Ki67 expression in invasive breast cancer: the use of tissue microarrays compared with whole tissue sections View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2017-07

AUTHORS

Abir A. Muftah, Mohammed A. Aleskandarany, Methaq M. Al-kaabi, Sultan N. Sonbul, Maria Diez-Rodriguez, Chris C. Nolan, Carlos Caldas, Ian O. Ellis, Emad A. Rakha, Andrew R. Green

ABSTRACT

BACKGROUND: Although the prognostic value of Ki67 in breast cancer is well documented, using optimal cut-points for patient stratification, reproducibility of the scoring and interpretation of the results remains a matter of debate particularly when using tissue microarrays (TMAs). This study aims to assess Ki67 expression assessed on TMAs and their matched whole tissue sections (WTS). Moreover, whether the cut-off used for WTS is reproducible on TMA in BC molecular classes and the association between Ki67 expression cut-off, assessed on TMAs and WTS, and clinicopathological parameters and patient outcome were tested. METHOD: A large series (n = 707) of primary invasive breast tumours were immunostained for Ki67 using both TMA and WTS and assessed as percentage staining and correlated with each other, clinicopathological parameters and patient outcome. In addition, MKI67 mRNA expression was correlated with Ki67 protein levels on WTS and TMAs in a subset of cases included in the METABRIC study. RESULTS: There was moderate concordance in Ki67 expression between WTS and TMA when analysed as a continuous variable (Intraclass correlation coefficient = 0.61) and low concordance when dichotomised (kappa value = 0.3). TMA showed low levels of Ki67 with mean percentage of expression of 35 and 22% on WTS and TMA, respectively. MKI67 mRNA expression was significantly correlated with protein expression determined on WTS (Spearman Correlation, r = 0.52) and to a lesser extent on TMA (r = 0.34) (p < 0.001). Regarding prediction of patient outcome, statistically significant differences were detected upon stratification of patients with tumours expressing Ki67 at 10, 15, 20, 25 or 30% in TMA. Using TMA, ≥20% Ki67 provided the best prognostic cut-off particularly in triple-negative and HER2-positive classes. CONCLUSION: Ki67 expression in breast cancer can be evaluated using TMA although different cut-points are required to emulate results from WTS. A cut-off of ≥20% for Ki67 expression in BC provides the best prognostic correlations when TMAs are used. More... »

PAGES

341-348

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10549-017-4270-0

DOI

http://dx.doi.org/10.1007/s10549-017-4270-0

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1085207596

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/28478613


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    "description": "BACKGROUND: Although the prognostic value of Ki67 in breast cancer is well documented, using optimal cut-points for patient stratification, reproducibility of the scoring and interpretation of the results remains a matter of debate particularly when using tissue microarrays (TMAs). This study aims to assess Ki67 expression assessed on TMAs and their matched whole tissue sections (WTS). Moreover, whether the cut-off used for WTS is reproducible on TMA in BC molecular classes and the association between Ki67 expression cut-off, assessed on TMAs and WTS, and clinicopathological parameters and patient outcome were tested.\nMETHOD: A large series (n\u00a0=\u00a0707) of primary invasive breast tumours were immunostained for Ki67 using both TMA and WTS and assessed as percentage staining and correlated with each other, clinicopathological parameters and patient outcome. In addition, MKI67 mRNA expression was correlated with Ki67 protein levels on WTS and TMAs in a subset of cases included in the METABRIC study.\nRESULTS: There was moderate concordance in Ki67 expression between WTS and TMA when analysed as a continuous variable (Intraclass correlation coefficient\u00a0=\u00a00.61) and low concordance when dichotomised (kappa value\u00a0=\u00a00.3). TMA showed low levels of Ki67 with mean percentage of expression\u00a0of 35 and 22% on WTS and TMA, respectively. MKI67 mRNA expression was significantly correlated with protein expression determined on WTS (Spearman Correlation, r\u00a0=\u00a00.52) and to a lesser extent on TMA (r\u00a0=\u00a00.34) (p\u00a0<\u00a00.001). Regarding prediction of patient outcome, statistically significant differences were detected upon stratification of patients with tumours expressing Ki67 at 10, 15, 20, 25 or 30% in TMA. Using TMA,\u00a0\u226520% Ki67 provided the best prognostic cut-off particularly in triple-negative and HER2-positive classes.\nCONCLUSION: Ki67 expression in breast cancer can be evaluated using TMA although different cut-points are required to emulate results from WTS. A cut-off of\u00a0\u226520% for Ki67 expression in BC provides the best prognostic correlations when TMAs are used.", 
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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s10549-017-4270-0'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s10549-017-4270-0'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s10549-017-4270-0'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s10549-017-4270-0'


 

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293 schema:name Department of Histopathology, Division of Cancer and Stem Cells, School of Medicine, Nottingham City Hospital, The University of Nottingham and Nottingham University Hospitals NHS Trust, Nottingham, UK
294 Department of Pathology, Faculty of Medicine, University of Benghazi, Benghazi, Libya
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296 https://www.grid.ac/institutes/grid.412920.c schema:alternateName Nottingham City Hospital
297 schema:name Department of Histopathology, Division of Cancer and Stem Cells, School of Medicine, Nottingham City Hospital, The University of Nottingham and Nottingham University Hospitals NHS Trust, Nottingham, UK
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299 https://www.grid.ac/institutes/grid.470869.4 schema:alternateName Cancer Research UK Cambridge Institute
300 schema:name Cancer Research UK Cambridge Institute, Li Ka Shing Centre, University of Cambridge, Cambridge, UK
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