121
Views
3
CrossRef citations to date
0
Altmetric
Invited Articles

Tissue microarray studies in bladder cancer

Pages 141-146 | Received 24 Apr 2008, Published online: 31 Mar 2010
 

Abstract

The introduction of tissue microarray (TMA) methodology 10 years ago has provided a valuable tool for high-throughput genomic and proteomic analyses. Using this method hundreds of minute tissue samples can be investigated on one microscopic glass slide. Several studies demonstrated that these small tissue areas are representative for the entire tumour block and can provide reliable information on the relation of molecular markers and clinical outcome of the patient. Types of TMA used in bladder cancer research include defined clinical case series, stage-specific series (e.g. pT1), stage progression series, TMAs containing all specimens from clinical trials for specific therapies, flat (pre)neoplastic lesions, cell culture pellets and mouse model TMAs. The TMA technique has frequently been used in bladder cancer research to evaluate immunohistochemical candidate markers for prognosis and to reveal the amplification frequency of candidate oncogenes in regions with copy number alterations detected by comparative genomic hybridization and array-based methods. In addition, multimarker expression studies of several specific biological functions (e.g. apoptosis or cell-cycle proteins) or signal transduction pathways have been performed. TMAs are also used for validation of array-based gene expression studies on the protein level. TMA technology represents a crucial technique for translating new information on molecular changes in bladder cancer into clinical practice.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access
  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 65.00 Add to cart
* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.