Intensity-based signal separation algorithm for accuratequantification of clustered centrosomes in tissue sections

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Centrosomes are small organelles that organize the mitoticspindle during cell division and are also involved in cell shape andpolarity. Within epithelial tumors, such as breast cancer, and somehematological tumors, centrosome abnormalities (CA) are common, occurearly in disease etiology, and correlate with chromosomal instability anddisease stage. In situ quantification of CA by optical microscopy ishampered by overlap and clustering of these organelles, which appear asfocal structures. CA has been frequently associated with Tp53 status inpremalignant lesions and tumors. Here we describe an approach toaccurately quantify centrosomes in tissue sections and tumors.Considering proliferation and baseline amplification rate the resultingpopulation based ratio of ... continued below

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Fleisch, Markus C.; Maxell, Christopher A.; Kuper, Claudia K.; Brown, Erika T.; Parvin, Bahram; Barcellos-Hoff, Mary-Helen et al. March 8, 2006.

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Centrosomes are small organelles that organize the mitoticspindle during cell division and are also involved in cell shape andpolarity. Within epithelial tumors, such as breast cancer, and somehematological tumors, centrosome abnormalities (CA) are common, occurearly in disease etiology, and correlate with chromosomal instability anddisease stage. In situ quantification of CA by optical microscopy ishampered by overlap and clustering of these organelles, which appear asfocal structures. CA has been frequently associated with Tp53 status inpremalignant lesions and tumors. Here we describe an approach toaccurately quantify centrosomes in tissue sections and tumors.Considering proliferation and baseline amplification rate the resultingpopulation based ratio of centrosomes per nucleus allow the approximationof the proportion of cells with CA. Using this technique we show that20-30 percent of cells have amplified centrosomes in Tp53 null mammarytumors. Combining fluorescence detection, deconvolution microscopy and amathematical algorithm applied to a maximum intensity projection we showthat this approach is superior to traditional investigator based visualanalysis or threshold-based techniques.

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  • Journal Name: Microscopy Research Techniques; Journal Volume: 69; Journal Issue: 12; Related Information: Journal Publication Date: 12/2006

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  • Report No.: LBNL--59831
  • Grant Number: DE-AC02-05CH11231
  • Office of Scientific & Technical Information Report Number: 919758
  • Archival Resource Key: ark:/67531/metadc896777

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Office of Scientific & Technical Information Technical Reports

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Office of Scientific and Technical Information (OSTI) is the Department of Energy (DOE) office that collects, preserves, and disseminates DOE-sponsored research and development (R&D) results that are the outcomes of R&D projects or other funded activities at DOE labs and facilities nationwide and grantees at universities and other institutions.

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  • March 8, 2006

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  • Sept. 27, 2016, 1:39 a.m.

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  • Sept. 25, 2017, 3:51 p.m.

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Fleisch, Markus C.; Maxell, Christopher A.; Kuper, Claudia K.; Brown, Erika T.; Parvin, Bahram; Barcellos-Hoff, Mary-Helen et al. Intensity-based signal separation algorithm for accuratequantification of clustered centrosomes in tissue sections, article, March 8, 2006; Berkeley, California. (digital.library.unt.edu/ark:/67531/metadc896777/: accessed October 16, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.