A Five-microRNA Signature for Survival Prognosis in Pancreatic Adenocarcinoma based on TCGA Data.
A Five-microRNA Signature for Survival Prognosis in Pancreatic Adenocarcinoma based on TCGA Data.
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基于 TCGA 数据的胰腺腺癌生存预测的五种 microRNA 特征
DOI:
10.1038/s41598-018-22493-5
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发表时间:
2018-05-16
影响因子:
4.6
通讯作者:
Qin RY
中科院分区:
文献类型:
--
作者:
Shi XH;Li X;Zhang H;He RZ;Zhao Y;Zhou M;Pan ST;Zhao CL;Feng YC;Wang M;Guo XJ;Qin RY
Novel biomarkers for pancreatic adenocarcinoma are urgently needed because of its poor prognosis. Here, by using The Cancer Genome Atlas (TCGA) RNA-seq data, we evaluated the prognostic values of the differentially expressed miRNAs and constructed a five-miRNA signature that could effectively predict patient overall survival (OS). The Kaplan-Meier overall survival curves of two groups based on the five miRNAs were notably different, showing overall survival in 10.2% and 47.8% at five years for patients in high-risk and low-risk groups, respectively. The ROC curve analysis achieved AUC of 0.775, showing good sensitivity and specificity of the five-miRNA signature model in predicting pancreatic adenocarcinoma patient survival risk. The functional enrichment analysis suggested that the target genes of the miRNA signature may be involved in various pathways related to cancer, including PI3K-Akt, TGF-β, and pluripotent stem cell signaling pathways. Finally, we analyzed expression of the five specific miRNAs in the miRNA signature, and validated the reliability of the results in 20 newly diagnosed pancreatic adenocarcinoma patients using qRT-PCR. The expression results of qRT-PCR were consistent with the TCGA results. Taken together, these findings suggested that the five-miRNA signature (hsa-miR-203, hsa-miR-424, hsa-miR-1266 hsa-miR-1293, and hsa-miR-4772) could be used as a prognostic marker for pancreatic adenocarcinoma.
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影响因子:
2.9
作者:
Eguchi, Hidetoshi;Ishikawa, Osamu;Nakagawa, Hidewaki
通讯作者:
Nakagawa, Hidewaki
影响因子:
--
作者:
Song, Bin;Zheng, Kailian;Jin, Gang
通讯作者:
Jin, Gang
影响因子:
14.9
作者:
Xie C;Mao X;Huang J;Ding Y;Wu J;Dong S;Kong L;Gao G;Li CY;Wei L
通讯作者:
Wei L
影响因子:
4
作者:
Luo, Wen;Wang, Lei;Wang, Xiu-Xin
通讯作者:
Wang, Xiu-Xin
影响因子:
14.8
作者:
Huang, Da Wei;Sherman, Brad T.;Lempicki, Richard A.
通讯作者:
Lempicki, Richard A.