Wang Jukun, Han Ke, Zhang Chao, Chen Xin, Li Yu, Zhu Linzhong, Luo Tao
Department of General Surgery, Xuanwu Hospital, Capital Medical University, Beijing, China.
Department of Thoracic Surgery, Xuanwu Hospital, Capital Medical University, Beijing, China.
J Gastrointest Oncol. 2021 Oct;12(5):2345-2360. doi: 10.21037/jgo-21-237.
Ferroptosis has been found to affect the prognosis and immunotherapy of hepatocellular carcinoma (HCC). However, the association between ferroptosis-related genes and infiltrating immune cells in tumor immune microenvironment (TIME) has not been fully elucidated. This study aimed at establishing a prediction model for the progression of HCC using ferroptosis-associated genes based on immune score.
Transcriptomic, mutation and clinicopathological information were downloaded from TCGA and International Cancer Genome Consortium (ICGC) for this study. Construction of the prediction model was done by Lasso regression analysis. Estimation of the clustering ability of the prediction model was done by t-distributed stochastic neighbor embedding (t-SNE) and principal component analysis (PCA) analyses. Assessment of the accuracy of the prediction model was done by receiver operating characteristic (ROC) and Kaplan-Meier curves.
A prediction model was formulated utilizing three ferroptosis-related genes (G6PD, SAT1 and SLC1A5). The model independently predicted the overall survival (OS). Differentially expressed genes (DEGs) linked to based on Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene ontology (GO) analyses immune-associated pathways and functions. Single-sample gene set enrichment analysis (ssGSEA) strategy further confirmed the model was related to immune-associated functions as well as immune cell infiltration.
The three ferroptosis-associated gene-based prediction model was good at predicting the OS outcomes of HCC, improve HCC prognostication and treatment in the clinic.
铁死亡已被发现影响肝细胞癌（HCC）的预后和免疫治疗。然而，铁死亡相关基因与肿瘤免疫微环境（TIME）中浸润免疫细胞之间的关联尚未完全阐明。本研究旨在基于免疫评分，利用铁死亡相关基因建立HCC进展的预测模型。
本研究从TCGA和国际癌症基因组联盟（ICGC）下载了转录组学、突变和临床病理信息。通过套索回归分析构建预测模型。通过t分布随机邻域嵌入（t-SNE）和主成分分析（PCA）分析评估预测模型的聚类能力。通过受试者工作特征（ROC）和Kaplan-Meier曲线评估预测模型的准确性。
利用三个铁死亡相关基因（G6PD、SAT1和SLC1A5）制定了预测模型。该模型独立预测总生存期（OS）。基于京都基因与基因组百科全书（KEGG）和基因本体（GO）分析，差异表达基因（DEG）与免疫相关途径和功能相关。单样本基因集富集分析（ssGSEA）策略进一步证实该模型与免疫相关功能以及免疫细胞浸润有关。
基于三个铁死亡相关基因的预测模型擅长预测HCC的OS结果，改善临床中HCC的预后和治疗。
