Biomarkers For Detection Of Lung Cancer Research Articles

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.

Overexpression of TMPRSS4 in non-small cell lung cancer is associated with poor prognosis in patients with squamous histology

Background:Mortality rates in lung cancer patients have not decreased significantly in recent years, even with the implementation of new therapeutic regimens. One of the main problems is that a large proportion of patients present local or distant metastasis at the time of diagnosis. The need for identification of novel biomarkers and therapeutic targets for a more effective management of lung cancer led us to investigate TMPRSS4, a protease reported to promote tumour growth and metastasis.Material and methods:In all, 34 lung cancer cell lines were used to evaluate the TMPRSS4 expression. Cell migration and clonogenic assays, and an in-vivo lung metastasis model were used for functional analysis of the TMPRSS4 downregulation in H358, H441 and H2170 cell lines. The TMPRSS4 expression analysis in normal and malignant lung tissue samples was performed by qPCR. Five different microarray-based publicly available expression databases were used to validate our results and to study prognosis.Results:The TMPRSS4 knock down in H358, H441 and H2170 cells resulted in a significant reduction in proliferation, clonogenic capacity and invasion. A significant (P<0.05) decrease in the lung colonisation and growth was found when mice were injected with TMPRSS4-depleated H358-derived clones, as compared with controls. Expression of TMPRSS4 showed a >30-fold increase (P<0.001) in tumours in comparison with non-malignant samples. Levels in tumours with squamous cell carcinoma (SCC) histology were found to be significantly higher (P<0.001) than those with adenocarcinoma (AC) histology, which was confirmed in data retrieved from the microarrays. Kaplan–Meier curves demonstrated that high levels of TMPRSS4 were significantly associated (P=0.017) with reduced overall survival in the patients with SCC histology, whereas no correlation was found for the AC histology.Conclusion:Our results demonstrate that TMPRSS4 has a role in the lung cancer development. The potential use of TMPRSS4 as a biomarker for lung cancer detection or as a predictor of patient's outcome warrants further investigation.

Novel e-nose for the discrimination of volatile organic biomarkers with an array of carbon nanotubes (CNT) conductive polymer nanocomposites (CPC) sensors

We report the original design of a new type of electronic nose (e-nose) consisting of only five sensors made of hierarchically structured conductive polymer nanocomposites (CPC). Each sensor benefits from both the exceptional electrical properties of carbon nanotubes (CNT) used to build the conductive architecture and the spray layer by layer (sLbL) assembly technique, which provides the transducers with a highly specific 3D surface structure. Excellent sensitivity and selectivity were obtained by optimizing the amount of CNT with five different polymer matrices: poly(caprolactone) (PCL), poly(lactic acid) (PLA), poly(carbonate) (PC), poly(methyl methacrylate) (PMMA) and a biobased polyester (BPR). The ability of the resulting e-nose to detect nine organic solvent vapours (isopropanol, tetrahydrofuran, dichloromethane, n-heptane, cyclohexane, methanol, ethanol, water and toluene), as well as biomarkers for lung cancer detection in breath analysis, has been demonstrated. Principal component analysis (PCA) proved to be an excellent pattern recognition tool to separate vapour clusters.

Breath biomarkers for lung cancer detection and assessment of smoking related effects — confounding variables, influence of normalization and statistical algorithms

Up to now, none of the breath biomarkers or marker sets proposed for cancer recognition has reached clinical relevance. Possible reasons are the lack of standardized methods of sampling, analysis and data processing and effects of environmental contaminants. Concentration profiles of endogenous and exogenous breath markers were determined in exhaled breath of 31 lung cancer patients, 31 smokers and 31 healthy controls by means of SPME-GC-MS. Different correcting and normalization algorithms and a principal component analysis were applied to the data. Differences of exhalation profiles in cancer and non-cancer patients did not persist if physiology and confounding variables were taken into account. Smoking history, inspired substance concentrations, age and gender were recognized as the most important confounding variables. Normalization onto PCO2 or BSA or correction for inspired concentrations only partially solved the problem. In contrast, previous smoking behaviour could be recognized unequivocally. Exhaled substance concentrations may depend on a variety of parameters other than the disease under investigation. Normalization and correcting parameters have to be chosen with care as compensating effects may be different from one substance to the other. Only well-founded biomarker identification, normalization and data processing will provide clinically relevant information from breath analysis.

Combination of quantum dot fluorescence with enzyme chemiluminescence for multiplexed detection of lung cancer biomarkers

A new concept is proposed in this article to detect multiple cancer markers in a single sample. Quantum dot (QD) fluorescence (FL) labels were successfully combined with enzyme chemiluminescence (CL) labels for simultaneous detection of three cancer markers in human serum using just a common 96-well plate reader and with equal detection limits for the three markers. As a proof-of-concept, herein we coupled one QD FL label with two enzyme CL labels for hybrid multiplexed detection of lung cancer markers as exemplified by neuron-specific enolase (NSE), carcinoembryonic antigen (CEA) and cytokeratin fragment (Cyfra21-1). A homogeneous “sandwich-type” detection strategy was employed herein, where the bead–antibody mixture first reacts with NSE, CEA and Cyfra21-1 to initiate three immunoreactions in a single tube; and then the formed conjugates sandwiches with biotin, digoxin and fluoresceinisothiocyanate (FITC)-modified detection antibodies, and further reacts with a mixture of streptavidin QD, anti-FITC horseradish peroxidase (HRP) and anti-digoxin alkaline phosphatase (ALP) for subsequent CL and FL detection. The results show that NSE, CEA and Cyfra21-1 could be sensitively determined with a common 96-well plate reader and with equal detection limits down to the ng mL−1 level. Furthermore, the proposed method has been successfully applied to the determination of three cancer markers in human samples without cross-reaction. Because it is straightforward to adapt this strategy to detect a spectrum of other proteins by using different antibodies or aptamers, this new CL strategy might create a universal technology for developing simple biosensors in the sensitive and selective detection of multiple targets in a variety of clinical, environmental, and biodefense applications.

80P MULTIPLEX IMMUNOASSAY ASSAY ANALYSIS OF DIFFERENTIALLY EXPRESSED BIOMARKERS OF NON-SMALL CELL LUNG CANCER

Background: Symptoms of lung cancer (LC) often do not appear until the disease is advanced; only 15% of LC cases are discovered while the tumor is in the early stages of development. Carcinogen exposure, asthma and smoking have been identified as risk factors for the development of LC. Early detection of LC will likely have a major impact on the natural history of the disease and facilitate curative treatment. The objective of this study was to extend our previous efforts in the application multiplexed immunoassays to identify a panel of biomarkers for early detection of LC. Methods: Normal (NO) serum controls (n = 300) from healthy volunteers and non-small cell lung cancer patients (n = 334) were acquired from commercial vendors. Serum levels of 42 cytokines, growth factors and biologically active peptides were quantified using multiplexed immunoassays using the Luminex platform to identify biomarkers that are expressed in a significantly different manner in individuals with LC in comparison with NO subjects. Data were reduced using inter-pathology comparisons with statistical significance determined using Student’s t test. Results: Multiple analytes showed highly significant differences (p < 0.0002) between LC and healthy controls as single indices of pathologic state. Using multiplexed assays we found significant differences in biomarker levels in sera of LC compared to NO. Our results provide support for the application of multiplexed immunoassay-based analysis of serum biomarker profiles as clinical tools for the diagnosis of pathology and as an aid in the development of novel agents for prevention, early detection and treatment of LC. Conclusions: We have identified a group of markers having high inter-pathology discrimination power that are capable of reliably differentiating LC from normal specimens. This panel will be further validated by the application of confirmatory techniques but we are confident that these measures will produce clinical assays capable of reliably diagnosing lung pathology.

Multiple genetic and epigenetic biomarkers for lung cancer detection in cytologically negative sputum and a nested case–control study for risk assessment

The purpose of this study was to define a biomarker panel for detection of cancer cells in cytologically negative sputum and to evaluate the panel for assessment of lung cancer risk. We examined 19 genetic and epigenetic markers using a sensitive fluorescence-based method in cytologically negative sputum and in lung tumour tissues from 82 lung cancer patients. We also used these markers to test the sputum of 37 cancer-free individuals who were matched by age, sex, and smoking habit. Based on the concordance of biomarkers in lung tumours and corresponding sputum, and the low prevalence in cancer-free individuals, we selected seven markers for a nested case-control study: microsatellite instability of D9S942; loss of heterozygosity of D9S286, D9S942, GATA49D12, and D13S170; and methylation of p16INK4a and RARbeta. Based on the assumption that a lung cancer cell has alterations in two or more of the seven biomarkers, we compared the pattern of biomarker alteration in lung tumours and corresponding sputum. Our comparison yielded a sensitivity of 82%, specificity of 75%, and concordance of 79%. Three cancer-free individuals were considered to have an elevated risk based on the criterion that their sputum showed alteration in two of the seven biomarkers. One individual was indeed diagnosed as having lung cancer 18 months after sputum collection. In the nested case-control study, six biomarkers showed significantly increased odds ratios ranging from 3.14 to 11.24. Our study defines a biomarker panel for detection of cancer cells in cytologically negative sputum and verifies its use for risk assessment of lung cancer. In combination with conventional diagnostic tools, this multiple genetic and epigenetic panel should improve the detection or risk assessment of lung cancer.

Application of differential display to identify genes for lung cancer detection in peripheral blood.

A blood assay for detection of lung cancer biomarkers could significantly improve cancer patient prognosis and survival rates. Amplified fragment length polymorphism-differential display (AFLP-DD) was used to identify gene transcripts found in lung cancer tissue and the peripheral blood of lung cancer patients. The clones were evaluated for gene expression in lung cancer tissue, peripheral blood of lung cancer patients and healthy volunteers' blood. The isolated gene transcript clones were found to be from the syndecan 1 gene, collagen 1 gene and 2 novel genes. All 4 transcripts were expressed in normal lung tissue, 4 cultured primary lung cells and 6 lung cancer cell lines. RNA was isolated from peripheral blood samples of 69 lung cancer patients. Reverse transcriptase polymerase chain reaction (RT-PCR) was used to test for the presence of cytokeratin 19 and the 4 gene mRNA transcripts in blood RNA. The positive detection rate of at least 1 of the 5 transcripts was 79% for lung adenocarcinoma and 62% for squamous carcinoma. Using RT-PCR, at least 1 of the markers was found in 53% of stage I patients, 100% of stage II, 71% of stage III and 81% of stage IV lung cancer patients. Blood samples from 20 healthy volunteers were also tested, but only 1 of the 5 transcripts was found in 1 patient. These new molecular markers may aid early detection, staging and follow-up of lung cancer patients by RNA isolated from blood.