Several microRNAs could predict survival in patients with hepatitis B-related liver cancer.
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.
Department of Tumor Molecular Biology, Nankai University School of Medicine, Tianjin 371000, China.|School of public health, Taishan Medical University, Tai'an 271016, China.|Department of Infectious Disease, Tai'an Central Hospital, Tai'an 271000, China.
Ye
Y
Zhen
Laboratory of Vaccine and Antibody Engineering, Beijing Institute of Biotechnology, Beijing 100071, China.
Zhao
Z
Xinghui
Department of Tumor Molecular Biology, Nankai University School of Medicine, Tianjin 371000, China.
Wu
W
Chao
Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100190, China.
Zhao
Z
Yi
Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100190, China.
Chen
C
Jinwen
Department of Tumor Molecular Biology, Nankai University School of Medicine, Tianjin 371000, China.
Gao
G
Ruifang
College of Information Science and Engineering, Shandong Agriculture University, Tai'an 271000, China.
Zhang
Z
Chao
Department of Infectious Disease, Tai'an Central Hospital, Tai'an 271000, China.
Zhao
Z
Min
Department of Tumor Molecular Biology, Nankai University School of Medicine, Tianjin 371000, China.
Guo
G
Chunlei
Department of Tumor Molecular Biology, Nankai University School of Medicine, Tianjin 371000, China.
Fang
F
Yan
Department of Tumor Molecular Biology, Nankai University School of Medicine, Tianjin 371000, China.
Du
D
Lingfang
Department of Tumor Molecular Biology, Nankai University School of Medicine, Tianjin 371000, China.
Shen
S
Long
Department of Tumor Molecular Biology, Nankai University School of Medicine, Tianjin 371000, China.
Shen
S
Wenzhi
Department of Tumor Molecular Biology, Nankai University School of Medicine, Tianjin 371000, China.
Luo
L
Xiaohe
Department of Tumor Molecular Biology, Nankai University School of Medicine, Tianjin 371000, China.|The 2011 Project Collaborative Innovation Center for Biological Therapy, Nankai University School of Medicine, Tianjin 371000, China.|The International Collaborative Laboratory for Biological Medicine of the Ministry of Education, Nankai University School of Medicine, Tianjin 371000, China.
Xiang
X
Rong
D014408:Biomarkers, Tumor / Q000378:metabolism*; D006528:Carcinoma, Hepatocellular / Q000235:genetics* / Q000473:pathology / Q000821:virology; D045744:Cell Line, Tumor; D005260:Female; D006509:Hepatitis B / Q000150:complications*; D006801:Humans; D008113:Liver Neoplasms / Q000235:genetics* / Q000473:pathology / Q000821:virology; D008297:Male; D035683:MicroRNAs / Q000235:genetics* / Q000378:metabolism; D008875:Middle Aged
D014408:Biomarkers, Tumor; D035683:MicroRNAs