Flow cytometric analysis of S-phase fraction in breast carcinomas using gating on cells containing cytokeratin View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

1994-03

AUTHORS

S Wingren, O Stål, B Nordenskjöld

ABSTRACT

We investigated distant recurrence and S-phase fraction (SPF), estimated by flow cytometry with and without selection of the epithelial cell population, in 201 stage II breast carcinomas. The tumour tissue was disintegrated mechanically by scissors and one part of the cell suspension was treated with a detergent-trypsin method for single-parameter analysis, and the other part, for immunological selection of epithelial cells, was incubated with a monoclonal antibody (CAM 5.2) recognising cytokeratins 8 and 18 and a secondary fluorescein isothiocyanate-labelled antibody. DNA was stained with propidium iodide. In order to compare the methods, statistical analysis was performed on the 152 tumours with S-phase fraction estimated by both methods. Sixty-five tumours were diploid, 81 were aneuploid and six tumours had different ploidy determined by the two methods. Using univariate regression analysis, SPF of the epithelial cell population predicted recurrence more effectively than SPF from single-parameter analysis. In multivariate regression analysis, SPF of the cytokeratin-containing population added significant prognostic information to the SPF of the non-selected cells. We concluded that the use of flow cytometric selection of epithelial breast carcinoma cells enhances the predictability value of SPF. More... »

PAGES

546

References to SciGraph publications

  • 1991-11. Categorising continuous variables in BRITISH JOURNAL OF CANCER
  • 1975-06. Analysis of PCP-data to determine the fraction of cells in the various phases of cell cycle in RADIATION AND ENVIRONMENTAL BIOPHYSICS
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/bjc.1994.99

    DOI

    http://dx.doi.org/10.1038/bjc.1994.99

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1001764806

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/7510119


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