ArticlePeerJ2021
Development and validation of a novel survival model for acute myeloid leukemia based on autophagy-related genes.
Article in PeerJ, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Integrated machine learning-based establishment of a prognostic model in multicenter cohorts for acute myeloid leukemia.Frontiers in oncology · 2025Article
- Crosstalk between autophagy and metabolism: implications for cell survival in acute myeloid leukemia.Cell death discovery · 2024Review
- Review
- Deconvolution of tumor composition using partially available DNA methylation data.BMC bioinformatics · 2022Article
- The clinical significance of integrin subunit alpha V in cancers: from small cell lung carcinoma to pan-cancer.BMC pulmonary medicine · 2022Article
- Clinical significance of cyclin-dependent kinase inhibitor 2C expression in cancers: from small cell lung carcinoma to pan-cancers.BMC pulmonary medicine · 2022Article
- The dual role of autophagy in acute myeloid leukemia.Journal of hematology & oncology · 2022Review
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAcute myeloid leukemia (AML) is one of the most common blood cancers, and is characterized by impaired hematopoietic function and bone marrow (BM) failure. Under normal circumstances, autophagy may suppress tumorigenesis, however under the stressful conditions of late stage tumor growth autophagy actually protects tumor cells, so inhibiting autophagy in these cases also inhibits tumor growth and promotes tumor cell death.
methodsAML gene expression profile data and corresponding clinical data were obtained from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, from which prognostic-related genes were screened to construct a risk score model through LASSO and univariate and multivariate Cox analyses. Then the model was verified in the TCGA cohort and GEO cohorts. In addition, we also analyzed the relationship between autophagy genes and immune infiltrating cells and therapeutic drugs.
resultsWe built a model containing 10 autophagy-related genes to predict the survival of AML patients by dividing them into high- or low-risk subgroups. The high-risk subgroup was prone to a poorer prognosis in both the training TCGA-LAML cohort and the validation GSE37642 cohort. Univariate and multivariate Cox analysis revealed that the risk score of the autophagy model can be used as an independent prognostic factor. The high-risk subgroup had not only higher fractions of CD4 naïve T cell, NK cell activated, and resting mast cells but also higher expression of immune checkpoint genes
conclusionThe risk score model based on 10 autophagy-related genes can serve as an effective prognostic predictor for AML patients and may guide for patient stratification for immunotherapies and drugs.
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