Acute myeloid leukemia (AML) is a malignant clonal disease characterized by abnormal proliferation of immature myeloid cells and bone marrow failure. Regulatory T cells (Treg) play a suppressive role in the anti-tumor immune response in the tumor microenvironment. Screening biomarkers based on Treg immune-related genes may help to predict the prognosis and the efficacy of immunotherapy of AML.
Gene expression profiles of AML (non-M3) were obtained from the TCGA and GEO databases. Gene module related to Treg was extracted using CIBERSORT and WGCNA algorithms. Univariate Cox regression and LASSO analyses were performed to identify hub genes and constructed the immune prognostic model. Molecular and immunological features associated with risk signature were explored, and TIDE was used to predict the efficacy of immunotherapy.
A risk signature was constructed based on the five IRGs (IFI27L1, YIPF6, PARVB, TRIM32 and RHOBTB3). The risk signature could be served as an independent prognostic factor of AML. Patients in the high-risk group had a poorer OS than those in the low-risk group. In addition, patients in the high-risk group had higher TP53 mutation rate, higher infiltration of Treg, higher immune escape potential and less benefit from ICI therapy compared to low-risk group.
Our study constructed a prognostic index based on five Treg-related biomarkers, which help to facilitate the differentiation of immunological and molecular characteristics of AML, predict patient prognosis and provide a reference for predicting benefits from ICI therapy.
Keywords: Acute myeloid leukemia; immunotherapy; prognosis; regulatory T cells.