Table2_Recurrence Risk of Liver Cancer Post-hepatectomy Using Machine Learning and Study of Correlation With Immune Infiltration.PDF

Postoperative recurrence of liver cancer is the main obstacle to improving the survival rate of patients with liver cancer. We established an mRNA-based model to predict the risk of recurrence after hepatectomy for liver cancer and explored the relationship between immune infiltration and the risk of recurrence after hepatectomy for liver cancer. We performed a series of bioinformatics analyses on the gene expression profiles of patients with liver cancer, and selected 18 mRNAs as biomarkers for predicting the risk of recurrence of liver cancer using a machine learning method. At the same time, we evaluated the immune infiltration of the samples and conducted a joint analysis of the recurrence risk of liver cancer and found that B cell, B cell naive, T cell CD4+ memory resting, and T cell CD4+ were significantly correlated with the risk of postoperative recurrence of liver cancer. These results are helpful for early detection, intervention, and the individualized treatment of patients with liver cancer after surgical resection, and help to reveal the potential mechanism of liver cancer recurrence.

肝癌术后复发是提升肝癌患者生存率的核心阻碍。本研究构建了基于信使核糖核酸（mRNA）的预测模型，用于评估肝癌肝切除术后的复发风险，并探究了免疫浸润与肝癌肝切除术后复发风险之间的关联。本研究对肝癌患者的基因表达谱开展了一系列生物信息学分析，通过机器学习方法筛选出18个mRNA作为预测肝癌复发风险的生物标志物。与此同时，本研究对样本的免疫浸润情况进行了评估，并针对肝癌复发风险开展联合分析，结果发现B细胞、初始B细胞（B cell naive）、静息CD4+记忆性T细胞（T cell CD4+ memory resting）以及CD4+ T细胞均与肝癌术后复发风险存在显著相关性。上述研究结果有助于肝癌术后患者的早期筛查、临床干预及个体化治疗，同时可为揭示肝癌复发的潜在机制提供参考。