Premium
Virtual tissue microarrays: a novel and viable approach to optimizing tissue microarrays for biomarker research applied to ductal carcinoma in situ
Author(s) -
Quintayo Mary Anne,
Starczynski Jane,
Yan Fu Jian,
Wedad Hanna,
NofechMozes Sharon,
Rakovitch Eileen,
Bartlett John M S
Publication year - 2014
Publication title -
histopathology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.626
H-Index - 124
eISSN - 1365-2559
pISSN - 0309-0167
DOI - 10.1111/his.12336
Subject(s) - tissue microarray , ductal carcinoma , biomarker , in situ , breast cancer , biomarker discovery , dna microarray , immunohistochemistry , computational biology , cancer , oncology , pathology , biology , computer science , medicine , chemistry , proteomics , biochemistry , gene expression , organic chemistry , gene
Aims Tissue microarrays ( TMA s) are effective tools for performing high‐throughput standardization analyses of biomarkers, but evidence indicating the core number required to be representative of the whole tumour is lacking. Ductal carcinoma in situ ( DCIS ) is a non‐obligate precursor of invasive breast cancer. The number and size of cores that can best represent a DCIS lesion are unknown. Rather than performing extensive experiments using several variants of physical TMA s, the aim of this study was to develop a ‘virtual TMA ’ approach that is effective at optimizing biomarker discovery and validation. Methods and results Whole DCIS sections from 95 patients were evaluated by immunohistochemistry for oestrogen receptor ( ER ), progesterone receptor (PgR), HER 2, and Ki67. Histoscores were generated manually for ER , PgR, and HER 2, as well as percentage positivity for Ki67. Slides were scanned using the FDA ‐approved Ariol SL 50 Image Analysis system, and the virtual array (V‐Array) module was used. Virtual cores created virtual TMA s, and our validated scoring classifiers were applied. Automated histoscores and percentage positivity were determined, and compared against increasing numbers of cores. The optimal number of cores was based on concordant results between virtual TMA s and corresponding whole sections. Conclusions We have shown that virtual arrays constitute an important tool in digital pathology in both research and clinical settings.