Data-driven derivation of cutoffs from a pool of 3,030 Affymetrix arrays to stratify distinct clinical types of breast cancer.
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.
Karn
Thomas
T
Department of Obstetrics and Gynecology, J. W. Goethe University, Theodor-Stern-Kai 7, 60590, Frankfurt, Germany. t.karn@em.uni-frankfurt.de
Metzler
Dirk
D
Ruckhäberle
Eugen
E
Hanker
Lars
L
Gätje
Regine
R
Solbach
Christine
C
Ahr
Andre
A
Schmidt
Marcus
M
Holtrich
Uwe
U
Kaufmann
Manfred
M
Rody
Achim
A
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
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