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Prognostic Alternative mRNA Splicing Signature and a Novel Biomarker in Triple-Negative Breast Cancer

机译:预后替代mRNA剪接签名和三阴性乳腺癌中的新型生物标志物

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Triple-negative breast cancer (TNBC) is a high-risk subtype of breast cancer defined by negative expression of estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2. Accumulating evidence indicates that alternative splicing (AS) events are correlated with the prognosis of cancer. RNA sequencing data and AS event data were manually curated from The Cancer Genome Atlas (TCGA) dataset and TCGA Splice Seq, respectively. Univariate and multivariate Cox regression analyses were applied to screen AS events associated with TNBC survival and to establish a prognostic model. A receiver operating characteristic (ROC) curve was used to evaluate the performance of the prognostic model. Differentially expressed gene analysis and functional enrichment analysis were harnessed to reveal the functional role of gene sets and to screen novel biomarkers. By integrated bioinformatics analysis of AS events and gene expression in TNBC, our study is the first to generate specific AS event profiles, prognostic AS event interaction networks, and splice factor-AS interaction networks for TNBC. Surprisingly, we found that the performance of the AS-based prognostic model was encouraging with a mean area under the ROC curve of 0.957 at 2-10 years. We also found that chemokine (C-C motif) ligand 16 (CCL16) expression was correlated with TNBC grade and could be a potential novel biomarker. In conclusion, this study provided a systematic analysis of prognostic AS event profiles and gene expression in TNBC. A novel prognostic model based on AS events may establish a foundation for future research investigating the diagnosis and treatment of TNBC.
机译:三阴性乳腺癌(TNBC)是由雌激素受体,孕酮受体和人表皮生长因子受体的阴性表达定义的乳腺癌的高风险亚型2.积累证据表明替代剪接(AS)事件与之相关癌症预后。 RNA测序数据和事件数据分别从癌症基因组Atlas(TCGA)数据集和TCGA均衡SEQ手动策略。单变量和多变量的COX回归分析将筛选与TNBC存活相关的事件并建立预后模型。接收器操作特征(ROC)曲线用于评估预后模型的性能。利用差异表达的基因分析和功能性富集分析,揭示基因套和筛选新型生物标志物的功能作用。通过综合生物信息学分析作为TNBC中的事件和基因表达,我们的研究是第一个生成特定的事件谱,预后作为事件交互网络和剪接因子作为TNBC的交互网络。令人惊讶的是,我们发现,AS的预后模型的表现令人抱歉,在2-10年的ROC曲线下的平均面积为0.957。我们还发现趋化因子(C-C基序)配体16(CCL16)表达与TNBC等级相关,并且可以是潜在的新型生物标志物。总之,本研究提供了对TNBC中预后的预后和基因表达的系统分析。基于事件的新型预后模型可以为未来的研究确定研究TNBC的诊断和治疗来建立一个基础。

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