Abstract
Deep sequencing is an advanced technology in genomic biology to detect the precise order of nucleotides in a strand of DNA/RNA molecule. The analysis of deep sequencing data also requires sophisticated knowledge in both computational software and bioinformatics. In this chapter, the procedures of deep sequencing analysis of microRNA (miRNA) transcriptome in triple-negative breast cancer and adjacent normal tissue are described in detail. As miRNAs are critical regulators of gene expression and many of them were previously reported to be associated with the malignant progression of human cancer, the analytical method that accurately identifies deregulated miRNAs in a specific type of cancer is thus important for the understanding of its tumor behavior. We obtained raw sequence reads of miRNA expression from 24 triple-negative breast cancers and 14 adjacent normal tissues using deep sequencing technology in this work. Expression data of miRNA reads were normalized with the quantile-quantile scaling method and were analyzed statistically. A miRNA expression signature composed of 25 differentially expressed miRNAs showed to be an effective classifier between triple-negative breast cancers and adjacent normal tissues in a hierarchical clustering analysis.
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Acknowledgment
This work was supported by the National Science Council (NSC97-2314-B-002-154-MY3), the Department of Health (DOH101-TDC-111-001), and the National Health Research Institutes (NHRI-EX105-10419BI) in Taiwan.
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Chang, YY., Lai, LC., Tsai, MH., Chuang, E.Y. (2018). Deep Sequencing Reveals a MicroRNA Expression Signature in Triple-Negative Breast Cancer. In: Wu, W. (eds) MicroRNA and Cancer. Methods in Molecular Biology, vol 1699. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7435-1_8
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DOI: https://doi.org/10.1007/978-1-4939-7435-1_8
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