Identification of a venetoclax-resistance prognostic signature base on 6-senescence genes and its clinical significance for acute myeloid leukemia

Front Oncol. 2023 Nov 30:13:1302356. doi: 10.3389/fonc.2023.1302356. eCollection 2023.

Abstract

Background: Satisfactory responses can be obtained for acute myeloid leukemia (AML) treated by Venetoclax (VEN)-based therapy. However, there are still quite a few AML patients (AMLs) resistant to VEN, and it is critical to understand whether VEN-resistance is regulated by senescence.

Methods: Here, we established and validated a signature for predicting AML prognosis based on VEN resistance-related senescence genes (VRSGs). In this study, 51 senescence genes were identified with VEN-resistance in AML. Using LASSO algorithms and multiple AML cohorts, a VEN-resistance senescence prognostic model (VRSP-M) was developed and validated based on 6-senescence genes.

Results: According to the median score of the signature, AMLs were classified into two subtypes. A worse prognosis and more adverse features occurred in the high-risk subtype, including older patients, non-de novo AML, poor cytogenetics, adverse risk of European LeukemiaNet (ELN) 2017 recommendation, and TP53 mutation. Patients in the high-risk subtype were mainly involved in monocyte differentiation, senescence, NADPH oxidases, and PD1 signaling pathway. The model's risk score was significantly associated with VEN-resistance, immune features, and immunotherapy response in AML. In vitro, the IC50 values of ABT-199 (VEN) rose progressively with increasing expression of G6PD and BAG3 in AML cell lines.

Conclusions: The 6-senescence genes prognostic model has significant meaning for the prediction of VEN-resistance, guiding personalized molecularly targeted therapies, and improving AML prognosis.

Keywords: acute myeloid leukemia; immunotherapy; prognosis; senescence; venetoclax resistance.

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This study was supported by a grant from the National Key R&D Program of China (2019YFA0111004), the National Natural Science Foundation of China (82170158), the Natural Science Foundation of the Jiangsu Higher Education Institutions of China (21KJD320002), and the Translational Research Grant of NCRCH (2021WSB01).