Journal
BREAST CANCER RESEARCH AND TREATMENT
Volume 120, Issue 3, Pages 567-579Publisher
SPRINGER
DOI: 10.1007/s10549-009-0416-z
Keywords
Breast cancer; Microarray; Cutoff; Distribution; Pooling; Meta-analysis; Bimodal markers
Categories
Funding
- Deutsche Krebshilfe, the Margarete Bonifer-Stiftung, Bad Soden
- BANSS-Stiftung, Biedenkopf
- Dr. Robert Pfleger-Stiftung, Bamberg
Ask authors/readers for more resources
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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available