ArticleBMC cancer2022
Novel γδ T cell-based prognostic signature to estimate risk and aid therapy in hepatocellular carcinoma.
Article in BMC cancer, 2022. 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, 3 citations in OpenAlex.
- Unraveling the Causal Links Between Immune Traits and Hepatocellular Carcinoma: Insights From a Bi-Directional Mendelian Randomization Study.The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology · 2025Article
- Article
- γδ T Cells: A Game Changer in the Future of Hepatocellular Carcinoma Immunotherapy.International journal of molecular sciences · 2024Review
- Integration of proteomics and transcriptomics to construct a prognostic signature of renal clear cell carcinoma.International journal of medical sciences · 2024Article
- Prognostic value of combined inflammatory and nutritional biomarkers in HCC within the Milan criteria after hepatectomy.Frontiers in oncology · 2022Article
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundNumerous studies have revealed that gamma delta (γδ) T cell infiltration plays a crucial regulatory role in hepatocellular carcinoma (HCC) development. Nonetheless, a comprehensive analysis of γδ T cell infiltration in prognosis evaluation and therapeutic prediction remains unclear.
methodsMulti-omic data on HCC patients were obtained from public databases. The CIBERSORT algorithm was applied to decipher the tumor immune microenvironment (TIME) of HCC. Weighted gene co-expression network analysis (WGCNA) was performed to determine significant modules with γδ T cell-specific genes. Kaplan-Meier survival curves and receiver operating characteristic analyses were used to validate prognostic capability. Additionally, the potential role of RFESD inhibition by si-RFESD in vitro was investigated using EdU and CCK-8 assays.
resultsA total of 16,421 genes from 746 HCC samples (616 cancer and 130 normal) were identified based on three distinct cohorts. Using WGCNA, candidate modules (brown) with 1755 significant corresponding genes were extracted as γδ T cell-specific genes. Next, a novel risk signature consisting of 11 hub genes was constructed using multiple bioinformatic analyses, which presented great prognosis prediction reliability. The risk score exhibited a significant correlation with ICI and chemotherapeutic targets. HCC samples with different risks experienced diverse signalling pathway activities. The possible interaction of risk score with tumor mutation burden (TMB) was further analyzed. Subsequently, the potential functions of the RFESD gene were explored in HCC, and knockdown of RFESD inhibited cell proliferation in HCC cells. Finally, a robust prognostic risk-clinical nomogram was developed and validated to quantify clinical outcomes.
conclusionsCollectively, comprehensive analyses focusing on γδ T cell patterns will provide insights into prognosis prediction, the mechanisms of immune infiltration, and advanced therapy strategies in HCC.
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