Stromal Ki67 Expression Might be a Useful Marker for Distinguishing Fibroadenoma From Benign Phyllodes Tumor of the Breast

Author:

Yuan Men1,Saeki Harumi1,Horimoto Yoshiya1ORCID,Ishizuka Yumiko1,Onagi Hiroko1,Saito Mitsue1,Hayashi Takuo1,Arakawa Atsushi1,Yao Takashi1

Affiliation:

1. Juntendo University School of Medicine, Tokyo, Japan

Abstract

Background. Fibroadenoma (FA) and benign phyllodes tumor (PT) of the breast often have similar appearances on imaging. While an exact diagnosis of biopsy specimens is required to choose adequate treatment, including surgical procedures, it is sometimes difficult to pathologically differentiate these 2 tumors due to histological resemblances. To elucidate markers for distinguishing FA from benign PT, we analyzed clinical samples immunohistochemically. Methods. We retrospectively investigated 80 breast fibroepithelial lesions. As a discovery set, 60 surgical excision samples (30 FA and 30 benign PT) were examined. Twenty biopsy samples (10 FA and 10 benign PT) were examined as a validation set. To determine targets for immunohistochemistry, we first tested some proteins based on previous reports. As a result, Ki67 was chosen for differentiating FA and PT; thus further examinations were conducted with this protein. Results. Among the proteins examined, stromal Ki67 was significantly higher in PT than in FA. Benign PT had significantly higher stromal Ki67 expression both at random and at hotspots ( p < .001 and <.001, respectively). The receiver operating characteristic curve analysis identified 3.5% and 8.5% (at random spots and hotspots, respectively) as the optimal cutoff values of stromal Ki67 for distinguishing between these 2 tumors. In the validation cohort employing needle biopsy specimens, we confirmed that these 2 cutoff values properly classified these 2 tumors ( p = .043 and .029, respectively). Conclusion.We revealed that stromal Ki67 might be a potential marker for distinguishing FA from benign PT.

Publisher

SAGE Publications

Subject

Pathology and Forensic Medicine,Surgery,Anatomy

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3