Literature DB >> 26818835

Bimodality of intratumor Ki67 expression is an independent prognostic factor of overall survival in patients with invasive breast carcinoma.

Arvydas Laurinavicius1,2, Benoit Plancoulaine3, Allan Rasmusson4, Justinas Besusparis5,4, Renaldas Augulis5,4, Raimundas Meskauskas4, Paulette Herlin5, Aida Laurinaviciene5,4, Abir A Abdelhadi Muftah6, Islam Miligy6, Mohammed Aleskandarany6, Emad A Rakha6,7, Andrew R Green6, Ian O Ellis6,7.   

Abstract

Proliferative activity, assessed by Ki67 immunohistochemistry (IHC), is an established prognostic and predictive biomarker of breast cancer (BC). However, it remains under-utilized due to lack of standardized robust measurement methodologies and significant intratumor heterogeneity of expression. A recently proposed methodology for IHC biomarker assessment in whole slide images (WSI), based on systematic subsampling of tissue information extracted by digital image analysis (DIA) into hexagonal tiling arrays, enables computation of a comprehensive set of Ki67 indicators, including intratumor variability. In this study, the tiling methodology was applied to assess Ki67 expression in WSI of 152 surgically removed Ki67-stained (on full-face sections) BC specimens and to test which, if any, Ki67 indicators can predict overall survival (OS). Visual Ki67 IHC estimates and conventional clinico-pathologic parameters were also included in the study. Analysis revealed linearly independent intrinsic factors of the Ki67 IHC variance: proliferation (level of expression), disordered texture (entropy), tumor size and Nottingham Prognostic Index, bimodality, and correlation. All visual and DIA-generated indicators of the level of Ki67 expression provided significant cutoff values as single predictors of OS. However, only bimodality indicators (Ashman's D, in particular) were independent predictors of OS in the context of hormone receptor and HER2 status. From this, we conclude that spatial heterogeneity of proliferative tumor activity, measured by DIA of Ki67 IHC expression and analyzed by the hexagonal tiling approach, can serve as an independent prognostic indicator of OS in BC patients that outperforms the prognostic power of the level of proliferative activity.

Entities:  

Keywords:  Automated image analysis; Breast cancer; Digital pathology; Heterogeneity; Hexagonal tiling; Honeycomb; Immunohistochemistry; Ki-67

Mesh:

Substances:

Year:  2016        PMID: 26818835     DOI: 10.1007/s00428-016-1907-z

Source DB:  PubMed          Journal:  Virchows Arch        ISSN: 0945-6317            Impact factor:   4.064


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Review 2.  Prognostic value of different cut-off levels of Ki-67 in breast cancer: a systematic review and meta-analysis of 64,196 patients.

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Journal:  Lab Invest       Date:  2013-11-04       Impact factor: 5.662

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Authors:  Arvydas Laurinavicius; Andrew R Green; Aida Laurinaviciene; Giedre Smailyte; Valerijus Ostapenko; Raimundas Meskauskas; Ian O Ellis
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Authors:  A Goldhirsch; E P Winer; A S Coates; R D Gelber; M Piccart-Gebhart; B Thürlimann; H-J Senn
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  15 in total

1.  Quality assurance trials for Ki67 assessment in pathology.

Authors:  M Raap; S Ließem; J Rüschoff; A Fisseler-Eckhoff; A Reiner; S Dirnhofer; R von Wasielewski; H Kreipe
Journal:  Virchows Arch       Date:  2017-05-11       Impact factor: 4.064

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Authors:  Mustafa Yousif; Paul J van Diest; Arvydas Laurinavicius; David Rimm; Jeroen van der Laak; Anant Madabhushi; Stuart Schnitt; Liron Pantanowitz
Journal:  Virchows Arch       Date:  2021-11-18       Impact factor: 4.064

Review 3.  The state of the art for artificial intelligence in lung digital pathology.

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Journal:  J Pathol       Date:  2022-06-20       Impact factor: 9.883

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Authors:  Martial Guillaud; Qian Ye; Sam Leung; Anita Carraro; Alan Harrison; Malcolm Hayes; Alan Nichol; Mira Keyes
Journal:  Med Oncol       Date:  2017-12-06       Impact factor: 3.064

5.  How the variability between computer-assisted analysis procedures evaluating immune markers can influence patients' outcome prediction.

Authors:  Marylène Lejeune; Benoît Plancoulaine; Nicolas Elie; Ramon Bosch; Laia Fontoura; Izar de Villasante; Anna Korzyńska; Andrea Gras Navarro; Esther Sauras Colón; Carlos López
Journal:  Histochem Cell Biol       Date:  2021-08-12       Impact factor: 4.304

6.  Automated Image Analysis of HER2 Fluorescence In Situ Hybridization to Refine Definitions of Genetic Heterogeneity in Breast Cancer Tissue.

Authors:  Gedmante Radziuviene; Allan Rasmusson; Renaldas Augulis; Daiva Lesciute-Krilaviciene; Aida Laurinaviciene; Eduard Clim; Arvydas Laurinavicius
Journal:  Biomed Res Int       Date:  2017-05-28       Impact factor: 3.411

7.  Programmed death-ligand 1 expression by digital image analysis advances thyroid cancer diagnosis among encapsulated follicular lesions.

Authors:  Anne M-Y Hsieh; Olena Polyakova; Guodong Fu; Ronald S Chazen; Christina MacMillan; Ian J Witterick; Ranju Ralhan; Paul G Walfish
Journal:  Oncotarget       Date:  2018-04-13

8.  Characterizing the heterogeneity of tumor tissues from spatially resolved molecular measures.

Authors:  John F Graf; Maria I Zavodszky
Journal:  PLoS One       Date:  2017-11-30       Impact factor: 3.240

9.  Digital image analysis of Ki67 proliferation index in breast cancer using virtual dual staining on whole tissue sections: clinical validation and inter-platform agreement.

Authors:  Timco Koopman; Henk J Buikema; Harry Hollema; Geertruida H de Bock; Bert van der Vegt
Journal:  Breast Cancer Res Treat       Date:  2018-01-18       Impact factor: 4.872

10.  Evaluation of the metastatic potential of malignant cells by image processing of digital holographic microscopy data.

Authors:  Violeta L Calin; Mona Mihailescu; Eugen I Scarlat; Alexandra V Baluta; Daniel Calin; Eugenia Kovacs; Tudor Savopol; Mihaela G Moisescu
Journal:  FEBS Open Bio       Date:  2017-09-02       Impact factor: 2.693

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