Dataset Information

Identification of an RNA binding protein-related gene signature in hepatocellular carcinoma patients.

ABSTRACT:

Background

Hepatocellular carcinoma (HCC) is a common malignant primary cancer with high mortality. Previous studies have demonstrated that RNA binding proteins (RBPs) are involved in the biological processes of cancers, including hepatocellular cancer.

Methods

In this study, we aimed to identify the clinical value of RNA-binding proteins for hepatocellular carcinoma. We obtained gene expression and clinical data of hepatocellular carcinoma patients from the TCGA and ICGC databases. The prognostic value of RBP-related genes in patients with hepatocellular carcinoma and their function were studied by comprehensive bioinformatics analyses. The gene signature of SMG5, EZH2, FBLL1, ZNF239, and IGF2BP3 was generated by univariate and multivariate Cox regression and LASSO regression analyses. We built and verified a prognostic nomogram based on RBP-related genes. The gene signature was validated by the ICGC database. The expression of RBP-related genes was validated by the Oncomine database, the Human Protein Atlas and Kaplan-Meier plotter.

Result

Most RBP-related genes were significantly different in cancer and normal tissues. The survival of patients in the different groups was significantly different. The gene signature showed good performance for predicting the survival of HCC patients by having a better area under the receiver operating characteristic curve than other clinicopathological parameters.

Conclusion

Gene signatures based on RNA-binding proteins can be independent risk factors for hepatocellular carcinoma patients.

SUBMITTER: Wang L

PROVIDER: S-EPMC7727152 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Publications

Identification of an RNA binding protein-related gene signature in hepatocellular carcinoma patients.

Wang Li L Zhou Na N Qu Jialin J Jiang Man M Zhang Xiaochun X

Molecular medicine (Cambridge, Mass.) 20201209 1

<h4>Background</h4>Hepatocellular carcinoma (HCC) is a common malignant primary cancer with high mortality. Previous studies have demonstrated that RNA binding proteins (RBPs) are involved in the biological processes of cancers, including hepatocellular cancer.<h4>Methods</h4>In this study, we aimed to identify the clinical value of RNA-binding proteins for hepatocellular carcinoma. We obtained gene expression and clinical data of hepatocellular carcinoma patients from the TCGA and ICGC database ...[more]

PMID: 33297932

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Project description:Hepatocellular carcinoma (HCC) is a common type of liver cancer and one of the highly lethal diseases worldwide. Hypoxia plays an important role in the development and prognosis of HCC. This study aimed to construct a new hypoxia-related prognosis signature and investigate its potential ceRNA axes in HCC. RNA profiles and hypoxia genes were downloaded, respectively, from the Cancer Genome Atlas hepatocellular carcinoma database and Gene Set Enrichment Analysis website. Cox regression analyses were performed to select the prognostic genes and construct the risk model. The ENCORI database was applied to build the lncRNA-miRNA-mRNA prognosis-related network. The TIMER and CellMiner databases were employed to analyze the association of gene expression in ceRNA with immune infiltration and drug sensitivity, respectively. Finally, the co-expression analysis was carried out to construct the potential lncRNA/miRNA/mRNA regulatory axes. We obtained a prognostic signature including eight hypoxia genes (ENO2, KDELR3, PFKP, SLC2A1, PGF, PPFIA4, SAP30, and TKTL1) and further established a hypoxia-related prognostic ceRNA network including 17 lncRNAs, six miRNAs, and seven mRNAs for hepatocellular carcinoma. Then, the analysis of immune infiltration and drug sensitivity showed that gene expression in the ceRNA network was significantly correlated with the infiltration abundance of multiple immune cells, the expression level of immune checkpoints, and drug sensitivity. Finally, we identified three ceRNA regulatory axes (SNHG1/miR-101-3p/PPFIA4, SNHG1/miR-101-3p/SAP30, and SNHG1/miR-101-3p/TKTL1) associated with the progression of HCC under hypoxia. Here, we constructed a prognosis gene signature and a ceRNA network related to hypoxia for hepatocellular carcinoma. Among the ceRNA network, six highly expressed lncRNAs (AC005540.1, AC012146.1, AC073529.1, AC090772.3, AC138150.2, AL390728.6) and one highly expressed mRNA (PPFIA4) were the potential biomarkers of hepatocellular carcinoma which we firstly reported. The three predicted hypoxia-related regulatory axes may play a vital role in the progression of hepatocellular carcinoma.

Project description:Background: Hepatocellular carcinoma (HCC) is a typical inflammatory-related malignant tumor with complex immune tolerance microenvironment and poor prognosis. In this study, we aimed to construct a novel immune-related gene signature for the prognosis of HCC patients, exploring tumor microenvironment (TME) cell infiltration characterization and potential mechanisms. Methods: A total of 364 HCC samples with follow-up information in the TCGA-LIHC dataset were analyzed for the training of the prognostic signature. The Least Absolute Shrinkage and Selector Operation (LASSO) regression based on the IRGs was conducted to identify the prognostic genes and establish an immune risk signature. The immune cell infiltration in TME was estimated via the CIBERSORT method. Gene Set Variation Analysis (GSVA) was conducted to compare the biological pathways involved in the low-risk and high-risk groups. Furthermore, paraffin sections of HCC tissue microarrays containing 77 patients from Fudan University Shanghai Cancer Center were used for IHC staining. The clinical characteristics of the 77 HCC patients were collected and summarized for survival analysis validation via the Kaplan-Meier (KM) method. Results: Three-gene signature with close immune correlation (Risk score = EPO * 0.02838 + BIRC5 * 0.02477 + SPP1 * 0.0002044) was constructed eventually and proven to be an effective prognostic factor for HCC patients. The patients were divided into a high-risk and a low-risk group according to the optimal cutoff, and the survival analysis revealed that HCC samples with high-risk immuno-score had significantly poorer outcomes than the low-risk group (p < 0.0001). The results of CIBERSORT suggested that the immune cell activation was relatively higher in the low-risk group with better prognosis. Besides, GSVA analysis showed multiple signaling differences between the high- and low-risk group, indicating that the three-gene prognostic model can affect the prognosis of patients by affecting immune-related mechanisms. Tissue microarray (TMA) results further confirmed that the expression of three genes in HCC tissues was closely related to the prognosis of patients, respectively. Conclusion: In this study, we constructed and validated a robust three-gene signature with close immune correlation in HCC, which presented a reliable performance in the prediction of HCC patients' survival.

Dataset Information

Identification of an RNA binding protein-related gene signature in hepatocellular carcinoma patients.

Background

Methods

Result

Conclusion

Publications

Identification of an RNA binding protein-related gene signature in hepatocellular carcinoma patients.

Similar Datasets

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