背景:据报道,肝细胞癌(HCC)的发生和发展与免疫相关基因和肿瘤微环境有关。然而,没有足够的预后生物标志物和模型可供临床使用.基于七个预后基因,这项研究使用预后生存模型计算了HCC患者的总生存期,并揭示了肿瘤微环境(TME)的免疫状态.
目的:开发一种新型的HCC免疫细胞相关预后模型,并描述HCC免疫反应的基本概况。
方法:我们从癌症基因组图谱(TCGA)和国际癌症基因组联盟(ICGC)数据集获得了HCC的临床信息和基因表达数据。TCGA和ICGC数据集用于筛选预后基因,并通过加权基因共表达网络分析和最小绝对收缩以及Cox回归的选择算子回归来开发和验证七基因预后生存模型。肿瘤突变负荷(TMB)的相对分析,TME细胞浸润,免疫检查点,免疫疗法,和功能通路也基于预后基因进行。
结果:鉴定了7个预后基因用于签名构建。生存接受者工作特征曲线分析显示生存预测性能良好。TMB可作为肝癌生存预测的独立因素。基质评分有显著差异,免疫评分,并根据七基因预后模型得出的风险评分对高风险和低风险组之间的评分进行分层。几个免疫检查点,包括VTCN1和TNFSF9,被发现与7个预后基因和风险评分相关.针对抑制性CTLA4和PD1受体的检查点阻断和潜在的化疗药物的不同组合对于特定的HCC治疗具有很大的希望。潜在途径,如细胞周期调控和某些氨基酸的代谢,还进行了识别和分析。
结论:新的七基因(CYTH3,ENG,HTRA3,PDZD4,SAMD14,PGF,和PLN)预后模型显示出较高的预测效率。基于七个基因的TMB分析可以描述HCC免疫反应的基本概况,值得临床推广应用。
BACKGROUND: The development and progression of hepatocellular carcinoma (HCC) have been reported to be associated with immune-related genes and the tumor microenvironment. Nevertheless, there are not enough prognostic biomarkers and models available for clinical use. Based on seven prognostic genes, this study calculated overall survival in patients with HCC using a prognostic survival model and revealed the immune status of the tumor microenvironment (TME).
OBJECTIVE: To develop a novel immune cell-related prognostic model of HCC and depict the basic profile of the immune response in HCC.
METHODS: We obtained clinical information and gene expression data of HCC from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) datasets. TCGA and ICGC datasets were used for screening prognostic genes along with developing and validating a seven-gene prognostic survival model by weighted gene coexpression network analysis and least absolute shrinkage and selection operator regression with Cox regression. The relative analysis of tumor mutation burden (TMB), TME cell infiltration, immune checkpoints, immune therapy, and functional pathways was also performed based on prognostic genes.
RESULTS: Seven prognostic genes were identified for signature construction. Survival receiver operating characteristic curve analysis showed the good performance of survival prediction. TMB could be regarded as an independent factor in HCC survival prediction. There was a significant difference in stromal score, immune score, and estimate score between the high-risk and low-risk groups stratified based on the risk score derived from the seven-gene prognostic model. Several immune checkpoints, including VTCN1 and TNFSF9, were found to be associated with the seven prognostic genes and risk score. Different combinations of checkpoint blockade targeting inhibitory CTLA4 and PD1 receptors and potential chemotherapy drugs hold great promise for specific HCC therapies. Potential pathways, such as cell cycle regulation and metabolism of some amino acids, were also identified and analyzed.
CONCLUSIONS: The novel seven-gene (CYTH3, ENG, HTRA3, PDZD4, SAMD14, PGF, and PLN) prognostic model showed high predictive efficiency. The TMB analysis based on the seven genes could depict the basic profile of the immune response in HCC, which might be worthy of clinical application.