Routine assessment of prognostic factors in breast cancer using a multicore tissue microarray procedure

Virchows Arch. 2006 Sep;449(3):288-96. doi: 10.1007/s00428-006-0233-2. Epub 2006 Jun 13.


We propose multicore tissue microarray (TMA) as an alternative to whole section for routine assessment of prognostic factors in breast cancer. Since 2004, we introduced the multicore TMA for testing estrogen (ER) and progesterone receptors (PR), proliferation activity by Ki67, and HER2 overexpression and amplification in routine work. At least four tumor foci were selected on the whole section, and a dedicated technician used a stereomicroscope for accurate sampling of the selected areas. To identify a specific case in the TMA, a separate file and a computerized reporting form with the TMA map were created. A preliminary pilot study comparing the TMA results with those obtained on whole sections showed the specificity of the procedure. Moreover, in everyday diagnosis, hormone receptors were repeated on full section when negative in TMA, without significant discrepancy. Retrospective analysis of the 237 breast carcinomas studied by TMA showed the expected correspondence of tumor-grade differentiation with the hormone receptor pattern, the proliferation activity, and HER2 immunohistochemical and FISH values. In conclusion, multicore TMA may be an efficient approach in the routine study of prognostic factors in breast cancer, significantly reducing costs, time, and burden of slides necessary to accomplish these mandatory tests.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biomarkers, Tumor / analysis
  • Breast Neoplasms / chemistry
  • Breast Neoplasms / pathology*
  • Carcinoma, Ductal, Breast / chemistry
  • Carcinoma, Ductal, Breast / secondary*
  • Carcinoma, Lobular / chemistry
  • Carcinoma, Lobular / secondary*
  • Cell Proliferation
  • Female
  • Humans
  • In Situ Hybridization, Fluorescence
  • Middle Aged
  • Prognosis
  • Receptor, ErbB-2 / analysis
  • Tissue Array Analysis / economics
  • Tissue Array Analysis / methods*


  • Biomarkers, Tumor
  • Receptor, ErbB-2