AUTHOR=Yang You , Yang Yan , Liu Jing , Zeng Yan , Guo Qulian , Guo Jing , Guo Ling , Lu Haiquan , Liu Wenjun 

TITLE=Establishment and validation of a carbohydrate metabolism-related gene signature for prognostic model and immune response in acute myeloid leukemia

JOURNAL=Frontiers in Immunology

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2022.1038570

DOI=10.3389/fimmu.2022.1038570

ISSN=1664-3224

ABSTRACT=The heterogeneity of treatment response in acute myeloid leukemia (AML) patients poses great challenges for risk scoring and treatment stratification. In this multicohort study, we investigated whether carbohydrate metabolism-related genes (CRGs) could improve prognostic classification in AML patients. Using univariate regression and LASSO-Cox stepwise regression analysis, we developed a CRG prognostic signature that consists of 10 genes. Using TCGA and GEO public data cohorts and our cohort (1042 non-M3 patients in total), we demonstrate the consistency and accuracy of the CRG score on the predictive performance of AML survival. Stratified by the median risk score，the overall survival (OS) was significantly shorter in high-risk group. Analysis of differentially expressed genes between risk groups demonstrated that they were mainly involved in immune response signaling pathways. Analysis of tumor-infiltrating immune cells confirmed that the immune microenvironment was strongly suppressed in high-risk group. The results of potential drugs for risk groups showed that inhibitors of PI3K/AKT/mTOR signaling pathway and carbohydrate metabolism were effective. A novel risk model based on CRGs proposed in our study is promising prognostic classifications in AML, which may provide novel insights for developing accurate targeted cancer therapies.