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An automated staining protocol for seven-colour immunofluorescence of human tissue sections for diagnostic and prognostic use.

Authors :
Lim JCT
Yeong JPS
Lim CJ
Ong CCH
Wong SC
Chew VSP
Ahmed SS
Tan PH
Iqbal J
Source :
Pathology [Pathology] 2018 Apr; Vol. 50 (3), pp. 333-341. Date of Electronic Publication: 2018 Feb 09.
Publication Year :
2018

Abstract

Multiplex immunofluorescence (mIF) allows simultaneous antibody-based detection and quantification of the expression of up to six markers, plus a nuclear counterstain, on a single tissue section. Recent studies have shown the potential for mIF to advance our understanding of complex disease processes, including cancer. It is important that the technique be standardised and validated to facilitate its transition into clinical use. Traditional approaches to mIF rely on manual processing of sections, which is time-consuming and a source of significant variation between samples/individuals. Here we determined if an automated diagnostic tissue stainer could be used for mIF incorporating tyramide signal amplification (TSA), and how the final image quality compared with sections stained semi-automatically or manually. Using tissue microarrays of fixed human breast tumour sections, we observed comparable antibody labelling between the diagnostic autostainer and manual technique. The diagnostic autostainer produced higher signal intensity with similar spectral unmixing efficiency. We also found that microwave treatment for antibody stripping during TSA labelling could be replaced by the heating option incorporated within the diagnostic-use autostainer. These data show that diagnostic autostainers used for traditional immunohistochemistry protocols can be readily adapted to achieve rapid preparation of high-quality sections using a TSA method for clinical mIF.<br /> (Copyright © 2018 Royal College of Pathologists of Australasia. Published by Elsevier B.V. All rights reserved.)

Details

Language :
English
ISSN :
1465-3931
Volume :
50
Issue :
3
Database :
MEDLINE
Journal :
Pathology
Publication Type :
Academic Journal
Accession number :
29429740
Full Text :
https://doi.org/10.1016/j.pathol.2017.11.087