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Clinicopathological Analysis of miRNA Expression in Breast Cancer Tissues by Using miRNA In Situ Hybridization
Published on: June 7, 2016
Prognostic and Clinicopathological Correlations of Cell Cycle Marker Expressions before and after the Primary
Tímea Tőkés1, Anna-Mária Tőkés2, Gyöngyvér Szentmártoni3
1Oncology Center, Semmelweis University, Tömő utca 25-29, 4th floor, Budapest, H-1083, Hungary. timi.tokes@gmail.com.
Abstract:
We aimed to analyze the expression of cell-cycle regulation markers - minichromosome maintenance protein 2 (MCM2), Ki-67, Cyclin-A and phosphohistone-H3 (PHH3) - in pre-treatment core-biopsy samples of breast carcinomas in correlation with known predictive and prognostic factors. Totally 52 core biopsy samples obtained prior to neoadjuvant therapy were analyzed. Immunohistochemistry was performed to analyze the expression of MCM2, Ki-67, Cyclin A and PHH3, which were correlated with the following clinicopathological parameters: clinical TNM, tumor grade, biological subtype, the presence of tumor infiltrating lymphocytes (TIL), pathological tumor response rate to the neoadjuvant therapy and patient survival. All investigated markers showed higher expression in high grade and in triple negative tumors (p < 0.01 and p < 0.05, respectively). Hormone receptor negative tumors showed significantly higher expression of Ki-67 (p < 0.01), MCM2 (p < 0.01) and Cyclin A (p < 0.01) than hormone receptor positive ones. Tumors with increased TIL showed significantly higher Ki-67 expression (p = 0.04). Pattern analysis suggested that novel cell-cycle marker-based subgrouping reveals predictive and prognostic potential. Tumors with high MCM2, Cyclin A or PHH3 expression showed significantly higher rate of pathological complete remission. Tumors with early relapse (progression-free survival ≤2 years) and shortened overall survival also show a higher rate of proliferation. Our cell cycle marker (Ki-67, MCM2, Cyclin A, PHH3) based testing could identify tumors with worse prognosis, but with a favorable response to primary systemic therapy. The pattern of cell-cycle activity could also be useful for predicting early relapse, but our findings need to be further substantiated in larger patient cohorts.
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