Abstract
Acute myeloid leukemia (AML), a highly prevalent hematological malignancy, heavily relies on animal models that can mimic the genetic and biological characteristics of the disease for research advancement. Among various modeling approaches, genetically engineered animal models have emerged as critical tools for deciphering AML pathogenesis and developing novel therapies, leveraging their precise gene targeting, robust experimental reproducibility, and diverse model types. These models not only enable meticulous dissection of gene functions but also highly simulate human disease traits, fulfilling the needs of diversified research, thus gaining widespread favor among researchers. The mainstream genetically engineered animal models for AML currently mainly cover four categories: Mouse models dominate mechanistic research due to their highly humanized hematopoietic system and compatibility with complex gene-editing technologies such as CRISPR (e.g., PML-RARA fusion gene models). However, limitations such as heterogeneity in the immune microenvironment and long reproductive cycles deserve attention. Zebrafish models serve as efficient platforms for early drug screening (e.g., NHA9 mutation models) due to the transparency of their embryos. However, the absence of an adaptive immune system and pathological discrepancies in some subtypes with human conditions restrict their application scope. Rhesus monkey models possess unique value in preclinical safety evaluations due to their highly conserved genetic and physiological characteristics (e.g., CD33 gene-editing models). However, the high experimental costs and ethical constraints must be balanced. Drosophila models achieve efficient gene regulation through the UAS-Gal4 system (e.g., RUNX1-ETO fusion gene models), demonstrating significant advantages in large-scale genetic screening. Nevertheless, issues such as insufficient complexity of the hematopoietic system and the absence of key genes still require careful consideration. This article describes the characteristics and application scenarios of these four model types, aiming to provide references for researchers to optimize model selection strategies and develop novel tools.
