Novel γδ T cell-based prognostic signature to estimate risk and aid therapy in hepatocellular carcinoma

被引:5
作者
Wang, Jingrui [1 ]
Ling, Sunbin [1 ]
Ni, Jie [1 ]
Wan, Yafeng [1 ]
机构
[1] Zhejiang Univ, Affiliated Hangzhou Peoples Hosp 1, Dept Hepatobiliary & Pancreat Surg, Sch Med, 261 Huansha Rd, Hangzhou, Zhejiang, Peoples R China
关键词
Hepatocellular carcinoma; gamma delta T cells; Prognosis predition; Tumor immune microenvironment; Tumor mutation burden; RFESD; QUALITY-OF-LIFE; OPEN-LABEL; NIVOLUMAB; EXPRESSION; DOCETAXEL; ANTI-PD-1;
D O I
10.1186/s12885-022-09662-6
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Background: Numerous studies have revealed that gamma delta (gamma delta) T cell infiltration plays a crucial regulatory role in hepatocellular carcinoma (HCC) development. Nonetheless, a comprehensive analysis of gamma delta T cell infiltration in prognosis evaluation and therapeutic prediction remains unclear. Methods: Multi-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 gamma delta 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. Results: A 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 gamma delta 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. Conclusions: Collectively, comprehensive analyses focusing on gamma delta T cell patterns will provide insights into prognosis prediction, the mechanisms of immune infiltration, and advanced therapy strategies in HCC.
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页数:19
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