乳腺癌患者中与总生存期相关的五基因特征的鉴定与验证
Identification and Validation of a Five-Gene Signature Associated With Overall Survival in Breast Cancer Patients.
作者信息
Wang Xiaolong, Li Chen, Chen Tong, Li Wenhao, Zhang Hanwen, Zhang Dong, Liu Ying, Han Dianwen, Li Yaming, Li Zheng, Luo Dan, Zhang Ning, Yang Qifeng
机构信息
Department of Breast Surgery, Qilu Hospital of Shandong University, Jinan, China.
Department of Pathology Tissue Bank, Qilu Hospital of Shandong University, Jinan, China.
出版信息
Front Oncol. 2021 Aug 26;11:660242. doi: 10.3389/fonc.2021.660242. eCollection 2021.
BACKGROUND
Recent years, the global prevalence of breast cancer (BC) was still high and the underlying molecular mechanisms remained largely unknown. The investigation of prognosis-related biomarkers had become an urgent demand.
RESULTS
In this study, gene expression profiles and clinical information of breast cancer patients were downloaded from the TCGA database. The differentially expressed genes (DEGs) were estimated by Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. A risk score formula involving five novel prognostic associated biomarkers (EDN2, CLEC3B, SV2C, WT1, and MUC2) were then constructed by LASSO. The prognostic value of the risk model was further confirmed in the TCGA entire cohort and an independent external validation cohort. To explore the biological functions of the selected genes, assays were performed, indicating that these novel biomarkers could markedly influence breast cancer progression.
CONCLUSIONS
We established a predictive five-gene signature, which could be helpful for a personalized management in breast cancer patients.
背景
近年来，全球乳腺癌（BC）患病率仍然很高，其潜在分子机制在很大程度上仍不清楚。对预后相关生物标志物的研究已成为迫切需求。
结果
在本研究中，从TCGA数据库下载了乳腺癌患者的基因表达谱和临床信息。通过基因本体论（GO）分析和京都基因与基因组百科全书（KEGG）分析来估计差异表达基因（DEG）。然后通过LASSO构建了一个包含五个新的预后相关生物标志物（内皮素2、C型凝集素结构域家族3成员B、囊泡相关膜蛋白2C、威尔姆斯瘤1和黏蛋白2）的风险评分公式。风险模型的预后价值在TCGA整个队列和一个独立的外部验证队列中得到进一步证实。为了探索所选基因的生物学功能，进行了相关实验，表明这些新生物标志物可显著影响乳腺癌进展。
结论
我们建立了一个预测性的五基因特征，这可能有助于对乳腺癌患者进行个性化管理。
Zotero 插件