Inflammation in the tumor-adjacent lung as a predictor of clinical outcome in lung adenocarcinoma.

Approximately 30% of early-stage lung adenocarcinoma patients present with disease progression after successful surgical resection. Despite efforts of mapping the genetic landscape, there has been limited success in discovering predictive biomarkers of disease outcomes. Here we performed a systematic multi-omic assessment of 143 tumors and matched tumor-adjacent, histologically-normal lung tissue with long-term patient follow-up. Through histologic, mutational, and transcriptomic profiling of tumor and adjacent-normal tissue, we identified an inflammatory gene signature in tumor-adjacent tissue as the strongest clinical predictor of disease progression. Single-cell transcriptomic analysis demonstrated the progression-associated inflammatory signature was expressed in both immune and non-immune cells, and cell type-specific profiling in monocytes further improved outcome predictions. Additional analyses of tumor-adjacent transcriptomic data from The Cancer Genome Atlas validated the association of the inflammatory signature with worse outcomes across cancers. Collectively, our study suggests that molecular profiling of tumor-adjacent tissue can identify patients at high risk for disease progression.

Lower Airway Dysbiosis Augments Lung Inflammatory Injury in Mild-to-Moderate Chronic Obstructive Pulmonary Disease.

Rationale: Chronic obstructive pulmonary disease (COPD) is associated with high morbidity, mortality, and healthcare costs. Cigarette smoke is a causative factor; however, not all heavy smokers develop COPD. Microbial colonization and infections are contributing factors to disease progression in advanced stages. Objectives: We investigated whether lower airway dysbiosis occurs in mild-to-moderate COPD and analyzed possible mechanistic contributions to COPD pathogenesis. Methods: We recruited 57 patients with a >10 pack-year smoking history: 26 had physiological evidence of COPD, and 31 had normal lung function (smoker control subjects). Bronchoscopy sampled the upper airways, lower airways, and environmental background. Samples were analyzed by 16S rRNA gene sequencing, whole genome, RNA metatranscriptome, and host RNA transcriptome. A preclinical mouse model was used to evaluate the contributions of cigarette smoke and dysbiosis on lower airway inflammatory injury. Measurements and Main Results: Compared with smoker control subjects, microbiome analyses showed that the lower airways of subjects with COPD were enriched with common oral commensals. The lower airway host transcriptomics demonstrated differences in markers of inflammation and tumorigenesis, such as upregulation of IL-17, IL-6, ERK/MAPK, PI3K, MUC1, and MUC4 in mild-to-moderate COPD. Finally, in a preclinical murine model exposed to cigarette smoke, lower airway dysbiosis with common oral commensals augments the inflammatory injury, revealing transcriptomic signatures similar to those observed in human subjects with COPD. Conclusions: Lower airway dysbiosis in the setting of smoke exposure contributes to inflammatory injury early in COPD. Targeting the lower airway microbiome in combination with smoking cessation may be of potential therapeutic relevance.

Pleural fluid microbiota as a biomarker for malignancy and prognosis.

Malignant pleural effusions (MPE) complicate malignancies and portend worse outcomes. MPE is comprised of various components, including immune cells, cancer cells, and cell-free DNA/RNA. There have been investigations into using these components to diagnose and prognosticate MPE. We hypothesize that the microbiome of MPE is unique and may be associated with diagnosis and prognosis. We compared the microbiota of MPE against microbiota of pleural effusions from non-malignant and paramalignant states. We collected a total of 165 pleural fluid samples from 165 subjects; Benign (n = 16), Paramalignant (n = 21), MPE-Lung (n = 57), MPE-Other (n = 22), and Mesothelioma (n = 49). We performed high throughput 16S rRNA gene sequencing on pleural fluid samples and controls. We showed that there are compositional differences among pleural effusions related to non-malignant, paramalignant, and malignant disease. Furthermore, we showed differential enrichment of bacterial taxa within MPE depending on the site of primary malignancy. Pleural fluid of MPE-Lung and Mesothelioma were associated with enrichment with oral and gut bacteria that are commonly thought to be commensals, including Rickettsiella, Ruminococcus, Enterococcus, and Lactobacillales. Mortality in MPE-Lung is associated with enrichment in Methylobacterium, Blattabacterium, and Deinococcus. These observations lay the groundwork for future studies that explore host-microbiome interactions and their influence on carcinogenesis.

The lung microbiome, peripheral gene expression, and recurrence-free survival after resection of stage II non-small cell lung cancer.

BACKGROUND: Cancer recurrence after tumor resection in early-stage non-small cell lung cancer (NSCLC) is common, yet difficult to predict. The lung microbiota and systemic immunity may be important modulators of risk for lung cancer recurrence, yet biomarkers from the lung microbiome and peripheral immune environment are understudied. Such markers may hold promise for prediction as well as improved etiologic understanding of lung cancer recurrence. METHODS: In tumor and distant normal lung samples from 46 stage II NSCLC patients with curative resection (39 tumor samples, 41 normal lung samples), we conducted 16S rRNA gene sequencing. We also measured peripheral blood immune gene expression with nanoString®. We examined associations of lung microbiota and peripheral gene expression with recurrence-free survival (RFS) and disease-free survival (DFS) using 500 × 10-fold cross-validated elastic-net penalized Cox regression, and examined predictive accuracy using time-dependent receiver operating characteristic (ROC) curves. RESULTS: Over a median of 4.8 years of follow-up (range 0.2-12.2 years), 43% of patients experienced a recurrence, and 50% died. In normal lung tissue, a higher abundance of classes Bacteroidia and Clostridia, and orders Bacteroidales and Clostridiales, were associated with worse RFS, while a higher abundance of classes Alphaproteobacteria and Betaproteobacteria, and orders Burkholderiales and Neisseriales, were associated with better RFS. In tumor tissue, a higher abundance of orders Actinomycetales and Pseudomonadales were associated with worse DFS. Among these taxa, normal lung Clostridiales and Bacteroidales were also related to worse survival in a previous small pilot study and an additional independent validation cohort. In peripheral blood, higher expression of genes TAP1, TAPBP, CSF2RB, and IFITM2 were associated with better DFS. Analysis of ROC curves revealed that lung microbiome and peripheral gene expression biomarkers provided significant additional recurrence risk discrimination over standard demographic and clinical covariates, with microbiome biomarkers contributing more to short-term (1-year) prediction and gene biomarkers contributing to longer-term (2-5-year) prediction. CONCLUSIONS: We identified compelling biomarkers in under-explored data types, the lung microbiome, and peripheral blood gene expression, which may improve risk prediction of recurrence in early-stage NSCLC patients. These findings will require validation in a larger cohort.

Controversies and challenges in lung cancer screening.

Two large randomized controlled trials have shown mortality benefit from lung cancer screening (LCS) in high-risk groups. Updated guidelines by the United State Preventative Service Task Force in 2020 will allow for inclusion of more patients who are at high risk of developing lung cancer and benefit from screening. As medical clinics and lung cancer screening programs around the country continue to work on perfecting the LCS workflow, it is important to understand some controversial issues surrounding LCS that should be addressed. In this article, we identify some of these issues, including false positive rates of low-dose CT, over-diagnosis, cost expenditure, LCS disparities in minorities, and utility of biomarkers. We hope to provide clarity, potential solutions, and future directions on how to address these controversies.

Lower Airway Dysbiosis Affects Lung Cancer Progression.

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 the stage IIIB-IV tumor-node-metastasis lung cancer group 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 stage IIIB-IV disease. In addition, this lower airway microbiota signature was associated with upregulation of the IL17, 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, IL17 inflammatory phenotype, and activation of checkpoint inhibitor markers. SIGNIFICANCE: Multiple lines of investigation have shown that the gut microbiota affects host immune response to immunotherapy in cancer. Here, we support that the local airway microbiota modulates the host immune tone in lung cancer, affecting tumor progression and prognosis.See related commentary by Zitvogel and Kroemer, p. 224.This article is highlighted in the In This Issue feature, p. 211.

Value of metalloproteinases in predicting COPD in heavy urban smokers.

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: Three hundred sixteen study subjects were enrolled. Of the 222 patients who met the inclusion criteria, 46% had emphysema. Smokers with emphysema had increased pack-years of smoking compared to smokers without emphysema (51 ± 24 pack-years (mean ± sd) versus 37 ± 20; p < 0.0001). Smokers with emphysema also had lower FEV1/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: Emphysema was detected by CT in almost half of heavy urban smokers. Serum MMP levels provided minimal additional information to improve the detection of mild emphysema among smokers given their clinical characteristics (age, pack-years, and FEV1/FVC ratio).

Tumor-draining lymph nodes demonstrate a suppressive immunophenotype in patients with non-small cell lung cancer assessed by endobronchial ultrasound-guided transbronchial needle aspiration: A pilot study.

OBJECTIVES: Tumor draining lymph nodes (TDLN) are key sites of early immunoediting in patients with non-small cell lung cancer (NSCLC) and play an important role in generating anti-tumor immunity. Immune suppression in the tumor microenvironment has prognostic implications and may predict therapeutic response. T cell composition of draining lymph nodes may reflect an immunophenotype with similar prognostic potential which could be measured during standard-of-care bronchoscopic assessment. In this study, we compared the immunophenotype from different sites within individuals to primary tumor characteristics in patients with NSCLC to see whether there were tumor-regional differences in immunophenotype which could be evaluated from transbronchial needle aspirates. MATERIALS AND METHODS: Twenty patients were enrolled in this study and had tissue (lymph node aspirates and/or peripheral blood) obtained during standard of care bronchoscopy with endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) for diagnosis or staging of known or suspected NSCLC. Aspirates and blood underwent flow-assisted cell sorting and a subset of sorted effector T cells underwent RNA quantitation to determine feasibility of this approach. Immunophenotypic patterns from twelve patients with paired data from tumor-draining and non-tumor draining lymph nodes (NDLN) were compared relative to one another and based on PD-L1 immunohistochemistry and primary tumor histology. RESULTS: TDLN had significantly fewer CD4+ T cells (12.68% vs 27%, p = 0.002) and significantly more regulatory T cells (Treg, 12.03% vs 9.52%, p = 0.03) relative to paired NDLN suggesting tumor-regional immunosuppression. There were significantly more Treg in NDLN relative to paired PBMC (9.52% vs 5.6%, p = 0.016). Patients with PD-L1 expression ≥50% had significantly greater tumor-regional CD4+ T cell depletion compared to patients with PD-L1 expression <50% (-35.98% vs -1.89%, p = 0.0357; negative values represent absolute difference between paired TDLN and NDLN). CONCLUSIONS: In patients with NSCLC, TDLN have a suppressive immunophenotype correlating with tumor PD-L1 status and can be assessed during routine EBUS-TBNA.

A Gene Expression Classifier from Whole Blood Distinguishes Benign from Malignant Lung Nodules Detected by Low-Dose CT.

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.

Epigenetically regulated PAX6 drives cancer cells toward a stem-like state via GLI-SOX2 signaling axis in lung adenocarcinoma.

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.

Airway Microbiota Is Associated with Upregulation of the PI3K Pathway in Lung Cancer.

RATIONALE: In lung cancer, upregulation of the PI3K (phosphoinositide 3-kinase) 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. OBJECTIVES: We hypothesize that host-microbe interactions in the lower airways of subjects with lung cancer affect known cancer pathways. METHODS: Airway brushings 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 noncancer diagnoses. In addition, samples from 10 healthy control subjects were included. 16S ribosomal RNA gene amplicon sequencing and paired transcriptome sequencing were performed on all airway samples. In addition, an in vitro model with airway epithelial cells exposed to bacteria/bacterial products was performed. MEASUREMENTS AND MAIN RESULTS: The composition of the lower airway transcriptome in the patients with cancer was significantly different from the control subjects, which included up-regulation of ERK (extracellular signal-regulated kinase) and PI3K signaling pathways. The lower airways of patients with lung cancer were enriched for oral taxa (Streptococcus and Veillonella), which was associated with up-regulation 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 show that several transcriptomic signatures previously identified as relevant to lung cancer pathogenesis are associated with enrichment of the lower airway microbiota with oral commensals.

A Panel of Novel Detection and Prognostic Methylated DNA Markers in Primary Non-Small Cell Lung Cancer and Serum DNA.

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 (DMR) 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 paralog group for HOXA9, predominantly overexpressed in subjects with HOXA9 methylation, showed poor outcomes.Conclusions: 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. Clin Cancer Res; 23(22); 7141-52. ©2017 AACR.

Identification of autoantibodies to ECH1 and HNRNPA2B1 as potential biomarkers in the early detection of lung cancer.

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.

Autoantibodies against tumor-associated antigens in the early detection of lung cancer.

OBJECTIVES: Autoantibodies against tumor-associated antigens (TAAs) identified in patients with advanced lung cancer may be detected in subjects with early lung cancer or even predate the diagnosis. The purpose of this study is to address the temporal relationship between lung cancer development and serum autoantibody response. MATERIALS AND METHODS: Two cohorts of patients with newly diagnosed lung cancer were included. The first cohort included 90 sera from patients with lung cancer (Stages I-III) and 89 normal control sera. In the second cohort, 93 serial serum samples from 25 patients with CT-scan screen-detected stage I lung cancer were collected before the diagnosis of lung cancer (average 32 months) and 56 controls were matched on age, gender, and smoking. Autoantibody levels were measured by immunoassay. RESULTS: Measurement of autoantibodies against seven TAAs (14-3-3ζ, c-Myc, MDM2, NPM1, p16, p53 and cyclin B1) individually could discriminate lung cancer patients from normal individuals in the first cohort and the area under curve (AUC) was 0.863 based on a panel of seven autoantibodies, with sensitivity of 68.9% and specificity of 79.5%. Autoantibodies in serial pre-diagnostic serum samples against the same panel of seven TAAs were detected prior to lung cancer diagnosis with sensitivity of 76.0% and specificity of 73.2% (AUC) (95%CI): 0.885 (0.797-0.973)). Elevated autoantibody levels could be detected greater than four years prior to lung cancer diagnosis. CONCLUSION: A panel of seven TAAs may enhance the early detection of lung cancer, consistent with a humoral immune response to TAAs that can be detected months to years prior to the diagnosis.

Comparative Study of Autoantibody Responses between Lung Adenocarcinoma and Benign Pulmonary Nodules.

INTRODUCTION: The reduction in lung cancer mortality associated with computed tomography (CT) screening has led to its increased use and a concomitant increase in the detection of benign pulmonary nodules. Many individuals found to have benign nodules undergo unnecessary, costly, and invasive procedures. Therefore, there is a need for companion diagnostics that stratify individuals with pulmonary nodules into high-risk or low-risk groups. Lung cancers can trigger host immune responses and elicit antibodies against tumor antigens. The identification of these autoantibodies (AAbs) and their corresponding antigens may expand our knowledge of cancer immunity, leading to early diagnosis or even benefiting immunotherapy. Previous studies were performed mostly in the context of comparing cancers and healthy (smoker) controls. We have performed one of the first studies to understand humoral immune response in patients with cancer, patients with benign nodules, and healthy smokers. METHODS: We first profiled seroreactivity to 10,000 full-length human proteins in 40 patients with early-stage lung cancer and 40 smoker controls by using nucleic acid programmable protein arrays to identify candidate cancer-specific AAbs. Enzyme-linked immunosorbent assays of promising candidates were performed on 137 patients with lung cancer and 127 smoker controls, as well as on 170 subjects with benign pulmonary nodules. RESULTS: From protein microarray screening experiments using a discovery set of 40 patients and 40 smoker controls, 17 antigens showing higher reactivity in lung cancer cases relative to the controls were subsequently selected for evaluation in a large sample set (n = 264) by using enzyme-linked immunosorbent assay. A five-AAb classifier (tetratricopeptide repeat domain 14 [TTC14], B-Raf proto-oncogene, serine/threonine kinase [BRAF], actin like 6B [ACTL6B], MORC family CW-type zinc finger 2 [MORC2], and cancer/testis antigen 1B [CTAG1B]) that can differentiate lung cancers from smoker controls with a sensitivity of 30% at 89% specificity was developed. We further tested AAb responses in subjects with CT-positive benign nodules (n = 170), and developed a five-AAb panel (keratin 8, type II, TTC14, Kruppel-like factor 8, BRAF, and tousled like kinase 1) with a sensitivity of 30% at 88% specificity. Interestingly, messenger RNA levels of six AAb targets (TTC14, BRAF, MORC family CW-type zinc finger 2, cancer/testis antigen 1B, keratin 8, type II, and tousled like kinase 1) were also found to increase in lung adenocarcinoma tissues based on The Cancer Genome Atlas data set. CONCLUSION: We discovered AAbs associated with lung adenocaricnoma that have the potential to differentiate cancer from CT-positive benign diseases. We believe that these antibodies warrant future validation using a larger sample set and/or longitudinal samples individually or as a panel. They could potentially be part of companion molecular diagnostic modalities that will benefit subjects undergoing CT screening for lung cancer.

Inflammatory cytokines and non-small cell lung cancer in a CT-scan screening cohort: Background review of the literature.

BACKGROUND: Inflammatory cytokines are at the intersection of tumor cell biology and host immune response. Peripheral cytokine expression levels may reflect the microscopic tumor milieu, and specific cytokines play an integral role in tumor initiation, growth, and metastasis. High-throughput cytokine analysis may identify panels for early-stage non-small cell lung cancer (NSCLC) diagnosis and identify individuals at high-risk for lung cancer with indeterminate lung nodules 8-20 mm in size. METHODS: Thirteen serum cytokines from the NYU Lung Cancer Biomarker Center cohort with early-stage NSCLC were analyzed using bead-based immunoassay technology. RESULTS: In the NYU cohort, a one unit increase in interferon-γ increased risk of lung cancer by 3% (OR = 1.03, 95% CI, 1.02-1.05) and a one unit increase in TNF-α decreased the risk of lung cancer by 53% (OR = 0.47, 95% Cl, 0.31-0.71) when both cytokines were included in a logistic regression model with adjustments for age and pack-years of smoking. The resulting AUC for the Receiver Operating Characteristic (ROC) curve was 0.88; the sensitivity and specificity at the optimal cutpoint were 78.9% and 90.3%, respectively. CONCLUSIONS: Cytokines have limited value in the early diagnosis of early-stage NSCLC. Our review of the literature suggests that although inflammation is important for the development of NSCLC, that cytokines are increased in more advanced lung cancer than when the diagnosis occurs at presentation.

Molecular characterization of the peripheral airway field of cancerization in lung adenocarcinoma.

Field of cancerization in the airway epithelium has been increasingly examined to understand early pathogenesis of non-small cell lung cancer. However, the extent of field of cancerization throughout the lung airways is unclear. Here we sought to determine the differential gene and microRNA expressions associated with field of cancerization in the peripheral airway epithelial cells of patients with lung adenocarcinoma. We obtained peripheral airway brushings from smoker controls (n=13) and from the lung contralateral to the tumor in cancer patients (n=17). We performed gene and microRNA expression profiling on these peripheral airway epithelial cells using Affymetrix GeneChip and TaqMan Array. Integrated gene and microRNA analysis was performed to identify significant molecular pathways. We identified 26 mRNAs and 5 miRNAs that were significantly (FDR <0.1) up-regulated and 38 mRNAs and 12 miRNAs that were significantly down-regulated in the cancer patients when compared to smoker controls. Functional analysis identified differential transcriptomic expressions related to tumorigenesis. Integration of miRNA-mRNA data into interaction network analysis showed modulation of the extracellular signal-regulated kinase/mitogen-activated protein kinase (ERK/MAPK) pathway in the contralateral lung field of cancerization. In conclusion, patients with lung adenocarcinoma have tumor related molecules and pathways in histologically normal appearing peripheral airway epithelial cells, a substantial distance from the tumor itself. This finding can potentially provide new biomarkers for early detection of lung cancer and novel therapeutic targets.

Current readings: blood-based biomarkers for lung cancer.

Lung cancer is the leading cause of cancer deaths worldwide largely owing to diagnosis of the disease at an advanced stage. Recent advances in blood-based biomarker research have the potential to reduce mortality by providing a means for detecting lung cancer at an earlier stage. Since the publication of the National Lung Cancer Screening Trial demonstrating reduction in mortality with computed tomography (CT) scan screening, the U.S. Preventive Services Task Force has released a draft statement recommending annual low-dose CT scan screening for high-risk patients. However, CT screening has a high false-positive rate leading to the need for additional imaging and invasive procedures. In this article, we review recent literature on blood-based lung cancer biomarkers that we believe will have a significant role in enhancing screening efficacy in the near future.