Gene Signature-Based Prognostic Model for Acute Myeloid Leukemia: The Role of BATF, EGR1, PD-1, PD-L1, and TIM-3.

Background

Acute myeloid leukemia (AML) is a malignancy of hematopoietic stem and progenitor cells, with T cell exhaustion linked to poor outcomes. Our previous research has shown that basic leucine zipper ATF-like transcription factor (BATF) and early growth response 1 (EGR1) play a role in chimeric antigen receptor T (CAR-T) cell exhaustion during AML tumor elimination. However, the roles of BATF and EGR1 and their association with immune checkpoint genes in AML prognosis remain underexplored.

Methods

Bone marrow (BM) samples from 92 newly diagnosed AML patients at our clinical center (JUN-dataset) were analyzed to detect the expression levels of BATF, EGR1, programmed cell death 1 (PD-1), programmed death-ligand 1 (PD-L1), T cell immunoglobulin and mucin domain-containing protein 3 (TIM3) together with conducting a prognostic assessment. Our findings were validated using RNA sequencing data from 155 AML patients from the TCGA database and 199 AML patients from the Beat-AML database.

Results

High BATF expression correlated with poor overall survival (OS) (P = 0.030), whereas high EGR1 expression indicated a favorable prognosis (P = 0.040). Patients with high BATF and low EGR1 expression had worst outcomes (P < 0.001). Among those receiving allogenic hematopoietic stem cell transplantation (allo-HSCT), high BATF expression was linked to shorter OS (P = 0.004). Moreover, a prognostic model incorporating BATF, EGR1, PD-1, PD-L1, and TIM-3 calculated a risk score, with high-risk patients demonstrating significantly shorter OS than low-risk patients in both total AML patients and allo-HSCT recipients (P < 0.001). Similar results were found in both the TCGA and Beat-AML datasets.

Conclusions

We establish a prognostic model based on BATF, EGR1, PD-1, PD-L1, and TIM-3 expression that effectively predicts survival outcomes for AML patients and allo-HSCT recipients. This model may provide valuable insights for prognosis assessment and treatment strategies.