ArticleBMC bioinformatics2023
Comprehensive analysis of cuproptosis-related lncRNAs in immune infiltration and prognosis in hepatocellular carcinoma.
Article in BMC bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed, 9 citations in OpenAlex.
- Predicting prognosis and drug sensitivity in patients with hepatocellular carcinoma using an lncRNA signature associated with cuproptosis.BMC cancer · 2026Article
- Targeting copper death-related long non-coding RNAs: a novel strategy to overcome immunotherapy resistance in liver cancer.Frontiers in immunology · 2026Review
- Machine learning-based disulfidptosis-related lncRNA signature predicts prognosis, immune infiltration and drug sensitivity in hepatocellular carcinoma.Scientific reports · 2024Article
- Article
- Cuproptosis as the new kryptonite of cancer: a copper-dependent novel cell death mechanism with promising implications for the treatment of hepatocellular carcinoma.Journal of cancer research and clinical oncology · 2023Review
- Clinical Significance of Non-Coding RNA Regulation of Programmed Cell Death in Hepatocellular Carcinoma.Cancers · 2023Review
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7 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundBeing among the most common malignancies worldwide, hepatocellular carcinoma (HCC) accounting for the third cause of cancer mortality. The regulation of cell death is the most crucial step in tumor progression and has become a crucial target for nearly all therapeutic options. Cuproptosis, a copper-induced cell death, was recently reported in Science. However, its primary function in carcinogenesis is still unclear.
methodsCuproptosis-related lncRNAs significantly associated with overall survival (OS) were screened by stepwise univariate Cox regression. The signature of cuproptosis-related lncRNAs for HCC prognosis was constructed by the LASSO algorithm and multivariate Cox regression. Further Kaplan-Meier analysis, proportional hazards model, and ROC analysis were performed. Functional annotation was performed using gene set enrichment analysis (GSEA). The relationship between prognostic cuproptosis-related lncRNAs and HCC prognosis was further explored by GEPIA( http://gepia.cancer-pku.cn/ ) online analysis tool. Finally, we used the ESTIMATE and XCELL algorithms to estimate stromal and immune cells in tumor tissue and cast each sample to infer the underlying mechanism of cuproptosis-related lncRNAs in the tumor immune microenvironment (TIME) of HCC patients.
resultsFour cuproptosis-related lncRNAs were used to construct a prognostic lncRNA signature, which was an independent factor in predicting OS in HCC patients. Kaplan-Meier curves showed significant differences in survival rates between risk subgroups (p = 0.002). At the same time, we found that the expression levels of most immune checkpoint genes increased with increasing risk scores. Tumorigenesis and immunological-related pathways were primarily enhanced in the high-risk group, as determined by GSEA. The results of drug sensitivity analysis showed that compared with patients in the high-risk group, the IC50 values of erlotinib and lapatinib were lower in patients in the low-risk group, while the opposite was true for sunitinib, paclitaxel, gemcitabine, and imatinib. We also found that elevated AL133243.2 expression was significantly associated with worse OS and disease-free survival (DFS), more advanced T stage and higher tumor grade, and reduced immune cell infiltration, suggesting that HCC patients with low AL133243.2 expression in tumor tissues may have a better response to immunotherapy.
conclusionCollectively, the cuproptosis-associated lncRNA signature can serve as an independent predictor to guide individual treatment strategies. Furthermore, AL133243.2 is a promising marker for predicting immunotherapy response in HCC patients. This data may facilitate further exploration of more effective immunotherapy strategies for HCC.
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