistically, PAX6 promotes GLI transcription, resulting in SOX2 upregulation directly by the binding of GLI to the proximal promoter region of the SOX2 gene. The overexpressed SOX2 enhances the expression of key pluripotent factors (OCT4 and NANOG) and suppresses differentiation lineage factors (HOPX and NKX2-1), driving cancer cells toward a stem-like state. In contrast, in the differentiated non-CSCs, PAX6 is transcriptionally silenced by its promoter methylation. In human lung cancer tissues, the positive linear correlations of PAX6 expression with GLI and SOX2 expression and its negative correlations with HOPX and NKX2-1 expression were observed. Therapeutically, the blockade of the PAX6-GLI-SOX2 signaling axis elicits a long-lasting therapeutic efficacy by limiting CSC expansion following chemotherapy. Furthermore, a methylation panel including the PAX6 gene yielded a sensitivity of 79.1% and specificity of 83.3% for cancer detection using serum DNA from stage IA LUAD. Our findings provide a rationale for targeting the PAX6-GLI-SOX2 signaling axis with chemotherapy as an effective therapeutic strategy and support the clinical utility of PAX6 gene promoter methylation as a biomarker for early lung cancer detection.

Tobacco smoke (TS) contains numerous cancer-causing agents, with polycyclic aromatic hydrocarbons (PAHs) and nitrosamines being most frequently cited as the major TS human cancer agents. Many lines of evidence seriously question this conclusion. To resolve this issue, we determined DNA adducts induced by the three major TS carcinogens: benzo(a)pyrene (BP), 4-(methylnitrosamine)-1-(3-pyridyl)-1-butanoe (NNK), and aldehydes in humans and mice. In mice, TS induces abundant aldehyde-induced γ-hydroxy-propano-deoxyguanosine (γ-OH-PdG) and α-methyl-γ-OH-PdG adducts in the lung and bladder, but not in the heart and liver. TS does not induce the BP- and NNK-DNA adducts in lung, heart, liver, and bladder. TS also reduces DNA repair activity and the abundance of repair proteins, XPC and OGG1/2, in lung tissues. These TS effects were greatly reduced by diet with polyphenols. We found that γ-OH-PdG and α-methyl-γ-OH-PdG are the major adducts formed in tobacco smokers' buccal cells as well as the normal lung tissues of tobacco-smoking lung cancer patients, but not in lung tissues of nonsmokers. However, the levels of BP- and NNK-DNA adducts are the same in lung tissues of smokers and nonsmokers. We found that while BP and NNK can induce BPDE-dG and O⁶-methyl-dG adducts in human lung and bladder epithelial cells, these inductions can be inhibited by acrolein. Acrolein also can reduce DNA repair activity and repair proteins. We propose a TS carcinogenesis paradigm. Aldehydes are major TS carcinogens exerting dominant effect: Aldehydes induce mutagenic PdG adducts, impair DNA repair functions, and inhibit many procarcinogens in TS from becoming DNA-damaging agents.

While long-term survival rates for early-stage lung cancer are high, most cases are diagnosed in later stages that can negatively impact survival rates. We aim to design a simple, single biomarker blood test for early-stage lung cancer that is robust to preclinical variables and can be readily implemented in the clinic. Whole blood was collected in PAXgene tubes from a training set of 29 patients, and a validation set of 260 patients, of which samples from 58 patients were prospectively collected in a clinical trial specifically for this study. After RNA was extracted, the expression of FPR1 and a reference gene were quantified by an automated one-step Taqman RT-PCR assay. Elevated levels of FPR1 mRNA in whole blood predicted lung cancer status with a sensitivity of 55% and a specificity of 87% on all validation specimens. The prospectively collected specimens had a significantly higher 68% sensitivity and 89% specificity. Results from patients with benign nodules were similar to healthy volunteers. No meaningful correlation was present between our test results and any clinical characteristic other than lung cancer diagnosis. FPR1 mRNA levels in whole blood can predict the presence of lung cancer. Using this as a reflex test for positive lung cancer screening computed tomography (CT) scans has the potential to increase the positive predictive value. This marker can be easily measured in an automated process utilizing off-the-shelf equipment and reagents. Further work is justified to explain the source of this biomarker.