Related Experiment Video
Updated: Sep 28, 2025

Author Spotlight: Transmitochondrial Cybrid Generation Using Cancer Cell Lines
Published on: March 17, 2023
Identification of a Mitochondria-Related Gene Signature to Predict the Prognosis in AML
Nan Jiang1,2,3, Xinzhuo Zhang2, Qi Chen4
1School of Pharmacy, Southwest Medical University, Luzhou, China.
Abstract:
Mitochondria-related metabolic reprogramming plays a major role in the occurrence, development, drug resistance, and recurrence of acute myeloid leukemia (AML). However, the roles of mitochondria-related genes (MRGs) in the prognosis and immune microenvironment for AML patients remain largely unknown. In this study, by least absolute shrinkage and selection operator (LASSO) Cox regression analysis, 4 MRGs' (HPDL, CPT1A, IDH3A, and ETFB) signature was established that demonstrated good robustness in TARGET AML datasets. The univariate and multivariate Cox regression analyses both demonstrated that the MRG signature was a robust independent prognostic factor in overall survival prediction with high accuracy for AML patients. Based on the risk score calculated by the signature, samples were divided into high- and low-risk groups. Gene set enrichment analysis (GSEA) suggested that the MRG signature is involved in the immune-related pathways. Via immune infiltration analysis and immunosuppressive genes analysis, we found that MRG risk of AML patients was strikingly positively correlated with an immune cell infiltration and expression of critical immune checkpoints, indicating that the poor prognosis might be caused by immunosuppressive tumor microenvironment (TME). In summary, the signature based on MRGs could act as an independent risk factor for predicting the clinical prognosis of AML and could also reflect an association with the immunosuppressive microenvironment, providing a novel method for AML metabolic and immune therapy based on the regulation of mitochondrial function.
Insights
Mitochondria-related genes impact acute myeloid leukemia (AML) prognosis and the immune microenvironment. A novel 4-gene signature predicts survival and identifies an immunosuppressive tumor microenvironment in AML patients.
Area of Science:
- Biochemistry
- Oncology
- Immunology
Background:
- Mitochondria-driven metabolic reprogramming is crucial in acute myeloid leukemia (AML) progression, drug resistance, and recurrence.
- The specific roles of mitochondria-related genes (MRGs) in AML patient prognosis and immune microenvironment modulation are not well understood.
Purpose of the Study:
- To establish and validate a prognostic signature based on MRGs for acute myeloid leukemia (AML).
- To investigate the association between the MRG signature and the tumor immune microenvironment (TME) in AML.
Main Methods:
- Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analysis to identify key MRGs.
- Univariate and multivariate Cox regression analyses for prognostic validation.
- Gene Set Enrichment Analysis (GSEA) and immune infiltration analysis to assess TME characteristics.
Main Results:
- A robust 4-gene signature (HPDL, CPT1A, IDH3A, ETFB) was developed, demonstrating strong prognostic value for overall survival in AML.
- The MRG signature risk score effectively stratified patients into high- and low-risk groups.
- Higher MRG risk scores correlated significantly with increased immune cell infiltration and expression of immune checkpoints, suggesting an immunosuppressive TME.
Conclusions:
- The established MRG signature serves as an independent prognostic factor for AML, accurately predicting patient survival.
- The MRG signature reflects the status of the immunosuppressive tumor microenvironment in AML.
- This signature offers a novel therapeutic strategy targeting mitochondrial function for AML metabolic and immune therapy.
More Related Videos
11:15Next Generation Sequencing for the Detection of Actionable Mutations in Solid and Liquid Tumors
Published on: September 20, 2016
07:47Author Spotlight: Unveiling Transmembrane Protein Family-Related Markers in Gastric Cancer and Implications for Targeted Therapies
Published on: September 15, 2023