Visual and digital assessment of Ki-67 in breast cancer tissue - a comparison of methods.
Breast cancer
Cell proliferation
Digital image assessment
Digital pathology
Immunohistochemistry
Ki-67
Journal
Diagnostic pathology
ISSN: 1746-1596
Titre abrégé: Diagn Pathol
Pays: England
ID NLM: 101251558
Informations de publication
Date de publication:
06 May 2022
06 May 2022
Historique:
received:
09
02
2022
accepted:
12
04
2022
entrez:
6
5
2022
pubmed:
7
5
2022
medline:
11
5
2022
Statut:
epublish
Résumé
In breast cancer (BC) Ki-67 cut-off levels, counting methods and inter- and intraobserver variation are still unresolved. To reduce inter-laboratory differences, it has been proposed that cut-off levels for Ki-67 should be determined based on the in-house median of 500 counted tumour cell nuclei. Digital image analysis (DIA) has been proposed as a means to standardize assessment of Ki-67 staining in tumour tissue. In this study we compared digital and visual assessment (VA) of Ki-67 protein expression levels in full-face sections from a consecutive series of BCs. The aim was to identify the number of tumour cells necessary to count in order to reflect the growth potential of a given tumour in both methods, as measured by tumour grade, mitotic count and patient outcome. A series of whole sections from 248 invasive carcinomas of no special type were immunohistochemically stained for Ki-67 and then assessed by VA and DIA. Five 100-cell increments were counted in hot spot areas using both VA and DIA. The median numbers of Ki-67 positive tumour cells were used to calculate cut-off levels for Low, Intermediate and High Ki-67 protein expression in both methods. We found that the percentage of Ki-67 positive tumour cells was higher in DIA compared to VA (medians after 500 tumour cells counted were 22.3% for VA and 30% for DIA). While the median Ki-67% values remained largely unchanged across the 100-cell increments for VA, median values were highest in the first 1-200 cells counted using DIA. We also found that the DIA100 High group identified the largest proportion of histopathological grade 3 tumours 70/101 (69.3%). We show that assessment of Ki-67 in breast tumours using DIA identifies a greater proportion of cases with high Ki-67 levels compared to VA of the same tumours. Furthermore, we show that diagnostic cut-off levels should be calibrated appropriately on the introduction of new methodology.
Sections du résumé
BACKGROUND
BACKGROUND
In breast cancer (BC) Ki-67 cut-off levels, counting methods and inter- and intraobserver variation are still unresolved. To reduce inter-laboratory differences, it has been proposed that cut-off levels for Ki-67 should be determined based on the in-house median of 500 counted tumour cell nuclei. Digital image analysis (DIA) has been proposed as a means to standardize assessment of Ki-67 staining in tumour tissue. In this study we compared digital and visual assessment (VA) of Ki-67 protein expression levels in full-face sections from a consecutive series of BCs. The aim was to identify the number of tumour cells necessary to count in order to reflect the growth potential of a given tumour in both methods, as measured by tumour grade, mitotic count and patient outcome.
METHODS
METHODS
A series of whole sections from 248 invasive carcinomas of no special type were immunohistochemically stained for Ki-67 and then assessed by VA and DIA. Five 100-cell increments were counted in hot spot areas using both VA and DIA. The median numbers of Ki-67 positive tumour cells were used to calculate cut-off levels for Low, Intermediate and High Ki-67 protein expression in both methods.
RESULTS
RESULTS
We found that the percentage of Ki-67 positive tumour cells was higher in DIA compared to VA (medians after 500 tumour cells counted were 22.3% for VA and 30% for DIA). While the median Ki-67% values remained largely unchanged across the 100-cell increments for VA, median values were highest in the first 1-200 cells counted using DIA. We also found that the DIA100 High group identified the largest proportion of histopathological grade 3 tumours 70/101 (69.3%).
CONCLUSIONS
CONCLUSIONS
We show that assessment of Ki-67 in breast tumours using DIA identifies a greater proportion of cases with high Ki-67 levels compared to VA of the same tumours. Furthermore, we show that diagnostic cut-off levels should be calibrated appropriately on the introduction of new methodology.
Identifiants
pubmed: 35524221
doi: 10.1186/s13000-022-01225-4
pii: 10.1186/s13000-022-01225-4
pmc: PMC9074355
doi:
Substances chimiques
Ki-67 Antigen
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
45Informations de copyright
© 2022. The Author(s).
Références
NPJ Breast Cancer. 2016 May 18;2:16014
pubmed: 28721378
BMC Cancer. 2011 Aug 07;11:341
pubmed: 21819622
Breast Care (Basel). 2013 Jun;8(3):221-9
pubmed: 24415975
JAMA. 1982 May 14;247(18):2543-6
pubmed: 7069920
J Pathol. 2002 Nov;198(3):292-9
pubmed: 12375261
Lab Invest. 2018 Jan;98(1):15-26
pubmed: 29251737
Ann Biol Clin (Paris). 2016 Dec 1;74(6):653-660
pubmed: 27848916
J Am Coll Surg. 2013 Feb;216(2):239-51
pubmed: 23141136
PLoS One. 2012;7(5):e37379
pubmed: 22662150
Breast Cancer Res Treat. 2018 May;169(1):33-42
pubmed: 29349710
J Clin Oncol. 2008 Dec 1;26(34):5569-75
pubmed: 18981464
Breast Cancer Res Treat. 2013 Aug;140(3):463-73
pubmed: 23901018
Breast Care (Basel). 2015 Apr;10(2):124-30
pubmed: 26195941
Diagn Pathol. 2014 Jun 16;9:118
pubmed: 24934660
Clin Epidemiol. 2020 Jul 20;12:771-781
pubmed: 32801916
Cell. 2011 Mar 4;144(5):646-74
pubmed: 21376230
Ecancermedicalscience. 2021 May 18;15:1236
pubmed: 34221119
Ann Oncol. 2015 Aug;26(8):1533-46
pubmed: 25939896
Histopathology. 2018 May;72(6):974-989
pubmed: 29220095
Histopathology. 2018 Aug;73(2):327-338
pubmed: 29575153
Breast Cancer Res Treat. 2020 Aug;183(1):161-175
pubmed: 32572716
J Pathol. 1992 Dec;168(4):357-63
pubmed: 1484317
J Immunol. 1984 Oct;133(4):1710-5
pubmed: 6206131
PLoS One. 2016 Feb 29;11(2):e0150505
pubmed: 26928407
J Natl Cancer Inst. 2011 Nov 16;103(22):1656-64
pubmed: 21960707
Acta Oncol. 2018 Jan;57(1):83-89
pubmed: 29202622
PLoS One. 2019 Feb 20;14(2):e0212309
pubmed: 30785924
Lab Invest. 2004 Aug;84(8):1071-8
pubmed: 15195116
J Clin Oncol. 2005 Oct 1;23(28):7212-20
pubmed: 16192605
Sci Rep. 2017 Dec 4;7(1):16878
pubmed: 29203879
Breast Cancer Res Treat. 2018 Jan;167(1):31-37
pubmed: 28865009
Br J Cancer. 2007 May 21;96(10):1504-13
pubmed: 17453008
Tissue Cell. 2019 Jun;58:12-16
pubmed: 31133239
Ann Oncol. 2011 Aug;22(8):1736-47
pubmed: 21709140
Appl Immunohistochem Mol Morphol. 2021 Aug 1;29(7):499-505
pubmed: 33758143
Cell Prolif. 1997 Mar-Apr;30(3-4):107-15
pubmed: 9375023
J Clin Oncol. 2013 Jan 10;31(2):203-9
pubmed: 23233704
Oncol Lett. 2015 Mar;9(3):1046-1054
pubmed: 25663855
Breast. 2014 Feb;23(1):69-75
pubmed: 24314620
Pol J Pathol. 2013 Apr;64(1):1-8
pubmed: 23625593
Breast Cancer Res. 2014;16(2):R35
pubmed: 24708745
J Natl Cancer Inst. 2013 Dec 18;105(24):1897-906
pubmed: 24203987
J Pathol Inform. 2019 Mar 08;10:8
pubmed: 30984468
Nature. 1982 Sep 2;299(5878):65-7
pubmed: 7110326
J Breast Cancer. 2014 Mar;17(1):40-6
pubmed: 24744796
Cancer Epidemiol Biomarkers Prev. 2016 Dec;25(12):1625-1634
pubmed: 27672056
Eur J Cancer. 2017 Oct;84:219-227
pubmed: 28829990
Biochem Med (Zagreb). 2015 Jun 05;25(2):141-51
pubmed: 26110027
Appl Immunohistochem Mol Morphol. 2002 Jun;10(2):183-6
pubmed: 12051639
Int J Cancer. 2010 Apr 1;126(7):1761-9
pubmed: 19711345
Lab Invest. 2019 Jan;99(1):107-117
pubmed: 30181553
Breast Care (Basel). 2013 May;8(2):101
pubmed: 24415963
Lab Invest. 2000 Dec;80(12):1943-9
pubmed: 11140706
J Natl Cancer Inst. 2021 Jul 1;113(7):808-819
pubmed: 33369635