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COMMENTARY Pitfalls in the Use of DNA Microarray Data for Diagnostic and Prognostic Classification
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TLDR
Statistical issues that arise from the use of DNA microarrays for an important group of objectives that has been called “class prediction” are addressed, which includes derivation of predictors of prognosis, response to therapy, or any phenotype or genotype defined independently of the gene expression profile.About:
The article was published on 2003-01-01 and is currently open access. It has received 951 citations till now.read more
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TL;DR: This study validates the "breast tumor intrinsic" subtype classification as an objective means of tumor classification that should be translated into a clinical assay for further retrospective and prospective validation.
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Bias in error estimation when using cross-validation for model selection
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Validation and Clinical Utility of a 70-Gene Prognostic Signature for Women With Node-Negative Breast Cancer
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References
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Classification and regression trees
TL;DR: The methodology used to construct tree structured rules is the focus of a monograph as mentioned in this paper, covering the use of trees as a data analysis method, and in a more mathematical framework, proving some of their fundamental properties.
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Molecular classification of cancer: class discovery and class prediction by gene expression monitoring.
Todd R. Golub,Todd R. Golub,Donna K. Slonim,Pablo Tamayo,Christine Huard,Michelle Gaasenbeek,Jill P. Mesirov,Hilary A. Coller,Mignon L. Loh,James R. Downing,Michael A. Caligiuri,Clara D. Bloomfield,Eric S. Lander +12 more
TL;DR: A generic approach to cancer classification based on gene expression monitoring by DNA microarrays is described and applied to human acute leukemias as a test case and suggests a general strategy for discovering and predicting cancer classes for other types of cancer, independent of previous biological knowledge.
Journal ArticleDOI
Gene expression profiling predicts clinical outcome of breast cancer
Laura J. van't Veer,Hongyue Dai,Marc J. van de Vijver,Yudong D. He,Augustinus A. M. Hart,Mao Mao,Hans Peterse,Karin van der Kooy,Matthew J. Marton,Anke T. Witteveen,George J. Schreiber,Ron M. Kerkhoven,Christopher J. Roberts,Peter S. Linsley,René Bernards,Stephen H. Friend +15 more
TL;DR: DNA microarray analysis on primary breast tumours of 117 young patients is used and supervised classification is applied to identify a gene expression signature strongly predictive of a short interval to distant metastases (‘poor prognosis’ signature) in patients without tumour cells in local lymph nodes at diagnosis, providing a strategy to select patients who would benefit from adjuvant therapy.
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Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling
Ash A. Alizadeh,Michael B. Eisen,R. Eric Davis,Izidore S. Lossos,Andreas Rosenwald,Jennifer C. Boldrick,Hajeer Sabet,Truc Tran,Xin Yu,John Powell,Liming Yang,Gerald E. Marti,Troy Moore,James I. Hudson,Li-Sheng Lu,David B. Lewis,Robert Tibshirani,Gavin Sherlock,Wing C. Chan,Timothy C. Greiner,Dennis D. Weisenburger,James O. Armitage,Roger A. Warnke,Ronald Levy,Wyndham H. Wilson,M. R. Grever,John C. Byrd,David Botstein,Patrick O. Brown,Louis M. Staudt +29 more
TL;DR: It is shown that there is diversity in gene expression among the tumours of DLBCL patients, apparently reflecting the variation in tumour proliferation rate, host response and differentiation state of the tumour.