ArticleJournal of hepatocellular carcinoma2024
Comprehensive Analysis of Angiogenesis and Ferroptosis Genes for Predicting the Survival Outcome and Immunotherapy Response of Hepatocellular Carcinoma.
Article in Journal of hepatocellular carcinoma, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Integrated Transcriptomic Analyses Identify Four Prognosis-Associated Genes in Hepatocellular Carcinoma.International journal of molecular sciences · 2026Article
- ZG16B: A key regulator of tumor progression and immune microenvironment modulation in cancer (Review).International journal of molecular medicine · 2026Review
- Targeting ferroptosis by noncoding RNAs as a novel therapeutic strategy for hepatocellular carcinoma.Discover oncology · 2025Review
- Robust Cancer Biomarker Identification From Matched Transcriptomic Data Via Bootstrapped Regularized Conditional Logistic Regression.Cancer informatics · 2025Article
- Identification of potential biomarkers for hepatocellular carcinoma based on machine learning and bioinformatics analysis.Discover oncology · 2024Article
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Authors and funding
2 authors.
Funding
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Abstract
Background: Angiogenesis and ferroptosis are both linked to hepatocellular carcinoma (HCC) development, recurrence, and medication resistance. As a result, a thorough examination of the link between genes associated with angiogenesis and ferroptosis and immunotherapy efficacy is required to improve the dismal prognosis of HCC patients. Methods: The molecular subtypes were found using a non-negative matrix factorization technique (NMF) based on the genes associated with angiogenesis and ferroptosis. Based on the differentially expressed genes (DEGs) screed between different molecular subtypes, an angiogenesis and ferroptosis-related prognostic stratification model was built using LASSO-COX regression, random forest technique, and extreme gradient boosting (XGBoost), which was further validated in the ICGC and GSE14520 databases. The impact of this model on tumor microenvironment (TME) and immunotherapy sensitivity was also investigated. The expression levels of candidate genes were detected and validated by Real-Time PCR and immunohistochemistry between liver cancer tissues and adjacent non-tumor liver tissues. Results: Both angiogenesis and ferroptosis-related genes can significantly divide HCC patients into two subgroups with different survival outcomes, mutation profiles, and immune microenvironments. We screened six core genes (SLC10A1, PAEP, DPYSL4, MSC, NQO1, and CD24) for the construction of prognostic models by three machine learning methods after intersecting DEGs between angiogenesis and ferroptosis-related subgroups. In both the TCGA, ICGC, and GSE14520 datasets, the model exhibits high prediction efficiency based on the analysis of KM survival curves and ROC curves. Immunomodulatory genes analysis suggested that the model could be used to predict which patients are most likely to benefit from immunotherapy. Furthermore, the transcriptional expression levels of SLC10A1 in the validation experiment matched the outcomes derived from public datasets. Conclusions: We identified a new angiogenesis and ferroptosis-related signature that might offer the molecular characteristic information needed for an efficient prognostic assessment and perhaps tailored treatment for HCC patients.
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