Literature DB >> 1348424

Predicting outcome for patients with node negative breast cancer: a comparative study of the value of flow cytometry and cell image analysis for determination of DNA ploidy.

J Yuan1, C Hennessy, A L Givan, I P Corbett, J A Henry, G V Sherbet, T W Lennard.   

Abstract

This study was aimed at determining whether tumour DNA content measured by cell image analysis could provide additional prognostic information when compared to that provided by flow cytometry. Sections cut from paraffin blocks of tumours from 101 patients with node negative breast cancer were analysed by both methods and the results related to other prognostic variables and to patient relapse and overall survival. DNA ploidy measured by flow cytometry classified 46 tumours as diploid and 55 as aneuploid, whereas by cell image analysis 30 were diploid and 71 aneuploid (P less than 0.002). There were 20 tumours with discrepancies between the two methods; 18 of these were tumours with only one peak in flow analysis, but determined to be aneuploid with image analysis. DNA content as measured by both methods was significant for predicting relapse and survival by log-rank test, as were tumour histological grade, c-erbB-2 expression and tumour size. Multivariate analysis showed DNA ploidy measured by flow cytometry to be the only variable of independent significance (P less than 0.02) for both relapse and overall survival. Compared with cell image analysis, flow cytometry demonstrated a significantly higher proportion of diploid tumours, which may be related to differences in the internal standards applied to each method. We suggest that cell image analysis techniques can provide more sensitive information on the DNA content of tumour cells by direct measurement of nuclear DNA density of both normal lymphocytes and tumour cells in the same section. However, although image analysis appears to be more sensitive than flow cytometry in detecting DNA aneuploidy, the image technique appears to lack the specificity of flow cytometry in correlation with clinical outcome.

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Year:  1992        PMID: 1348424      PMCID: PMC1977588          DOI: 10.1038/bjc.1992.93

Source DB:  PubMed          Journal:  Br J Cancer        ISSN: 0007-0920            Impact factor:   7.640


  12 in total

1.  A prospective comparison of DNA quantitation by image and flow cytometry.

Authors:  T W Bauer; R R Tubbs; M G Edinger; P F Suit; G N Gephardt; H S Levin
Journal:  Am J Clin Pathol       Date:  1990-03       Impact factor: 2.493

2.  Meeting highlights: adjuvant therapy for breast cancer.

Authors:  J H Glick
Journal:  J Natl Cancer Inst       Date:  1988-06-01       Impact factor: 13.506

3.  Image analysis confirmation of DNA aneuploidy in flow cytometric DNA distributions having a wide coefficient of variation of the G0/G1 peak.

Authors:  P W McFadden; L J Clowry; K Daehnert; L L Hause; S M Koethe
Journal:  Am J Clin Pathol       Date:  1990-05       Impact factor: 2.493

4.  Node negative breast cancer: the prognostic value of DNA ploidy for long-term survival.

Authors:  J Yuan; C Hennessy; I P Corbett; R Dykin; A L Givan; B K Shenton; J A Henry; C Wright; T W Lennard
Journal:  Br J Surg       Date:  1991-07       Impact factor: 6.939

5.  Method for analysis of cellular DNA content of paraffin-embedded pathological material using flow cytometry.

Authors:  D W Hedley; M L Friedlander; I W Taylor; C A Rugg; E A Musgrove
Journal:  J Histochem Cytochem       Date:  1983-11       Impact factor: 2.479

6.  Improving the prognostic value of DNA flow cytometry in breast cancer by combining DNA index and S-phase fraction. A proposed classification of DNA histograms in breast cancer.

Authors:  O P Kallioniemi; G Blanco; M Alavaikko; T Hietanen; J Mattila; K Lauslahti; M Lehtinen; T Koivula
Journal:  Cancer       Date:  1988-11-15       Impact factor: 6.860

7.  DNA ploidy and survival in breast cancer patients.

Authors:  C J Cornelisse; C J van de Velde; R J Caspers; A J Moolenaar; J Hermans
Journal:  Cytometry       Date:  1987-03

8.  The relation of flow cytometry to clinical and biologic characteristics in women with node negative primary breast cancer.

Authors:  H B Muss; T E Kute; L D Case; L R Smith; C Booher; R Long; L Kammire; B Gregory; J K Brockschmidt
Journal:  Cancer       Date:  1989-11-01       Impact factor: 6.860

9.  DNA ploidy of human breast cancer.

Authors:  G Del Bino; R Silvestrini; M R Zucconi; G Marchese; B Valentinis; G Di Fronzo; S Andreola
Journal:  Anal Cell Pathol       Date:  1989-08       Impact factor: 2.916

10.  DNA index, S-phase fraction, histological grade and prognosis in breast cancer.

Authors:  S M O'Reilly; R S Camplejohn; D M Barnes; R R Millis; D Allen; R D Rubens; M A Richards
Journal:  Br J Cancer       Date:  1990-05       Impact factor: 7.640

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  3 in total

1.  Genome Instability Profiles Predict Disease Outcome in a Cohort of 4,003 Patients with Breast Cancer.

Authors:  Annette Lischka; Natalie Doberstein; Sandra Freitag-Wolf; Ayla Koçak; Timo Gemoll; Kerstin Heselmeyer-Haddad; Thomas Ried; Gert Auer; Jens K Habermann
Journal:  Clin Cancer Res       Date:  2020-06-10       Impact factor: 12.531

2.  Improved prognostication in small (pT1) breast cancers by image cytometry.

Authors:  M Aubele; G Auer; U Falkmer; A Voss; K Rodenacker; L E Rutquist; H Höfler
Journal:  Breast Cancer Res Treat       Date:  1995       Impact factor: 4.872

3.  The prognostic significance of determining DNA content in breast cancer by DNA image cytometry: the role of high grade aneuploidy in node negative breast cancer.

Authors:  Selma Yildirim-Assaf; Alexandra Coumbos; Werner Hopfenmüller; Hans-Dieter Foss; Harald Stein; Wolfgang Kühn
Journal:  J Clin Pathol       Date:  2007-06       Impact factor: 3.411

  3 in total

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