ArticlePeerJ2020
Bioinformatics profiling identifies seven immune-related risk signatures for hepatocellular carcinoma.
Article in PeerJ, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Integrated transcriptomic analysis and machine learning identify immunogenic cell death genes as prognostic markers and therapeutic targets in non-small cell lung cancer.Translational cancer research · 2026Article
- Similarity of immune-associated markers in COVID-19 and Kawasaki disease: analyses from bioinformatics and machine learning.BMC pediatrics · 2025Article
- MRI T2WI-based radiomics combined with KRAS gene mutation constructed models for predicting liver metastasis in rectal cancer.BMC medical imaging · 2024Article
- Single-cell profiling reveals the metastasis-associated immune signature of hepatocellular carcinoma.Immunity, inflammation and disease · 2024Article
- Selective profiling of liver-related specific proteins based on sofosbuvir-modified magnetic separation material.Analytical sciences : the international journal of the Japan Society for Analytical Chemistry · 2023Article
- A novel immune-related model to predict prognosis and responsiveness to checkpoint and angiogenesis blockade therapy in advanced renal cancer.Frontiers in oncology · 2023Article
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- Identification of prognostic alternative splicing events related to the immune microenvironment of hepatocellular carcinoma.Molecular medicine (Cambridge, Mass.) · 2021Article
- Construction and Validation of a Prognostic Gene-Based Model for Overall Survival Prediction in Hepatocellular Carcinoma Using an Integrated Statistical and Bioinformatic Approach.International journal of molecular sciences · 2021Article
- "Complimenting the Complement": Mechanistic Insights and Opportunities for Therapeutics in Hepatocellular Carcinoma.Frontiers in oncology · 2020Review
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Authors and funding
7 authors.
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Abstract
backgroundDensity of tumor infiltrating lymphocytes (TIL) and expressions of certain immune-related genes have prognostic and predictive values in hepatocellular carcinoma (HCC); however, factors determining the immunophenotype of HCC patients are still unclear. In the current study, the transcript sequencing data of liver cancer were systematically analyzed to determine an immune gene marker for the prediction of clinical outcome of HCC.
methodsRNASeq data and clinical follow-up information were downloaded from The Cancer Genome Atlas (TCGA), and the samples were assigned into high-stage and low-stage groups. Immune pathway-related genes were screened from the Molecular Signatures Database v4.0 (MsigDB) database. LASSO regression analysis was performed to identify robust immune-related biomarkers in predicting HCC clinical outcomes. Moreover, an immune gene-related prognostic model was established and validated by test sets and Gene Expression Omnibus (GEO) external validation sets.
resultsWe obtained 319 immune genes from MsigDB, and the genes have different expression profiles in high-stage and low-stage of HCC. Univariate survival analysis found that 17 genes had a significant effect on HCC prognosis, among them, 13 (76.5%) genes were prognostically protective factors. Further lasso regression analysis identified seven potential prognostic markers (IL27, CD1D, NCOA6, CTSE, FCGRT, CFHR1, and APOA2) of robustness, most of which are related to tumor development. Cox regression analysis was further performed to establish a seven immune gene signature, which could stratify the risk of samples in training set, test set and external verification set (
conclusionThis study constructed a 7-immunogenic marker as novel prognostic markers for predicting survival of HCC patients.
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