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Classification of Breast Cancer Using Genetic Algorithms and Tissue Microarrays

👥 Marisa P Dolled-Filhart; Lisa Rydén; Melissa A. Cregger; Karin Jirström; Malini Harigopal; Robert L. Camp; David L. Rimm 📚 Clinical Cancer Research 🗄 OpenAlex 被引 107 👁 21
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📝 摘要

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.

🧾 论文要素

作者Marisa P Dolled-Filhart; Lisa Rydén; Melissa A. Cregger; Karin Jirström; Malini Harigopal; Robert L. Camp; David L. Rimm
期刊Clinical Cancer Research
出版机构https://openalex.org/P4310320273
年份2006
归属类乳腺癌
平台OpenAlex
被引数107
阅读量21
DOI10.1158/1078-0432.ccr-06-1383 ↗
关键词Breast cancer; Tissue microarray; DNA microarray; Oncology; Algorithm