title: Data-driven derivation of cutoffs from a pool of 3,030 Affymetrix arrays to stratify distinct clinical types of breast cancer.
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.
authors.affiliation: Department of Obstetrics and Gynecology, J. W. Goethe University, Theodor-Stern-Kai 7, 60590, Frankfurt, Germany. t.karn@em.uni-frankfurt.de
authors.forename: Thomas
authors.initials: T
authors.lastname: Karn
authors.forename: Dirk
authors.initials: D
authors.lastname: Metzler
authors.forename: Eugen
authors.initials: E
authors.lastname: Ruckhäberle
authors.forename: Lars
authors.initials: L
authors.lastname: Hanker
authors.forename: Regine
authors.initials: R
authors.lastname: Gätje
authors.forename: Christine
authors.initials: C
authors.lastname: Solbach
authors.forename: Andre
authors.initials: A
authors.lastname: Ahr
authors.forename: Marcus
authors.initials: M
authors.lastname: Schmidt
authors.forename: Uwe
authors.initials: U
authors.lastname: Holtrich
authors.forename: Manfred
authors.initials: M
authors.lastname: Kaufmann
authors.forename: Achim
authors.initials: A
authors.lastname: Rody
mesh_terms: D019540:Area Under Curve; D014408:Biomarkers, Tumor / Q000235:genetics*; D001943:Breast Neoplasms / Q000737:chemistry / Q000145:classification* / Q000235:genetics / Q000401:mortality; D004273:DNA, Neoplasm / Q000032:analysis*; D018572:Disease-Free Survival; D005260:Female; D005500:Follow-Up Studies; D018734:Genes, erbB-2; D006801:Humans; D053208:Kaplan-Meier Estimate; D019394:Ki-67 Antigen; D009363:Neoplasm Proteins / Q000235:genetics; D009376:Neoplasms, Hormone-Dependent / Q000737:chemistry / Q000235:genetics; D016011:Normal Distribution; D020411:Oligonucleotide Array Sequence Analysis / Q000706:statistics & numerical data*; D011237:Predictive Value of Tests; D011379:Prognosis; D016016:Proportional Hazards Models; D012372:ROC Curve; D018719:Erb-b2 Receptor Tyrosine Kinases / Q000032:analysis; D011960:Receptors, Estrogen / Q000032:analysis / Q000235:genetics; D011980:Receptors, Progesterone / Q000032:analysis / Q000235:genetics; D012680:Sensitivity and Specificity
chemical_list: D014408:Biomarkers, Tumor; D004273:DNA, Neoplasm; D019394:Ki-67 Antigen; D009363:Neoplasm Proteins; D018719:Erb-b2 Receptor Tyrosine Kinases; D011960:Receptors, Estrogen; D011980:Receptors, Progesterone; C508053:ERBB2 protein, human