Biomarkers For Detection Of Lung Cancer Research Articles

Transthyretin Stimulates Tumor Growth through Regulation of Tumor, Immune, and Endothelial Cells.

Early detection of lung cancer offers an important opportunity to decrease mortality while it is still treatable and curable. Thirteen secretory proteins that are Stat3 downstream gene products were identified as a panel of biomarkers for lung cancer detection in human sera. This panel of biomarkers potentially differentiates different types of lung cancer for classification. Among them, the transthyretin (TTR) concentration was highly increased in human serum of lung cancer patients. TTR concentration was also induced in the serum, bronchoalveolar lavage fluid, alveolar type II epithelial cells, and alveolar myeloid cells of the CCSP-rtTA/(tetO)7-Stat3C lung tumor mouse model. Recombinant TTR stimulated lung tumor cell proliferation and growth, which were mediated by activation of mitogenic and oncogenic molecules. TTR possesses cytokine functions to stimulate myeloid cell differentiation, which are known to play roles in tumor environment. Further analyses showed that TTR treatment enhanced the reactive oxygen species production in myeloid cells and enabled them to become functional myeloid-derived suppressive cells. TTR demonstrated a great influence on a wide spectrum of endothelial cell functions to control tumor and immune cell migration and infiltration. TTR-treated endothelial cells suppressed T cell proliferation. Taken together, these 13 Stat3 downstream inducible secretory protein biomarkers potentially can be used for lung cancer diagnosis, classification, and as clinical targets for lung cancer personalized treatment if their expression levels are increased in a given lung cancer patient in the blood.

Determination of Non-Invasive Lung Cancer Biomarker by Quartz Crystal Microbalance Coated with Pegylated Lipopolymer

This study presents the application of pegylated lipopolymer to coat a sensor device called quartz crystal microbalance (QCM) for analysis of volatile organic compounds (VOC) on the non-invasive detection of lung cancer biomarkers. The chosen biomarker for this study was propanol, ethyl benzene, hexanal, and decane. QCM with fundamental frequency 30 MHz AT-cut with gold electrode was coated with sensing material composed of lipid, and pegylated lipopolymer with functional group carboxyl and succinyl to increase sensor sensitivity for biomarker detection purposes. The fabricated sensors could detect all presented biomarker with various selectivity and sensitivity responses. Furthermore, the results from biomarker exposure indicated that the sensitivity of sensors coated with succinyl pegylated lipopolymer film was better than non-coated sensor or coated with carboxyl lipopolymer and lipid films to each selected biomarkers.

Circulating microRNA biomarkers for lung cancer detection in Western populations.

Lung cancer (LC) is a leading cause of cancer‐related death in the Western world. Patients with LC usually have poor prognosis due to the difficulties in detecting tumors at early stages. Multiple studies have shown that circulating miRNAs might be promising biomarkers for early detection of LC. We aimed to provide an overview of published studies on circulating miRNA markers for early detection of LC and to summarize their diagnostic performance in Western populations. A systematic literature search was performed in PubMed and ISI Web of Knowledge to find relevant studies published up to 11 August 2017. Information on study design, population characteristics, miRNA markers, and diagnostic accuracy (including sensitivity, specificity, and AUC) were independently extracted by two reviewers. Overall, 17 studies evaluating 35 circulating miRNA markers and 19 miRNA panels in serum or plasma were included. The median sensitivity (range) and specificity (range) were, respectively, 78.4% (51.7%‐100%) and 78.7% (42.9%‐93.5%) for individual miRNAs, and 83.0% (64.0%‐100%) and 84.9% (71.0%‐100%) for miRNA panels. Most studies incorporated individual miRNA markers as panels (with 2‐34 markers), with multiple miRNA‐based panels generally outperforming individual markers. Two promising miRNA panels were discovered and verified in prospective cohorts. Of note, both studies exclusively applied miRNA ratios when building up panels. In conclusion, circulating miRNAs may bear potential for noninvasive LC screening, but large studies conducted in screening or longitudinal settings are needed to validate the promising results and optimize the marker panels.

Selective Surface Enhanced Raman Scattering for Quantitative Detection of Lung Cancer Biomarkers in Superparticle@MOF Structure.

Surface enhanced Raman scattering (SERS) is a trace detection technique that extends even to single molecule detection. Its potential application to the noninvasive recognition of lung malignancies by detecting volatile organic compounds (VOCs) that serve as biomarkers would be a breakthrough in early cancer diagnostics. This application, however, is currently limited by two main factors: (1) most VOC biomarkers exhibit only weak Raman scattering; and (2) the high mobility of gaseous molecules results in a low adsorptivity on solid substrates. To enhance the adsorption of gaseous molecules, a ZIF-8 layer is coated onto a self-assembly of gold superparticles (GSPs) in order to slow the flow rate of gaseous biomarkers and depress the exponential decay of the electromagnetic field around the GSP surfaces. Gaseous aldehydes that are released as a result of tumor-specific tissue composition and metabolism, thereby acting as indicators of lung cancer, are guided onto SERS-active GSPs substrates through a ZIF-8 channel. Through a Schiff base reaction with 4-aminothiophenol pregrafted onto gold GSPs, gaseous aldehydes are captured with a 10 ppb limit of detection, demonstrating tremendous prospects for in vitro diagnoses of early stage lung cancer.

1-D grating based SPR biosensor for the detection of lung cancer biomarkers using Vroman effect

Grating based surface plasmon resonance waveguide biosensor have been reported for the detection of lung cancer biomarkers using Vroman effect. The proposed grating based multilayered biosensor is designed with high detection accuracy for Epidermal growth factor receptor (EGFR) and also analysed to show high detection accuracy with acceptable sensitivity for both cancer biomarkers. The introduction of periodic grating with multilayer metals generates a good resonance that make it possible for early detection of cancerous cells. Using finite difference time domain method, it is observed wavelength of biosensor get red-shifted on variations of the refractive index due to the presence of both the cancerous bio-markers. The reported detection accuracy and sensitivity of proposed biosensor is quite acceptable for both lung cancer biomarkers i.e. Carcinoembryonic antigen (CEA) and Epidermal growth factor receptor (EGFR) which further offer us label free early detection of lung cancer using these biomarkers.

Shared Gene Expression Alterations in Nasal and Bronchial Epithelium for Lung Cancer Detection.

We previously derived and validated a bronchial epithelial gene expression biomarker to detect lung cancer in current and former smokers. Given that bronchial and nasal epithelial gene expression are similarly altered by cigarette smoke exposure, we sought to determine if cancer-associated gene expression might also be detectable in the more readily accessible nasal epithelium. Nasal epithelial brushings were prospectively collected from current and former smokers undergoing diagnostic evaluation for pulmonary lesions suspicious for lung cancer in the AEGIS-1 (n = 375) and AEGIS-2 (n = 130) clinical trials and gene expression profiled using microarrays. All statistical tests were two-sided. We identified 535 genes that were differentially expressed in the nasal epithelium of AEGIS-1 patients diagnosed with lung cancer vs those with benign disease after one year of follow-up ( P < .001). Using bronchial gene expression data from the AEGIS-1 patients, we found statistically significant concordant cancer-associated gene expression alterations between the two airway sites ( P < .001). Differentially expressed genes in the nose were enriched for genes associated with the regulation of apoptosis and immune system signaling. A nasal lung cancer classifier derived in the AEGIS-1 cohort that combined clinical factors (age, smoking status, time since quit, mass size) and nasal gene expression (30 genes) had statistically significantly higher area under the curve (0.81; 95% confidence interval [CI] = 0.74 to 0.89, P = .01) and sensitivity (0.91; 95% CI = 0.81 to 0.97, P = .03) than a clinical-factor only model in independent samples from the AEGIS-2 cohort. These results support that the airway epithelial field of lung cancer-associated injury in ever smokers extends to the nose and demonstrates the potential of using nasal gene expression as a noninvasive biomarker for lung cancer detection.

Ultrasensitive Surface-Enhanced Raman Scattering Sensor of Gaseous Aldehydes as Biomarkers of Lung Cancer on Dendritic Ag Nanocrystals.

Surface-enhanced Raman scattering (SERS) is expected as a technique that even theoretically detected chemicals at the single molecule level by surface plasmon phenomena of noble metal nanostructures. Insensitivity of detecting Raman weak-intensity molecules and low adsorptivity of gaseous molecules on solid substrates are two main factors hindering the application of SERS in gas detectors. In this manuscript, we demonstrated an operational SERS strategy to detect gaseous Raman weak-intensity aldehydes that have been considered as a biomarker of lung cancer for abnormal content was measured in volatile organic compounds (VOCs) of lung cancer patients. To enhance the adsorption of gaseous molecules, dendritic Ag nanocrystals mimicking the structural feature (dendritic) of moth's antennae were formed, wherein the existence of numerous cavity traps in Ag dendritic nanocrystals prolonged reaction time of the gaseous molecules on the surface of solid surface through the "cavity-vortex" effect. By the nucleophilic addition reaction with the Raman-active probe molecule p-aminothiophenol (4-ATP) pregrafted on dendritic Ag nanocrystals, the gaseous aldehyde molecules were sensitively captured to detect at the ppb (parts per billion) level. Additionally, the sensitivity of this operational SERS strategy to detection of lung cancer biomarkers was not affected by the humidity, which represented a great potential in fast, easy, cost-effective, and noninvasive recognition of lung malignancies.

Multiplexed detection of lung cancer biomarkers in patients serum with CMOS-compatible silicon nanowire arrays

In this work, a real-time assay for highly sensitive, label-free, multiplexed electrical detection of lung cancer biomarkers was developed by using silicon nanowire field-effect (SiNW-FET) devices. Highly responsive SiNW arrays were fabricated using a CMOS-compatible anisotropic self-stop etching technique with mass reproducibility and low cost character. The SiNW nanosensor was integrated with PDMS microfluidic device, which allows rapid analyte delivery, makes the analysis to be conducted using exceedingly small samples and enables potential multiplexed detection. The nanowire arrays allowed highly selective and sensitive multiplexed detection of microRNA (miRNA)−126 and CEA. Due to high surface-to-volume ratio that the nanowire dimensions confer, the detection floor of single molecule was achieved. The potential utility in identifying clinical samples for early diagnosis of cancer was demonstrated by analyzing biomarkers in clinical related samples. The developed nanosensor with capability for multiplexed real-time monitoring of biomarkers with high sensitivity and selectivity in clinically relevant samples is highly attractive for diagnosis and treatment of cancer and other diseases.

Abstract 1954: microRNA expression in bronchial epithelium for lung cancer detection

Abstract Introduction We have previously shown that gene expression alterations in the cytologically-normal mainstem bronchus can be leveraged as a biomarker for lung cancer detection (Silvestri et al. NEJM 2015), a test that is now used clinically. Extending this approach, we hypothesized that bronchial microRNA (miRNA) expression is altered in patients with lung cancer and that incorporating miRNA expression into the mRNA classifier may improve its performance. Methods Using bronchial brushes collected prospectively from current and former smokers undergoing bronchoscopy for suspect lung cancer across 28 medical centers as part of the AEGIS 1 and 2 clinical trials, we profiled miRNA expression via small RNA sequencing of 341 patients for which gene expression data was also available on the same bronchial brush sample. Patients were followed for up to one year post-bronchoscopy until a final diagnosis was established. 138 patients from AEGIS 1 (88 cancer-positive and 50 cancer-free) served as a discovery set, while other 203 patients from AEGIS 1 and 2 (103 cancer-positive and 100 cancer-free) were used as an independent test set. First, we identified miRNAs whose expression is associated with cancer by linear modeling in the discovery set. We next explored the relationships between the expression of these miRNAs and their predicted mRNA targets. Lastly, using logistic regression, we incorporated a cancer miRNA feature into our bronchial gene-expression classifier (Silvestri et al., NEJM 2015) and validated its performance in the test set. Results We found that expression profiles of 42 miRNAs were associated with cancer status in the discovery set (p&amp;lt;0.05, 23 miRNAs expected by chance). The top four differentially expressed miRNAs (q&amp;lt;0.2) were all decreased in the bronchial epithelium of cancer patients. The expression values of these miRNAs were significantly negatively correlated with the expression of their predicted mRNA targets (p&amp;lt;0.05). The predicted gene targets of the top miRNAs were significantly enriched (p&amp;lt;0.05) for cancer-related processes including the PDGF signaling pathway, insulin/IGF pathway-mitogen and activated protein kinase/MAP kinase cascade. Moreover, we found that the addition of one of the top differentially expressed miRNAs in the discovery set to the existing gene expression biomarker significantly improved the classifier's performance (ROC AUC) in the test set (p = 0.025). Conclusions We have established that there are alterations in miRNA expression in the cytologically normal mainstem bronchus of smokers with lung cancer. Importantly, we demonstrated the potential of these miRNA alterations to improve the performance of an existing bronchial gene expression biomarker for lung cancer detection. Citation Format: Ana Brandusa Pavel, Joshua Campbell, Gang Liu, Sherry Zhang, Hanqiao Liu, Ji Xiao, Kate Porta, Duncan Whitney, Steven Dubinett, David Elashoff, Marc Lenburg, Avrum Spira. microRNA expression in bronchial epithelium for lung cancer detection. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1954.

Multiplexed detection of lung cancer biomarkers based on quantum dots and microbeads

We have developed a multiplexed fluoroimmunoassay of three lung cancer biomarkers based on multicolor quantum dots (QDs) as detection elements and micro-magnetic beads as immune carriers. QDs have the ability to simplify multiplexed analysis. In our method, the fluorescent signals derived from three cross-talk-free QD conjugated probes with emission maxima at 525, 585 and 625nm could be analyzed to determine the concentrations of the target proteins. With this system, fragments of cytokeratin 19 (CYRFA 21-1), carcinoembryonic antigen (CEA), and neuron-specific enolase (NSE), were simultaneously detected in a single sample with a low detection limit down to the 1.0ng/mL level (364pg/mL for CYRFA 21-1, 38pg/mL for CEA, 370pg/mL for NSE in a single detection). Additional advantages of the presented method include ease of operation, low cost, and a very low sample volume (20µL).

The metabolomic detection of lung cancer biomarkers in sputum

ObjectivesDeveloping screening and diagnosis methodologies based on novel biomarkers should allow for the detection of the lung cancer (LC) and possibly at an earlier stage and thereby increase the effectiveness of clinical interventions. Here, our primary objective was to evaluate the potential of spontaneous sputum as a source of non-invasive metabolomic biomarkers for LC status. Materials and methodsSpontaneous sputum was collected and processed from 34 patients with suspected LC, alongside 33 healthy controls. Of the 34 patients, 23 were subsequently diagnosed with LC (LC+, 16 NSCLC, six SCLC, and one radiological diagnosis), at various stages of disease progression. The 67 samples were analysed using flow infusion electrospray ion mass spectrometry (FIE-MS) and gas-chromatography mass spectrometry (GC–MS). ResultsPrincipal component analysis identified negative mode FIE-MS as having the main separating power between samples from healthy and LC. Discriminatory metabolites were identified using ANOVA and Random Forest. Indications of potential diagnostic accuracy involved the use of receiver operating characteristic/area under the curve (ROC/AUC) analyses. This approach identified metabolites changes that were only observed with LC. Metabolites with AUC values of greater than 0.8 which distinguished between LC+/LC− binary classifications where identified and included Ganglioside GM1 which has previously been linked to LC. ConclusionThis study indicates that metabolomics based on sputum can yield metabolites that can be used as a diagnostic and/or discriminator tool. These could aid clinical intervention and targeted diagnosis of LC within an ‘at risk’ LC− population group. The use of sputum as a non-invasive source of metabolite biomarkers may aid in the development of an at-risk population screening programme for lung cancer or enhanced clinical diagnostic pathways.

Abstract A1-66: Leveraging Gene Expression in the Bronchial Airway to Develop a Nasal Biomarker for Early Detection of Lung Cancer

Abstract Rationale: Lung cancer results in five times more deaths per year than car accidents in the United States. Approximately 57% of lung cancers diagnosed this year will be diagnosed at a late stage and these patients will exhibit a 5-year survival rate of only 4%. Annual screening of high-risk current and former smokers by chest-CT can reduce cancer mortality, however this procedure has a 95% false positive rate. It is therefore critical to develop methods to rapidly and accurately determine which patients with nodules on chest CT have lung cancer and potentially spare those with benign disease an unnecessary invasive procedure. We have previously demonstrated that specific gene expression alterations in cytologically normal bronchial epithelial cells from patients with lung cancer can be leveraged to form a clinically informative lung cancer biomarker in the population of patients undergoing bronchoscopy for suspect lung cancer. We hypothesized that there might be similar expression differences in nasal epithelium and that these could form the basis of a less invasive test that could be applied more broadly to individuals with screen detected nodules on chest CT. Methods: Bronchial (n=676) and nasal (n=280) epithelial brushings were collected from current and former smokers undergoing bronchoscopy for clinical suspicion of lung cancer within the AEGIS clinical trial. 271 subjects had matched bronchial and nasal samples. RNA was extracted and hybridized to Affymetrix Human Gene ST 1.0 Arrays. To establish a connection between bronchial and nasal epithelial gene expression signal for cancer, we first applied the bronchial gene expression-based diagnostic test, BronchoGen, directly to our nasal cohort. Gene Set Enrichment Analysis was then used to determine the concordance of cancer signal between the bronchial and nasal epithelium. To develop the nasal gene expression biomarker for lung cancer detection, we examined the correlation of each gene between the bronchial and nasal epithelium as well as the significance of each gene's association with cancer in each tissue. Genes passing our selection criteria were passed to a biomarker discovery pipeline in which we examined the performance of different biomarker algorithm configurations (e.g. feature-selection algorithms, classification algorithms, and other biomarker parameters) using cross-validation. Results: Direct application of BronchoGen to our nasal cohort resulted in an AUC of 0.64 on a set of NE samples (n=110) with a matched bronchial sample in the training set used to develop the test. On an independent set of nasal samples (n=109), BronchoGen achieved an AUC of 0.67. Gene Set Enrichment Analysis revealed high levels of concordance between cancer-associated nasal and bronchial gene expression. Using a cross-validation approach, we found that nasal biomarkers built from sets of genes showing significant correlation (p&amp;lt;0.05) between the bronchial and nasal epithelium as well as significance for cancer in both tissues (p&amp;lt;0.05) perform better, on average, than biomarkers build from genes significant for cancer (p&amp;lt;0.05) in the nasal epithelium alone. Conclusions: Given the larger sample size, more isolated location in the airway, and higher RIN scores that characterize the bronchial cohort, we sought to leverage bronchial airway epithelial gene-expression to inform which genes in the nasal epithelium should be indicative of the presence of cancer. We have shown that gene expression in the nasal epithelium reflects the presence of lung cancer and can serve as a diagnostic biomarker. We have further demonstrated concordance between bronchial and nasal airway gene expression differences associated with lung cancer. These results suggest the potential to develop a robust nasal gene expression biomarker for lung cancer diagnosis that leverages cancer-associated gene expression differences occurring at other airway sites. Citation Format: Joseph F. Perez-Rogers, Joseph Gerrein, Christina Anderlind, Rebecca L. Kusko, Joshua D. Campbell, Teresa W. Wang, Kate Porta, Duncan Whitney, Avrum Spira, Marc Lenburg. Leveraging Gene Expression in the Bronchial Airway to Develop a Nasal Biomarker for Early Detection of Lung Cancer. [abstract]. In: Proceedings of the AACR Special Conference on Translation of the Cancer Genome; Feb 7-9, 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 1):Abstract nr A1-66.

Abstract B1-50: Leveraging gene expression in the bronchial airway to develop a nasal biomarker for early detection of lung cancer

Abstract Rationale: Lung cancer results in five times more deaths per year than car accidents in the United States. Approximately 57% of lung cancers diagnosed this year will be diagnosed at a late stage and these patients will exhibit a 5-year survival rate of only 4%. Annual screening of high-risk current and former smokers by chest-CT can reduce cancer mortality, however this procedure has a 95% false positive rate. It is therefore critical to develop methods to rapidly and accurately determine which patients with nodules on chest CT have lung cancer and potentially spare those with benign disease an unnecessary invasive procedure. We have previously demonstrated that specific gene expression alterations in cytologically normal bronchial epithelial cells from patients with lung cancer can be leveraged to form a clinically informative lung cancer biomarker in the population of patients undergoing bronchoscopy for suspect lung cancer. We hypothesized that there might be similar expression differences in nasal epithelium and that these could form the basis of a less invasive test that could be applied more broadly to individuals with screen detected nodules on chest CT. Methods: Bronchial (n=676) and nasal (n=280) epithelial brushings were collected from current and former smokers undergoing bronchoscopy for clinical suspicion of lung cancer within the AEGIS clinical trial. 271 subjects had matched bronchial and nasal samples. RNA was extracted and hybridized to Affymetrix Human Gene ST 1.0 Arrays. To establish a connection between bronchial and nasal epithelial gene expression signal for cancer, we first applied the bronchial gene expression based diagnostic test, BronchoGen, directly to our nasal cohort. Gene Set Enrichment Analysis was then used to determine the concordance of cancer signal between the bronchial and nasal epithelium. To develop the nasal gene-expression biomarker for lung cancer detection, we examined the correlation of each gene between the bronchial and nasal epithelium as well as the significance of each gene's association with cancer in each tissue. Genes passing our selection criteria were passed to a biomarker discovery pipeline in which we examined the performance of different biomarker algorithm configurations (e.g. feature-selection algorithms, classification algorithms, and other biomarker parameters) using cross-validation. Results: Direct application of BronchoGen to our nasal cohort resulted in an AUC of 0.64 on a set of NE samples (n=110) with a matched bronchial sample in the training set used to develop the test. On an independent set of nasal samples (n=109), BronchoGen achieved an AUC of 0.67. Gene Set Enrichment Analysis revealed high levels of concordance between cancer-associated nasal and bronchial gene expression. Using a cross-validation approach, we found that nasal biomarkers built from sets of genes showing significant correlation (p&amp;lt;0.05) between the bronchial and nasal epithelium as well as significance for cancer in both tissues (p&amp;lt;0.05) perform better, on average, than biomarkers build from genes significant for cancer (p&amp;lt;0.05) in the nasal epithelium alone. Conclusions: Given the larger sample size, more isolated location in the airway, and higher RIN scores that characterize the bronchial cohort, we sought to leverage bronchial airway epithelial gene expression to inform which genes in the nasal epithelium should be indicative of the presence of cancer. We have shown that gene expression in the nasal epithelium reflects the presence of lung cancer and can serve as a diagnostic biomarker. We have further demonstrated concordance between bronchial and nasal airway gene expression differences associated with lung cancer. These results suggest the potential to develop a robust nasal gene expression biomarker for lung cancer diagnosis that leverages cancer-associated gene expression differences occurring at other airway sites. Citation Format: Joseph F. Perez-Rogers, Joseph Gerrein, Christina Anderlind, Rebecca L. Kusko, Joshua D. Campbell, Teresa Wang, Kate Porta, Duncan Whitney, Avrum Spira, Marc Lenburg. Leveraging gene expression in the bronchial airway to develop a nasal biomarker for early detection of lung cancer. [abstract]. In: Proceedings of the AACR Special Conference on Computational and Systems Biology of Cancer; Feb 8-11 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 2):Abstract nr B1-50.

Abstract 1574: Leveraging bronchial airway gene expression to develop a nasal biomarker for lung cancer detection

Abstract Rationale: Using nasal gene expression to predict the presence of lung cancer would offer a less invasive alternative to diagnostic approaches we have pioneered using bronchial airway epithelial (BE) gene expression. We have previously demonstrated that cytologically normal BE and nasal epithelial (NE) cells harbor gene expression differences that reflect tobacco-related lung disease and that these changes in the BE form the basis of a clinically informative lung cancer biomarker. Given the concordance of BE and NE gene-expression, we hypothesized that gene signatures associated with the presence of lung cancer extend from the airway to the nose and that lung cancer associated BE gene-expression could be leveraged to develop more accurate nasal lung cancer biomarkers. Methods: BE (n = 676) and NE (n = 280) brushings were collected from current and former smokers undergoing bronchoscopy for clinical suspicion of lung cancer. We leveraged two methods to determine the concordance between BE and NE gene-expression signal for cancer. First we applied the bronchial gene expression-based diagnostic test directly to our nasal cohort. Second, we used Gene Set Enrichment Analysis (GSEA) to quantify the relationship between the BE and NE. To develop the nasal gene expression biomarker, we examined the correlation of each gene between the BE and NE. Genes passing our selection criteria were passed to a biomarker discovery pipeline in which we examined the performance of different biomarker algorithm configurations using cross-validation. Results: Direct application of the bronchial airway gene-expression classifier to an independent set of nasal samples (n = 109) resulted in an AUC of 0.67. GSEA revealed high concordance (p&amp;lt;0.001) between cancer-associated nasal and bronchial gene expression profiles from the same patients. Using a cross-validation approach, we found that nasal biomarkers built from sets of genes showing significant correlation (p&amp;lt;0.05) between the BE and NE as well as significance for cancer in both tissues (p&amp;lt;0.05) perform better, on average, than biomarkers built from genes significant for cancer (p&amp;lt;0.05) in the NE alone. Conclusions. We have demonstrated concordance between BE and NE gene expression differences associated with lung cancer. We have further shown that gene expression in the NE reflects the presence of lung cancer and can serve as a diagnostic biomarker. These results demonstrate the feasibility of leveraging cancer-associated gene expression changes throughout the airway to develop a minimally invasive and robust nasal gene expression biomarker for lung cancer diagnosis. Citation Format: Joseph Perez-Rogers, Joseph Gerrein, Christina Anderlind, Xiaohui Xiao, Hanqiao Liu, Rebecca Kusko, Joshua Campbell, Teresa Wang, Yuriy Alekseyev, Gang Liu, Kate Porta, Duncan Whitney, Avrum Spira, Marc Lenburg. Leveraging bronchial airway gene expression to develop a nasal biomarker for lung cancer detection. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1574. doi:10.1158/1538-7445.AM2015-1574

Abstract 3077: Dysregulation of microRNA-mRNA regulatory networks in the bronchial airway epithelium of smokers with lung cancer

Abstract We have previously shown that gene expression alterations in cytologically normal epithelial cells from the bronchial airway can be used as an early detection biomarker for lung cancer in smokers. We hypothesize that bronchial epithelial expression of microRNAs, as regulators of gene expression, may also be affected by the presence of cancer and may regulate some of these gene expression differences. We propose a novel method to identify microRNAs functionally associated with disease that leverages the relationship between microRNA and mRNA expression by determining the differential connectivity (DC) of microRNA-mRNA association networks between disease and normal states. Bronchial epithelial brushes were collected from 220 former and current smokers who underwent bronchoscopy for suspicion of lung cancer (120 lung cancer patients and 100 healthy controls). For these subjects, we profiled microRNA expression via small RNA sequencing and gene expression via microarray. Each microRNA node is assigned a DC score, which captures the overall difference in the pairwise microRNA-gene correlation strengths between lung cancer and control subjects. We quantify the change in both the directionality and strength of the correlations between a microRNA and the gene nodes. Then, the observed DC scores are compared to the DC scores obtained with permuted class labels to identify microRNAs with signinficant disease-specific differences in microRNA-mRNA connectivity. The proposed DC method identifies 54 microRNAs which are significantly differentially connected in lung cancer cases compared to controls (FDR&amp;lt;0.1). Among the 54 microRNAs we find those previously associated with lung cancer, such as known dysregulated oncomirs, regulators of drug sensitivity to anticancer agents or targets for DNA methylation in non-small cell lung cancers. In addition, the genes that are significantly correlated with the DC microRNAs are enriched in cancer and immune system related pathways, such as membrane trafficking, apoptosis, mitotic cell cycle, hemostasis, FC gamma R mediated phagocytosis and signaling by Rho GTPases (FDR&amp;lt;0.1). We propose a novel approach for integrating microRNA and gene expression data to identify disease-associated changes in gene regulation by microRNAs and show that the microRNA-mRNA networks are significantly different between disease and normal states. These data suggest that changes in microRNA expression may drive some of the gene expression alterations observed in the cytologically normal epithelium from the proximal airway of patients with lung cancer and that airway microRNA-mRNA expression changes may ultimately serve as a biomarker for lung cancer detection. Citation Format: Ana Brandusa Pavel, Joshua D. Campbell, Gang Liu, Sherry Zhang, Hanqiao Liu, Lingqi Luo, Ji Xiao, Kate Porta, Duncan Whitney, Steven Dubinett, David Elashoff, Marc E. Lenburg, Avrum Spira. Dysregulation of microRNA-mRNA regulatory networks in the bronchial airway epithelium of smokers with lung cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 3077. doi:10.1158/1538-7445.AM2015-3077

Detection of Lung Cancer Bio-markers in Human Breath Using a Micro-fabricated Air Analyzer

The analysis of volatile organic compounds (VOCs) that are linked to lung cancer is a very promising way in medical diagnostics because it is non-invasive and potentially inexpensive. In that sense, a silicon micro-analytical platform consisting of a three-dimensional micro-preconcentrator coupled to a silicon spiral gas chromatographic micro-column was built. A metal oxide-based gas sensor acted as a miniaturized gas detector. This system allowed selective detection of VOCs at the sub-ppm level. The present study is focused first on the chromatographic air analyzer fabrication and second on the selection of an appropriate adsorbent. Various adsorbents such as activated carbon microspheres and zeolites were then studied in order to identify the best material for the concentration of one representative lung cancer biomarker: toluene.

Rapid and Sensitive Detection of Lung Cancer Biomarker Using Nanoporous Biosensor Based on Localized Surface Plasmon Resonance Coupled with Interferometry

We propose a nanobiosensor to evaluate a lung cancer‐specific biomarker. The nanobiosensor is based on an anodic aluminum oxide (AAO) chip and functions on the principles of localized surface plasmon resonance (LSPR) and interferometry. The pore‐depth of the fabricated nanoporous AAO chip was 1 µm and was obtained using a two‐step electrochemical anodization process. The sensor chip is sensitive to the refractive index (RI) changes of the surrounding medium and also provides simple and label‐free detection when specific antibodies are immobilized on the gold‐deposited surface of the AAO chip. In order to confirm the effectiveness of the sensor, the antibodies were immobilized on the surface of the AAO chip, and the lung cancer‐specific biomarker was applied atop of the immobilized‐antibody layer using the self‐assembled monolayer method. The nanoporous AAO chip was used as a sensor system to detect serum amyloid A1, which is a lung cancer‐specific biomarker. The specific reaction of the antigen‐antibody contributes to the change in the RI. This in turn causes a shift in the resonance spectrum in the refractive interference pattern. The limit of detection (LOD) was found to be 100 ag/mL and the biosensor had high sensitivity over a wide concentration range.

Facile and label-free detection of lung cancer biomarker in urine by magnetically assisted surface-enhanced Raman scattering.

Adenosine plays a crucial role in the regulation of physiological activity in various tissues and organs. As adenosine is a possible biomarker for cancer, the determination of its level presents a demanding task for deeply monitoring progress of diseases. Through the synthesis of Fe3O4/Au/Ag nanocomposites weaved and stabilized by phytic acid and its salt, we develop a magnetically assisted surface-enhanced Raman scattering (SERS) protocol to determine trace level adenosine in urine samples from both lung cancer patients and health human. The magnetic properties of the nanocomposites enable to realize the simple separation of targeted molecules from a complex matrix and the Au/Ag nanoparticles moieties act as the SERS platform. This label-free Fe3O4/Au/Ag-nanocomposites-based SERS protocol shows a good stability, reproducibility, time efficiency (less than 20 min for one sample test), and huge sensitivity down to 1 × 10(-10) M. The protocol also has high selectivity because SERS signal of adenosine provides the molecular fingerprint information as well as an azo coupling pretreatment is performed to remove the interference of urea. Furthermore, a SERS array is designed for on-site screening adenosine in urine samples in a massive way using a portable Raman. Such a magnetically assisted SERS method as a powerful alternative can be expected as a smart and promising tool for effective assessment of healthcare.

Enhancing lung cancer diagnosis: electrochemical simultaneous bianalyte immunosensing using carbon nanotubes-chitosan nanocomposite.

A label-free electrochemical bianalyte immunosensor has been designed for simultaneous detection of lung cancer biomarkers (anti-MAGE A2 and anti-MAGE A11) using carbon nanotubes-chitosan (CNT-CHI) composite. To achieve this, acid-functionalized single-walled CNTs were used to prepare CNT-CHI gel and electrodes were fabricated by drop casting method onto graphite surface. Lung cancer biomarkers specific antigens (Ag), i.e., MAGE A2 and MAGE A11, were covalently immobilized onto CNT-CHI/graphite electrode separately for fabrication process. Fabricated immunoelectrodes (MAGE A2/CNT-CHI/graphite and MAGE A11/CNT-CHI/graphite) were characterized at each modification step by cyclic voltammetry (CV), Fourier transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM). Both immunoelectrodes showed successful detection of respective analytes (anti-MAGE A2 and anti-MAGE A11) from 5fgmL(-1) to 50ngmL(-1) using differential pulse voltammetry (DPV). Both Ag/CNT-CHI/graphite immunoelectrodes (using MAGE A2 and MAGE A11) were independently capable of distinguishing specific and nonspecific analytes like CD59, D-dimers, etc. Response studies of both immunoelectrodes revealed successful demonstration of simultaneous detection of anti-MAGE A2 and A11 independently in a single experimental run when exposed to a mixture of various analyte concentrations in different combinations irrespective of the presence of other analyte present in the same vessel.

Toward rapid, high-sensitivity, volume-constrained biomarker quantification and validation using backscattering interferometry.

Realizing personalized medicine, which promises to enable early disease detection, efficient diagnostic staging, and therapeutic efficacy monitoring, hinges on biomarker quantification in patient samples. Yet, the lack of a sensitive technology and assay methodology to rapidly validate biomarker candidates continues to be a bottleneck for clinical translation. In our first direct and quantitative comparison of backscattering interferometry (BSI) to fluorescence sensing by ELISA, we show that BSI could aid in overcoming this limitation. The analytical validation study was performed against ELISA for two biomarkers for lung cancer detection: Cyfra 21-1 and Galectin-7. Spiked serum was used for calibration and comparison of analytical figures of merit, followed by analysis of blinded patient samples. Using the ELISA antibody as the probe chemistry in a mix-and-read assay, BSI provided significantly lower detection limits for spiked serum samples with each of the biomarkers. The limit of quantification (LOQ) for Cyrfa-21-1 was measured to be 230 pg/mL for BSI versus 4000 pg/mL for ELISA, and for Galectin-7, it was 13 pg/mL versus 500 pg/mL. The coefficient of variation for 5 day, triplicate determinations was <15% for BSI and <10% for ELISA. The two techniques correlated well, ranging from 3–29% difference for Cyfra 21-1 in a blinded patient sample analysis. The label-free and free-solution operation of BSI allowed for a significant improvement in analysis speed, with greater ease, improved LOQ values, and excellent day-to-day reproducibility. In this unoptimized format, BSI required 5.5-fold less sample quantity needed for ELISA (a 10 point calibration curve measured in triplicate required 36 μL of serum for BSI vs 200 μL for ELISA). The results indicate that the BSI platform can enable rapid, sensitive analytical validation of serum biomarkers and should significantly impact the validation bottleneck of biomarkers.