Establishment and verification of a TME prognosis scoring model based on the acute myeloid leukemia single-cell transcriptome.

The tumor microenvironment (TME) plays an important role in the occurrence and progression of Acute Myeloid Leukemia (AML). Single-cell sequencing has enabled researchers to explore the correlation between TME subgroups and tumor prognosis, distinguish the existence of drug-resistant subgroups of tumor cells, and unravel the complexity of the AML cellular heterogeneity. We used bone marrow immune cell enrichment analysis from public databases to screen prognostic genes, construct prognostic models, and validate their prognostic significance on independent external datasets and patient samples. A total of 18,251 single cells were obtained to establish prognostic scoring models for 10 key genes including CCL5, ETLS2, and IL2RA.The AML cases were divided into two groups: high-risk and low-risk. The low-risk group exhibited a higher survival rate than the high-risk group. The areas under curves (AUC) of 1-, 3- and 5-year survival curves in the TCGA and GEO training sets were greater than 0.8 and 0.6, respectively, indicating effective prediction. The model's prognostic efficacy was confirmed across multiple validation sets. It demonstrated increased expression of ETS2, CCL5, and IL2RA in AML samples compared to controls, which was associated with decreased overall survival (OS). This prognostic scoring model based on tumor immune infiltration provides a reference for developing novel treatment strategies for recurrent/refractory AML.