The Department of Breast Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
The Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Aging (Albany NY). 2020 Aug 3;12(16):16491-16513. doi: 10.18632/aging.103753.
Advancements in immunotherapy have improved our understanding of the immune characteristics of breast cancer. Here, we analyzed gene expression profiles and clinical data obtained from The Cancer Genome Atlas database to identify genes that were differentially expressed between breast tumor tissues and normal breast tissues. Comparisons with the Immunology Database and Analysis Portal (ImmPort) indicated that many of the identified differentially expressed genes were immune-related. Risk scores calculated based on an eight-gene signature constructed from these immune-related genes predicted both overall survival and relapse-free survival outcomes in breast cancer patients. The predictive value of the eight-gene signature was validated in different breast cancer subtypes using external datasets. Associations between risk score and breast cancer immune characteristics were also identified; experiments using breast cancer cell lines confirmed those associations. Thus, the novel eight-gene signature described here accurately predicts breast cancer survival outcomes as well as immune checkpoint expression and immune cell infiltration processes.
免疫疗法的进步提高了我们对乳腺癌免疫特征的理解。在这里，我们分析了从癌症基因组图谱数据库获得的基因表达谱和临床数据，以鉴定乳腺癌肿瘤组织和正常乳腺组织之间差异表达的基因。与免疫数据库和分析门户（ImmPort）的比较表明，许多鉴定出的差异表达基因与免疫相关。基于从这些免疫相关基因构建的八个基因特征计算的风险评分可预测乳腺癌患者的总生存和无复发生存结局。使用外部数据集在不同的乳腺癌亚型中验证了八个基因特征的预测价值。还确定了风险评分与乳腺癌免疫特征之间的关联；使用乳腺癌细胞系进行的实验证实了这些关联。因此，这里描述的新型八个基因特征可准确预测乳腺癌的生存结果以及免疫检查点表达和免疫细胞浸润过程。
