Wang Yichao, Zhong Qianyi, Li Zhaoyun, Lin Zhu, Chen Hanjun, Wang Pan
Department of Clinical Laboratory Medicine, Taizhou Central Hospital (Taizhou University Hospital), Taizhou, Zhejiang, 318000, People's Republic of China.
Department of Ultrasound, Taizhou Central Hospital (Taizhou University Hospital), Taizhou, Zhejiang, 318000, People's Republic of China.
Onco Targets Ther. 2021 Apr 9;14:2433-2448. doi: 10.2147/OTT.S296373. eCollection 2021.
Breast cancer is the main reason for cancer-related deaths in women and the most common malignant cancer among women. In recent years, immunosuppressive factors have become a new type of treatment for cancer. However, there are no effective biomarkers for breast cancer immunotherapy. Therefore, exploring immune-related biomarkers is presently an important topic in breast cancer.
Gene expression profile data of breast cancer from The Cancer Genome Atlas (TCGA) was downloaded. Scale-free gene co-expression networks were built with weighted gene co-expression network analysis. The correlation of genes was performed with Pearson's correlation values. The potential associations between clinical features and gene sets were studied, and the hub genes were screened out. Gene Ontology and gene set enrichment analysis were used to reveal the function of hub gene in breast cancer. The gene expression profiles of GSE15852, downloaded from the Gene Expression Omnibus database, were used for hub gene verification. In addition, candidate biomarkers expression in breast cancer was studied. Survival analysis was performed using Log rank test and Kaplan-Meier. Immunohistochemistry was used to analyze the expression of .
A total of 6 modules related to immune cell infiltration were identified via the average linkage hierarchical clustering. According to the threshold criteria (module membership >0.9 and gene significance >0.35), a significant module consisting of 13 genes associated with immune cells infiltration were identified as candidate hub genes after performed with the human protein interaction network. And 3 genes with high correlation to clinical traits were identified as hub genes, which were negatively associated with the overall survival. Among them, the expression of was increased in metastatic breast cancer compare with non-metastatic breast cancer, who underwent immunotherapy. Immunohistochemistry results showed that expression in carcinoma tissues was elevated compared with normal control.
identified as a potential immune therapy marker in breast cancer, which were first reported here and deserved further research.
乳腺癌是女性癌症相关死亡的主要原因,也是女性中最常见的恶性肿瘤。近年来,免疫抑制因子已成为一种新型癌症治疗方法。然而,目前尚无用于乳腺癌免疫治疗的有效生物标志物。因此,探索免疫相关生物标志物是当前乳腺癌研究的一个重要课题。
从癌症基因组图谱(TCGA)下载乳腺癌的基因表达谱数据。使用加权基因共表达网络分析构建无标度基因共表达网络。通过Pearson相关值进行基因相关性分析。研究临床特征与基因集之间的潜在关联,并筛选出枢纽基因。利用基因本体论和基因集富集分析来揭示枢纽基因在乳腺癌中的功能。从基因表达综合数据库下载的GSE15852基因表达谱用于枢纽基因验证。此外,研究了候选生物标志物在乳腺癌中的表达。使用对数秩检验和Kaplan-Meier进行生存分析。采用免疫组织化学分析……的表达。
通过平均连锁层次聚类共鉴定出6个与免疫细胞浸润相关的模块。根据阈值标准(模块成员关系>0.9且基因显著性>0.35),在与人类蛋白质相互作用网络进行分析后,一个由13个与免疫细胞浸润相关的基因组成的显著模块被鉴定为候选枢纽基因。并且鉴定出3个与临床特征高度相关的基因作为枢纽基因,它们与总生存期呈负相关。其中,与未发生转移且接受免疫治疗的乳腺癌相比,转移性乳腺癌中……的表达增加。免疫组织化学结果显示,癌组织中的……表达高于正常对照。
……被鉴定为乳腺癌潜在的免疫治疗标志物,本文首次报道,值得进一步研究。