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01-04-2010 | Preclinical study

Data driven derivation of cutoffs from a pool of 3,030 Affymetrix arrays to stratify distinct clinical types of breast cancer

Authors: Thomas Karn, Dirk Metzler, Eugen Ruckhäberle, Lars Hanker, Regine Gätje, Christine Solbach, Andre Ahr, Marcus Schmidt, Uwe Holtrich, Manfred Kaufmann, Achim Rody

Published in: Breast Cancer Research and Treatment | Issue 3/2010

Abstract

Pooling of microarray datasets seems to be a reasonable approach to increase sample size when a heterogeneous disease like breast cancer is concerned. Different methods for the adaption of datasets have been used in the literature. We have analyzed influences of these strategies using a pool of 3,030 Affymetrix U133A microarrays from breast cancer samples. We present data on the resulting concordance with biochemical assays of well known parameters and highlight critical pitfalls. We further propose a method for the inference of cutoff values directly from the data without prior knowledge of the true result. The cutoffs derived by this method displayed high specificity and sensitivity. Markers with a bimodal distribution like ER, PgR, and HER2 discriminate different biological subtypes of disease with distinct clinical courses. In contrast, markers displaying a continuous distribution like proliferation markers as Ki67 rather describe the composition of the mixture of cells in the tumor.

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Title: Data driven derivation of cutoffs from a pool of 3,030 Affymetrix arrays to stratify distinct clinical types of breast cancer
Authors: Thomas Karn
Dirk Metzler
Eugen Ruckhäberle
Lars Hanker
Regine Gätje
Christine Solbach
Andre Ahr
Marcus Schmidt
Uwe Holtrich
Manfred Kaufmann
Achim Rody
Publication date: 01-04-2010
Publisher: Springer US
Published in: Breast Cancer Research and Treatment / Issue 3/2010
Print ISSN: 0167-6806
Electronic ISSN: 1573-7217
DOI: https://doi.org/10.1007/s10549-009-0416-z

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