A Novel Amino Acid-Related Gene Signature Predicts Overall Survival in Patients With Hepatocellular Carcinoma

IF 1.5 Q4 ONCOLOGY

Cancer reports Pub Date : 2024-07-23 DOI:10.1002/cnr2.2131

Shuyi Wang, Hong Huang, Xingwang Hu, Meifang Xiao, Kaili Yang, Haiyan Bu, Yupeng Jiang, Zebing Huang

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Abstract

Background and Aims

Hepatocellular carcinoma (HCC) is an extremely harmful malignant tumor in the world. Since the energy metabolism and biosynthesis of HCC cells are closely related to amino acids, it is necessary to further explore the relationship between amino acid-related genes and the prognosis of HCC to achieve individualized treatment. We herein aimed to develop a prognostic model for HCC based on amino acid genes.

Methods

In this study, RNA-sequencing data of HCC patients were downloaded from the TCGA-LIHC cohort as the training cohort and the GSE14520 cohort as the validation cohort. Amino acid-related genes were derived from the Molecular Signatures Database. Univariate Cox and Lasso regression analysis were used to construct an amino acid-related signature (AARS). The predictive value of this risk score was evaluated by Kaplan–Meier (K–M) curve, receiver operating characteristic (ROC) curve, univariate and multivariate Cox regression analysis. Gene set variation analysis (GSVA) and immune characteristics evaluation were used to explore the underlying mechanisms. Finally, a nomogram was established to help the personalized prognosis assessment of patients with HCC.

Results

The AARS comprises 14 amino acid-related genes to predict overall survival (OS) in HCC patients. HCC patients were divided into AARS-high group and AARS-low group according to the AARS scores. The K–M curve, ROC curve, and univariate and multivariate Cox regression analysis verified the good prediction efficiency of the risk score. Using GSVA, we found that AARS variants were concentrated in four pathways, including cholesterol metabolism, delayed estrogen response, fatty acid metabolism, and myogenesis metabolism.

Conclusion

Our results suggest that the AARS as a prognostic model based on amino acid-related genes is of great value in the prediction of survival of HCC, and can help improve the individualized treatment of patients with HCC.

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一种新型氨基酸相关基因信号可预测肝细胞癌患者的总生存期

背景和目的：肝细胞癌（HCC）是世界上危害极大的恶性肿瘤。由于 HCC 细胞的能量代谢和生物合成与氨基酸密切相关，因此有必要进一步探讨氨基酸相关基因与 HCC 预后的关系，以实现个体化治疗。在此，我们旨在建立一个基于氨基酸基因的HCC预后模型：在本研究中，HCC 患者的 RNA 序列数据下载自 TCGA-LIHC 队列作为训练队列，GSE14520 队列作为验证队列。氨基酸相关基因来自分子特征数据库。利用单变量 Cox 和 Lasso 回归分析构建了氨基酸相关特征（AARS）。通过Kaplan-Meier（K-M）曲线、接收器操作特征（ROC）曲线、单变量和多变量Cox回归分析评估了该风险评分的预测价值。基因组变异分析（GSVA）和免疫特征评估被用来探索潜在的机制。最后，建立了有助于对 HCC 患者进行个性化预后评估的提名图：AARS由14个氨基酸相关基因组成，可预测HCC患者的总生存期（OS）。根据 AARS 评分将 HCC 患者分为 AARS 高分组和 AARS 低分组。K-M曲线、ROC曲线以及单变量和多变量Cox回归分析验证了该风险评分的良好预测效果。通过GSVA，我们发现AARS变异集中在四个通路，包括胆固醇代谢、雌激素反应延迟、脂肪酸代谢和肌生成代谢：我们的研究结果表明，基于氨基酸相关基因的 AARS 预后模型在预测 HCC 患者的生存率方面具有重要价值，有助于改善 HCC 患者的个体化治疗。

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