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In Vitro and In Vivo Detection of Mitophagy in Human Cells, C. Elegans, and Mice
Published on: November 22, 2017
Identification of the prognostic effect of mitophagy-related genes in acute myeloid leukemia
Fan Xuan1, Wenyuan Zhu2, Baoxi Zhang1
1Department of Pediatrics, Hematology and Oncology, Second Hospital of Hebei Medical University, Shijiazhuang, China.
Background:
Mitophagy has been implicated in the pathogenesis of acute myeloid leukemia (AML), yet its precise molecular mechanisms remain poorly understood. Understanding the roles of mitophagy-related genes (MRGs) may provide new insights into AML classification, prognosis, and therapeutic response.
Methods:
We analyzed 72 MRGs using three independent AML datasets (TCGA-LAML, GSE24395, and GSE146173). Consensus clustering based on MRG expression was used to identify AML molecular subtypes. Differentially expressed genes (DEGs) common to AML subtypes and GSE24395 were identified. Prognostic genes were screened using univariate Cox regression and least absolute shrinkage and selection operator (Lasso) regression analyses. A prognostic risk model was constructed and validated. Functional enrichment, immune infiltration, and drug sensitivity analyses were conducted to explore the biological relevance of the model. In addition, regulatory elements including microRNAs, lncRNAs, and transcription factors targeting model genes were predicted.
Results:
Twenty-six overlapping DEGs were identified between AML subtypes and GSE24395. Five MRG-associated genes (ITGB2, VIP, PTK2, FHL2, BAG3) were selected to construct a prognostic model that stratified patients into high- and low-risk groups with significantly different overall survival. Multivariate Cox analysis confirmed that risk score, age, and treatment status were independent prognostic indicators. Gene set enrichment analysis (GSEA) revealed 731 significantly enriched pathways, including mononuclear cell migration. Immune cell infiltration analysis showed a positive correlation between risk score and monocytes, and negative correlations with plasma B cells and activated mast cells. Drug sensitivity prediction identified 84 compounds with differential responses between risk groups. Regulatory network prediction highlighted hsa-miR-135b-5p, FTX, and SOX11 as potential upstream regulators of the prognostic genes.
Conclusion:
This study identified five mitophagy-related genes as prognostic biomarkers in AML and developed a robust risk model that correlates with survival outcome, immune infiltration, and drug sensitivity. These findings offer new insights into mitophagy-related mechanisms in AML and may guide personalized therapeutic strategies.
Insights
This study identifies five mitophagy-related genes as key prognostic biomarkers for acute myeloid leukemia (AML). A new risk model predicts patient survival, immune infiltration, and drug response, offering insights for personalized AML therapies.
Area of Science:
- Molecular Biology
- Oncology
- Genetics
Background:
- Mitophagy plays a role in acute myeloid leukemia (AML) pathogenesis, but its molecular mechanisms are not fully understood.
- Investigating mitophagy-related genes (MRGs) can offer novel insights into AML classification, prognosis, and treatment response.
Purpose of the Study:
- To identify prognostic biomarkers for acute myeloid leukemia (AML) based on mitophagy-related genes (MRGs).
- To develop and validate a risk model correlating with AML patient survival, immune infiltration, and drug sensitivity.
Main Methods:
- Analysis of 72 MRGs across three independent AML datasets (TCGA-LAML, GSE24395, GSE146173).
- Consensus clustering to identify AML molecular subtypes and differentially expressed genes (DEGs).
- Prognostic gene screening using Cox and Lasso regression, followed by risk model construction and validation.
- Functional enrichment, immune infiltration, and drug sensitivity analyses were performed.
Main Results:
- Five MRG-associated genes (ITGB2, VIP, PTK2, FHL2, BAG3) were selected to build a prognostic model, stratifying AML patients into high- and low-risk groups with distinct overall survival.
- The risk score, age, and treatment status were confirmed as independent prognostic indicators.
- Gene set enrichment analysis revealed pathways including mononuclear cell migration; immune cell infiltration analysis showed correlations with monocytes, plasma B cells, and mast cells.
- Drug sensitivity analysis identified 84 compounds with differential responses between risk groups.
Conclusions:
- Five mitophagy-related genes serve as robust prognostic biomarkers for AML.
- The developed risk model effectively correlates with patient survival, immune infiltration patterns, and drug sensitivity.
- These findings provide valuable insights into mitophagy's role in AML and support the development of personalized therapeutic strategies.
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