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Prediction of hepatocellular carcinoma prognosis based on expression of an immune-related gene set.

ABSTRACT: Hepatocellular carcinoma (HCC) is a common type of malignant tumor with an extremely poor prognosis. Because many HCC patients are diagnosed with advanced disease, surgical treatment is typically not possible, and other currently available treatments are often ineffective. Immunotherapy is being explored as a new treatment method for a variety of cancers, including HCC. However, there have been no systematic reports about the relationship between immune-related genes and HCC patient prognosis. In this study, we established and verified a gene set-based model to examine the relationship between immune-related genes and prognosis in HCC patients. The model was based on a dataset from The Cancer Genome Atlas (TCGA), and its stability and reliability was confirmed in four verification datasets. In addition, we performed multivariate Cox regression analyses to identify the independent risk factors affecting HCC patient prognoses. We found that this new model based on immune-related genes was effective for predicting prognosis, evaluating disease state, and identifying treatment options for HCC patients.

SUBMITTER: He Y

PROVIDER: S-EPMC6977696 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Prediction of hepatocellular carcinoma prognosis based on expression of an immune-related gene set.

He Yuting Y Dang Qin Q Li Jie J Zhang Qiyao Q Yu Xiao X Xue Miaomiao M Guo Wenzhi W

Aging 20200112 1

Hepatocellular carcinoma (HCC) is a common type of malignant tumor with an extremely poor prognosis. Because many HCC patients are diagnosed with advanced disease, surgical treatment is typically not possible, and other currently available treatments are often ineffective. Immunotherapy is being explored as a new treatment method for a variety of cancers, including HCC. However, there have been no systematic reports about the relationship between immune-related genes and HCC patient prognosis. I ...[more]

PMID: 31929113

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Project description:Immune checkpoint genes (ICGs), the foundation of immunotherapy, are involved in the incidence and progression of hepatocellular carcinoma (HCC). Cuproptosis is characterized by copper-induced cell death, and this novel cell death pathway has piqued the interest of researchers in recent years. It is worth noting that there is little information available in the literature to determine the relationship between cuproptosis and anti-tumor immunity. We identified 39 cuproptosis-related ICGs using ICGs co-expressed with cuproptosis-related genes. A prognostic risk signature was constructed using the Cox regression and the least absolute shrinkage and selection operator analysis methods. The signature was built using the Cancer Genome Atlas (TCGA)-Liver Hepatocellular Carcinoma database. The TCGA and International Cancer Genome Consortium cohorts were classified into two groups; the low- and high-risk groups were determined using a prognostic signature comprised of five genes. The multivariate Cox regression analysis revealed that the signature could independently predict overall survival. Furthermore, the level of immune infiltration analysis revealed the robustness of the prognostic signature-immune cell infiltration relationship observed for Tregs, macrophages, helper T cells, and naive B cells. Both groups showed significant differences in immune checkpoint expression levels. The gene enrichment analysis was used for characterization, and the results revealed that enriching various pathways such as PI3K-AKT-mTOR signaling, glycolysis, Wnt/beta-catenin signaling, and unfolded protein response could potentially influence the prognosis of patients with HCC and the level of immune infiltration. The sensitivity of the two groups of patients to various drug-targeted therapy methods and immunotherapy was analyzed. In conclusion, the findings presented here lay the foundation for developing individualized treatment methods for HCC patients. The findings also revealed that studying the cuproptosis-based pathway can aid in the prognosis of HCC patients. It is also possible that cuproptosis contributes to developing anti-tumor immunity in patients.

Project description:BackgroundAn immune-related gene signature (IGS) was established for discriminating prognosis, predicting benefit of immunotherapy, and exploring therapeutic options in hepatocellular carcinoma (HCC).MethodsBased on Immune-related hub genes and The Cancer Genome Atlas (TCGA) LIHC dataset (n = 363), an immune-related gene signature (IGS) was established by least absolute shrinkage and selection operator (LASSO) analysis. The prognostic significance and clinical implications of IGS were verified in International Cancer Genome Consortium (ICGC) and Chinese HCC (CHCC) cohorts. The molecular and immune characteristics and the benefit of immune checkpoint inhibitor (ICI) therapy in IGS-defined subgroups were analyzed. In addition, by leveraging the Cancer Therapeutics Response Portal (CTRP) and PRISM Repurposing datasets, we determined the potential therapeutic agents for high IGS-risk patients.ResultsThe IGS was constructed based on 8 immune-related hub genes with individual coefficients. The IGS risk model could robustly predict the survival of HCC patients in TCGA, ICGC, and CHCC cohorts. Compared with 4 previous established immune genes-based signatures, IGS exhibited superior performance in survival prediction. Additionally, for immunological characteristics and enriched pathways, a low-IGS score was correlated with IL-6/JAK/STAT3 signaling, inflammatory response and interferon α/γ response pathways, low TP53 mutation rate, high infiltration level, and more benefit from ICI therapy. In contrast, high IGS score manifested an immunosuppressive microenvironment and activated aggressive pathways. Finally, by in silico screening potential compounds, vindesine, ispinesib and dasatinib were identified as potential therapeutic agents for high-IGS risk patients.ConclusionsThis study developed a robust IGS model for survival prediction of HCC patients, providing new insights into integrating tailored risk stratification with precise immunotherapy and screening potentially targeted agents.

Project description:BackgroundHepatocellular carcinoma (HCC) is a global health burden with poor prognosis. Anoikis, a novel programmed cell death, has a close interaction with metastasis and progression of cancer. In this study, we aimed to construct a novel bioinformatics model for evaluating the prognosis of HCC based on anoikis-related gene signatures as well as exploring the potential mechanisms.Materials and methodsWe downloaded the RNA expression profiles and clinical data of liver hepatocellular carcinoma from TCGA database, ICGC database and GEO database. DEG analysis was performed using TCGA and verified in the GEO database. The anoikis-related risk score was developed via univariate Cox regression, LASSO Cox regression and multivariate Cox regression, which was then used to categorize patients into high- and low-risk groups. Then GO and KEGG enrichment analyses were performed to investigate the function between the two groups. CIBERSORT was used for determining the fractions of 22 immune cell types, while the ssGSEA analyses was used to estimate the differential immune cell infiltrations and related pathways. The "pRRophetic" R package was applied to predict the sensitivity of administering chemotherapeutic and targeted drugs.ResultsA total of 49 anoikis-related DEGs in HCC were detected and 3 genes (EZH2, KIF18A and NQO1) were selected out to build a prognostic model. Furthermore, GO and KEGG functional enrichment analyses indicated that the difference in overall survival between risk groups was closely related to cell cycle pathway. Notably, further analyses found the frequency of tumor mutations, immune infiltration level and expression of immune checkpoints were significantly different between the two risk groups, and the results of the immunotherapy cohort showed that patients in the high-risk group have a better immune response. Additionally, the high-risk group was found to have higher sensitivity to 5-fluorouracil, doxorubicin and gemcitabine.ConclusionThe novel signature of 3 anoikis-related genes (EZH2, KIF18A and NQO1) can predict the prognosis of patients with HCC, and provide a revealing insight into personalized treatments in HCC.

Dataset Information

Prediction of hepatocellular carcinoma prognosis based on expression of an immune-related gene set.

Publications

Prediction of hepatocellular carcinoma prognosis based on expression of an immune-related gene set.

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