Faculty Bibliography

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.

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.

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.

PURPOSE: Diagnosis of lung cancer at an earlier stage results in improved survival, and many cancer-related biomarkers have been studied for their potential roles in early lung cancer detection. One underutilized strategy for biomarker development is the use of mixed panels consisting of combinations of different biomarkers that may increase sensitivity and specificity. We examined correlations among previously studied biomarkers with the goal of identifying an ideal panel of biomarkers with an enhanced discriminatory ability for lung cancer. METHODS: Case and smoker control samples were selected from the NYU Lung Cancer Biomarker Center (part of the NCI Early Detection Research Network). The NYU cohort consisted of high risk smokers who participated in low-dose computed tomography (LDCT) lung cancer screening. Serum samples from each individual were used to develop four different bloodbased platform testing 34 biomarkers, over the last 5 years - Luminex technology for matrix metalloproteinase (MMPs); enzymelinked immunosorbent assay (ELISA) for Achaete-scute homolog 1 (ASCL1), forkhead box P3 (FOXP3), and autoantibodies to tumor associated antigens (TAAs); millipore bead-based immunoassay for 13 cytokines. Statistical analyses were performed using Spearman's correlation. RESULTS: 31 of the 1122 biomarker-biomarker correlations were statistically significant. Eighteen of the significant correlations were in cancer patients, including : MDM2-IL4, MDM2-IL6, IL17-IMP1, MMP9-TNFA, MMP7-FOXP3, MMP10-FOXP3, and MMP10-P62. There was a strong positive correlation between MDM2 and IL4 in lung cancer patients (p=0.002). There was also a strong positive correlation between MDM2 and IL6 in cancer patients (p= 0.001). In non-cancer patients, these two correlations were not significant CONCLUSIONS: In this study we found 18 serum biomarker-biomarker correlations which were significant in cancer patients. MDM2-IL4 and MDM2-IL6 were two strong positive correlates which were not seen in non-cancer patients

Lung cancer is the leading cause of cancer mortality in the United States with non-small cell lung cancer (NSCLC) adenocarcinoma being the most common histological type. Early perturbations in cellular metabolism are a hallmark of cancer, but the extent of these changes in early stage lung adenocarcinoma remains largely unknown. In the current study, an integrated metabolomics and proteomics approach was utilized to characterize the biochemical and molecular alterations between malignant and matched control tissue from 27 subjects diagnosed with early stage lung adenocarcinoma. Differential analysis identified 71 metabolites and 1102 proteins that delineated tumor from control tissue. Integrated results indicated four major metabolic changes in early stage adenocarcinoma: (1) increased glycosylation and glutaminolysis; (2) elevated Nrf2 activation; (3) increase in nicotinic and nicotinamide salvaging pathways; and (4) elevated polyamine biosynthesis linked to differential regulation of the SAM/nicotinamide methyl-donor pathway. Genomic data from publicly available databases were included to strengthen proteomic findings. Our findings provide insight into the biochemical and molecular biological reprogramming that may accompanies early stage lung tumorigenesis and highlight potential therapeutic targets.

PURPOSE: To establish a novel panel of cancer-specific methylated genes for cancer detection and prognostic stratification of early stage non-small cell lung cancer (NSCLC). EXPERIMENTAL DESIGN: Identification of differentially methylated regions (DMRs) was performed with bumphunter on "The Cancer Genome Atlas (TCGA)" dataset, and clinical utility was assessed using quantitative methylation-specific PCR assay in multiple sets of primary NSCLC and body fluids that included serum, pleural effusion, and ascites samples. RESULTS: A methylation panel of 6 genes (CDO1, HOXA9, AJAP1, PTGDR, UNCX, and MARCH11) was selected from TCGA dataset. Promoter methylation of the gene panel was detected in 92.2% (83/90) of the training cohort with a specificity of 72.0% (18/25) and in 93.0% (40/43) of an independent cohort of stage IA primary NSCLC. In serum samples from the later 43 stage IA subjects and population-matched 42 control subjects, the gene panel yielded a sensitivity of 72.1% (31/41) and specificity of 71.4% (30/42). Similar diagnostic accuracy was observed in pleural effusion and ascites samples. A prognostic risk category based on the methylation status of CDO1, HOXA9, PTGDR, and AJAP1 refined the risk stratification for outcomes as an independent prognostic factor for an early stage disease. Moreover, the paralogue group for HOXA9, predominantly overexpressed in subjects with HOXA9 methylation, showed poor outcomes. CONCLUSION: Promoter methylation of a panel of 6 genes has potential for use as a biomarker for early cancer detection and to predict prognosis at the time of diagnosis.

BACKGROUND: The number of pulmonary nodules detected in the US is expected to increase substantially following recent recommendations for nationwide CT-based lung cancer screening. Given the low specificity of CT screening, non-invasive adjuvant methods are needed to differentiate cancerous lesions from benign nodules to help avoid unnecessary invasive procedures in the asymptomatic population. We have constructed a serum-based multi-biomarker panel and assessed its clinical accuracy in a retrospective analysis of samples collected from participants with suspicious radiographic findings in the Prostate, Lung, Chest and Ovarian (PLCO) cancer screening trial. METHODS: Starting with a set of 9 candidate biomarkers, we identified 8 that exhibited limited pre-analytical variability with increasing clotting time, a key pre-analytical variable associated with the collection of serum. These 8 biomarkers were evaluated in a training study consisting of 95 stage I NSCLC patients and 186 smoker controls where a 5-biomarker pulmonary nodule classifier (PNC) was selected. The clinical accuracy of the PNC was determined in a blinded study of asymptomatic individuals comprising 119 confirmed malignant nodule cases and 119 benign nodule controls selected from the PLCO screening trial. RESULTS: A PNC comprising 5 biomarkers: CEA, CYFRA 21-1, OPN, SCC, and TFPI, was selected in the training study. In an independent validation study, the PNC resolved lung cancer cases from benign nodule controls with an AUC of 0.653 (p < 0.0001). CEA and CYFRA 21-1, two of the markers included in the PNC, also accurately distinguished malignant lesions from benign controls. CONCLUSIONS: A 5-biomarker blood test has been developed for the diagnostic evaluation of asymptomatic individuals with solitary pulmonary nodules.

Identification of biomarkers for early detection of lung cancer (LC) is important, in turn leading to more effective treatment and reduction of mortality. Serological proteome analysis (SERPA) was used to identify proteins around 34 kD as ECH1 and HNRNPA2B1, which had been recognized by serum autoantibody from 25 LC patients. In the validation study, including 90 sera from LC patients and 89 sera from normal individuals, autoantibody to ECH1 achieved an area under the curve (AUC) of 0.799 with sensitivity of 62.2% and specificity of 95.5% in discriminating LC from normal individuals, and showed negative correlation with tumor size (rs = -0.256, p = 0.023). Autoantibody to HNRNPA2B1 performed an AUC of 0.874 with sensitivity of 72.2% and specificity of 95.5%, and showed negative correlation with lymph node metastasis (rs = -0.279, p = 0.012). By using longitudinal preclinical samples, autoantibody to ECH1 showed an AUC of 0.763 with sensitivity of 60.0% and specificity of 89.3% in distinguishing early stage LC from matched normal controls, and elevated autoantibody levels could be detected greater than 2 y before LC diagnosis. ECH1 and HNRNPA2B1 are autoantigens that elicit autoimmune responses in LC and their autoantibody can be the potential biomarkers for the early detection of LC.