Multiple biomarker tissue microarrays: bioinformatics and practical approaches.
BACKGROUND
Tissue microarrays (TMAs) facilitate high-throughput immunohistochemical analysis of potential predictive and prognostic biomarkers in tumor or normal tissue samples. This technology and the practical issues involved in designing TMAs for translational research are reviewed. A main field of application of TMAs is in the search for predictive and prognostic markers in specific types of cancer.


CONCLUSIONS
Standard data analytical approaches are discussed and some of the issues in applying these in practice are described.


CONCLUSIONS
TMAs allow the collection of information-rich datasets on the simultaneous expression of multiple biomarkers. Supervised and unsupervised strategies have been developed for handling datasets where the number of covariates, in this case biomarker expression data, is large in relation to the number of patients in the sample. Some future research pathways are briefly presented together with the recent attempts to improve the reporting quality of biomarker studies.
Bentzen
Søren M
SM
Department of Human Oncology, University of Wisconsin School of Medicine and Public Health, K4/316 Clinical Science Center, 600 Highland Avenue, Madison, WI 53792, USA. bentzen@humonc.wisc.edu
Buffa
Francesca M
FM
Wilson
George D
GD
D000818:Animals; D015415:Biomarkers / Q000032:analysis*; D019295:Computational Biology / Q000379:methods* / Q000639:trends; D006801:Humans; D007150:Immunohistochemistry; D046888:Tissue Array Analysis / Q000379:methods*
D015415:Biomarkers