Research Paper Volume 11, Issue 22 pp 10557—10580
Identification of prognostic genes in the acute myeloid leukemia microenvironment
- 1 School of Basic Medicine, Jiujiang University, Jiujiang, Jiangxi 332005, China
- 2 School of Pharmacy and Life Science, Jiujiang University, Jiujiang, Jiangxi 332005, China
- 3 Key Laboratory of System Bio-medicine of Jiangxi Province, Jiujiang University, Jiujiang, Jiangxi 332000, China
- 4 Institute of Genomic and Personalized Medicine, School of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
received: August 8, 2019 ; accepted: November 8, 2019 ; published: November 18, 2019 ;https://doi.org/10.18632/aging.102477
How to Cite
Copyright © 2019 Huang et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
The tumor microenvironment (TME) has a strong influence on the progression, therapeutic response, and clinical outcome of acute myeloid leukemia (AML), one of the most common hematopoietic malignancies in adults. In this study, we identified TME-related genes associated with AML prognosis. Gene expression profiles from AML patients were downloaded from TCGA database, and immune and stromal scores were calculated using the ESTIMATE algorithm. Immune scores were correlated with clinical features such as FAB subtypes and patient’s age. After categorizing AML cases into high and low score groups, an association between several differentially expressed genes (DEGs) and overall survival was identified. Functional enrichment analysis of the DEGs showed that they were primarily enriched in the immune response, inflammatory response, and cytokine activity, and were involved in signaling processes related to hematopoietic cell lineage, B cell receptor, and chemokine pathways. Two significant modules, dominated respectively by CCR5 and ITGAM nodes, were identified from the PPI network, and 20 hub genes were extracted. A total of 112 DEGs correlated with poor overall survival of AML patients, and 11 of those genes were validated in a separate TARGET-AML cohort. By identifying TME-associated genes, our findings may lead to improved prognoses and therapies for AML.