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. 2021 Jan 21:7:620765.
doi: 10.3389/fmolb.2020.620765. eCollection 2020.

Development and External Validation of a Novel Immune Checkpoint-Related Gene Signature for Prediction of Overall Survival in Hepatocellular Carcinoma

Affiliations

Development and External Validation of a Novel Immune Checkpoint-Related Gene Signature for Prediction of Overall Survival in Hepatocellular Carcinoma

Enfa Zhao et al. Front Mol Biosci. .

Abstract

Objective: The purpose of this study was to develop and validate a novel immune checkpoint-related gene signature for prediction of overall survival (OS) in hepatocellular carcinoma (HCC). Methods: mRNA expression profiles and clinical follow-up information were obtained in the International Cancer Genome Consortium database. An external dataset from The Cancer Genome Atlas (TCGA) Liver Hepatocellular Carcinoma database was used to validate the results. The univariate and multivariate Cox regression analyses were performed based on the differentially expressed genes. We generated a four-mRNA signature to predict patient survival. Furthermore, the reliability and validity were validated in TCGA cohort. An integrated bioinformatics approach was performed to evaluate its diagnostic and prognostic value. Results: A four-gene (epidermal growth factor, mutated in colorectal cancer, mitogen-activated protein kinase kinase 2, and NRAS proto-oncogene, GTPase) signature was built to classify patients into two risk groups using a risk score with different OS in two cohorts (all P < 0.0001). Multivariate regression analysis demonstrated the signature was an independent predictor of HCC. Furthermore, the signature presented an excellent diagnostic power in differentiating HCC and adjacent tissues. Immune cell infiltration analysis revealed that the signature was associated with a number of immune cell subtypes. Conclusion: We identified a four-immune checkpoint-related gene signature as a robust biomarker with great potential for clinical application in risk stratification and OS prediction in HCC patients and could be a potential indicator of immunotherapy in HCC. The diagnostic signature had been validated to accurately distinguish HCC from adjacent tissues.

Keywords: database; hepatocellular carcinoma; immune checkpoint; overall survival; signature.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Flowchart of the research procedure in this study.
Figure 2
Figure 2
Identification of the candidate immune checkpoint–related genes in the ICGC cohort. (A) The volcano plot of the differentially expressed genes between hepatocellular carcinoma and adjacent normal samples. (B) Univariate Cox regression analysis identifying prognostic variables with HR with 95% CI and P values. (C) Selecting the tuning parameters for the LASSO regression algorithm. (D) Forest plots illustrating the associations of identified four immune checkpoint–related genes with OS in the ICGC cohort.
Figure 3
Figure 3
Prognostic value of the four immune checkpoint–related gene signature for prediction of overall survival of patients with hepatocellular carcinoma in the ICGC cohort. (A) ROC curve analysis for predicting survival in HCC patients according to the risk score in the ICGC cohort. (B) From top to bottom are the risk score, patients' survival status distribution, and the expression heatmap of four prognostic immune checkpoint–related genes in the low- and high-risk groups in the ICGC cohort. (C) ROC curve analysis for predicting survival in HCC patients according to the risk score in the TCGA cohort. (D) From top to bottom are the risk score, patients' survival status distribution, and the expression heatmap of four prognostic immune checkpoint–related genes in the low- and high-risk groups in the TCGA cohort.
Figure 4
Figure 4
Validation of expression pattern of four identified genes (A, MAP2K2; B, NRAS; C, EGF, and D, MCC) in the TCGA cohort.
Figure 5
Figure 5
The diagnostic performance of signature in distinguishing HCC from normal samples. The ROC curves of single gene in the signature in the ICGC cohort (A) and the independent TCGA validation cohort (B); ROC curves of the diagnostic prediction model for the ICGC cohort (C) and TCGA validation cohort (D). ROC curves of the diagnostic prediction model for stage I patients with HCC in the ICGC cohort (E) and the TCGA cohort (F).
Figure 6
Figure 6
Distribution and visualization of immune cell infiltration in HCC patients. (A) Summary of estimated compositions of 22 immune cell subtypes from the CIBERSORT algorithm. (B) Comparison of 22 immune cell subtypes between low- and high-risk samples. Blue and red colors represent low- and high-risk samples, respectively.
Figure 7
Figure 7
Correlation between NRAS (A), MAP2K2 (B), MCC (C), EGF (D), and infiltrating immune cells in patients with HCC.

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References

    1. Aho K., Derryberry D., Peterson T. (2014). Model selection for ecologists: the worldviews of AIC and BIC. Ecology 95, 631–636. 10.1890/13-1452.1 - DOI - PubMed
    1. Ali H. R., Chlon L., Pharoah P. D., Markowetz F., Caldas C. (2016). Patterns of immune infiltration in breast cancer and their clinical implications: a gene-expression-based retrospective study. PLoS Med. 13:e1002194. 10.1371/journal.pmed.1002194 - DOI - PMC - PubMed
    1. Bray F., Ferlay J., Soerjomataram I., Siegel R. L., Torre L. A., Jemal A. (2018). Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. Cancer J. Clin. 68, 394–424. 10.3322/caac.21492 - DOI - PubMed
    1. Bruix J., Gores G. J., Mazzaferro V. (2014). Hepatocellular carcinoma: clinical frontiers and perspectives. Gut 63, 844–855. 10.1136/gutjnl-2013-306627 - DOI - PMC - PubMed
    1. Bruix J., Reig M., Sherman M. (2016). Evidence-based diagnosis, staging, and treatment of patients with hepatocellular carcinoma. Gastroenterology 150, 835–853. 10.1053/j.gastro.2015.12.041 - DOI - PubMed

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