Biomarkers For Detection Of Lung Cancer Research Articles

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.