Li Junjian, Chen Ji, Tao Qiqi, Zheng Jianjian, Zhou Zhenxu
Department of Hepatobiliary Surgery, The First Affiliated Hospital of Wenzhou Medical University Wenzhou 325000, Zhejiang, P. R. China.
Key Laboratory of Diagnosis and Treatment of Severe Hepato-Pancreatic Diseases of Zhejiang Province, The First Affiliated Hospital of Wenzhou Medical University Wenzhou 325000, Zhejiang, P. R. China.
Am J Cancer Res. 2023 Jan 15;13(1):66-85. eCollection 2023.
Hepatocellular carcinoma (HCC) is characterized by high rates of recurrence and metastasis and poor prognosis. A recently discovered concept of T cell tolerance (TCT) has become an entirely new target of cancer immunotherapy. Unfortunately, the effect of TCT on the outcomes of HCC has not been explored. In this study, 7 public datasets and one external clinical cohort, including 1716 HCC patients were explored. Through WGCNA analysis and differential analysis, we explored the key TCT-related modulates. A total of 95 machine learning integrations across all validation cohorts were compared and the optimal method with the highest average C-index value was selected to construct the TCT derived signature (TCTS). In all independent clinical cohorts, TCTS showed accurate prediction of the prognosis, and was significantly correlated with clinical indicators and molecular features. Compared with 77 published gene signatures, the TCTS exhibited superior predictive performance. In the external clinical cohort, a novel nomogram (comprising TNM stage, Hepatitis B, Vascular invasion, Perineural invasion, AFP and TCTS) was constructed to test the clinical performance of TCTS. The results showed that the high TCTS scoring group showed dismal prognosis, improved sensitivity to oxaliplatin and good response to anti-PD-1/PD-L1 immunotherapy. Moreover, the low TCTS score group had few genomic alterations, low immune activation and low PD-1/PD-L1 expression levels. In conclusion, TCTS is an ideal biomarker for predicting the clinical outcomes and improving precision treatment of HCC.
肝细胞癌（HCC）的特点是复发率和转移率高，预后差。最近发现的T细胞耐受性（TCT）概念已成为癌症免疫治疗的全新靶点。遗憾的是，TCT对HCC预后的影响尚未得到探索。在本研究中，我们对7个公共数据集和1个外部临床队列进行了探索，其中包括1716例HCC患者。通过加权基因共表达网络分析（WGCNA）和差异分析，我们探索了与TCT相关的关键调节因子。比较了所有验证队列中的95种机器学习整合方法，并选择平均C指数值最高的最佳方法来构建TCT衍生特征（TCTS）。在所有独立临床队列中，TCTS显示出对预后的准确预测，并且与临床指标和分子特征显著相关。与77个已发表的基因特征相比，TCTS表现出卓越的预测性能。在外部临床队列中，构建了一种新型列线图（包括TNM分期、乙型肝炎、血管侵犯、神经周围侵犯、甲胎蛋白和TCTS）以测试TCTS的临床性能。结果表明，TCTS评分高的组预后不佳，对奥沙利铂的敏感性提高，对抗PD-1/PD-L1免疫治疗反应良好。此外，TCTS评分低的组基因组改变较少，免疫激活低，PD-1/PD-L1表达水平低。总之，TCTS是预测HCC临床预后和改善精准治疗的理想生物标志物。
