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      Detection of Cancer with Serum miRNAs on an Oligonucleotide Microarray

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          Abstract

          Micro RNAs (miRNAs) are a class of small, non-coding RNA species that play critical roles throughout cellular development and regulation. miRNA expression patterns taken from various tissue types often point to the cellular lineage of an individual tissue type, thereby being a more invariant hallmark of tissue type. Recent work has shown that these miRNA expression patterns can be used to classify tumor cells, and that this classification can be more accurate than the classification achieved by using messenger RNA gene expression patterns. One aspect of miRNA biogenesis that makes them particularly attractive as a biomarker is the fact that they are maintained in a protected state in serum and plasma, thus allowing the detection of miRNA expression patterns directly from serum. This study is focused on the evaluation of miRNA expression patterns in human serum for five types of human cancer, prostate, colon, ovarian, breast and lung, using a pan-human microRNA, high density microarray. This microarray platform enables the simultaneous analysis of all human microRNAs by either fluorescent or electrochemical signals, and can be easily redesigned to include newly identified miRNAs. We show that sufficient miRNAs are present in one milliliter of serum to detect miRNA expression patterns, without the need for amplification techniques. In addition, we are able to use these expression patterns to correctly discriminate between normal and cancer patient samples.

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          Cluster analysis and display of genome-wide expression patterns.

          A system of cluster analysis for genome-wide expression data from DNA microarray hybridization is described that uses standard statistical algorithms to arrange genes according to similarity in pattern of gene expression. The output is displayed graphically, conveying the clustering and the underlying expression data simultaneously in a form intuitive for biologists. We have found in the budding yeast Saccharomyces cerevisiae that clustering gene expression data groups together efficiently genes of known similar function, and we find a similar tendency in human data. Thus patterns seen in genome-wide expression experiments can be interpreted as indications of the status of cellular processes. Also, coexpression of genes of known function with poorly characterized or novel genes may provide a simple means of gaining leads to the functions of many genes for which information is not available currently.
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            TreeView: an application to display phylogenetic trees on personal computers.

            R D Page (1996)
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              The thermodynamics of DNA structural motifs.

              DNA secondary structure plays an important role in biology, genotyping diagnostics, a variety of molecular biology techniques, in vitro-selected DNA catalysts, nanotechnology, and DNA-based computing. Accurate prediction of DNA secondary structure and hybridization using dynamic programming algorithms requires a database of thermodynamic parameters for several motifs including Watson-Crick base pairs, internal mismatches, terminal mismatches, terminal dangling ends, hairpins, bulges, internal loops, and multibranched loops. To make the database useful for predictions under a variety of salt conditions, empirical equations for monovalent and magnesium dependence of thermodynamics have been developed. Bimolecular hybridization is often inhibited by competing unimolecular folding of a target or probe DNA. Powerful numerical methods have been developed to solve multistate-coupled equilibria in bimolecular and higher-order complexes. This review presents the current parameter set available for making accurate DNA structure predictions and also points to future directions for improvement.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2009
                14 July 2009
                : 4
                : 7
                : e6229
                Affiliations
                [1]CombiMatrix Corporation, Mukilteo, Washington, United States of America
                Cinvestav, Mexico
                Author notes

                Conceived and designed the experiments: MJL DS AK BA. Performed the experiments: MJL MC SM. Analyzed the data: MC DS BA. Wrote the paper: MJL.

                Article
                09-PONE-RA-08537R1
                10.1371/journal.pone.0006229
                2704963
                19597549
                5f25e771-c1c2-4f69-b3f2-47b01b4b0187
                Lodes et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 3 February 2009
                : 4 June 2009
                Page count
                Pages: 12
                Categories
                Research Article
                Biotechnology
                Molecular Biology
                Oncology
                Public Health and Epidemiology/Screening

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                Uncategorized

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