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


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

1999-05

AUTHORS

Sylvie Ménard, Patrizia Casalini, Gorana Tomasic, Silvana Pilotti, Natale Cascinelli, Rosaria Bufalino, Franco Perrone, Chiara Longhi, Franco Rilke, M. Ines Colnaghi

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. More... »

PAGES

167-175

Identifiers

URI

http://scigraph.springernature.com/pub.10.1023/a:1006262324959

DOI

http://dx.doi.org/10.1023/a:1006262324959

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1047763314

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/10481944


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