Construction and Validation of a Novel Ferroptosis-Related Prognostic Model for Acute Myeloid Leukemia

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.

Prediction of Prognosis in Patients With Endometrial Carcinoma and Immune Microenvironment Estimation Based on Ferroptosis-Related Genes

“…Remarkably, it has been reported that AIFM2 protects cancer cells from erastin-, sorafenib-, and RSL3induced ferroptosis via an approach independent of ubiquinol (Bersuker et al, 2019;Doll et al, 2019). Similarly, several studies have shown that AIFM2 represents an unfavorable prognostic factor in prostate cancer, acute myeloid leukemia and uveal melanoma (Luo and Ma, 2021;Lv et al, 2021;Song et al, 2021). However, a recent study has indicated that AIFM2 act as a favorable factor for OS of gastric cancer patients, which is consistent with the findings of our study (Shao et al, 2021).…”

Comprehensive analysis of ferroptosis-related gene signatures as a potential therapeutic target for acute myeloid leukemia: A bioinformatics analysis and experimental verification

“…As a new form of cell death, ferroptosis has demonstrated potential in the treatment of various cancers, including AML ( 18 , 19 ). In fact, researchers have linked ferroptosis-related genes with the prognosis of AML patients and constructed corresponding prognostic models to guide the treatment of AML patients ( 7 , 8 ). However, these findings are biased as the researchers could not confirm whether certain key genes were involved in the regulation of AML ferroptosis in these models.…”

“…Leukemia cells are highly sensitive to ferroptosis inducers ( 6 ); therefore, ferroptosis may be closely related to the development of leukemia. Researchers have constructed corresponding prognostic prediction models based on the expression levels of ferroptosis-related genes in AML patients, which are available in public databases ( 7 , 8 ), to identify potential therapeutic targets and mechanisms. Then, the corresponding predictive model needs further experimental studies to confirm whether some key genes in the model are involved in the regulation of ferroptosis in AML.…”

Identification of Novel Immune Ferropotosis-Related Genes Associated With Clinical and Prognostic Features in Gastric Cancer

“…To compare differentially expressed genes (IFR-DEG) associated with immune ferropotosis in STAD, TCGA database was used for subsequent analysis. The downloading of human immune-related genes (IRGs) from the ImmPort database ( ) and the GeneCard database ( ) reached 17,500 in total, and the downloading of ferropotosis-related genes (FRGs) from the FerrDb database ( ) and previous literature ( 18 ) reached 398 in total. The cutoff condition settings are log2 fold change (logFC) < -2, p -value < 0.05, which is statistically evident.…”