Research article

miRNAs in lung cancer - Studying complex fingerprints in patient's blood cells by microarray experiments

Andreas Keller^1* , Petra Leidinger^2* , Anne Borries¹ , Anke Wendschlag¹ , Frank Wucherpfennig¹ , Matthias Scheffler¹ , Hanno Huwer³ , Hans-Peter Lenhof⁴ and Eckart Meese²

¹  febit biomed gmbh, Im Neuenheimer Feld 519, 69120 Heidelberg, Germany

²  Department of Human Genetics, Medical School, Saarland University, Building 60, 66421 Homburg, Germany

³  Department of Cardiothoracic Surgery, Voelklingen Heart Center, 66333 Voelklingen, Germany

⁴  Center for Bioinformatics, Saarland University, Building E 1 1, 66041Saarbruecken, Germany

author email corresponding author email* Contributed equally

BMC Cancer 2009, 9:353doi:10.1186/1471-2407-9-353

Published:	6 October 2009

Abstract

Background

Deregulated miRNAs are found in cancer cells and recently in blood cells of cancer patients. Due to their inherent stability miRNAs may offer themselves for blood based tumor diagnosis. Here we addressed the question whether there is a sufficient number of miRNAs deregulated in blood cells of cancer patients to be able to distinguish between cancer patients and controls.

Methods

We synthesized 866 human miRNAs and miRNA star sequences as annotated in the Sanger miRBase onto a microarray designed by febit biomed gmbh. Using the fully automated Geniom Real Time Analyzer platform, we analyzed the miRNA expression in 17 blood cell samples of patients with non-small cell lung carcinomas (NSCLC) and in 19 blood samples of healthy controls.

Results

Using t-test, we detected 27 miRNAs significantly deregulated in blood cells of lung cancer patients as compared to the controls. Some of these miRNAs were validated using qRT-PCR. To estimate the value of each deregulated miRNA, we grouped all miRNAs according to their diagnostic information that was measured by Mutual Information. Using a subset of 24 miRNAs, a radial basis function Support Vector Machine allowed for discriminating between blood cellsamples of tumor patients and controls with an accuracy of 95.4% [94.9%-95.9%], a specificity of 98.1% [97.3%-98.8%], and a sensitivity of 92.5% [91.8%-92.5%].

Conclusion

Our findings support the idea that neoplasia may lead to a deregulation of miRNA expression in blood cells of cancer patients compared to blood cells of healthy individuals. Furthermore, we provide evidence that miRNA patterns can be used to detect human cancers from blood cells.