EXPLORATION OF MUTATIONAL PATTERNS AND THEIR IMPACT ON THE IMMUNE EXPLORATION OF MUTATIONAL PATTERNS AND THEIR IMPACT ON THE IMMUNE MICROENVIRONMENT IN ACUTE MYELOID LEUKEMIA THROUGH IN SILICO ANALYSES

Acute myeloid leukemia (AML) is a hematological malignancy characterized by significant genetic and prognostic heterogeneity. Identifying recurrent mutations in genes such as FLT3, NPM1, DNMT3A, RUNX1, ASXL1, IDH1/IDH2, and TP53 is crucial for risk stratification and therapeutic personalization. However, understanding the interactions between these mutations and their impact on the AML immune microenvironment remains limited. This study aims to integrate the analysis of mutations present in AML patients to identify genetic patterns that influence disease prognosis and treatment response. Using public data from 671 patients from the Beat AML2.0 database, we investigated the frequency and co-occurrence of mutations in genes relevant to AML pathogenesis and their association with the hematopoietic microenvironment and cellular subtypes. Statistical analysis was performed using the Kruskal-Wallis test, p < 0.05 considered significant, followed by Dunn’s post-hoc test adjusted by the Bonferroni method. Our analysis identified the presence or absence of mutations in FLT3 (23.55%), NPM1 (25.93%), DNMT3A (14.60%), IDH2 (8.49%), TP53 (8.94%), and RUNX1 (12.82%) were detected in significant proportions, highlighting their role in AML biology. Less frequent mutations were found in GATA1 (0.74%) and KRAS (3.72%), which, though limited in their role, may contribute to AML pathogenesis in specific cases. FLT3 and NPM1 mutations predominated in de novo AML patients, indicating their relevance in this clinical context, which aligns with the prevalence observed in our cohort. Conversely, TP53 mutations were more common in secondary AML, often associated with poorer prognosis. Recurrent mutations in AML are believed to distinctively influence the hematopoietic microenvironment, promoting uncontrolled proliferation or aberrant differentiation, which could determine immune outcomes. We also analysis common AML mutations in specific cellular subpopulations. FLT3-ITD, DNMT3A, NPM1, and NRAS mutations frequently occurred in effector memory CD8 T cells, suggesting an association with increased presence or activation of this cell type. Similarly, RUNX1, NRAS, KMT2A, DNMT3A, CEBPA, and ASXL1 mutations exhibited higher scores in hematopoietic stem cells, indicating a potential impact on early hematopoiesis. KRAS and TET2 mutations showed notable distribution in mesenchymal stem cells. GATA1 mutations were frequent in NK cells, while other mutations had low scores in this immune cell type. Notably, the KMT2A mutation was linked to a multifaceted influence, affecting both early hematopoiesis and immune subtypes. Although mutations in the FLT3/NPM1 groups did not show significant differences in cellular distribution, phenotypic variations seem more reflective of the broader molecular context of the disease than of specific alterations in cellular subtypes. Investigating the impact of these mutations on the cellular microenvironment revealed that FLT3-ITD, DNMT3A, and NPM1 were associated with effector memory CD8 T cell activation, while RUNX1, KMT2A, DNMT3A, and ASXL1 mutations showed increased expression in hematopoietic stem cells, suggesting a role in hematopoiesis regulation. These findings reinforce the hypothesis that mutations in AML not only drive neoplastic proliferation but also influence the immune and hematopoietic microenvironment, potentially affecting treatment response.