Li Meng-Ting, Zheng Kai-Feng, Qiu Yi-Er
Department of Gastroenterology, The Affiliated People's Hospital of Ningbo University, Ningbo 315000, Zhejiang Province, China.
World J Clin Oncol. 2024 Feb 24;15(2):243-270. doi: 10.5306/wjco.v15.i2.243.
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).
To develop a novel immune cell-related prognostic model of HCC and depict the basic profile of the immune response in HCC.
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.
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.
The novel seven-gene (, and ) 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.
据报道,肝细胞癌(HCC)的发生和发展与免疫相关基因及肿瘤微环境有关。然而,目前尚无足够的预后生物标志物和模型可供临床使用。本研究基于七个预后基因,使用预后生存模型计算HCC患者的总生存期,并揭示肿瘤微环境(TME)的免疫状态。
建立一种新的HCC免疫细胞相关预后模型,并描绘HCC免疫反应的基本概况。
我们从癌症基因组图谱(TCGA)和国际癌症基因组联盟(ICGC)数据集中获取了HCC的临床信息和基因表达数据。利用TCGA和ICGC数据集筛选预后基因,并通过加权基因共表达网络分析以及结合Cox回归的最小绝对收缩和选择算子回归来开发和验证七基因预后生存模型。还基于预后基因对肿瘤突变负荷(TMB)、TME细胞浸润、免疫检查点、免疫治疗和功能通路进行了相关分析。
确定了七个用于构建特征的预后基因。生存受试者工作特征曲线分析显示生存预测性能良好。TMB可被视为HCC生存预测的独立因素。根据七基因预后模型得出的风险评分将患者分为高风险组和低风险组,两组之间的基质评分、免疫评分和估计评分存在显著差异。发现包括VTCN1和TNFSF9在内的几个免疫检查点与七个预后基因和风险评分相关。针对抑制性CTLA4和PD1受体的检查点阻断与潜在化疗药物的不同组合对特定的HCC治疗具有很大前景。还识别并分析了潜在通路,如细胞周期调控和某些氨基酸的代谢。
新的七基因( 、 和 )预后模型显示出较高的预测效率。基于这七个基因的TMB分析可以描绘HCC免疫反应的基本概况,可能值得临床应用。