ArticleAnnals of translational medicine2021
Construction and validation of a prognostic signature using CNV-driven genes for hepatocellular carcinoma.
Article in Annals of translational medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 8 citations in OpenAlex.
- Single-cell spatial landscape of aggrephagy activity stratifies hepatocellular carcinoma neutrophils and delivers a 5-gene diagnostic panel for patient stratification.Translational oncology · 2026Article
- Integrative Multi-Omics Analysis Identifies NUP205 as a Candidate Prognostic Biomarker in Liver Hepatocellular Carcinoma.International journal of molecular sciences · 2026Article
- Integration of Nuclear, Clinical, and Genetic Features for Lung Cancer Subtype Classification and Survival Prediction Based on Machine- and Deep-Learning Models.Diagnostics (Basel, Switzerland) · 2025Article
- An original aneuploidy-related gene model for predicting lung adenocarcinoma survival and guiding therapy.Scientific reports · 2024Article
- Article
- Application of single-cell RNA sequencing analysis of novel breast cancer phenotypes based on the activation of ferroptosis-related genes.Functional & integrative genomics · 2023Article
- Differential methylation patterns in lean and obese non-alcoholic steatohepatitis-associated hepatocellular carcinoma.BMC cancer · 2022Article
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHepatocellular carcinoma (HCC) is one of the major causes of cancer-related deaths worldwide. Copy number variations (CNVs) affect the expression of genes and play critical roles in carcinogenesis. We aimed to identify specific CNV-driven genes and establish a prognostic model for HCC.
methodsIntegrative analysis of CNVs difference data and differentially expressed genes (DEGs) data from The Cancer Genome Atlas (TCGA) were conducted to identify critical CNV-driven genes for HCC. A risk model was constructed based on univariate Cox regression analysis, Least Absolute Shrinkage and Selection Operator (LASSO), and multivariate Cox regression analyses. The associations between CNV-driven genes signature and infiltrating immune cells were explored. The International Cancer Genome Consortium (ICGC) dataset was utilized to validate this model.
resultsAfter integrative analysis of CNVs and corresponding mRNA expression profiles, 568 CNV-driven genes were identified. Sixty-three CNV-driven genes were found to be markedly associated with overall survival (OS) after univariate Cox regression analysis. Finally, eight CNV-driven genes were screened to generate a prognostic risk model. Compared with low-risk group, the OS of patients in the high-risk group was significantly shorter in both the TCGA [hazard ratio (HR) =6.14, 95% confidence interval (CI): 2.72-13.86, P<0.001] and ICGC (HR =3.23, 95% CI: 1.17-8.92, P<0.001) datasets. Further analysis revealed the infiltrating neutrophils were positively correlated with risk score. Meanwhile, the high-risk group was associated with higher expression of immune checkpoint genes.
conclusionsA novel signature based on CNV-driven genes was built to predict the survival of HCC patients and showed good performance. The results of our study may improve understanding of the mechanism that drives HCC, and provide an immunological perspective for individualized therapies.
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