AUTHOR=Tong Xiqin , Zhou Fuling 

TITLE=Integrated bioinformatic analysis of mitochondrial metabolism-related genes in acute myeloid leukemia

JOURNAL=Frontiers in Immunology

VOLUME=Volume 14 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2023.1120670

DOI=10.3389/fimmu.2023.1120670

ISSN=1664-3224

ABSTRACT=Background: Acute myeloid leukemia (AML) is a common hematologic malignancy characterized by poor prognoses and high recurrence rates. Studies have shown that mitochondrial metabolism is crucial in leukemia stem cell (LSC) maintenance and treatment resistance for AML. Therefore, it is necessary to identify novel prognostic biomarkers targeting mitochondrial metabolism to improve AML outcomes. 
Methods: In this study, GSE12417, GSE37642, and the Cancer Genome Atlas (TCGA-LAML) datasets were downloaded from the public databases for further analysis. Single sample gene set enrichment analysis (ssGSEA) and weighted co-expression network analysis (WGCNA) were performed to identify MMRGs. A prognosis model was then constructed using the least absolute and selection operator (LASSO) regression and multivariate COX regression. Differential analysis was performed to identify differentially expressed genes (DEGs). Functional enrichment, interaction networks, drug sensitivity, immune microenvironment, and immunotherapy and mutation analyses were also performed.
Results: A prognosis model constructed based on five mitochondrial metabolism-related genes (MMRGs) could distinguish high-risk patients from low-risk patients in TCGA-LAML dataset and Gene-Expression Omnibus (GEO) datasets, with significant differences in overall survival. Additionally, the 38 DEGs were mainly related to mitochondrial metabolism, immune signaling, and multiple drug resistance pathways. In addition, high-risk patients with more immune-cell infiltration had higher Tumor Immune Dysfunction and Exclusion (TIDE) scores, indicating poor immunotherapy response. mRNA-drug interactions and drug sensitivity analyses were performed to explore potential druggable hub genes.
Conclusions: MMRGs were systematically evaluated based on AML prognosis and tumor microenvironment (TME). This study can provide important prognostic information and a more sensitive therapeutic alternative for AML patients.