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Development and Validation of an RNA Binding Protein- Associated Prognostic Model for Hepatocellular Carcinoma

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Development and Validation of an RNA Binding Protein- Associated Prognostic Model for Hepatocellular Carcinoma Journal of Clinical and Translational Hepatology 2021 DOI: 10.14218/JCTH.2020.00103 Original Article Development and Validation of an RNA Binding Protein- associated Prognostic Model for Hepatocellular Carcinoma Hao Zhang , Peng Xia, Weijie Ma and Yufeng Yuan* Department of Hepatobiliary and Pancreatic Surgery, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China Received: 7 November 2020 | Revised: 24 February 2021 | Accepted: 26 March 2021 | Published: 13 April 2021 Abstract ated prognostic model for hepatocellular carcinoma. J Clin Transl Hepatol 2021. doi: 10.14218/JCTH.2020.00103. Background and Aims: The survival rate of patients with hepatocellular carcinoma is variable. The abnormal expres- sion of RNA-binding proteins (RBPs) is closely related to the occurrence and development of malignant tumors. The pri- Introduction mary aim of this study was to identify RBPs related to the prognosis of liver cancer and to construct a prognostic model Worldwide, liver cancer is the fourth leading cause of can- of liver cancer. Methods: We downloaded the hepatocellular cer-related deaths and has the sixth highest incidence.1 carcinoma gene sequencing data from The Cancer Genome It is estimated that 840,000 new cases of liver cancer are Atlas (cancergenome.nih.gov/) database, constructed a diagnosed and at least 780,000 people die of liver cancer protein-protein interaction network, and used Cytoscape to every year, with China accounting for 47% of the total num- realize the visualization. From among 325 abnormally ex- ber of liver cancer cases as well as the related mortality.2,3 pressed genes for RBPs, 9 (XPO5, enhancer of zeste 2 poly- Hepatocellular carcinoma (HCC) is the predominant type of comb repressive complex 2 subunit [EZH2], CSTF2, BRCA1, primary liver cancer, accounting for approximately 90% of RRP12, MRPL54, EIF2AK4, PPARGC1A, and SEPSECS) were all liver cancer cases.4 Although great progress has been selected for construction of the prognostic model. Then, made in the diagnosis and treatment of liver cancer, the we further verified the results through the Gene Expres- 5-year survival rate of patients with advanced liver cancer sion Omnibus (www.ncbi.nlm.nih.gov/geo/) database and is still less than 20%.5 In China, liver cancer ranks third in in vitro experiments. Results: A prognostic model was con- cancer-related mortality due to the large number of liver structed, which determined that the survival time of patients cancer patients, delayed diagnosis, and limited treatment in the high-risk group was significantly shorter than that options.6 Therefore, it is important to study the molecular of the low-risk group (p<0.01). Univariate and multivari- mechanism of tumorigenesis and development, to find new ate Cox regression analysis suggested that the risk score targets of drug therapy, to identify new tumor markers, and was an independent prognostic factor (p<0.01). We also to achieve an earlier diagnosis of liver cancer. constructed a nomogram based on the risk score, survival RNA-binding proteins (RBPs) are a group of proteins as- time, and survival status. At the same time, we verified the sociated with RNA regulation and metabolism. Their main high expression and cancer-promoting effects of EZH2 in role is to mediate the maturation, transport, localization tumors. Conclusions: Survival, receiver operating charac- and translation of RNA, and their abnormal expression can teristic curve and independent prognostic analyses demon- cause a variety of diseases. At present, there are approxi- strated that we constructed a good prognostic model, which mately 1,542 known human RBPs, accounting for approxi- might be useful for estimating the survival of patients with mately 7.5% of all protein-coding genes. It is now clear that hepatocellular carcinoma. RBPs are dysregulated in different types of cancer, affect- Citation of this article: Zhang H, Xia P, Ma W, Yuan Y. De- ing the expression and function of oncoproteins and tumor velopment and validation of an RNA binding protein-associ- suppressors. For example, IGF-II mRNA-binding proteins (IMPs) are involved in the progression of tumors and the establishment and maintenance of tumor cell hierarchies.7 Keywords: Hepatocellular carcinoma; RNA binding protein; Prognostic model; Therefore, studying the complex interaction network be- Nomogram. tween RBPs and their cancer-related RNA targets will help Abbreviations: AUC, area under the curve; BP, biological processes; CC, cel- in understanding the molecular mechanisms of RBPs in can- lular components; DERs, differentially-expressed RBPs; EZH2, enhancer of zeste 2 polycomb repressive complex 2 subunit; FC, fold-change; FDR, false cer progression, and may also enable the discovery of new discovery rate; GEO, Gene Expression Omnibus (www.ncbi.nlm.nih.gov/geo/); cancer treatment targets. Although RBPs are known to be GO, gene ontology; HCC, hepatocellular carcinoma; ICC, intrahepatic cholan- involved in the occurrence and development of a variety of giocarcinoma; KEGG, Kyoto Encyclopedia of Genes and Genomes; MF, molecular tumors, we still know very little about the molecular mecha- functions; PI, propidium Iodide; PPI, protein-protein interactions network; qRT- PCR, quantitative real-time PCR; RBPs, RNA-binding proteins; ROC, receiver nism of RBPs in tumor progression. operating characteristic; si, small interfering; TCGA, The Cancer Genome Atlas Because there are few studies on the role of RBPs in the (cancergenome.nih.gov/). occurrence and development of liver cancer, we designed * Correspondence to: Yufeng Yuan, Department of Hepatobiliary and Pancre- this study to screen-out RBPs related to the prognosis of pa- atic Surgery, Zhongnan Hospital of Wuhan University, Donghu Road 169#, Wu- han, Hubei 430071, China. ORCID: https://orcid.org/0000-0003-3924-3803. tients. We aimed to construct a predictive model that would E-mail: [email protected] be able to provide some help to clinical work and direction Copyright: © 2021 The Author(s). This article has been published under the terms of Creative Commons Attribution-Noncommercial 4.0 International License (CC BY-NC 4.0), which permits noncommercial unrestricted use, distribution, and reproduction in any medium, provided that the following statement is provided. “This article has been published in Journal of Clinical and Translational Hepatology at https://doi.org/10.14218/JCTH.2020.00103 and can also be viewed on the Journal’s website at http://www.jcthnet.com ”. Zhang H. et al: RNA binding protein-associated model for future research, including of molecular mechanisms and out nine RBPs. A prognostic model was constructed based the identification of molecular targets for treatment. on the relationship between the expression levels of these nine RBPs and the patients’ outcomes in the training group. The risk score of the HCC patients in the test group was cal- Methods culated according to the prognostic model, and the patients in the test group were divided into high-risk and low-risk groups according to the risk scores. Then, we used survival Clinical data and RNA sequencing data of the patients curves, receiver operating characteristic (ROC) curves, risk curves and independent prognostic analysis to test the pre- We downloaded the RNA high-throughput sequencing data dictive power of the prognostic model. In addition, we still from The Cancer Genome Atlas (cancergenome.nih.gov/; used the data GSE76427 in the Gene Expression Omnibus TCGA) database, including 374 tumor tissue samples and 50 (GEO) database to verify our model externally. normal liver tissue samples (www.cancer.gov/about-nci/or- ganization/ccg/research/structural-genomics/tcga). We also downloaded the clinical data of 377 HCC patients from the Construction of the nomogram TCGA. After excluding six patients with incomplete data, a total of three hundred and seventy-one patients were finally The coefficients obtained by the Cox regression model were included in the study, with each having data on follow-up used to construct the nomogram of overall survival. To con- time, survival status, disease stage, etc. The RNA high- struct the nomogram, we first determined a scale axis of throughput sequencing data included the expression data 0–100 to represent the score (in order to make the ex- of 60,483 genes, and we extracted the expression levels of pression of the RBPs correspond to the scores on the scale 1,473 RBPs from such. As this research did not involve hu- axis) and we calculated the score of each RBP. We added man participants, no research ethics review was necessary. the scores of each RBP to obtain the total score. Based on the correspondence between the total score axis and the survival rate, the 1-, 2-, 3- and 5-year survival rates of the Identification of the differentially-expressed RBPs patients could be predicted. (DERs) in HCC patients We used R software to analyze expression of the extracted Cell culture, RNA isolation and quantitative real-time 1,473 RBPs. A total of 325 RBPs showed expression differ- PCR (qRT-PCR) analysis ences between the tumor tissues and normal tissues, in- cluding 203 up-regulated and 122 down-regulated DERs. Because the risk ratio of enhancer of zeste 2 polycomb re- The threshold for the DERs was set as |log fold-change pressive complex 2 subunit (EZH2) is greater and the co- (FC)|>1 and false discovery rate (FDR) <0.05. efficient in the risk score calculation formula is greater, we choose EZH2 for further verification. A total of 20 HCC patient samples and paired non-tumor liver tissue samples were col- Enrichment analysis and protein-protein interaction lected from the patients hospitalized at the Zhongnan Hos- (PPI) network of the DERs pital, Wuhan University (Hubei Province, China). All patients provided written informed consent to the use of tissues for We divided the DERs into an up-regulated group and a scientific research in the Department of Hepatobiliary and down-regulated group, and then performed gene ontology Pancreatic Surgery.
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