Development and validation of predictive molecular signatures.
Since the different, so-called omics disciplines generate huge amount of data, the application of appropriate, sophisticated statistical methods for developing and validating predictive molecular signatures for drug development, for prevention, screening, diagnosis, monitoring of treatment or after treatment of diseases as well as for stratification of individuals is fundamental. The development and validation require several steps and it is quite a long journey from the detection of a molecular predictive signature to the routine use in clinical practice. In our review we focus on data obtained from cDNA expression microarrays. We describe the necessary development and validation steps including recent results of the second phase of the MAQC project (MAQC-II) and emphasise on potential pitfalls.
Kohl
M
M
Department of Mathematics, University of Bayreuth, Bayreuth, Germany. matthias.kohl@stamats.de
D015415:Biomarkers; D020869:Gene Expression Profiling / Q000379:methods*; D006801:Humans; D008403:Mass Screening / Q000379:methods; D009693:Nucleic Acid Hybridization; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D010363:Pattern Recognition, Automated; D011237:Predictive Value of Tests; D015995:Prevalence; D011786:Quality Control; D015203:Reproducibility of Results; D012107:Research Design; D018401:Sample Size; D012680:Sensitivity and Specificity
D015415:Biomarkers