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- W1992316503 abstract "Abstract Purpose: A multitude of breast cancer mRNA profiling studies has stratified breast cancer and defined gene sets that correlate with outcome. However, the number of genes used to predict patient outcome or define tumor subtypes by RNA expression studies is variable, nonoverlapping, and generally requires specialized technologies that are beyond those used in the routine pathology laboratory. It would be ideal if the familiarity and streamlined nature of immunohistochemistry could be combined with the rigorously quantitative and highly specific properties of nucleic acid–based analysis to predict patient outcome. Experimental Design: We have used AQUA-based objective quantitative analysis of tissue microarrays toward the goal of discovery of a minimal number of markers with maximal prognostic or predictive value that can be applied to the conventional formalin-fixed, paraffin-embedded tissue section. Results: The minimal discovered multiplexed set of tissue biomarkers was GATA3, NAT1, and estrogen receptor. Genetic algorithms were then applied after division of our cohort into a training set of 223 breast cancer patients to discover a prospectively applicable solution that can define a subset of patients with 5-year survival of 96%. This algorithm was then validated on an internal validation set (n = 223, 5-year survival = 95.8%) and further validated on an independent cohort from Sweden, which showed 5-year survival of 92.7% (n = 149). Conclusions: With further validation, this test has both the familiarity and specificity for widespread use in management of breast cancer. More generally, this work illustrates the potential for multiplexed biomarker discovery on the tissue microarray platform." @default.
- W1992316503 created "2016-06-24" @default.
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- W1992316503 date "2006-11-01" @default.
- W1992316503 modified "2023-10-08" @default.
- W1992316503 title "Classification of Breast Cancer Using Genetic Algorithms and Tissue Microarrays" @default.
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- W1992316503 cites W1988242406 @default.
- W1992316503 cites W1989259799 @default.
- W1992316503 cites W1989790390 @default.
- W1992316503 cites W1991527725 @default.
- W1992316503 cites W1994468555 @default.
- W1992316503 cites W1995591153 @default.
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- W1992316503 cites W2035344810 @default.
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- W1992316503 doi "https://doi.org/10.1158/1078-0432.ccr-06-1383" @default.
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