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Pathobiologic identification of two distinct breast carcinoma subsets with diverging clinical behaviors

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Abstract

Many different pathological and biological variables which characterize breast carcinomas have been found to be associated. The aim of this work was to analyze the complex relationship among these parameters. The pathologic, biologic, and clinical characteristics of a series of primary breast carcinomas from 676 patients were retrospectively investigated. Multiple correspondence analysis of 13 factors revealed clustering of eight pathobiologic variables, that is histologic grade, necrosis, lymphoid infiltration, number of mitoses, c‐erbB‐2 overexpression, p53, progesterone receptor, and bcl2 expression. An index for each tumor calculated on the basis of these eight factors served to distinguish two different tumor phenotypes, designated A and B. Phenotype A is represented by tumors sharing most of the biologic features of normal breast tissues: indeed, these tumors are characterized by a relatively high degree of differentiation, low proliferation, no necrosis or leukocyte infiltration, and no gene alterations. By contrast, phenotype B is quite divergent from the normal tissue because of its poor differentiation, high proliferation, frequent gene alterations and evidence of a host immune reaction. As regards the disease progression, these two subsets showed marked differences: phenotype A tumors had a low recurrence rate per year that remained constant over time and affected more frequently elderly patients, whereas group B tumors showed high aggressivity in the first years after surgery followed by a low long‐term recurrence rate and were more frequently seen in younger patients. These data suggest that breast carcinoma consists of two different subsets that can be identified on the basis of pathobiologic features.

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References

  1. McGuire WL, Clark GM: Prognostic factors and treatment decisions in axillary-node-negative breast cancer. N Engl J Med 326: 1756–1761, 1992

    Google Scholar 

  2. Clark GM: Do we really need prognostic factors for breast cancer? Breast Cancer Res Treat 30: 117–126, 1994

    Google Scholar 

  3. Clinical practice guidelines for the use of tumor markers in breast and colorectal cancer. J Clin Oncol 14: 2843–2877, 1996

  4. Slamon DJ, Clark GM, Wong SG, Levin WJ, Ullrich A, McGuire WL: Human breast cancer: correlation of relapse and survival with amplification of the HER-2/neu oncogene. Science 235: 177–182, 1987

    Google Scholar 

  5. Silvestrini R, Benini E, Daidone MG, Veneroni S, Boracchi P, Cappelletti V, Di Fronzo G, Veronesi U: p53 as an independent prognostic marker in lymph node-negative breast cancer patients. J Natl Cancer Inst 85: 965–970, 1993

    Google Scholar 

  6. Keshgegian AA: Biochemically estrogen receptor-negative, progesterone receptor-positive breast carcinoma: immunocytochemical hormone receptors and prognostic factors. Arch Pathol Lab Med 118: 240–244, 1994

    Google Scholar 

  7. Rilke F, Colnaghi MI, Cascinelli N, Andreola S, Baldini MT, Bufalino R, Della Porta G, Ménard S, Pierotti MA, Testori A: Prognostic significance of HER2lneu expression in breast cancer and its relationship to other prognostic factors. Int J Cancer 49: 44–49, 1991

    Google Scholar 

  8. Visscher DW, Castellani R, Wykes SM, Sarkar FH, Hussain ME: Concurrent abnormal expression of ERBB-2, EGFR, and p53 genes and clinical disease progression of breast carcinoma. Breast Cancer Res Treat 28: 261–266, 1993

    Google Scholar 

  9. Silvestrini R, Veneroni S, Daidone MG, Benini E, Boracchi P, Mezzetti M, Di Fronzo G, Rilke F, Veronesi U: The bcl-2 protein: a prognostic indicator strongly related to p53 protein in lymph node-negative breast cancer patients. J Natl Cancer Inst 86: 499–504, 1994

    Google Scholar 

  10. Martinazzi M, Crivelli F, Zampatti C, Martinazzi S: Relationship between p53 expression and other prognostic factors in human breast carcinoma: an immunohistochemical study. Am J Clin Pathol 100: 213–217, 1993

    Google Scholar 

  11. Hilsenbeck SG, Clark GM, Chamness GC, Osborne CK: Untangling the multiple prognostic factor problem. Proc Am Assoc Cancer Res 34: 193, 1993

    Google Scholar 

  12. Pereira H, Pinder SE, Sibbering DM, Galea MH, Elston CW, Blamey RW, Robertson JFR, Ellis IO: Pathological prognostic factors in breast cancer: IV. Should you be a typer or a grader? A comparative study of two histological prognostic features in operable breast carcinoma. Histopathology 27: 219–226, 1995

    Google Scholar 

  13. Martignone S, Pellegrini R, Villa E, Tandon NN, Mastroianni A, Tagliabue E, Ménard S, Colnaghi MI: Characterization of two monoclonal antibodies directed against the 67kDa high affinity laminin receptor and application for the study of breast carcinoma progression. Clin Exp Metastasis 10: 379–386, 1992

    Google Scholar 

  14. Cattoretti G, Becker MHG, Key G, Duchrow M, Schlüter C, Galle J, Gerdes J: Monoclonal antibodies against recombinant parts of the Ki-67 antigen (MIB 1 and MIB 3) detect proliferating cells in microwave-processed formalin-fixed paraffin sections. J Pathol 168: 357–363, 1992

    Google Scholar 

  15. Benzecri JP: Analyse des Donnes. II. Analyse des Correspondance. Dunod, Paris, 1973

    Google Scholar 

  16. Greenacre M, Hastie T: The geometric interpretation of the correspondence analysis. JASA 82: 437–447, 1987

    Google Scholar 

  17. Peto R, Pike MC, Breslow NE, Cox RD, Howard SV, Mantel N, McPherson K, Peto J, Smith PG: Design and analysis of randomized clinical trials requiring prolonged observations of each patient. Br J Cancer 35: 1–27, 1977

    Google Scholar 

  18. Demicheli R, Abbattista A, Miceli R, Valagussa P, Bonadonna G: Time distribution of the recurrence risk for breast cancer patients undergoing mastectomy: further support about the concept of tumor dormancy. Breast Cancer Res Treat 41: 177–185, 1996

    Google Scholar 

  19. Pupa SM, Bufalino R, Invernizzi AM, Andreola S, Rilke F, Lombardi L, Colnaghi MI, Ménard S: Macrophage infiltrate and prognosis in c-erbB-2-overexpressing breast carcinomas. J Clin Oncol 14: 85–94, 1996

    Google Scholar 

  20. Melief CJM, Kast WM: Potential immunogenicity of oncogene and tumor suppressor gene products. Curr Opin Immunol 5: 709–713, 1993

    Google Scholar 

  21. Pupa SM, Ménard S, Andreola S, Colnaghi MI: Antibody response against the c-erbB-2 oncoprotein in breast carcinoma patients. Cancer Res 53: 5864–5866, 1993

    Google Scholar 

  22. Evans AJ, Pinder SE, Ellis IO, Sibbering DM, Elston CW, Poller DN, Wilson ARM: Correlations between the mammographic features of ductal carcinoma in situ (DCIS) and c-erbB-2 oncogene expression. Clin Radiol 49: 559–562, 1994

    Google Scholar 

  23. Carlomagno C, Perrone F, Gallo C, De Laurentiis M, Lauria R, Morabito A, Pettinato G, Panico L, D'Antonio A, Bianco AR, De Placido S: c-erbB2 overexpression decreases the bene-fit of adjuvant tamoxifen in early-stage breast cancer without axillary lymph node metastases. J Clin Oncol 14: 2702–2708, 1996

    Google Scholar 

  24. Jacquemier J, Penault-Llorca F, Viens P, Houvenaeghel G, Hassoun J, Torrente M, Adélaïde J, Birnbaum D: Breast cancer response to adjuvant chemotherapy in correlation with erbB2 and p53 expression. Anticancer Res 14: 2773–2778, 1994

    Google Scholar 

  25. Neville AM, Bettelheim R, Gelber RD, Säve-Söderbergh J, Davis BW, Reed R, Torhorst J, Golouh R, Peterson HF, Price KN, Isley M, Rudenstam C-M, Collins J, Castiglione M, Senn H-J, Goldhirsch A: Factors predicting treatment responsiveness and prognosis in node-negative breast cancer. J Clin Oncol 10: 696–705, 1992

    Google Scholar 

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Ménard, S., Casalini, P., Tomasic, G. et al. Pathobiologic identification of two distinct breast carcinoma subsets with diverging clinical behaviors. Breast Cancer Res Treat 55, 167–175 (1999). https://doi.org/10.1023/A:1006262324959

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