A potential prognostic model based on miRNA expression profile in The Cancer Genome Atlas for bladder cancer patients.

IF 1.9 3区 生物学 Q2 BIOLOGY Journal of Biological Research-Thessaloniki Pub Date : 2020-05-19 eCollection Date: 2020-12-01 DOI:10.1186/s40709-020-00116-3
Yan Liu, Dong Yan Zhu, Hong Jian Xing, Yi Hou, Yan Sun
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引用次数: 4

Abstract

Background: This study aimed to construct prognostic model by screening prognostic miRNA signature of bladder cancer.

Methods: The miRNA expression profile data of bladder cancer (BC) in The Cancer Genome Atlas (TCGA) were obtained and randomly divided into the training set and the validation set. Differentially expressed miRNAs (DEMs) between BC and normal control samples in the training set were firstly identified, and DEMs related to prognosis were screened by Cox Regression analysis. Then, the MiR Score system was constructed using X-Tile based cutoff points and verified in the validation set. The prognostic clinical factors are selected out by univariate and multivariate Cox Regression analysis. Finally, the mRNAs related to prognosis were screened and the biological pathway analysis was carried out.

Results: We identified the 7-miRNA signature was significantly associated with the patient's Overall Survival (OS). A prognostic model was constructed based on the prognostic 7-miRNA signature, and possessed a relative satisfying predicted ability both in the training set and validation set. In addition, univariate and multivariate Cox Regression analysis showed that age, lymphovascular invasion and MiR Score were considered as independent prognostic factors in BC patients. Furthermore, based on MiR Score prognostic model, several differentially expressed genes (DEGs), such as WISP3 and UNC5C, as well as their related biological pathway(s), including cell-cell adhesion and neuroactive ligand-receptor interaction, were considered to be related to BC prognosis.

Conclusion: The prognostic model which was constructed based on the prognostic 7-miRNA signature presented a high predictive ability for BC.

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基于肿瘤基因组图谱中miRNA表达谱的膀胱癌患者潜在预后模型
背景:本研究旨在通过筛选膀胱癌预后miRNA特征构建预后模型。方法:获取cancer Genome Atlas (TCGA)中膀胱癌(BC) miRNA表达谱数据,随机分为训练集和验证集。首先在训练集中鉴定BC与正常对照样本的差异表达miRNAs (differential expression miRNAs, DEMs),并通过Cox回归分析筛选与预后相关的DEMs。然后,使用基于X-Tile的截止点构建MiR评分系统,并在验证集中进行验证。通过单因素和多因素Cox回归分析筛选出影响预后的临床因素。最后筛选与预后相关的mrna,并进行生物学通路分析。结果:我们发现7-miRNA特征与患者的总生存期(OS)显著相关。基于7-miRNA的预后特征构建预后模型,在训练集和验证集均具有较满意的预测能力。此外,单因素和多因素Cox回归分析显示,年龄、淋巴血管侵犯和MiR评分是BC患者预后的独立因素。此外,基于MiR Score预后模型,几种差异表达基因(DEGs),如WISP3和UNC5C,以及它们相关的生物学途径,包括细胞-细胞粘附和神经活性配体-受体相互作用,被认为与BC预后相关。结论:基于预后7-miRNA特征构建的预后模型对BC具有较高的预测能力。
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来源期刊
CiteScore
5.20
自引率
0.00%
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0
审稿时长
>12 weeks
期刊介绍: Journal of Biological Research-Thessaloniki is a peer-reviewed, open access, international journal that publishes articles providing novel insights into the major fields of biology. Topics covered in Journal of Biological Research-Thessaloniki include, but are not limited to: molecular biology, cytology, genetics, evolutionary biology, morphology, development and differentiation, taxonomy, bioinformatics, physiology, marine biology, behaviour, ecology and conservation.
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