Jin Yixun, Huang Xinyang, Wang Zhuoxin, Xu Hui, Wang Qi, Wang Lifu
Department of Gastroenterology, Ruijin Hospital Affiliated to The Shanghai Jiao Tong University School of Medicine, Shanghai, China.
J Clin Transl Hepatol. 2023 Aug 28;11(4):877-888. doi: 10.14218/JCTH.2022.00301. Epub 2023 Jan 17.
Aminoacyl-tRNA synthetases (ARSs) participate in tumor initiation and progression but their involvement in hepatocellular carcinoma (HCC) is not clear. This study aimed to investigate the prognostic value and underlying mechanisms of ARS in HCC.
Data were obtained from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium, Gene Expression Omnibus and Human Protein Atlas databases. The prognostic model was constructed with the use of Cox regression and least absolute shrinkage and selection operator regression. Kaplan-Meier survival analysis, enrichment analysis, single sample gene set enrichment analysis and tumor mutation burden calculation were performed with R to evaluate the model and explore the underlying mechanism. Wilcoxon tests were used for comparisons between groups.
Aspartyl-tRNA synthetase 2 (DARS2), tyrosyl-tRNA synthetase 1 (YARS1) and cysteinyl-tRNA synthetase 2 (CARS2) were identified as prognostic biomarkers and enrolled in model construction. The area under receiver operating characteristic curve of the model was 0.775. The model was used to assign patients from TCGA into low- and high-risk groups. Those in the high-risk group had a worse prognosis (<0.001). The clinical significance of the model was tested in different clinical subgroups. Genetic mutation analysis had a higher mutation frequency in high-risk group. Enrichment analysis and study of immune-related cells and molecules found that the high-risk group was characterized by immune-cell infiltration and immunosuppression states.
A novel ARS family-based model of HCC prognosis was constructed. mutation frequency and immune-suppressive status accounted for a worse prognosis in patients included in the high-risk group.
氨酰-tRNA合成酶（ARSs）参与肿瘤的发生和发展，但其在肝细胞癌（HCC）中的作用尚不清楚。本研究旨在探讨ARS在HCC中的预后价值及潜在机制。
数据来源于癌症基因组图谱（TCGA）、国际癌症基因组联盟、基因表达综合数据库和人类蛋白质图谱数据库。使用Cox回归和最小绝对收缩与选择算子回归构建预后模型。使用R软件进行Kaplan-Meier生存分析、富集分析、单样本基因集富集分析和肿瘤突变负荷计算，以评估模型并探索潜在机制。采用Wilcoxon检验进行组间比较。
天冬氨酰-tRNA合成酶2（DARS2）、酪氨酰-tRNA合成酶1（YARS1）和半胱氨酰-tRNA合成酶2（CARS2）被确定为预后生物标志物并纳入模型构建。该模型的受试者工作特征曲线下面积为0.775。该模型用于将TCGA中的患者分为低风险组和高风险组。高风险组患者的预后较差（<0.001）。在不同临床亚组中检验了该模型的临床意义。基因突变分析显示高风险组的突变频率更高。富集分析以及对免疫相关细胞和分子的研究发现，高风险组的特征是免疫细胞浸润和免疫抑制状态。
构建了一种基于ARS家族的HCC预后新模型。突变频率和免疫抑制状态导致高风险组患者预后较差。
