Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.lfs.2003.05.006
Title: Tissue microarray study for classification of breast tumors
Authors: Zhang, D.-H. 
Salto-Tellez, M. 
Chiu, L.-L.
Koay, E.S.-C. 
Shen, L.
Keywords: Breast cancer
Immunohistochemistry
Tissue microarray
Tumor classification
Issue Date: 2003
Source: Zhang, D.-H.,Salto-Tellez, M.,Chiu, L.-L.,Koay, E.S.-C.,Shen, L. (2003). Tissue microarray study for classification of breast tumors. Life Sciences 73 (25) : 3189-3199. ScholarBank@NUS Repository. https://doi.org/10.1016/j.lfs.2003.05.006
Abstract: Clinical and pathological heterogeneity of breast cancer hinders selection of appropriate treatment for individual cases. Molecular profiling at gene or protein levels may elucidate the biological variance of tumors 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 tumor tissue arrays. The tumor samples were then classified with a monothetic (binary variables) clustering algorithm. Two distinct groups of tumors are characterized by the estrogen receptor (ER) status and tumor grade (p = 0.0026). Four biomarkers, c-erbB2, Cox-2, p53 and VEGF, were significantly overexpressed in tumors with the ER-negative (ER-) phenotype. Eight subsets of tumors were further identified according to the expression status of VEGF, c-erbB2 and p53. The malignant potential of the ER-/VEGF+ subgroup was associated with the strong correlations of Cox-2 and c-erbB2 with VEGF. Our results indicate that this molecular classification system, based on the statistical analysis of immunohistochemical profiling, is a useful approach for tumor 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 breast tumors. © 2003 Elsevier Inc. All rights reserved.
Source Title: Life Sciences
URI: http://scholarbank.nus.edu.sg/handle/10635/30352
ISSN: 00243205
DOI: 10.1016/j.lfs.2003.05.006
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