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Network-based approach to identify prognosis-related genes in tamoxifen-treated patients with estrogen receptor-positive breast cancer.
Bioscience Reports ( IF 3.8 ) Pub Date : 2021-08-18 , DOI: 10.1042/bsr20203020
Yanyan Wang 1 , Xiaonan Gong 1 , Yujie Zhang 2
Affiliation  

Tamoxifen is an estrogen receptor (ER) antagonist that is most commonly used for the treatment of ER-positive breast cancer. However, tamoxifen resistance remains a major cause of cancer recurrence and progression. Here, we aimed to identify hub genes implicated in the progression and prognosis of ER-positive breast cancer following tamoxifen treatment. Microarray data (GSE9893) for 155 tamoxifen-treated primary ER-positive breast cancer samples were obtained from the Gene Expression Omnibus database. In total, 1,706 differentially expressed genes, including 859 upregulated genes and 847 downregulated genes, were identified between relapse samples and relapse-free samples. Weighted correlation network analysis clustered genes into 13 modules, among which the tan and blue modules were the most significantly related to prognosis. From these two modules, we further identified and validated two prognosis-related hub genes (GRSF1 and MAPT) via survival analysis based on several publicly available datasets. High expression of GRSF1 predicted poor prognosis, whereas MAPT indicated favorable outcomes in ER-positive breast cancer. Using breast cancer cell lines and tissue samples, we confirmed that GRSF1 was significantly upregulated and MAPT was downregulated in the tamoxifen-resistant group compared with the tamoxifen-sensitive group. The prognostic value of GRSF1 and MAPT was also verified in 48 tamoxifen-treated ER-positive breast cancer patients in our hospital. Gene set enrichment analysis suggested that GRSF1 was potentially involved in RNA degradation and cell cycle pathways, while MAPT was strongly linked to immune-related signaling pathways. Taken together, our findings established novel prognostic biomarkers to predict tamoxifen sensitivity, which may facilitate individualized management of breast cancer.

中文翻译:

基于网络的方法来识别他莫昔芬治疗的雌激素受体阳性乳腺癌患者的预后相关基因。

他莫昔芬是一种雌激素受体 (ER) 拮抗剂,最常用于治疗 ER 阳性乳腺癌。然而,他莫昔芬耐药仍然是癌症复发和进展的主要原因。在这里,我们旨在确定与他莫昔芬治疗后 ER 阳性乳腺癌的进展和预后有关的中枢基因。155 个他莫昔芬治疗的原发性 ER 阳性乳腺癌样本的微阵列数据 (GSE9893) 来自 Gene Expression Omnibus 数据库。在复发样本和无复发样本之间总共鉴定出 1,706 个差异表达基因,包括 859 个上调基因和 847 个下调基因。加权相关网络分析将基因聚类为 13 个模块,其中 tan 和 blue 模块与预后最显着相关。从这两个模块中,我们通过基于几个公开可用数据集的生存分析,进一步识别和验证了两个与预后相关的中枢基因(GRSF1 和 MAPT)。GRSF1 的高表达预示预后不良,而 MAPT 表明 ER 阳性乳腺癌预后良好。使用乳腺癌细胞系和组织样本,我们证实与他莫昔芬敏感组相比,他莫昔芬耐药组的 GRSF1 显着上调,MAPT 下调。GRSF1 和 MAPT 的预后价值也在我院 48 例他莫昔芬治疗的 ER 阳性乳腺癌患者中得到验证。基因集富集分析表明,GRSF1 可能参与 RNA 降解和细胞周期通路,而 MAPT 与免疫相关信号通路密切相关。综合起来,
更新日期:2021-08-18
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