ArticleCancer medicine2023
A signature based on NKG2D ligands to predict the recurrence of hepatocellular carcinoma after radical resection.
Article in Cancer medicine, 2023. 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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7 citing papers in PubMed, 6 citations in OpenAlex.
- Multi-omics integration identifies ribosome biogenesis-active macrophage subpopulation and its key gene GNL2 in driving liver hepatocellular carcinoma progression and mechanisms.Cancer cell international · 2026Article
- Hemopexin Suppresses Hepatocellular Carcinoma via TNF-α-Mediated Mitochondrial Apoptosis.Cancers · 2025Article
- Chimeric antigen receptor natural killer cell therapy for solid tumors: mechanisms, clinical progress, and strategies to overcome the tumor microenvironment.Experimental biology and medicine (Maywood, N.J.) · 2025Review
- Integrating T-cell inflammation features for prognosis in hepatocellular carcinoma: a novel predictive model.Journal of gastrointestinal oncology · 2024Article
- The current state of knowledge on the role of NKG2D ligands in multiple sclerosis and other autoimmune diseases.Frontiers in molecular neuroscience · 2024Review
- A signature based on NKG2D ligands to predict the recurrence of hepatocellular carcinoma after radical resection.Cancer medicine · 2023Article
- Evaluating Predictors of Quality in Liver NK Cells Among Deceased Donors.Cell transplantationArticle
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Authors and funding
9 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionDue to the high recurrence, the HCC prognosis remains poor. Yet, the biomarkers for predicting the recurrence of high-risk patients are currently lacking. We aimed to develop a signature to predict the recurrence of HCC based on NKG2D ligands.
methodsThe multivariate Cox proportional hazards regression was used to select recurrence-related variables of NKG2D ligands in HCC patients from The Cancer Genome Atlas (TCGA). HCC patients from the OEP000321 dataset and Guilin cohort were used to validate the predictive signature. The mRNA expression of NKG2D ligands was measured by QRT-PCR. Immunohistochemistry analysis of HCC tissue microarray samples was used to identify the expression of NKG2D ligands.
resultsIn this study, NKG2D ligands expression in the mRNA and protein level was both abnormally expressed in HCC and associated with recurrence-free survival (RFS). Then, the recurrence-related variables of NKG2D ligands in HCC were selected by the multivariate Cox proportional hazards regression. Among the eight NKG2D ligands, MICA (HR = 1.347; 95% CI = 1.012-1.793; p = 0.041), ULBP3 (HR = 0.453; 95% CI = 0.231-0.889; p = 0.021) and ULBP5 (HR = 3.617; 95% CI = 1.819-7.194; p < 0.001) were significantly correlated with RFS in the TCGA-LIHC cohort. Then, the signature was constructed by the three NKG2D ligands. The predictive effectiveness of this signature was also validated in the OEP000321 dataset and Guilin cohort. Further, HCC patients were classified into low-risk and high-risk subgroups by the predictive score. Compared with the low-risk group, the high-risk group had poor RFS in both training and validation cohorts. Importantly, compared with the low-risk patients with the G1-G2 stage, the levels of infiltrated NK-activated cells and NKG2D expression were both lower in the high-risk patients.
conclusionsThe signature based on MICA, ULBP3, and ULBP5 could predict HCC recurrence.
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