Back to Search Start Over

Decoupling Lineage-Associated Genes in Acute Myeloid Leukemia Reveals Inflammatory and Metabolic Signatures Associated With Outcomes

Authors :
Hussein A. Abbas
Vakul Mohanty
Ruiping Wang
Yuefan Huang
Shaoheng Liang
Feng Wang
Jianhua Zhang
Yihua Qiu
Chenyue W. Hu
Amina A. Qutub
Monique Dail
Christopher R. Bolen
Naval Daver
Marina Konopleva
Andrew Futreal
Ken Chen
Linghua Wang
Steven M. Kornblau
Source :
Frontiers in Oncology, Vol 11 (2021)
Publication Year :
2021
Publisher :
Frontiers Media S.A., 2021.

Abstract

Acute myeloid leukemia (AML) is a heterogeneous disease with variable responses to therapy. Cytogenetic and genomic features are used to classify AML patients into prognostic and treatment groups. However, these molecular characteristics harbor significant patient-to-patient variability and do not fully account for AML heterogeneity. RNA-based classifications have also been applied in AML as an alternative approach, but transcriptomic grouping is strongly associated with AML morphologic lineages. We used a training cohort of newly diagnosed AML patients and conducted unsupervised RNA-based classification after excluding lineage-associated genes. We identified three AML patient groups that have distinct biological pathways associated with outcomes. Enrichment of inflammatory pathways and downregulation of HOX pathways were associated with improved outcomes, and this was validated in 2 independent cohorts. We also identified a group of AML patients who harbored high metabolic and mTOR pathway activity, and this was associated with worse clinical outcomes. Using a comprehensive reverse phase protein array, we identified higher mTOR protein expression in the highly metabolic group. We also identified a positive correlation between degree of resistance to venetoclax and mTOR activation in myeloid and lymphoid cell lines. Our approach of integrating RNA, protein, and genomic data uncovered lineage-independent AML patient groups that share biologic mechanisms and can inform outcomes independent of commonly used clinical and demographic variables; these groups could be used to guide therapeutic strategies.

Details

Language :
English
ISSN :
2234943X
Volume :
11
Database :
Directory of Open Access Journals
Journal :
Frontiers in Oncology
Publication Type :
Academic Journal
Accession number :
edsdoj.3fa0453989f444be9cf6786abeda8ff8
Document Type :
article
Full Text :
https://doi.org/10.3389/fonc.2021.705627