Identification of lung cancer with high sensitivity and specificity by blood testing

<p>Abstract</p> <p>Background</p> <p>Lung cancer is a very frequent and lethal tumor with an identifiable risk population. Cytological analysis and chest X-ray failed to reduce mortality, and CT screenings are still controversially discussed. Recent studies provided first evidence for the potential usefulness of autoantigens as markers for lung cancer.</p> <p>Methods</p> <p>We used extended panels of arrayed antigens and determined autoantibody signatures of sera from patients with different kinds of lung cancer, different common non-tumor lung pathologies, and controls without any lung disease by a newly developed computer aided image analysis procedure. The resulting signatures were classified using linear kernel Support Vector Machines and 10-fold cross-validation.</p> <p>Results</p> <p>The novel approach allowed for discriminating lung cancer patients from controls without any lung disease with a specificity of 97.0%, a sensitivity of 97.9%, and an accuracy of 97.6%. The classification of stage IA/IB tumors and controls yielded a specificity of 97.6%, a sensitivity of 75.9%, and an accuracy of 92.9%. The discrimination of lung cancer patients from patients with non-tumor lung pathologies reached an accuracy of 88.5%.</p> <p>Conclusion</p> <p>We were able to separate lung cancer patients from subjects without any lung disease with high accuracy. Furthermore, lung cancer patients could be seprated from patients with other non-tumor lung diseases. These results provide clear evidence that blood-based tests open new avenues for the early diagnosis of lung cancer.</p

Toward the perfect membrane material for environmental x ray photoelectron spectroscopy

We outline our achievements in developing electron transparent, leak tight membranes required for environmental photoelectron spectroscopy PES . We discuss the mechanical constraints limiting the achievable membrane size and review the development of growth protocols for the chemical vapor deposition CVD of single crystalline graphene on highly 111 textured Cu foils serving as membrane material. During CVD growth, Cu tends to develop a mesoscopic staircase morphology consisting of alternating inclined surface planes, irrespective of whether the covering graphene film or the substrate are single crystalline. This morphology remains imprinted even when converting the film into freestanding graphene, which affects its mechanical properties. Determining the number of carbon layers in freestanding graphene, we show that membranes reported to suspend over distances larger than 20 m most likely consist of few layer graphene. The Raman band signature often used to confirm monolayer graphene rather relates to graphene with turbostratic stacking. The vertical corrugation of freestanding graphene was shown to be almost absent for tri and four layer thick graphene but substantial for bilayer and especially for monolayer graphene. The corrugation is reduced when mechanically straining the freestanding graphene through thermal expansion of the supporting frame, especially flattening membrane areas with imprinted staircase morphology. The electron signal attenuation through supported and freestanding graphene was determined as a function of the electron kinetic energy, verifying that large area graphene based electron windows have sufficient electron transparency required for environmental PES. Meanwhile, we managed to cover 100 m sized single holes by few layer graphene up to a coverage fraction of over 99.9998 , as deduced when applying 10 mbar air on one side of the sealing membrane without detecting any measurable pressure increase on its ultrahigh vacuum side. The reported achievements will pave the way toward the development of laboratory based environmental PE

Finding the association of mRNA and miRNA using Next Generation Sequencing data of Kidney renal cell carcinoma

MicroRNAs (miRNAs) are a class of 22-nucleotide endogenous noncod- ing RNAs, plays important role in regulating target gene expression via repress- ing translation or promoting messenger RNAs (mRNA) degradation. Numerous re- searchers have found that miRNAs have serious effects on cancer. Therefore, study of mRNAs and miRNAs together through the integrated analysis of mRNA and miRNA expression profiling could help us in getting a deeper insight into the can- cer research. In this regards, High-Throughput Sequencing data of Kidney renal cell carcinoma is used here. The proposed method focuses on identifying mRNA- miRNA pair that has a signature in kidney tumor sample. For this analysis, Ran- dom Forests, Particle Swarm Optimization and Support Vector Machine classifier is used to have best sets of mRNAs-miRNA pairs. Additionally, the significance of selected mRNA-miRNA pairs is tested using gene ontology and pathway analysis tools. Moreover, the selected mRNA-miRNA pairs are searched based on changes in expression values of the used mRNA and miRNA dataset

A blood based 12-miRNA signature of Alzheimer disease patients

Background: Alzheimer disease (AD) is the most common form of dementia but the identification of reliable, early and non-invasive biomarkers remains a major challenge. We present a novel miRNA-based signature for detecting AD from blood samples. Results: We apply next-generation sequencing to miRNAs from blood samples of 48 AD patients and 22 unaffected controls, yielding a total of 140 unique mature miRNAs with significantly changed expression levels. Of these, 82 have higher and 58 have lower abundance in AD patient samples. We selected a panel of 12 miRNAs for an RT-qPCR analysis on a larger cohort of 202 samples, comprising not only AD patients and healthy controls but also patients with other CNS illnesses. These included mild cognitive impairment, which is assumed to represent a transitional period before the development of AD, as well as multiple sclerosis, Parkinson disease, major depression, bipolar disorder and schizophrenia. miRNA target enrichment analysis of the selected 12 miRNAs indicates an involvement of miRNAs in nervous system development, neuron projection, neuron projection development and neuron projection morphogenesis. Using this 12-miRNA signature, we differentiate between AD and controls with an accuracy of 93%, a specificity of 95% and a sensitivity of 92%. The differentiation of AD from other neurological diseases is possible with accuracies between 74% and 78%. The differentiation of the other CNS disorders from controls yields even higher accuracies. Conclusions: The data indicate that deregulated miRNAs in blood might be used as biomarkers in the diagnosis of AD or other neurological diseases

Multiple Sclerosis: MicroRNA Expression Profiles Accurately Differentiate Patients with Relapsing-Remitting Disease from Healthy Controls

Multiple sclerosis (MS) is a chronic inflammatory demyelinating disease of the central nervous system, which is heterogenous with respect to clinical manifestations and response to therapy. Identification of biomarkers appears desirable for an improved diagnosis of MS as well as for monitoring of disease activity and treatment response. MicroRNAs (miRNAs) are short non-coding RNAs, which have been shown to have the potential to serve as biomarkers for different human diseases, most notably cancer. Here, we analyzed the expression profiles of 866 human miRNAs. In detail, we investigated the miRNA expression in blood cells of 20 patients with relapsing-remitting MS (RRMS) and 19 healthy controls using a human miRNA microarray and the Geniom Real Time Analyzer (GRTA) platform. We identified 165 miRNAs that were significantly up- or downregulated in patients with RRMS as compared to healthy controls. The best single miRNA marker, hsa-miR-145, allowed discriminating MS from controls with a specificity of 89.5%, a sensitivity of 90.0%, and an accuracy of 89.7%. A set of 48 miRNAs that was evaluated by radial basis function kernel support vector machines and 10-fold cross validation yielded a specificity of 95%, a sensitivity of 97.6%, and an accuracy of 96.3%. While 43 of the 165 miRNAs deregulated in patients with MS have previously been related to other human diseases, the remaining 122 miRNAs are so far exclusively associated with MS. The implications of our study are twofold. The miRNA expression profiles in blood cells may serve as a biomarker for MS, and deregulation of miRNA expression may play a role in the pathogenesis of MS