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      Reliability of tissue microarrays in detecting protein expression and gene amplification in breast cancer.

      Modern Pathology

      Tumor Markers, Biological, metabolism, pathology, Adult, Aged, Aged, 80 and over, Breast Neoplasms, genetics, DNA, Neoplasm, analysis, Female, Gene Amplification, Gene Expression Profiling, Histocytological Preparation Techniques, Humans, Immunoenzyme Techniques, In Situ Hybridization, Fluorescence, Middle Aged, Oligonucleotide Array Sequence Analysis, Protein Array Analysis, RNA, Neoplasm, Receptor, ErbB-2, Reproducibility of Results, Adenocarcinoma

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          Tissue microarrays allow high throughput molecular profiling of diagnostic or predictive markers in cancer specimens and rapid validation of novel potential candidates identified from genomic and proteomic analyses in a large number of tumor samples. To validate the use of tissue microarray technology for all the main biomarkers routinely used to decide breast cancer prognostication and postsurgical adjuvant therapy, we constructed a tissue microarray from 97 breast tumors, with a single 0.6 mm core per specimen. Immunostaining of tissue microarray sections and conventional full sections of each tumor were performed using well-characterized prognostic markers (estrogen receptor ER, progesterone receptor PR and c-erbB2). The full section versus tissue microarray concordance for these stains was 97% for ER, 98% for PR, and 97% for c-erbB2, respectively, with a strong statistical association (kappa value more than 0.90). Fluorescence in situ hybridization analysis for HER-2/neu gene amplification from the single-core tissue microarray was technically successful in about 90% (87/97) of the cases, with a concordance of 95% compared with parallel analyses with the full sections. The correlation with other pathological parameters was not significantly different between full-section and array-based results. It is concluded that the constructed tissue microarray with a single core per specimen ensures full biological representativeness to identify the associations between biomarkers and clinicopathological parameters, with no significant associated sampling bias.

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