ArticleScientific reports2020
Characterization of somatic mutation-associated microenvironment signatures in acute myeloid leukemia patients based on TCGA analysis.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- A deep learning method and device for bone marrow imaging cell detection.Annals of translational medicine · 2022Article
- Article
- Characteristics of Pyroptosis-Related Subtypes and Novel Scoring Tool for the Prognosis and Chemotherapy Response in Acute Myeloid Leukemia.Frontiers in oncology · 2022Article
- Identification of Potential Novel Prognosis-Related Genes Through Transcriptome Sequencing, Bioinformatics Analysis, and Clinical Validation in Acute Myeloid Leukemia.Frontiers in genetics · 2021Article
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4 authors.
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Abstract
Recurrent genetic mutations occur in acute myeloid leukemia (AML) and have been incorporated into risk stratification to predict the prognoses of AML patients. The bone marrow microenvironment plays a critical role in the development and progression of AML. However, the characteristics of the genetic mutation-associated microenvironment have not been comprehensively identified to date. In this study, we obtained the gene expression profiles of 173 AML patients from The Cancer Genome Atlas (TCGA) database and calculated their immune and stromal scores by applying the ESTIMATE algorithm. Immune scores were significantly associated with OS and cytogenetic risk. Next, we categorized the intermediate and poor cytogenetic risk patients into individual-mutation and wild-type groups according to RUNX1, ASXL1, TP53, FLT3-ITD, NPM1 and biallelic CEBPA mutation status. The relationships between the immune microenvironment and each genetic mutation were investigated by identifying differentially expressed genes (DEGs) and conducting functional enrichment analyses of them. Significant immune- and stromal-relevant DEGs associated with each mutation were identified, and most of the DEGs (from the FLT3-ITD, NPM1 and biallelic CEBPA mutation groups) were validated in the GSE14468 cohort downloaded from the Gene Expression Omnibus (GEO) database. In summary, we identified key immune- and stromal-relevant gene signatures associated with genetic mutations in AML, which may provide new biomarkers for risk stratification and personalized immunotherapy.
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