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Construction of a ceRNA network and a genomic-clinicopathologic nomogram to predict survival for HBV-related HCC

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Abstract

Some lncRNA-associated competing endogenous RNAs (ceRNAs) are considered as potential biomarkers for targeted therapies and prognosis in human cancer. In our present study, we aimed to construct a ceRNA network and establish a genomic-clinicopathologic nomogram to provide insights into the molecular mechanisms and predict survival for HBV-related HCC. The Cancer Genome Atlas (TCGA) database was applied to collect the data of LIHC RNA-seq dataset and miRNA-seq dataset as well as the clinicopathological information. Identification of differentially expressed RNAs (mRNAs, lncRNAs, and miRNAs) between HBV-related HCC samples and normal samples was conducted using Limma package in R. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) was used for performing the functional enrichment analysis of differentially expressed mRNAs. The ceRNA network was carried out using Cytoscape. The LASSO-penalized Cox regression analysis was implemented to identify HCC-related lncRNAs, and the multivariate Cox regression analysis was conducted for the establishment of a genomic-clinicopathology nomogram. A total of 1859 DEmRNAs, 113 DElncRNAs, and 89 DEmiRNAs were screened out etween HBV-related HCC samples and normal samples. A ceRNA network including 44 DEmRNAs, 7 DElncRNAs, and 20 DEmiRNAs was constructed. 7 DElncRNAs (PVT1, LINC01138, LINC02499, AL355488.2, FGF14-AS2, MAFG-AS1 and LINC00261) were finally identified as prognostic indicators. The area under the curve reached 0.8169 for the 7-lncRNA signature. The predictive accuracy and clinical application value were remarkably high for the genomic-clinicopathologic nomogram integrating the histological grade and the 7-gene-based prognostic index. Taken together, we have established a ceRNA network with HBV-related HCC-specific DElncRNAs, DEmiRNAs, and DEmRNAs. Furthermore, the genome-wide data of lncRNA expression were analyzed using the TCGA database, and a 7-lncRNA signature was identified as a potential prognostic predictor for HBV-related HCC patients. Novel functional studies were provided by our current findings for elucidating the molecular mechanism of lncRNA in HBV-related HCC.

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Data availability statement

All the data supporting the conclusions of this article are included in the article and its supplementary information files.

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Acknowledgements

Thanks for all the help from my tutors and friends.

Funding

Support for this study was provided by the Fundamental Research Funds for the Central Universities (No.2042020kf0155), and the Medical Science Advancement Program (Clinical Medicine) of Wuhan University (No. TFLC2018003).

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Author notes

  1. Kang Huang and Zhongshan Lu contributed equally to this work.

Authors and Affiliations

  1. Zhongnan Hospital of Wuhan University, Institute of Hepatobiliary Diseases of Wuhan University, Transplant Center of Wuhan University, National Quality Control Center for Donated Organ Procurement, Hubei Key Laboratory of Medical Technology on Transplantation, Hubei Clinical Research Center for Natural Polymer Biological Liver, Hubei Engineering Center of Natural Polymer-based Medical Materials, Wuhan, 430071, Hubei, China

    Kang Huang, Zhongshan Lu, Ling Li, Guizhu Peng, Wei Zhou & Qifa Ye

  2. The 3rd Xiangya Hospital of Central South University, Research Center of National Health Ministry on Transplantation Medicine Engineering and Technology, Changsha, 410013, Hunan, China

    Qifa Ye

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  1. Kang Huang
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  3. Ling Li
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Correspondence to Wei Zhou or Qifa Ye.

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Human ethics

We comply with National Medical Products Administration/Good Clinical Practice (NMPA/GCP) Principle and Helsinki Declaration. And this study was approved from the Medical Ethics Committee of Zhongnan Hospital of Wuhan University (Numbers: 2020178).

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Huang, K., Lu, Z., Li, L. et al. Construction of a ceRNA network and a genomic-clinicopathologic nomogram to predict survival for HBV-related HCC. Human Cell 34, 1830–1842 (2021). https://doi.org/10.1007/s13577-021-00607-y

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  • DOI: https://doi.org/10.1007/s13577-021-00607-y

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