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.
Highlights
Recurrent genetic mutations occur in acute myeloid leukemia (AML) and have been incorporated into risk stratification to predict the prognoses of AML patients
The complete gene expression profiles and clinical information of 173 AML patients were retrieved from the The Cancer Genome Atlas (TCGA) database for this study
A number of genetic mutations have presented immune microenvironment modulatory properties in solid tumors: EGFR mutations correlate with an immunosuppressive Tumor microenvironment (TME) and may impact the antitumor immune response in NSCLC22,23; TP53 and KRAS mutations in lung adenocarcinoma can regulate the immune microenvironment to affect PD-1 blockade immunotherapy[24,25]; JAK1 or JAK2 mutations may lead to acquired resistance to PD-1 blockade immunotherapy in patients with melanoma[26]
Summary
Recurrent genetic mutations occur in acute myeloid leukemia (AML) and have been incorporated into risk stratification to predict the prognoses of AML patients. 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. 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. Estimation of STromal and Immune cells in Malignant Tumors using Expression data’ (ESTIMATE) is a method that uses gene expression signatures to infer the fraction of stromal and immune cells in tumor samples[15] This algorithm has been employed to investigate the microenvironment of several solid tumors, such as gastric.
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