Development and validation of a novel immune-related prognostic model in hepatocellular carcinoma

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Abstract

Background

Growing evidence has suggested that immune-related genes play crucial roles in the development and progression of hepatocellular carcinoma (HCC). Nevertheless, the utility of immune-related genes for evaluating the prognosis of HCC patients are still lacking. The study aimed to explore gene signatures and prognostic values of immune-related genes in HCC.

Methods

We comprehensively integrated gene expression data acquired from 374 HCC and 50 normal tissues in The Cancer Genome Atlas (TCGA). Differentially expressed genes (DEGs) analysis and univariate Cox regression analysis were performed to identify DEGs that related to overall survival. An immune prognostic model was constructed using the Lasso and multivariate Cox regression analyses. Furthermore, Cox regression analysis was applied to identify independent prognostic factors in HCC. The correlation analysis between immune-related signature and immune cells infiltration were also investigated. Finally, the signature was validated in an external independent dataset.

Results

A total of 329 differentially expressed immune‐related genes were detected. 64 immune‐related genes were identified to be markedly related to overall survival in HCC patients using univariate Cox regression analysis. Then we established a TF-mediated network for exploring the regulatory mechanisms of these genes. Lasso and multivariate Cox regression analyses were applied to construct the immune-based prognostic model, which consisted of nine immune‐related genes. Further analysis indicated that this immune-related prognostic model could be an independent prognostic indicator after adjusting to other clinical factors. The relationships between the risk score model and immune cell infiltration suggested that the nine-gene signature could reflect the status of tumor immune microenvironment. The prognostic value of this nine-gene prognostic model was further successfully validated in an independent database.

Conclusions

Together, our study screened potential prognostic immune-related genes and established a novel immune-based prognostic model of HCC, which not only provides new potential prognostic biomarkers and therapeutic targets, but also deepens our understanding of tumor immune microenvironment status and lays a theoretical foundation for immunotherapy.

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Most cited references 31

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Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal.

J. Gao, B. A. Aksoy, U Dogrusoz … (2015)

The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics.

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The Gene Ontology (GO) project in 2006

(2005)

The Gene Ontology (GO) project () develops and uses a set of structured, controlled vocabularies for community use in annotating genes, gene products and sequences (also see ). The GO Consortium continues to improve to the vocabulary content, reflecting the impact of several novel mechanisms of incorporating community input. A growing number of model organism databases and genome annotation groups contribute annotation sets using GO terms to GO's public repository. Updates to the AmiGO browser have improved access to contributed genome annotations. As the GO project continues to grow, the use of the GO vocabularies is becoming more varied as well as more widespread. The GO project provides an ontological annotation system that enables biologists to infer knowledge from large amounts of data.

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Prediction of venous metastases, recurrence, and prognosis in hepatocellular carcinoma based on a unique immune response signature of the liver microenvironment.

Anuradha Budhu, Marshonna Forgues, Qing-Hai Ye … (2006)

Hepatocellular carcinoma (HCC) is an aggressive malignancy mainly due to metastases or postsurgical recurrence. We postulate that metastases are influenced by the liver microenvironment. Here, we show that a unique inflammation/immune response-related signature is associated with noncancerous hepatic tissues from metastatic HCC patients. This signature is principally different from that of the tumor. A global Th1/Th2-like cytokine shift in the venous metastasis-associated liver microenvironment coincides with elevated expression of macrophage colony-stimulating factor (CSF1). Moreover, a refined 17 gene signature was validated as a superior predictor of HCC venous metastases in an independent cohort, when compared to other clinical prognostic parameters. We suggest that a predominant humoral cytokine profile occurs in the metastatic liver milieu and that a shift toward anti-inflammatory/immune-suppressive responses may promote HCC metastases.

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Author and article information

Contributors

Fengzhe Chen: cfzj2019@sdu.edu.cn

Lixian Ma:

ORCID: http://orcid.org/0000-0002-7904-3841

mlx_sdu@163.com

Journal

Journal ID (nlm-ta): J Transl Med

Journal ID (iso-abbrev): J Transl Med

Title: Journal of Translational Medicine

Publisher: BioMed Central (London )

ISSN (Electronic): 1479-5876

Publication date (Electronic): 11 February 2020

Publication date PMC-release: 11 February 2020

Publication date Collection: 2020

Volume: 18

Electronic Location Identifier: 67

Affiliations

[1 ]GRID grid.27255.37, ISNI 0000 0004 1761 1174, Department of Infectious Diseases, Qilu Hospital, , Shandong University, ; Wenhua Xi Road 107, Jinan, 250012 Shandong China

[2 ]GRID grid.452422.7, Department of Gastroenterology, Shandong Provincial Qianfoshan Hospital, , The First Hospital Affiliated With Shandong First Medical University, ; Jingshi Road 16766, Jinan, 250014 Shandong China

[3 ]Shandong Center for Disease Control and Prevention, Health Education Institute, Jinan, 250000 Shandong China

Author information

Lixian Ma http://orcid.org/0000-0002-7904-3841

Article

Publisher ID: 2255

DOI: 10.1186/s12967-020-02255-6

PMC ID: 7011553

PubMed ID: 32046766

SO-VID: 31af87d5-1bd4-4c96-bda2-341c8c780e77

License:

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 29 November 2019

Date accepted : 1 February 2020

Funding

Funded by: Cultivating fund for Chinese National Natural Science Foundation of Shandong Provincial Qianfoshan Hospital

Award ID: QYPY2019NSFC0803

Award Recipient : Changhong Liu

Custom metadata

ScienceOpen disciplines: Medicine

Keywords: hepatocellular carcinoma,immune related gene,prognosis,prognostic signature,bioinformatics

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ScienceOpen disciplines: Medicine

Keywords: hepatocellular carcinoma, immune related gene, prognosis, prognostic signature, bioinformatics

Development and validation of a novel immune-related prognostic model in hepatocellular carcinoma

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Abstract

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Karger: Oncology

Most cited references 31

Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal.

The Gene Ontology (GO) project in 2006

Prediction of venous metastases, recurrence, and prognosis in hepatocellular carcinoma based on a unique immune response signature of the liver microenvironment.

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