Dataset Information

A novel immune-related genes prognosis biomarker for hepatocellular carcinoma.

ABSTRACT:

Background

Hepatocellular carcinoma (HCC) is closely associated with the immune microenvironment. To identify the effective population before administering treatment, the establishment of prognostic immune biomarkers is crucial for early HCC diagnosis and treatment.

Results

A total of 335 IRGs identified from 788 overlapping IRGs were associated with the survival of HCC. A prognostic immunoscore model was identified. The Kaplan-Meier survival curves and time-dependent ROC analysis revealed a powerful prognostic performance of immunoscore signature via multi validation. Besides, the immunoscore signature exhibited a better predictive power compared to other prognostic signatures. Gene set enrichment analysis showed multiple signaling differences between the high and low immunoscore group. Furthermore, immunoscore was significantly associated with multiple immune cells and immune infiltration in the tumor microenvironment.

Conclusions

We identified the immunoscore as a robust marker for predicting HCC patient survival.

Methods

Three sets of immune-related genes (IRGs) were integrated to identify the overlapping IRGs. Weighted gene co-expression network analysis was performed to obtain the survival-related IRGs. Further, the prognostic immunoscore model was constructed via LASSO-penalized Cox regression analysis. Then the prognostic performance of immunoscore was evaluated. In addition, ESTIMATE and CIBERSORT algorithms were applied to explore the relationship between immunoscore and tumor immune microenvironment.

SUBMITTER: Wang K

PROVIDER: S-EPMC7834986 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A novel immune-related genes prognosis biomarker for hepatocellular carcinoma.

Wang Kunpeng K Chen Xinyi X Jin Chong C Mo Jinggang J Jiang Hao H Yi Bin B Chen Xiang X

Aging 20201126 1

<h4>Background</h4>Hepatocellular carcinoma (HCC) is closely associated with the immune microenvironment. To identify the effective population before administering treatment, the establishment of prognostic immune biomarkers is crucial for early HCC diagnosis and treatment.<h4>Results</h4>A total of 335 IRGs identified from 788 overlapping IRGs were associated with the survival of HCC. A prognostic immunoscore model was identified. The Kaplan-Meier survival curves and time-dependent ROC analysis ...[more]

PMID: 33260154

Similar Datasets

Project description:Hepatocellular carcinoma is a common malignant tumor with poor prognosis, poor treatment effect, and lack of effective biomarkers. In this study, bioinformatics analysis of immune-related genes of hepatocellular carcinoma was used to construct a multi-gene combined marker that can predict the prognosis of patients. The RNA expression data of hepatocellular carcinoma were downloaded from The Cancer Genome Atlas (TCGA) database, and immune-related genes were obtained from the IMMPORT database. Differential analysis was performed by Wilcox test to obtain differentially expressed genes. Univariate Cox regression analysis, lasso regression analysis and multivariate Cox regression analysis were performed to establish a prognostic model of immune genes, a total of 5 genes (HDAC1, BIRC5, SPP1, STC2, NR6A1) were identified to construct the models. The expression levels of 5 genes in HCC tissues were significantly different from those in paracancerous tissues. The Kaplan-Meier survival curve showed that the risk score calculated according to the prognostic model was significantly related to the overall survival (OS) of HCC. The receiver operating characteristic (ROC) curve confirmed that the prognostic model had high accuracy. Independent prognostic analysis was performed to prove that the risk value can be used as an independent prognostic factor. Then, the gene expression data of hepatocellular carcinoma in the ICGC database was used as a validation data set for the verification of the above steps. In addition, we used the CIBERSORT software and TIMER database to conduct immune infiltration research, and the results showed that the five genes of the model and the risk score have a certain correlation with the content of immune cells. Moreover, through Gene Set Enrichment Analysis (GSEA) and the construction of protein interaction networks, we found that the p53-mediated signal transduction pathway is a potentially important signal pathway for hepatocellular carcinoma and is positively regulated by certain genes in the prognostic model. In conclusion, this study provides potential targets for predicting the prognosis and treatment of hepatocellular carcinoma patients, and also provides new ideas about the correlation between immune genes and potential pathways of hepatocellular carcinoma.

Dataset Information

A novel immune-related genes prognosis biomarker for hepatocellular carcinoma.

Background

Results

Conclusions

Methods

Publications

A novel immune-related genes prognosis biomarker for hepatocellular carcinoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets