The Multi-Omic Prognostic Model of Oxidative Stress-Related Genes in Acute Myeloid Leukemia - Dong, Chao; Zhang, Naijin; Zhang, Lijun (Frontiers in Genetics, 2021)
Background: Acute myeloid leukemia (AML) is one of the most common cancers in the world, and oxidative stress is closely related to leukemia. A lot of efforts have been made to improve the prognosis of AML. However, the situation remains serious. Hence, we focused on the study of prognostic genes in AML. Materials and methods: Prognostic oxidative stress genes were screened out. Gene expression profile of AML patients was downloaded from the TCGA database. The oxidative stress related model was constructed, by which the prognosis of AML patients was predicted using the two GEO GSE23143 datasets and the stability of GSE71014 authentication model. Results: Prognostic oxidative stress genes were screened out in AML, and the prognostic genes were significantly enriched in a large number of pathways based on GO and KEGG enrichment analysis. There was a complex interaction between prognostic genes and transcription factors. After constructing the prediction model, the clinical predictive value of the model was discussed in multi-omics study. We investigated the sensitivity of risk score to common chemotherapeutic agents, the influence of signaling pathways on the prognosis of AML patients, and the correlation of multiple genes with immune score and immune dysfunction. Conclusions: A highly effective prognostic risk model for AML patients was established and validated. The association of prognostic oxidative stress genes with drug sensitivity, signaling pathways, and immune infiltration was explored. The results suggested that oxidative stress genes may be potential prognostic biomarkers for AML, which will provide a new basis for disease management.