Faculty Bibliography

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.

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

Despite the immune-reconstitution with antiretroviral therapy (ART), HIV-infected individuals remain highly susceptible to tuberculosis (TB) and have an enrichment of oral anaerobes in the lung. Products of bacterial anaerobic metabolism, like butyrate and other short-chain fatty acids (SCFAs), induce regulatory T cells (Tregs). We tested whether SCFAs contribute to poor TB control in a longitudinal cohort of ART-treated HIV-infected South Africans. Increase in serum SCFAs was associated with increased TB susceptibility. SCFAs inhibited IFN-gamma and IL-17A production in peripheral blood mononuclear cells from HIV-infected ART-treated individuals in response to M. tuberculosis antigen stimulation. Pulmonary SCFAs correlated with increased oral anaerobes, such as Prevotella in the lung, and with M. tuberculosis antigen-induced Tregs. Metabolites from anaerobic bacterial fermentation may, therefore, increase TB susceptibility by suppressing IFN-gamma and IL-17A production during the cellular immune response to M. tuberculosis.

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.

INTRODUCTION: Azithromycin (AZM) reduces pulmonary inflammation and exacerbations in patients with COPD having emphysema. The antimicrobial effects of AZM on the lower airway microbiome are not known and may contribute to its beneficial effects. Here we tested whether AZM treatment affects the lung microbiome and bacterial metabolites that might contribute to changes in levels of inflammatory cytokines in the airways. METHODS: 20 smokers (current or ex-smokers) with emphysema were randomised to receive AZM 250 mg or placebo daily for 8 weeks. Bronchoalveolar lavage (BAL) was performed at baseline and after treatment. Measurements performed in acellular BAL fluid included 16S rRNA gene sequences and quantity; 39 cytokines, chemokines and growth factors and 119 identified metabolites. The response to lipopolysaccharide (LPS) by alveolar macrophages after ex-vivo treatment with AZM or bacterial metabolites was assessed. RESULTS: Compared with placebo, AZM did not alter bacterial burden but reduced alpha-diversity, decreasing 11 low abundance taxa, none of which are classical pulmonary pathogens. Compared with placebo, AZM treatment led to reduced in-vivo levels of chemokine (C-X-C) ligand 1 (CXCL1), tumour necrosis factor (TNF)-alpha, interleukin (IL)-13 and IL-12p40 in BAL, but increased bacterial metabolites including glycolic acid, indol-3-acetate and linoleic acid. Glycolic acid and indol-3-acetate, but not AZM, blunted ex-vivo LPS-induced alveolar macrophage generation of CXCL1, TNF-alpha, IL-13 and IL-12p40. CONCLUSION: AZM treatment altered both lung microbiota and metabolome, affecting anti-inflammatory bacterial metabolites that may contribute to its therapeutic effects. TRIAL REGISTRATION NUMBER: NCT02557958.

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.

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.