The Ki67 index (KI) is a standard clinical marker for tumor proliferation; however, its application is hindered by intratumoral heterogeneity. In this study, we used digital image analysis to comprehensively analyze Ki67 heterogeneity and distribution patterns in breast carcinoma. Using Smart Pathology software, we digitized and analyzed 42 excised breast carcinoma Ki67 slides. Boxplots, histograms, and heat maps were generated to illustrate the KI distribution. We found that 30% of cases (13/42) exhibited discrepancies between global and hotspot KI when using a 14% KI threshold for classification. Patients with higher global or hotspot KI values displayed greater heterogenicity. Ki67 distribution patterns were categorized as randomly distributed (52%, 22/42), peripheral (43%, 18/42), and centered (5%, 2/42). Our sampling simulator indicated analyzing more than 10 high-power fields was typically required to accurately estimate global KI, with sampling size being correlated with heterogeneity. In conclusion, using digital image analysis in whole-slide images allows for comprehensive Ki67 profile assessment, shedding light on heterogeneity and distribution patterns. This spatial information can facilitate KI surveys of breast cancer and other malignancies.
References
[1]
Sung, H., Ferlay, J., Siegel, R.L., Laversanne, M., Soerjomataram, I., Jemal, A. and Bray, F. (2021) Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA:ACancerJournalforClinicians, 71, 209-249. https://doi.org/10.3322/caac.21660
[2]
Abubakar, M., Figueroa, J., Ali, H.R., Blows, F., Lissowska, J., Caldas, C., etal. (2019) Combined Quantitative Measures of ER, PR, HER2, and KI67 Provide More Prognostic Information than Categorical Combinations in Luminal Breast Cancer. ModernPathology, 32, 1244-1256. https://doi.org/10.1038/s41379-019-0270-4
[3]
Gerdes, J., Lemke, H., Baisch, H., Wacker, H.H., Schwab, U. and Stein, H. (1984) Cell Cycle Analysis of a Cell Proliferation-Associated Human Nuclear Antigen Defined by the Monoclonal Antibody Ki-67. TheJournalofImmunology, 133, 1710-1715. https://doi.org/10.4049/jimmunol.133.4.1710
[4]
Soliman, N.A. and Yussif, S.M. (2016) Ki-67 as a Prognostic Marker According to Breast Cancer Molecular Subtype. CancerBiology&Medicine, 13, 496-504. https://doi.org/10.20892/j.issn.2095-3941.2016.0066
[5]
Lombardi, A., Lazzeroni, R., Bersigotti, L., Vitale, V. and Amanti, C. (2021) The Proper Ki-67 Cut-Off in Hormone Responsive Breast Cancer: A Monoinstitutional Analysis with Long-Term Follow-Up. BreastCancer, 13, 213-217. https://doi.org/10.2147/BCTT.S305440
[6]
Nielsen, T.O., Leung, S.C.Y., Rimm, D.L., Dodson, A., Acs, B., Badve, S., etal. (2021) Assessment of Ki67 in Breast Cancer: Updated Recommendations from the International Ki67 in Breast Cancer Working Group. JournaloftheNationalCancerInstitute, 113, 808-819. https://doi.org/10.1093/jnci/djaa201
[7]
Rimm, D.L., Leung, S.C.Y., McShane, L.M., Bai, Y., Bane, A.L., Bartlett, J.M.S., etal. (2019) An International Multicenter Study to Evaluate Reproducibility of Automated Scoring for Assessment of Ki67 in Breast Cancer. ModernPathology, 32, 59-69. https://doi.org/10.1038/s41379-018-0109-4
[8]
Gudlaugsson, E., Skaland, I., Janssen, E.A., Smaaland, R., Shao, Z., Malpica, A., Voorhorst, F. and Baak, J.P. (2012) Comparison of the Effect of Different Techniques for Measurement of Ki67 Proliferation on Reproducibility and Prognosis Prediction Accuracy in Breast Cancer. Histopathology, 61, 1134-1144. https://doi.org/10.1111/j.1365-2559.2012.04329.x
[9]
Arima, N., Nishimura, R., Osako, T., Nishiyama, Y., Fujisue, M., Okumura, Y., Nakano, M., Tashima, R. and Toyozumi, Y. (2016) A Comparison of the Hot Spot and the Average Cancer Cell Counting Methods and the Optimal Cutoff Point of the Ki-67 Index for Luminal Type Breast Cancer. Oncology, 90, 43-50. https://doi.org/10.1159/000441525
[10]
Himuro, T., Horimoto, Y., Arakawa, A., Tanabe, M. and Saito, M. (2016) Ki67 Heterogeneity in Estrogen Receptor-Positive Breast Cancers: Which Tumor Type Has the Most Heterogeneity? InternationalJournalofSurgicalPathology, 24, 103-107. https://doi.org/10.1177/1066896915605179
[11]
Focke, C.M., Decker, T. and Van Diest, P.J. (2016) Intratumoral Heterogeneity of Ki67 Expression in Early Breast Cancers Exceeds Variability between Individual Tumours. Histopathology, 69, 849-861. https://doi.org/10.1111/his.13007
[12]
Valkonen, M., Isola, J., Ylinen, O., Muhonen, V., Saxlin, A., Tolonen, T., Nykter, M. and Ruusuvuori, P. (2020) Cytokeratin-Supervised Deep Learning for Automatic Recognition of Epithelial Cells in Breast Cancers Stained for ER, PR, and Ki-67. IEEETransactionsonMedicalImaging, 39, 534-542. https://doi.org/10.1109/TMI.2019.2933656
[13]
Tuominen, V.J., Ruotoistenmäki, S., Viitanen, A., Jumppanen, M. and Isola, J. (2010) ImmunoRatio: A Publicly Available Web Application for Quantitative Image Analysis of Estrogen Receptor (ER), Progesterone Receptor (PR), and Ki-67. BreastCancerResearch, 12, R56. https://doi.org/10.1186/bcr2615
[14]
Skjervold, A.H., Pettersen, H.S., Valla, M., Opdahl, S. and Bofin, A.M. (2022) Visual and Digital Assessment of Ki-67 in Breast Cancer Tissue—A Comparison of Methods. DiagnosticPathology, 17, Article No. 45. https://doi.org/10.1186/s13000-022-01225-4
[15]
Mohammed, Z.M., McMillan, D.C., Elsberger, B., Going, J.J., Orange, C., Mallon, E., Doughty, J.C. and Edwards, J. (2012) Comparison of Visual and Automated Assessment of Ki-67 Proliferative Activity and Their Impact on Outcome in Primary Operable Invasive Ductal Breast Cancer. BritishJournalofCancer, 106, 383-388. https://doi.org/10.1038/bjc.2011.569
[16]
Klauschen, F., Wienert, S., Schmitt, W.D., Loibl, S., Gerber, B., Blohmer, J.U., etal. (2015) Standardized Ki67 Diagnostics Using Automated Scoring—Clinical Validation in the GeparTrio Breast Cancer Study. ClinicalCancerResearch, 21, 3651-3657. https://doi.org/10.1158/1078-0432.CCR-14-1283
[17]
Wessel Lindberg, A.S., Conradsen, K., Larsen, R., Friis Lippert, M., Røge, R. and Vyberg, M. (2017) Quantitative Tumor Heterogeneity Assessment on a Nuclear Population Basis. CytometryPartA, 91, 574-584. https://doi.org/10.1002/cyto.a.23047
[18]
Plancoulaine, B., Laurinaviciene, A., Herlin, P., Besusparis, J., Meskauskas, R., Baltrusaityte, I., Iqbal, Y. and Laurinavicius, A. (2015) A Methodology for Comprehensive Breast Cancer Ki67 Labeling Index with Intra-Tumor Heterogeneity Appraisal Based on Hexagonal Tiling of Digital Image Analysis Data. VirchowsArchiv, 467, 711-722. https://doi.org/10.1007/s00428-015-1865-x
[19]
Laurinavicius, A., Plancoulaine, B., Rasmusson, A., Besusparis, J., Augulis, R., Meskauskas, R., Herlin, P., etal. (2016) Bimodality of Intratumor Ki67 Expression Is an Independent Prognostic Factor of Overall Survival in Patients with Invasive Breast Carcinoma. VirchowsArchiv, 468, 493-502. https://doi.org/10.1007/s00428-016-1907-z
[20]
Kim, D., Pantanowitz, L., Schüffler, P., Yarlagadda, D.V.K., Ardon, O., Reuter, V.E., etal. (2020) (Re) Defining the High-Power Field for Digital Pathology. JournalofPathologyInformatics, 11, 33. https://doi.org/10.4103/jpi.jpi_48_20
[21]
Dowsett, M., Nielsen, T.O., A’Hern, R., Bartlett, J., Coombes, R.C., Cuzick, J., etal. (2011) Assessment of Ki67 in Breast Cancer: Recommendations from the International Ki67 in Breast Cancer Working Group. JournaloftheNationalCancerInstitute, 103, 1656-1664. https://doi.org/10.1093/jnci/djr393
[22]
Fasanella, S., Leonardi, E., Cantaloni, C., Eccher, C., Bazzanella, I., Aldovini, D., Bragantini, E., etal. (2011) Proliferative Activity in Human Breast Cancer: Ki-67 Automated Evaluation and the Influence of Different Ki-67 Equivalent Antibodies. DiagnosticPathology, 6, S7. https://doi.org/10.1186/1746-1596-6-S1-S7
[23]
Aleskandarany, M.A., Green, A.R., Ashankyty, I., Elmouna, A., Diez-Rodriguez, M., Nolan, C.C., Ellis, I.O. and Rakha, E.A. (2016) Impact of Intratumoural Heterogeneity on the Assessment of Ki67 Expression in Breast Cancer. BreastCancerResearchandTreatment, 158, 287-295. https://doi.org/10.1007/s10549-016-3893-x
[24]
Ellis, M.J., Suman, V.J., Hoog, J., Goncalves, R., Sanati, S., Creighton, C.J., etal. (2017) Ki67 Proliferation Index as a Tool for Chemotherapy Decisions during and after Neoadjuvant Aromatase Inhibitor Treatment of Breast Cancer: Results from the American College of Surgeons Oncology Group Z1031 Trial (Alliance). JournalofClinicalOncology, 35, 1061-1069. https://doi.org/10.1200/JCO.2016.69.4406
[25]
Thomssen, C., Balic, M., Harbeck, N. and Gnant, M. (2021) St. Gallen/Vienna 2021: A Brief Summary of the Consensus Discussion on Customizing Therapies for Women with Early Breast Cancer. BreastCare (Basel), 16, 135-143. https://doi.org/10.1159/000516114
[26]
Zilenaite, D., Rasmusson, A., Augulis, R., Besusparis, J., Laurinaviciene, A., Plancoulaine, B., Ostapenko, V. and Laurinavicius, A. (2020) Independent Prognostic Value of Intratumoral Heterogeneity and Immune Response Features by Automated Digital Immunohistochemistry Analysis in Early Hormone Receptor-Positive Breast Carcinoma. FrontiersinOncology, 10, Article No. 950. https://doi.org/10.3389/fonc.2020.00950
[27]
Acs, B., Leung, S.C.Y., Kidwell, K.M., Arun, I., Augulis, R., Badve, S.S., etal. (2022) Systematically Higher Ki67 Scores on Core Biopsy Samples Compared to Corresponding Resection Specimen in Breast Cancer: A Multi-Operator and Multi-Institutional Study. ModernPathology, 35, 1362-1369.
[28]
BrÁZdil, T., Gallo, M., Nenutil, R., Kubanda, A., Toufar, M. and Holub, P. (2022) Automated Annotations of Epithelial Cells and Stroma in Hematoxylin-Eosin-Stained Whole-Slide Images Using Cytokeratin Re-Staining. TheJournalofPathology:ClinicalResearch, 8, 129-142. https://doi.org/10.1002/cjp2.249
