Literature DB >> 27026269

Expression of cell cycle markers is predictive of the response to primary systemic therapy of locally advanced breast cancer.

Tímea Tőkés1, Anna-Mária Tőkés2,3, Gyöngyvér Szentmártoni1, Gergő Kiszner4, Lilla Madaras3, Janina Kulka3, Tibor Krenács2,4, Magdolna Dank5.   

Abstract

We aimed to analyze to what extent expression of four cell cycle regulation markers-minichromosome maintenance protein (MCM2), Ki-67, cyclin A, and phosphohistone-H3 (PHH3)-predict response to primary systemic therapy in terms of pathological complete remission (pCR). In search of an accurate and reproducible scoring method, we compared computer-assisted (CA) and routine visual assessment (VA) of immunoreactivity. We included 57 patients with breast cancer in the study. The cell cycle markers were detected using immunohistochemistry on pre-therapy core biopsy samples. Parallel CA (validated by manual labeling) and standard VA were performed and compared for diagnostic agreement and predictive value for pCR. CA and VA results were dichotomized based on receiver operating characteristic analysis defined optimal cut-off values. "High" was defined by staining scores above the optimal cut-off, while "low" had staining scores below the optimal cut-off. The CA method resulted in significantly lower values for Ki-67 and MCM2 compared to VA (mean difference, -3.939 and -4.323). Diagnostic agreement was highest for cyclin A and PHH3 (-0.586 and -0.666, respectively). Regardless of the method (CA/VA) used, all tested markers were predictive of pCR. Optimal cut-off-based dichotomization improved diagnostic agreement between the CA and VA methods for every marker, in particular for MCM2 (κ = 1, p < 0.000). Cyclin A displayed excellent agreement (κ = 0.925; p < 0.000), while Ki-67 and PHH3 showed good agreement (κ = 0.789, p < 0.000 and κ = 0.794, p < 0.000, respectively). We found all cell cycle markers (Ki-67, MCM2, cyclin A, and PHH3) predictive of pCR. Diagnostic agreement between CA and VA was better at lower staining scores but improved after optimal cut-off-based dichotomization.

Entities:  

Keywords:  Breast cancer; Cell cycle; Digital pathology; Primary systemic therapy; Proliferation

Mesh:

Substances:

Year:  2016        PMID: 27026269     DOI: 10.1007/s00428-016-1925-x

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


  60 in total

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Review 4.  The cell cycle and cancer.

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5.  Comparison of the effect of different techniques for measurement of Ki67 proliferation on reproducibility and prognosis prediction accuracy in breast cancer.

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Journal:  Histopathology       Date:  2012-09-11       Impact factor: 5.087

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Journal:  Diagn Pathol       Date:  2011-03-30       Impact factor: 2.644

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9.  Cell-cycle-phase progression analysis identifies unique phenotypes of major prognostic and predictive significance in breast cancer.

Authors:  M Loddo; S R Kingsbury; M Rashid; I Proctor; C Holt; J Young; S El-Sheikh; M Falzon; K L Eward; T Prevost; R Sainsbury; K Stoeber; G H Williams
Journal:  Br J Cancer       Date:  2009-02-24       Impact factor: 7.640

10.  DNA replication licensing and cell cycle kinetics of normal and neoplastic breast.

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  3 in total

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Journal:  Med Image Comput Comput Assist Interv       Date:  2021-09-21

2.  Minichromosome maintenance protein 2 correlates with the malignant status and regulates proliferation and cell cycle in lung squamous cell carcinoma.

Authors:  Wei Wu; Xianwei Wang; Changting Shan; Yong Li; Fengzhu Li
Journal:  Onco Targets Ther       Date:  2018-08-20       Impact factor: 4.345

3.  Prognostic and Clinicopathological Correlations of Cell Cycle Marker Expressions before and after the Primary Systemic Therapy of Breast Cancer.

Authors:  Tímea Tőkés; Anna-Mária Tőkés; Gyöngyvér Szentmártoni; Gergő Kiszner; Dorottya Mühl; Béla Ákos Molnár; Janina Kulka; Tibor Krenács; Magdolna Dank
Journal:  Pathol Oncol Res       Date:  2019-08-24       Impact factor: 3.201

  3 in total

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