Typing and modeling of hepatocellular carcinoma based on disulfidptosis-related amino acid metabolism genes for predicting prognosis and guiding individualized treatment

作者：Xuenuo Chen, Zhijian Wang, Yilin Wu, Yinghua Lan, Yongguo Li · 发表于：Frontiers in Oncology · 年份：2023 · DOI：10.3389/fonc.2023.1204335 · 被引用次数：28 · 研究领域：Ferroptosis and cancer prognosis、Endoplasmic Reticulum Stress and Disease、Cancer Research and Treatments

Introduction: Hepatocellular carcinoma (HCC) is the most common type of cancer worldwide and is a major public health problem in the 21st century. Disulfidopathy, a novel cystine-associated programmed cell death, plays complex roles in various tumors. However, the relationship between disulfidoptosis and prognosis in patients with HCC remains unclear. This study aimed to explore the relationship between disulfideptosis and the prognosis of liver cancer and to develop a prognostic model based on amino acid metabolism and disulfideptosis genes. Methods: We downloaded the clinicopathological information and gene expression data of patients with HCC from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and classified them into different molecular subtypes based on the expression patterns of disulfidoptosis-associated amino acid metabolism genes (DRAGs). Patients were then classified into different gene subtypes using the differential genes between the molecular subtypes, and the predictive value of staging was assessed using survival and clinicopathological analyses. Subsequently, risk prognosis models were constructed based on Cox regression analysis to assess patient prognosis, receiver operating characteristic (ROC) curves, somatic mutations, microsatellite instability, tumor microenvironment, and sensitivity to antitumor therapeutic agents. Results: Patients were classified into two subtypes based on differential DRAGs gene expression, with cluster B...