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SIRT1与凋亡相关蛋白的表达可预测腔面A型乳腺癌的淋巴结转移及无病生存期。

Expression of SIRT1 and apoptosis-related proteins is predictive for lymph node metastasis and disease-free survival in luminal A breast cancer.

作者信息

Kim Hyojin, Lee Kyung-Hun, Park In Ae, Chung Yul Ri, Im Seock-Ah, Noh Dong-Young, Han Wonshik, Moon Hyeong-Gon, Jung Yoon Yang, Ryu Han Suk

机构信息

Department of Pathology, Seoul National University Hospital, Seoul, Korea.

Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea.

出版信息

Virchows Arch. 2015 Nov;467(5):563-70. doi: 10.1007/s00428-015-1815-7. Epub 2015 Aug 18.

Abstract

Luminal A breast cancer can present with early, unexpected lymph node metastasis, and sentinel lymph node biopsy has been reported false negative in some cases. We aimed to construct a biomarker-based model that predicts lymph node metastasis in luminal A breast cancer, using expression of silent mating type information regulation 2 homolog 1 (SIRT1) and apoptosis-related factors, which are known to be closely related. We selected tissue samples of 278 cases of luminal A invasive ductal carcinoma, constructed tissue microarrays, and performed immunohistochemical staining for SIRT1 and four apoptosis-related proteins. In constructing the best predictive model for lymph node metastasis, six clinicopathological parameters and five molecular markers were considered. Independent factors predictive of lymph node metastasis were pT stage (OR 1.829, p = 0.027), lymphovascular invasion (OR 4.128, p < 0.001), and decreased expression of caspase-3 (OR 0.535, p = 0.034) and of SIRT1 (OR 0.526, p = 0.053). A combination nuclear grade, lymphovascular invasion, increased B-cell lymphoma 2 (Bcl-2) expression, and reduced expression of caspase-3 and of SIRT1 yielded the strongest predictive performance for lymph node metastasis with an area under the curve (AUC) of 0.696. This combination was also predictive of shortened disease-free survival (73.1 vs. 67.7 months, p = 0.003). Our data support a role of SIRT1 protein as tumor suppressor in luminal A breast cancer, in association with apoptosis-related proteins. Our model based upon a combination of these biomarkers is expected to increase accuracy of prediction of lymph node metastasis in luminal A breast cancer. This might serve as a valuable tool in determining the optimal surgical strategy in breast cancer patients.

摘要

管腔A型乳腺癌可出现早期意外的淋巴结转移,且前哨淋巴结活检在某些情况下已被报道为假阴性。我们旨在构建一种基于生物标志物的模型,该模型利用已知密切相关的沉默信息调节因子2同源物1(SIRT1)和凋亡相关因子的表达来预测管腔A型乳腺癌的淋巴结转移。我们选取了278例管腔A型浸润性导管癌的组织样本,构建组织芯片,并对SIRT1和四种凋亡相关蛋白进行免疫组织化学染色。在构建淋巴结转移的最佳预测模型时,考虑了六个临床病理参数和五个分子标志物。预测淋巴结转移的独立因素为pT分期(OR 1.829,p = 0.027)、淋巴管浸润(OR 4.128,p < 0.001)以及半胱天冬酶-3表达降低(OR 0.535,p = 0.034)和SIRT1表达降低(OR 0.526,p = 0.053)。核分级、淋巴管浸润、B细胞淋巴瘤2(Bcl-2)表达增加以及半胱天冬酶-3和SIRT1表达降低的组合对淋巴结转移具有最强的预测性能,曲线下面积(AUC)为0.696。该组合也可预测无病生存期缩短(73.1个月对67.7个月,p = 0.003)。我们的数据支持SIRT1蛋白作为管腔A型乳腺癌肿瘤抑制因子的作用,与凋亡相关蛋白有关。基于这些生物标志物组合的我们的模型有望提高管腔A型乳腺癌淋巴结转移预测的准确性。这可能成为确定乳腺癌患者最佳手术策略的有价值工具。

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