Automated Five-Color Multiplex Co-detection of MicroRNA and Protein Expression in Fixed Tissue Specimens

التفاصيل البيبلوغرافية
العنوان: Automated Five-Color Multiplex Co-detection of MicroRNA and Protein Expression in Fixed Tissue Specimens
المؤلفون: Matti Kiupel, Anna Moore, Elizabeth Kenyon, Erin Zaluzec, Lorenzo F. Sempere
المصدر: Methods in Molecular Biology ISBN: 9781071606223
بيانات النشر: Springer US, 2020.
سنة النشر: 2020
مصطلحات موضوعية: Cytokeratin, Molecular pathology, microRNA, biology.protein, Multiplex, Vimentin, In situ hybridization, Computational biology, Biology, Non-coding RNA, Small nuclear RNA
الوصف: microRNAs are an important class of noncoding regulatory RNAs with functional roles in development, physiology, and disease. Visualization of microRNA expression at a single-cell level has contributed to a better understanding of their biological function in animal models and their etiological contribution to human diseases. In addition, several microRNAs have been highlighted as potential biomarkers carrying diagnostic and prognostic information. Co-detection of microRNA expression with that of cell-type-specific proteins can enhance the interpretative power of expression changes during development or altered expression in pathological conditions. Here, we describe an automated fluorescence-based five-color multiplex assay for co-detection of microRNA (e.g., miR-10b, miR-21, miR-205), noncoding RNA (e.g., snRNA U6, 18S rRNA), and protein expression (e.g., cytokeratin 19, vimentin, collagen I) in paraffin-embedded formalin-fixed tissue slides on a Leica Bond Rx staining station. While this protocol uses mainly mouse tissues to demonstrate multiplex detection, it can be generally applied to single-cell expression analysis of other animal models and clinical specimens.
ردمك: 978-1-07-160622-3
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::7f0fd53ff48678550918df6c32de03b3
https://doi.org/10.1007/978-1-0716-0623-0_17
حقوق: CLOSED
رقم الأكسشن: edsair.doi...........7f0fd53ff48678550918df6c32de03b3
قاعدة البيانات: OpenAIRE