乳腺癌
肿瘤科
三阴性乳腺癌
医学
内科学
长非编码RNA
多元分析
癌症
单变量分析
单变量
核糖核酸
多元统计
生物
基因
统计
生物化学
数学
作者
Ting Zhu,Junjun Wang,Juan Li,Qichao Zhang,Yanyan Shang,Jiaju Zhou,Liu M,Bo Lv,Kai Luo
标识
DOI:10.1016/j.cca.2023.117535
摘要
Breast cancer is the leading causes of cancer-associated mortality among women, and triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer. Long non-coding RNAs (LncRNAs) have recently been studied to predict the prognosis of various cancers, but whether it is an effective marker in TNBC is inconclusive. We used RNA-sequencing analysis to identify differentially expressed exosomal LncRNAs, and qRT-PCR assay was performed to verify dysregulated LncRNAs in multicenter validation cohorts. A signature, which was composed of LINC00989, CEA, and CA153, was then utilized to predict the progression and recurrence of TNBC. Kaplan-Meier analysis was applied to evaluate the prognostic values of the signature. On the basis of RNA-sequencing analysis, we found that serum exosomal LncRNA LINC00989 was significantly up-regulated in metastatic patients of TNBC. Then LINC00989, together with clinic marker CEA and CA125, were selected to construct a prognostic signature. In both training and validation cohort, higher levels of this signature were significantly related with shorter overall and progression-free survival time. Univariate and multivariate analysis shown that the signature was the independent prognosis factor of TNBC patients. Our results suggested that this prognostic signature might potentially predict prognosis and recurrence of TNBC, and was worth validation in future clinical trials.
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