BACKGROUND: MicroRNA (miRNA) signatures are not only found in cancer tissue but also in blood of cancer patients. Specifically, miRNA detection in blood offers the prospect of a non-invasive analysis tool. METHODS: Using a microarray based approach we screened almost 900 human miRNAs to detect miRNAs that are deregulated in their expression in blood cells of melanoma patients. We analyzed 55 blood samples, including 20 samples of healthy individuals, 24 samples of melanoma patients as test set, and 11 samples of melanoma patients as independent validation set. RESULTS: A hypothesis test based approach detected 51 differentially regulated miRNAs, including 21 miRNAs that were downregulated in blood cells of melanoma patients and 30 miRNAs that were upregulated in blood cells of melanoma patients as compared to blood cells of healthy controls. The tets set and the independent validation set of the melanoma samples showed a high correlation of fold changes (0.81). Applying hierarchical clustering and principal component analysis we found that blood samples of melanoma patients and healthy individuals can be well differentiated from each other based on miRNA expression analysis. Using a subset of 16 significant deregulated miRNAs, we were able to reach a classification accuracy of 97.4%, a specificity of 95% and a sensitivity of 98.9% by supervised analysis. MiRNA microarray data were validated by qRT-PCR. CONCLUSIONS: Our study provides strong evidence for miRNA expression signatures of blood cells as useful biomarkers for melanoma.
BACKGROUND: MicroRNA (miRNA) signatures are not only found in cancer tissue but also in blood of cancerpatients. Specifically, miRNA detection in blood offers the prospect of a non-invasive analysis tool. METHODS: Using a microarray based approach we screened almost 900 human miRNAs to detect miRNAs that are deregulated in their expression in blood cells of melanomapatients. We analyzed 55 blood samples, including 20 samples of healthy individuals, 24 samples of melanomapatients as test set, and 11 samples of melanomapatients as independent validation set. RESULTS: A hypothesis test based approach detected 51 differentially regulated miRNAs, including 21 miRNAs that were downregulated in blood cells of melanomapatients and 30 miRNAs that were upregulated in blood cells of melanomapatients as compared to blood cells of healthy controls. The tets set and the independent validation set of the melanoma samples showed a high correlation of fold changes (0.81). Applying hierarchical clustering and principal component analysis we found that blood samples of melanomapatients and healthy individuals can be well differentiated from each other based on miRNA expression analysis. Using a subset of 16 significant deregulated miRNAs, we were able to reach a classification accuracy of 97.4%, a specificity of 95% and a sensitivity of 98.9% by supervised analysis. MiRNA microarray data were validated by qRT-PCR. CONCLUSIONS: Our study provides strong evidence for miRNA expression signatures of blood cells as useful biomarkers for melanoma.
Authors: Nozomu Yanaihara; Natasha Caplen; Elise Bowman; Masahiro Seike; Kensuke Kumamoto; Ming Yi; Robert M Stephens; Aikou Okamoto; Jun Yokota; Tadao Tanaka; George Adrian Calin; Chang-Gong Liu; Carlo M Croce; Curtis C Harris Journal: Cancer Cell Date: 2006-03 Impact factor: 31.743
Authors: Andreas Keller; Petra Leidinger; Andrea Bauer; Abdou Elsharawy; Jan Haas; Christina Backes; Anke Wendschlag; Nathalia Giese; Christine Tjaden; Katja Ott; Jens Werner; Thilo Hackert; Klemens Ruprecht; Hanno Huwer; Junko Huebers; Gunnar Jacobs; Philip Rosenstiel; Henrik Dommisch; Arne Schaefer; Joachim Müller-Quernheim; Bernd Wullich; Bastian Keck; Norbert Graf; Joerg Reichrath; Britta Vogel; Almut Nebel; Sven U Jager; Peer Staehler; Ioannis Amarantos; Valesca Boisguerin; Cord Staehler; Markus Beier; Matthias Scheffler; Markus W Büchler; Joerg Wischhusen; Sebastian F M Haeusler; Johannes Dietl; Sylvia Hofmann; Hans-Peter Lenhof; Stefan Schreiber; Hugo A Katus; Wolfgang Rottbauer; Benjamin Meder; Joerg D Hoheisel; Andre Franke; Eckart Meese Journal: Nat Methods Date: 2011-09-04 Impact factor: 28.547
Authors: Jiguo Wu; Ana P Ferragut Cardoso; Vanessa A R States; Laila Al-Eryani; Mark Doll; Sandra S Wise; Shesh N Rai; J Christopher States Journal: Toxicol Appl Pharmacol Date: 2019-06-06 Impact factor: 4.219