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Abstract

Prognostic Value of a Novel Multi-mRNA Signature for Predicting Disease Progression of Hepatoblastoma

Author(s): BINGRUI WANG, QIUCHENG HAN, HAN GUO, XIAOYE QU, FANG WANG, QIANG XIA AND XIAONI KONG
Department of Liver Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 1Department of Liver Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 2Institute of Clinical Immunology, Department of Liver Diseases, Central Laboratory, ShuGuang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, 3Department of Ultrosound, Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China

Correspondence Address:
XIAONI KONG, Department of Liver Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China, E-mail: [email protected]


Hepatoblastoma is the most common tumor of liver in childhood. The onset of the disease is insidious, and the early stage is mostly asymptomatic. About 20 % of the children had distant metastasis at diagnosis. Only 50 %-60 % of the tumors can be completely resected by surgery, and the relapse percentage of children who undergo surgical treatment alone is still high. Therefore, the aim was to conduct a multimessenger RNA signature to improve hepatoblastoma progression prediction. Messenger RNA expression profiling of Gene Expression Ominus dataset (GSE131329) was analyzed in a large hepatoblastoma cohort and screened the significantly differential expressed Messenger RNAs between normal tissues and tumors. Weighted correlation network analysis was used to select genes that correlated to disease progression. Data fitting analysis was performed and three samples were removed from subsequent analyses in GSE131329. A total of 1263 differentially expressed genes were screened, consisting 569 up-regulated genes and 694 down-regulated genes. Gene ontology and Kyoto encyclopedia of genes and genomes pathway enrichment analyses were performed and by using weighted correlation network analysis, 8 hub genes were selected and an 8-messenger RNA-based signature was established that was significantly related to the disease progression of hepatoblastoma. Our results might provide an efficient clinical multiple-messenger RNA signature for predicting disease progression and be potentially efficient targets for hepatoblastoma patients.

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