Development of a poor-prognostic-mutations derived immune prognostic model for acute myeloid leukemia

Leukemia cell-intrinsic somatic mutations and cytogenetic abnormalities have been used to define risk categories in acute myeloid leukemia (AML). In addition, since the immune microenvironment might influence prognosis and somatic mutations have been demonstrated to modulate the immune microenvironment in AML, there is need for developing and evaluating an immune prognostic model (IPM) derived from mutations associated with poor prognosis. Based on AML cases with intermediate and adverse-cytogenetic risk in the Cancer Genome Atlas (TCGA) database, 64 immune-related differentially expressed genes (DEGs) among patients with RUNX1, TP53, or ASXL1 mutations and patients without these mutations were identified. After Cox proportional hazards analysis, an IPM composed of PYCARD and PEAR1 genes was constructed. IPM defined high-risk (IPM-HR) independently predicted lower 2-year overall survival (OS) rates in both patients with intermediate and adverse-cytogenetic risks and non-M3 patients in the TCGA AML cohort. The poor prognostic impact of IPM-HR on OS was further validated by GSE71014, 37642, and 10358 downloaded from the Gene Expression Omnibus (GEO) database. Furthermore, IPM-HR was remarkably associated with higher proportions of CD8+T cells and regulatory T cells (Tregs), lower proportions of eosinophils, and higher expression of the checkpoint molecules CTLA-4, PD-1, and LAG3 in the TCGA non-M3 AML cohort. In summary, we developed and validated an IPM derived from mutations related with poor prognosis in AML, which would provide new biomarkers for patient stratification and personalized immunotherapy.

Automated summary

The study identified 64 immune-related differentially expressed genes (DEGs) associated with mutations in AML and developed an immune prognostic model (IPM) composed of PYCARD and PEAR1 genes, which independently predicted lower 2-year overall survival rates in AML patients. The IPM was validated in different databases and found to be associated with specific immune cell proportions and expression of checkpoint molecules in the AML cohort. The IPM derived from poor prognosis mutations in AML provides new biomarkers for patient stratification and personalized immunotherapy.