A Novel Predictive Model for Adrenocortical Carcinoma Based on Hypoxia- and Ferroptosis-Related Gene Expression.
A Novel Predictive Model for Adrenocortical Carcinoma Based on Hypoxia- and Ferroptosis-Related Gene Expression.
复制标题
基于缺氧和铁死亡相关基因表达的肾上腺皮质癌新预测模型
DOI：
10.3389/fmed.2022.856606
复制
发表时间：
2022
影响因子：
3.9
通讯作者：
中科院分区：
文献类型：
--
作者：
缺氧对铁凋亡的影响在肿瘤增殖中是重要的，但尚未报道缺氧和铁凋亡联合预测肾上腺皮质癌（ACC）的模型。本研究的目的是构建一个预测模型的基础上缺氧和铁凋亡相关基因表达ACC.We评估缺氧和铁凋亡相关基因表达的数据来自79例ACC的癌症基因组图谱（TCGA）。然后，使用最小绝对收缩和选择操作回归构建预测模型以分层患者生存。使用基因表达综合数据库（GEO）中ACC患者的基因表达谱来验证预测模型。根据缺氧相关基因表达，TCGA数据库中的79例ACC患者分为3种分子亚型（C1，C2和C3），具有不同的临床结局。C3亚型患者的生存期最短。铁中毒相关基因在三种亚型中表现出不同的表达模式。结合缺氧和铁蛋白沉积相关基因表达的预测模型的构建。使用年龄、性别、肿瘤分期和预测基因模型构建列线图。基因本体论和京都基因与基因组百科全书的分析表明，基因签名主要与细胞周期和细胞器分裂有关。这种缺氧和铁中毒相关的基因标记显示出对ACC的良好预测性能，并可作为ACC新治疗靶点的新兴来源。
The impact of hypoxia on ferroptosis is important in cancer proliferation, but no predictive model combining hypoxia and ferroptosis for adrenocortical carcinoma (ACC) has been reported. The purpose of this study was to construct a predictive model based on hypoxia- and ferroptosis-related gene expression in ACC. We assessed hypoxia- and ferroptosis-related gene expression using data from 79 patients with ACC in The Cancer Genome Atlas (TCGA). Then, a predictive model was constructed to stratify patient survival using least absolute contraction and selection operation regression. Gene expression profiles of patients with ACC in the Gene Expression Omnibus (GEO) database were used to verify the predictive model. Based on hypoxia-related gene expression, 79 patients with ACC in the TCGA database were divided into three molecular subtypes (C1, C2, and C3) with different clinical outcomes. Patients with the C3 subtype had the shortest survival. Ferroptosis-related genes exhibited distinct expression patterns in the three subtypes. A predictive model combining hypoxia- and ferroptosis-related gene expression was constructed. A nomogram was constructed using age, sex, tumor stage, and the predictive gene model. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses revealed that the gene signature was mainly related to the cell cycle and organelle fission. This hypoxia-and ferroptosis-related gene signature displayed excellent predictive performance for ACC and could serve as an emerging source of novel therapeutic targets in ACC.