Xie Fucun, Bai Yi, Yang Xu, Long Junyu, Mao Jinzhu, Lin Jianzhen, Wang Dongxu, Song Yang, Xun Ziyu, Huang Hanchan, Yang Xiaobo, Zhang Lei, Mao Yilei, Sang Xinting, Zhao Haitao
Department of Liver Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College (CAMS & PUMC), Beijing 100730, China.
Department of Liver Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College (CAMS & PUMC), Beijing 100730, China; Department of Hepatobiliary Surgery, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin 300192, China.
Int Immunopharmacol. 2020 Dec;89(Pt A):107135. doi: 10.1016/j.intimp.2020.107135. Epub 2020 Nov 12.
Tumour mutation burden (TMB) and the immune microenvironment (IME) are reportedly associated with immunotherapy responses, but this relationship remains unclear in hepatocellular carcinoma (HCC). We classified HCC patients in the liver hepatocellular carcinoma cohort from The Cancer Genome Atlas into low- and high-TMB groups and evaluated differences in immune infiltrates. Additionally, differentially expressed genes in the low- and high-TMB groups were identified, and functional analyses were conducted. A risk score model was constructed based on three differentially expressed immune genes (DEIGs). The Tumor Immune Estimation Resource database was utilized to analyse how the IME was affected by the three hub DEIGs. Finally, a prognostic nomogram combining risk scores and stages was established and externally validated with the International Cancer Genome Consortium and GSE14520 cohorts. High-TMB (top 20%) patients exhibited a worse prognosis (P = 0.017). Follicular helper cells (P = 0.001) and activated natural killer cells (P = 0.003) were enriched in high-TMB patients, while resting dendritic cells (P = 0.002) were enriched in low-TMB samples. A risk score model was generated with three hub DEIGs (CCR7, STC2 and S100A9) to predict overall survival in HCC cohorts. Moreover, copy number variations mainly reduced infiltration levels. The nomogram performed better than the risk score model in the training and validation datasets. Higher TMB was associated with IME diversification and worse prognosis in HCC. Mutations in three hub TMB-associated DEIGs correlated with lower immune cell infiltration.
据报道，肿瘤突变负荷（TMB）与免疫微环境（IME）与免疫治疗反应相关，但在肝细胞癌（HCC）中这种关系仍不清楚。我们将来自癌症基因组图谱的肝细胞癌队列中的HCC患者分为低TMB组和高TMB组，并评估免疫浸润的差异。此外，还鉴定了低TMB组和高TMB组中差异表达的基因，并进行了功能分析。基于三个差异表达的免疫基因（DEIG）构建了风险评分模型。利用肿瘤免疫估计资源数据库分析了三个核心DEIG对IME的影响。最后，建立了一个结合风险评分和分期的预后列线图，并在国际癌症基因组联盟和GSE14520队列中进行了外部验证。高TMB（前20%）患者的预后较差（P = 0.017）。高TMB患者中滤泡辅助性T细胞（P = 0.001）和活化自然杀伤细胞（P = 0.003）富集，而静息树突状细胞（P = 0.002）在低TMB样本中富集。利用三个核心DEIG（CCR7、STC2和S100A9）生成了一个风险评分模型，以预测HCC队列中的总生存期。此外，拷贝数变异主要降低了浸润水平。在训练和验证数据集中，列线图的表现优于风险评分模型。较高的TMB与HCC中的IME多样化和较差的预后相关。三个与TMB相关的核心DEIG中的突变与较低的免疫细胞浸润相关。
