Clinical and pathological heterogeneity of @entity0 hinders selection of appropriate treatment for individual cases. Molecular profiling at gene or protein levels may elucidate the biological variance of @entity5 and provide a new classification system that correlates better with biological, clinical and prognostic parameters. We studied the immunohistochemical profile of a panel of seven important biomarkers using @entity5 tissue arrays. The @entity5 samples were then classified with a monothetic (binary variables) clustering algorithm. Two distinct groups of @entity5 are characterized by the @entity172 receptor (ER) status and @entity5 grade (p = 0.0026). Four biomarkers, @entity1722 , @entity2247 , @entity876 and @entity7 , were significantly overexpressed in @entity5 with the ER-negative (ER-) phenotype. Eight subsets of @entity5 were further identified according to the expression status of @entity7 , @entity1722 and @entity876 . The malignant potential of the ER-/ @entity7 + subgroup was associated with the strong correlations of @entity2247 and @entity1722 with @entity7 . Our results indicate that this molecular classification system, based on the statistical analysis of immunohistochemical profiling, is a useful approach for @entity5 grouping. Some of these subgroups have a relative genetic homogeneity that may allow further study of specific genetically-controlled metabolic pathways. This approach may hold great promise in rationalizing the application of different therapeutic strategies for different subgroups of @entity0 .

Tissue microarray study for classification of XXXX .

@entity172 :: ('MESH:D004967', 'Chemical') :: ['estrogen'] @entity0 :: ('MESH:D001943', 'Disease') :: ['breast cancer', 'breast tumors'] @entity7 :: ('7422', 'Gene') :: ['VEGF'] @entity5 :: ('MESH:D009369', 'Disease') :: ['tumor', 'tumors'] @entity876 :: ('7157', 'Gene') :: ['p53'] @entity2247 :: ('4513', 'Gene') :: ['Cox-2'] @entity1722 :: ('2064', 'Gene') :: ['c-erbB2']
@entity0 :: (MESH:D001943,Disease) :: ['breast tumors']
