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当前的乳腺癌增殖标志物根据细胞周期各阶段解耦的持续时间呈现出不同的相关性。

Current breast cancer proliferative markers correlate variably based on decoupled duration of cell cycle phases.

作者信息

Lee Lik Hang, Yang Hua, Bigras Gilbert

机构信息

Department of Laboratory Medicine and Pathology, University of Calgary, AB, Canada.

Department of Laboratory Medicine and Pathology, Cross Cancer Institute, University of Alberta, AB, Canada.

出版信息

Sci Rep. 2014 May 30;4:5122. doi: 10.1038/srep05122.

Abstract

Mitotic count, PhH3, and MIB-1 are used as measures of the proportion of proliferating malignant cells in surgical pathology. They highlight different stages of the cell cycle, but little is known about how this affects their counts. This study assesses the strength of their correlations and attempts to determine the relationship between them. Proliferation counts for forty-nine consecutive cases of invasive breast carcinomas were analyzed, with the same tumor area on each stain counted using digital image analysis. The integrated optical density (IOD) of nuclei was measured as an approximation of nuclear DNA content. PhH3 strongly correlated with mitotic count (r = 0.94). Weaker correlations were found between MIB-1 versus PhH3 (r = 0.79) and mitotic count (r = 0.83). Nuclear IOD showed stronger correlation with MIB-1 (r = 0.37) than to mitotic count (r = 0.23) and PhH3 (r = 0.34). With evidence from a literature review, it is suggested that the weaker correlations with MIB-1 are not explained by count imprecision or error, but relies on temporal decorrelation between cell cycle phases. Consequences on correlation between these proliferative markers are illustrated by mathematical models.

摘要

有丝分裂计数、磷酸化组蛋白H3(PhH3)和MIB-1在外科病理学中被用作衡量增殖性恶性细胞比例的指标。它们突出了细胞周期的不同阶段,但对于这如何影响它们的计数却知之甚少。本研究评估了它们之间相关性的强度,并试图确定它们之间的关系。对连续49例浸润性乳腺癌病例的增殖计数进行了分析,使用数字图像分析对每种染色上相同的肿瘤区域进行计数。测量细胞核的积分光密度(IOD)作为核DNA含量的近似值。PhH3与有丝分裂计数密切相关(r = 0.94)。MIB-1与PhH3之间(r = 0.79)以及与有丝分裂计数之间(r = 0.83)的相关性较弱。核IOD与MIB-1的相关性(r = 0.37)强于与有丝分裂计数(r = 0.23)和PhH3(r = 0.34)的相关性。根据文献综述的证据,提示与MIB-1较弱的相关性并非由计数不精确或误差所解释,而是依赖于细胞周期各阶段之间的时间去相关性。数学模型说明了这些增殖标志物之间相关性的后果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e21/4038821/83f3fbc3d8f1/srep05122-f1.jpg

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