Detail
Experiment ID:
EXP00117
Reference:
- Title: MicroRNA profile predicts recurrence after resection in patients with hepatocellular carcinoma within the Milan Criteria.
- Author: Sato F, Hatano E, Kitamura K, Myomoto A, Fujiwara T, Takizawa S, Tsuchiya S, Tsujimoto G, Uemoto S, Shimizu K
- Journal: PloS one.2011 Jan 27;6(1):e16435.doi:10.1371/journal.pone.0016435.
- Abstract: Hepatocellular carcinoma (HCC) is difficult to manage due to the high frequency of post-surgical recurrence. Early detection of the HCC recurrence after liver resection is important in making further therapeutic options, such as salvage liver transplantation. In this study, we utilized microRNA expression profiling to assess the risk of HCC recurrence after liver resection., We examined microRNA expression profiling in paired tumor and non-tumor liver tissues from 73 HCC patients who satisfied the Milan Criteria. We constructed prediction models of recurrence-free survival using the Cox proportional hazard model and principal component analysis. The prediction efficiency was assessed by the leave-one-out cross-validation method, and the time-averaged area under the ROC curve (ta-AUROC)., "The univariate Cox analysis identified 13 and 56 recurrence-related microRNAs in the tumor and non-tumor tissues, such as miR-96. The number of recurrence-related microRNAs was significantly larger in the non-tumor-derived microRNAs (N-miRs) than in the tumor-derived microRNAs (T-miRs, P<0.0001). The best ta-AUROC using the whole dataset, T-miRs, N-miRs, and clinicopathological dataset were 0.8281, 0.7530, 0.7152, and 0.6835, respectively. The recurrence-free survival curve of the low-risk group stratified by the best model was significantly better than that of the high-risk group (Log-rank: P = 0.00029). The T-miRs tend to predict early recurrence better than late recurrence, whereas N-miRs tend to predict late recurrence better (P<0.0001). This finding supports the concept of early recurrence by the dissemination of primary tumor cells and multicentric late recurrence by the field effect.", MicroRNA profiling can predict HCC recurrence in Milan criteria cases.
- PMID: 21298008
Expression Profile:
- Description:MicroRNA Profile Predicts Recurrence of Hepatocellular Carcinoma in Milan Criteria Cases with Mild Liver Cirrhosis
- Organism:Homo sapiens
- Source:GEO
- Source ID:GSE21362
- Platform: GPL10312
- Number of samples:146
- Overall design:We examined microRNA expression profiling in paired tumor and non-tumor liver tissues of 73 HCC patients with mild cirrhosis (Child-Pugh A/B) who satisfy Milan Criteria. We constructed prediction models of recurrence-free survival using Cox proportional hazard model and principal component analysis.
- Instrument:3D-Gene Human miRNA Oligo chip v12-1.00
Design and Sample:
- Cancer Type:hepatocellular carcinoma
- Cancer SubType:N/A
- Cell Line:N/A
- Experimental Design:cancer vs normal
- Case Sample:hepatocellular carcinoma
- Control Sample:normal liver
- Num of Case:73
- Num of Control:73
- Quantification Software:Limma
- Num of miRNAs:856
Identification:
- Num of Up:69
- Num of Down:68
Time Info:
- Create Time2016-03-14
- Update Time:2021-05-27
Status:
| miRNA ID | Cancer Type | Design | logFC | AveExpr | T value | P value | adj Pvalue | Status | Plot |
|---|