Suppr超能文献

雄激素受体表达可预测按激素受体状态分层的乳腺癌患者的不同临床结局。

Androgen receptor expression predicts different clinical outcomes for breast cancer patients stratified by hormone receptor status.

作者信息

Jiang He-Sheng, Kuang Xia-Ying, Sun Wei-Li, Xu Yan, Zheng Yi-Zi, Liu Yi-Rong, Lang Guan-Tian, Qiao Feng, Hu Xin, Shao Zhi-Ming

机构信息

Key Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.

Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.

出版信息

Oncotarget. 2016 Jul 5;7(27):41285-41293. doi: 10.18632/oncotarget.9778.

Abstract

In this study we sought to correlate androgen receptor (AR) expression with tumor progression and disease-free survival (DFS) in breast cancer patients. We investigated AR expression in 450 breast cancer patients. We found that breast cancers expressing the estrogen receptor (ER) are more likely to co-express AR compared to ER-negative cancers (56.0% versus 28.1%, P < 0.001). In addition, we found that AR expression is correlated with increased DFS in patients with luminal breast cancer (P < 0.001), and decreased DFS in TNBC (triple negative breast cancer, P = 0.014). In addition, patients with HR+ tumors (Hormone receptor positive tumors) expressing low levels of AR have the lowest DFS among all receptor combinations. We also propose a novel prognostic model using AR receptor status, BRCA1, and present data showing that our model is more predictive of disease free survival compared to the traditional TMN staging system.

摘要

在本研究中,我们试图将雄激素受体(AR)表达与乳腺癌患者的肿瘤进展和无病生存期(DFS)相关联。我们调查了450例乳腺癌患者的AR表达情况。我们发现,与雌激素受体(ER)阴性的癌症相比,表达ER的乳腺癌更有可能共表达AR(56.0%对28.1%,P<0.001)。此外,我们发现AR表达与管腔型乳腺癌患者DFS增加相关(P<0.001),而与三阴性乳腺癌(TNBC)患者DFS降低相关(P = 0.014)。此外,在所有受体组合中,AR表达水平低的HR+肿瘤(激素受体阳性肿瘤)患者的DFS最低。我们还提出了一种使用AR受体状态、BRCA1的新型预后模型,并给出数据表明,与传统的TMN分期系统相比,我们的模型对无病生存期的预测性更强。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cfbc/5173059/0deeda96ecf5/oncotarget-07-41285-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验