Abstract
Acute myeloid leukemia (AML) is a clonal malignant proliferative blood disorder with a poor prognosis. Ferroptosis, a novel form of programmed cell death, holds great promise for oncology treatment, and has been demonstrated to interfere with the development of various diseases. A range of genes are involved in regulating ferroptosis and can serve as markers of it. Nevertheless, the prognostic significance of these genes in AML remains poorly understood. Transcriptomic and clinical data for AML patients were acquired from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). Univariate Cox analysis was performed to identify ferroptosis-related genes with prognostic value, and the least absolute shrinkage and selection operator (LASSO) algorithm and stepwise multivariate Cox regression analysis were utilized to optimize gene selection from the TCGA cohort (132 samples) for model construction. Tumor samples from the GEO database (136 samples and 104 samples) were used as validation groups to estimate the predictive performance of the risk model. Finally, an eight-gene prognostic signature (including CHAC1, CISD1, DPP4, GPX4, AIFM2, SQLE, PGD, and ACSF2) was identified for the prediction of survival probability and was used to stratify AML patients into high- and low-risk groups. Survival analysis illustrated significantly prolonged overall survival and lower mortality in the low-risk group. The area under the receiver operating characteristic curve demonstrated good results for the training set (1-year: 0.846, 2-years: 0.826, and 3-years: 0.837), which verified the accuracy of the model for predicting patient survival. Independent prognostic analysis indicated that the model could be used as a prognostic factor (p ≤ 0.001). Functional enrichment analyses revealed underlying mechanisms and notable differences in the immune status of the two risk groups. In brief, we conducted and validated a novel ferroptosis-related prognostic model for outcome prediction and risk stratification in AML, with great potential to guide individualized treatment strategies in the future.
Highlights
Acute myeloid leukemia (AML) originates from the malignant clonal proliferation of myeloid progenitor cells in bone marrow, peripheral blood, and other tissues and is a highly heterogeneous clinical syndrome
We aimed to explore the prognostic value of ferroptosis-associated genes, reveal the underlying mechanisms, and construct a novel prognosis prediction signature for AML according to the expression levels of ferroptosis-related genes
The standard for screening samples was as follows: 1) the samples were derived from the bone marrow of patients who were diagnosed with AML, based on relevant diagnostic standards; 2) the samples included integrated survival data; 3) the survival time of the patients was longer than 0 day
Summary
Acute myeloid leukemia (AML) originates from the malignant clonal proliferation of myeloid progenitor cells in bone marrow, peripheral blood, and other tissues and is a highly heterogeneous clinical syndrome It is the most common type of leukemia in adults, accounting for 2.5% of new cancer cases and 3.1% of new deaths worldwide in 2020, ranking among the top 10 causes of cancer-related deaths (Sung et al, 2021). Ferroptosis, first named in 2012, is an iron-dependent regulated cell death characterized by an imbalance in redox homeostasis caused by lipid peroxidation or decreased antioxidant capacity. It can be distinguished from other cell death pathways, including apoptosis, necrosis, and autophagy, through distinct morphologic, biochemical, and genetic characteristics. Its potent ability to suppress tumor growth and enhance chemotherapeutic sensitivity makes ferroptosis a promising strategy for cancer therapy (Lu et al, 2017)
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