A Novel Predictive Model for Adrenocortical Carcinoma Based on Hypoxia- and Ferroptosis-Related Gene Expression - Zhang, Tianyue; Song, Xiaoxiao; Qiao, Jie; Zhu, Ruiliang; Ren, Yuezhong; Shan, Peng-Fei (Frontiers in Medicine, 2022)
Background: The impact of hypoxia on ferroptosis plays an important role in cancer proliferation, while no predictive model combining hypoxia and ferroptosis for adrenocortical carcinoma (ACC) has been reported yet. The purpose was to construct a predictive model based on hypoxia and ferroptosis-related gene expression for ACC. Methods: 79 patients with ACC in the Cancer Genome Atlas (TCGA) database were subtyped into three groups according to the hypoxia-related gene expression. Prognosis and ferroptosis-related gene expression were compared among three groups. A gene predictive model was than constructed through the least absolute contraction and selection operation (LASSO) regression. Gene expression profiles of patients with ACC in the Gene Expression Omnibus (GEO) database were also obtained to verify the predictive model. Results: Based on the hypoxia-related gene expression, 79 patients with ACC in TCGA database were divided into three molecular subtypes (C1, C2 and C3), with different clinical outcomes. Among them, C3 subtype exhibited the shortest survival time. Ferroptosis related genes exhibited distinct levels in three subtypes. A predictive model combing hypoxia and ferroptosis-related gene expression was constructed. A nomogram combining age, gender, tumor stage and the predictive model was established. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that the gene signature was mainly related to cell cycle and organelle fission. Conclusion: The 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.