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Tissue Microarray Validation: A Methodologic Study with Special Reference to Lung Cancer
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DOI：10.1158/1055-9965.EPI-08-0743.png)
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Background: Although tissue microarray (TMA) studies of histopathologic material have been frequently reported in studies of malignant diseases, the question of sample size (i.e., the diameter and the number of tissue cylinders investigated) has been rarely discussed. This study addresses the methodologic question of sample size in a variety of tumor types. Material and Methods: Material from 29 cases of lung carcinoma (small cell, squamous cell, and adenocarcinomas) was examined immunohistochemically for Ki-67 and p53 expression in virtually constructed cylinders of different diameters. The influence of tissue sample size (i.e., different numbers of virtual cylinders) was also investigated. Results from Ki-67 evaluation were analyzed as a continuous variable, whereas p53 expression was scored. p53 evaluations based on scoring in cylinders versus scoring of whole sections were also compared. Furthermore, 10 cases of endometrial and breast carcinomas were evaluated for estrogen receptor, Ki-67, and HER2 by scoring up to five cylinders. Results and Conclusions: Tissue cylinders of 0.6 and 1.0 mm. diameters were compared and found equally informative about Ki-67 expression (intraclass correlation, 0.96). A statistical approach considering intra-individual and interindividual variation data is presented, indicating that in this specific setting three cylinders per case is an adequate sample size for TMA studies. Further sampling yields only a small gain in accuracy as determined by Ki-67 quantification and p53 scoring (kappa-coefficient, 0.9). For endometrial and breast tissues, TMA scoring of three cylinders yielded excellent agreement (kappa, >0.75) compared with whole-section scoring. (Cancer Epidemiol Biomarkers Prev 2009;18(7):2014-21)
Keyword:
PROTEIN EXPRESSION
PROSTATE-CANCER
BREAST-CANCER
GROWTH-FACTOR
TECHNOLOGY
IMMUNOHISTOCHEMISTRY
CARCINOMA
SPECIMENS
TUMORS
AGREEMENT
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3.4
论文数:
1.0W
被引数:
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