A method of quantifying centrosomes at the single-cell level in human normal and cancer tissue
AffiliationUniv Arizona, Canc Biol Res Program
Univ Arizona, Dept Pathol
Univ Arizona, Dept Cellular & Mol Med
Univ Arizona, Univ Arizona Canc Ctr
MetadataShow full item record
PublisherAMER SOC CELL BIOLOGY
CitationWang, M., Knudsen, B. S., Nagle, R. B., Rogers, G. C., & Cress, A. E. (2019). A method of quantifying centrosomes at the single-cell level in human normal and cancer tissue. Molecular biology of the cell, 30(7), 811-819.
JournalMOLECULAR BIOLOGY OF THE CELL
Rights© 2019 Wang et al. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License.
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AbstractCentrosome abnormalities are emerging hallmarks of cancer. The overproduction of centrosomes (known as centrosome amplification) has been reported in a variety of cancers and is currently being explored as a promising target for therapy. However, to understand different types of centrosome abnormalities and their impact on centrosome function during tumor progression, as well as to identify tumor subtypes that would respond to the targeting of a centrosome abnormality, a reliable method for accurately quantifying centrosomes in human tissue samples is needed. Here, we established a method of quantifying centrosomes at a single-cell level in different types of human tissue samples. We tested multiple anti-centriole and pericentriolar-material antibodies to identify bona fide centrosomes and multiplexed these with cell border markers to identify individual cells within the tissue. High-resolution microscopy was used to generate multiple Z-section images, allowing us to acquire whole cell volumes in which to scan for centrosomes. The normal cells within the tissue serve as internal positive controls. Our method provides a simple, accurate way to distinguish alterations in centrosome numbers at the level of single cells.
VersionFinal published version
SponsorsNational Cancer Institute (NCI) [P30CA23074]; Department of Defense Prostate Cancer Research Program [W81XWH-14-2-0182, W81XWH-14-2-0183, W81XWH-14-2-0185, W81XWH-14-2-0186, W81XWH-15-2-0062]; National Institutes of Health (NIH) [R01GM110166, R01GM126035]; NIH-NCI [RO1CA159406]; Tim and Diane Bowden Cancer Biology Research Fellowship
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