Several microRNAs could predict survival in patients with hepatitis B-related liver cancer - PubMed (original) (raw)

Ye Zhen 1 2 3, Wu Chao 1, Zhao Yi 5, Chen Jinwen 5, Gao Ruifang 1, Zhang Chao 6, Zhao Min 3, Guo Chunlei 1, Fang Yan 1, Du Lingfang 1, Shen Long 1, Shen Wenzhi 1, Luo Xiaohe 1, Xiang Rong 1 7 8

Affiliations

Ye Zhen et al. Sci Rep. 2017.

Abstract

MicroRNAs as biomarkers play an important role in the tumorigenesis process, including hepatocellular carcinomas (HCCs). In this paper, we used The Cancer Genome Atlas (TCGA) database to mine hepatitis B-related liver cancer microRNAs that could predict survival in patients with hepatitis B-related liver cancer. There were 93 cases of HBV-HCC and 49 cases of adjacent normal controls included in the study. Kaplan-Meier survival analysis of a liver cancer group versus a normal control group of differentially expressed genes identified eight genes with statistical significance. Compared with the normal liver cell line, hepatocellular carcinoma cell lines had high expression of 8 microRNAs, albeit at different levels. A Cox proportional hazards regression model for multivariate analysis showed that four genes had a significant difference. We established classification models to distinguish short survival time and long survival time of liver cancers. Eight genes (mir9-3, mir10b, mir31, mir519c, mir522, mir3660, mir4784, and mir6883) were identified could predict survival in patients with HBV-HCC. There was a significant correlation between mir10b and mir31 and clinical stages (p < 0.05). A random forests model effectively estimated patient survival times.

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Conflict of interest statement

The authors declare no competing financial interests.

Figures

Figure 1

Figure 1. Heat map comparing the liver cancer group with the normal control group.

Figure 2

Figure 2

(a) Kaplan-Meier survival analysis indicating that low expression of mir9-3 is superior to high expression, p < 0.05. (b) ROC curve of eight genes for use in the distinguish G3 and G4 of liver cancer patients.

Figure 3

Figure 3. The relative expression levels of 8 microRNAs in normal cell lines compared with liver cancer cell lines.

Figure 4

Figure 4. Decision tree model classified G3 and G4.

Figure 5

Figure 5. Adaboost model classified G3 and G4.

The importance of gene sequencing.

Figure 6

Figure 6. Random forests model classified G3 and G4.

The importance of gene sequencing.

References

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