ArticleAmerican journal of translational research2022
A novel immune prognostic model of non-M3 acute myeloid leukemia.
Article in American journal of translational research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed, 4 citations in OpenAlex.
- Immunoreactivity to WT1 peptide vaccine is associated with prognosis in elderly patients with acute myeloid leukemia: follow-up study of randomized phase II trial of OCV-501, an HLA class II-binding WT1 polypeptide.Cancer immunology, immunotherapy : CII · 2023Trial
- Machine learning-based integration develops a novel lysosome-related prognostic signature associated with prognosis and immune infiltration landscape in acute myeloid leukemia.Discover oncology · 2026Article
- Macrophage migration inhibitory factor blockade reprograms macrophages and disrupts prosurvival signaling in acute myeloid leukemia.Cell death discovery · 2024Article
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Authors and funding
13 authors at 1 institution in 1 country.
Funding
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Abstract
Acute myeloid leukemia (AML) is a common hematological malignancy in adults. AML patients exhibit clinical heterogeneity with complications of molecular basis. The leukemogenesis of AML involves immune escape, and the immunosuppression status of the patient might have great impact on AML treatment outcome. In this study, we established an immune prognostic model of AML using bioinformatics tools. With the data in the TCGA and GTEx datasets, we analyzed differentially expressed genes (DEGs) in non-M3 AML and identified 420 immune-related DEGs. Among which, 49 genes' expression was found to be related to AML prognosis based on univariate Cox regression analysis. Next, we established a prognostic model with these 49 genes in AML by LASSO regression and multivariate Cox regression analyses. In our model, the expressions of 5 immune genes, MIF, DEF6, OSM, MPO, AVPR1B, were used to stratify non-M3 AML patients' treatment outcome. A patient's risk score could be calculated as Risk Score=0.40081 × MIF (MIF expression) - 0.15201 × MPO + 0.78073 × DEF6 - 0.45192 × AVPR1B + 0.25912 × OSM. The area under the curve of the risk score signature was 0.8, 0.8, and 0.96 at 1 year, 3 years, and 5 years, respectively. The prognostic model was then validated internally by TCGA data and externally by GEO data. At last, the result of single-sample gene-set enrichment analysis demonstrated that compared with healthy samples, the abundance of non-turmeric immune cells was significantly repressed in AML. To summarize, we presented an immune-related 5-gene signature prognostic model in AML.
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36105048PMC9452334W4295904235What OpenQuestion holds
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