Open Access

ARTICLE

A model based on eight iron metabolism-related genes accurately predicts acute myeloid leukemia prognosis

by ZHANSHU LIU¹, XI HUANG^2,*

1 Department of Hematology, Yongchuan Hospital of Chongqing Medical University, Chongqing, 402160, China
2 Department of Hematology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, China

* Corresponding Author: XI HUANG. Email:

(This article belongs to the Special Issue: Bioinformatics Study of Diseases)

BIOCELL 2023, 47(3), 593-605. https://doi.org/10.32604/biocell.2023.024148

Received 26 May 2022; Accepted 29 August 2022; Issue published 03 January 2023

Abstract

Purpose: Iron metabolism maintains the balance between iron absorption and excretion. Abnormal iron metabolism can cause numerous diseases, including tumor. This study determined the iron metabolism-related genes (IMRGs) signature that can predict the prognosis of acute myeloid leukemia (AML). The roles of these genes in the immune microenvironment were also explored. Methods: A total of 514 IMRGs were downloaded from the Molecular Characteristics Database (MSigDB). IMRGs related to AML prognosis were identified using Cox regression and LASSO analyses and were used to construct the risk score model. AML patients were stratified into high-risk groups (cluster 1) and low-risk groups (cluster 2) based on the mean value of the risk score. The accuracy and prognosis prediction potential of the risk-score model was evaluated using Kaplan-Meier and receiver operating characteristics analysis. The stromal score, immune scores, and immune cells infiltrated in AML samples were estimated using CIBERSORT, MCPcountre, and Xcell algorithms. The role of immune checkpoint genes in the AML microenvironment and the prognostic value of the IMRGs were also evaluated. Results: An AML prognosis prediction model was established based on the eight most critical IMRGs. Further analyses revealed that the model could accurately predict AML prognosis. The expression of IMRGs correlated with the infiltration of several immune cells and could influence response to certain chemotherapy drugs and immunotherapy. Conclusion: A model based on IMRGs can accurately predict the overall survival and disease-free survival of AML patients.

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