Breast Cancer Research and Treatment

, Volume 28, Issue 1, pp 1–8 | Cite as

High DNA content and prognosis in lymph node positive breast cancer. A case control study by the university of Leiden and ECOG

  • Kennedy W. Gilchrist
  • Robert Gray
  • Anneke M. J. van Driel-Kulker
  • Wilma E. Mesker
  • Joke J. Ploem-Zaaijer
  • Johan S. Ploem
  • Samuel G. Taylor
  • Douglas C. Tormey
Report

Summary

To investigate whether breast cancer cells with unusually high nuclear DNA content are associated with an adverse outcome, Eastern Cooperative Oncology Group investigators selected breast cancer trial patients who suffered an early death (ED) within two years after diagnosis to compare with other trial patients who had a survival of at least 7.5 years. Paraffin blocks of primary breast cancers were obtained from 93 evaluable patients who had been enrolled in two surgical adjuvant trials for lymph node positive (LN +) disease (T1-3N1M0). Single cell monolayer preparations from these blocks were stained with acriflavine-Feulgen and analyzed by image analysis for DNA content with the automated Leiden Television Analysis System (LEYTAS). Standard prognostic variables (estrogen receptor (ER) status, number of lymph nodes with metastases, and size of the cancer) were compared with three DNA content characteristics: DNA ploidy status, number of nuclei with > 5C DNA content, and percent of nuclei with > 5 C. Estimates of the odds ratio in multivariate comparisons showed that ER negativity was associated with ED (p = 0.0005) and an odds ratio estimate using negative/positive of 4.87. The number of positive lymph nodes associated with ED had a p-value of 0.0005 and an odds ratio estimate of 4.63 when comparing the > 3 nodes group to the 1–3 nodes group. In contrast, the strongest association for any of the DNA content characteristics with ED had a p-value of 0.017 and an odds ratio estimate of 2.76. This power of association disappeared when stratified on ER status. Therefore, the presence of breast cancer cells with highly aneuploid (i.e. > 5 C) DNA content does not possess independent prognostic information in LN + breast cancer. An association remains to be tested in lymph node negative breast cancer.

Key words

breast cancer DNA aneuploidy LEYTAS image cytometry prognosis 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Dressler LG, Bartow SA: DNA flow cytometry in solid tumors: practical aspects and clinical applications. Semin Diagn Pathol 6: 55–82, 1989Google Scholar
  2. 2.
    Lee AKC, Dugan J, Hamilton WM, Cook L, Heatley G, Kamat B, Silverman ML: Quantitative DNA analysis in breast carcinomas: a comparison between image analysis and flow cytometry. Modern Pathol 4: 178–182, 1991Google Scholar
  3. 3.
    Fallenius AG, Franzen SA, Auer GU: Predictive value of nuclear DNA content in breast cancer in relation to clinical and morphologic factors. A retrospective study of 227 consecutive cases. Cancer 62: 521–530, 1988Google Scholar
  4. 4.
    von Rosen A, Rutqvist LE, Carstensen J, Fallenius A, Skoog L, Auer G: Prognostic value of nuclear DNA content in breast cancer in relation to tumor size, nodal status, and estrogen receptor content. Breast Cancer Res Treat 13: 23–32, 1989Google Scholar
  5. 5.
    Ploem JS, van Driel-Kulker AMJ, Goyarts-Veldstra L, Ploem-Zaaijer JJ, Verwoerd NP, van der Zwan M: Image analysis combined with quantitative cytochemistry. Histochem 84: 549–555, 1986Google Scholar
  6. 6.
    Rodenburg CJ, Ploem-Zaaijer JJ, Cornelisse CJ, Mesker WE, Hermans J, Heintz PAM, Ploem JS, Fleuren GJ: Use of DNA image cytometry in addition to flow cytometry for the study of patients with advanced ovarian cancer. Cancer Res 47: 3938–3941, 1987Google Scholar
  7. 7.
    Cornelisse CJ, van Driel-Kulker AMJ: DNA image cytometry on machine-selected breast cancer cells and a comparison between flow cytometry and scanning cytophotometry. Cytometry 6: 471–477, 1985Google Scholar
  8. 8.
    Ploem JS, van Driel-Kulker AMJ, Ploem-Zaaijer JJ: Automated cell analysis for DNA studies of large cell populations using the LEYTAS image cytometry system. Path Res Pract 185: 671–675, 1989Google Scholar
  9. 9.
    Taylor SG IV, Knuiman MW, Sleeper LA, Olson JE, Tormey DC, Gilchrist KW, Falkson G, Rosenthal SN, Carbone PP, Cummings FJ: Six-year results of the Eastern Cooperative Oncology Group trial of observation versus CMFP versus CMFPT in postmenopausal patients with node-positive breast cancer. J Clin Oncol 7: 879–889, 1989Google Scholar
  10. 10.
    Tormey DC, Gray R, Gilchrist KW, Grage T, Carbone PP, Wolter J, Woll JE, Cummings FJ: Adjuvant chemohormonal therapy with cyclophosphamide, methotrexate, 5-fluorouracil, and prednisone (CMFP) or CMFP plus tamoxifen compared with CMF for premenopausal breast cancer patients. An Eastern Cooperative Oncology Group trial. Cancer 65: 200–206, 1990Google Scholar
  11. 11.
    van Driel-Kulker AMJ, Mesker WE, van Velzen I, Tanke HJ, Feichtinger J, Ploem JS: Preparation of monolayer smears from paraffin-embedded tissue for image cytometry. Cytometry 6: 268–272, 1985Google Scholar
  12. 12.
    Mantel N, Haenszel W: Statistical aspects of the analysis of data from retrospective studies of disease. J Natl Cancer Inst 22: 719–748, 1959Google Scholar
  13. 13.
    Robins J, Breslow N, Greenland S: Estimators of the Mantal-Haenszel variance consistent in both sparse data and large-strata limiting models. Biometrics 40: 63–75, 1984Google Scholar
  14. 14.
    Lubin JH, Gail MH: Biased selection of controls for casecontrol analyses of cohort studies. Biometrics 40: 63–75, 1984Google Scholar
  15. 15.
    McGuire WL, Clark GM: Prognostic factors and treatment decisions in axillary-node-negative breast cancer. N Engl J Med 326: 1756–1761, 1992Google Scholar
  16. 16.
    Bennington JL: Significance of DNA content and proliferative rate of the invasive carcinoma found in the mammographically directed breast biopsy. In: Bennington JL, Lagios MD (eds) The Mammographically Directed Biopsy. Hanley & Belfus, Philadelphia, 1992, pp 137–160Google Scholar
  17. 17.
    Hitchcock A, Ellis IO, Robertson JFR, Gilmour A, Bell J, Elston CW, Blamey RW: An observation of DNA ploidy, histological grade, and immunoreactivity for tumour-related antigens in primary and metastatic breast carcinoma. J Pathol 159: 129–134, 1989Google Scholar
  18. 18.
    Meyer JS, Witliff JL: Regional heterogeneity in breast carcinoma: thymidine labelling index, steroid hormone receptors, DNA ploidy. Int J Cancer 47: 213–220, 1991Google Scholar
  19. 19.
    Fallenius AG, Auer GU, Carstensen JM: Prognostic significance of DNA measurements in 409 consecutive breast cancer patients. Cancer 62: 331–340, 1988Google Scholar
  20. 20.
    Shackney SE, Smith CA, Miller BW, Burholt DR, Murtha K, Giles HR, Ketterer DM, Police AA: Model for the genetic evolution of human solid tumors. Cancer Res 49: 3344–3354, 1989Google Scholar
  21. 21.
    Wolman SR, Feiner HD, Schinella RA, Gimotty P, Ownby H, Maloney T, Dawson PJ: A retrospective analysis of breast cancer based on outcome differences. Hum Pathol 22: 475–480, 1991Google Scholar

Copyright information

© Kluwer Academic Publishers 1993

Authors and Affiliations

  • Kennedy W. Gilchrist
    • 1
  • Robert Gray
    • 2
  • Anneke M. J. van Driel-Kulker
    • 3
  • Wilma E. Mesker
    • 3
  • Joke J. Ploem-Zaaijer
    • 3
  • Johan S. Ploem
    • 3
  • Samuel G. Taylor
    • 4
  • Douglas C. Tormey
    • 1
  1. 1.Wisconsin Comprehensive Cancer CenterMadisonUSA
  2. 2.Dana-Farber Cancer InstituteBostonUSA
  3. 3.Department of Cytochemistry & Cytometry, Sylvius LaboratoriaUniversity of LeidenLeidenThe Netherlands
  4. 4.Rush-Presbyterian-St. Luke's Medical CenterChicagoUSA

Personalised recommendations