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.
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.