Session: 617. Acute Myeloid Leukemia: Biology, Cytogenetics, and Molecular Markers in Diagnosis and Prognosis: Poster I
Hematology Disease Topics & Pathways:
AML, Diseases, Myeloid Malignancies
We studied the clinical and genomic characteristics of fully annotated sets of 198 AYA-AML and 414 E-AML cases from the Cleveland Clinic and publicly available data. Median age at diagnosis was 31 years for AYA-AML (range: 16-39 years) and 76 years (range: 71-100 years) for E-AML patients with a significant male preponderance noted in the latter cohort (65% vs 46%, P<0.0001). Based on the 2016 WHO classification, AML subtypes were differently distributed within the two subgroups. Low-risk AML (PML-RARA AML, core-binding factor AML, and CEBPA biallelic AML) was more prevalent among AYA cases while a higher odd of secondary AML (sAML) was found in E-AML. Compared to AYA-AML, E-AML were more typically presenting with a less proliferative disease phenotype, as outlined by a lower bone marrow blast infiltration (median: 34% vs 51%, P=0.04) and a higher frequency of leukopenia at baseline (66% vs 27%, P=0.009). In terms of cytogenetic abnormalities, when compared with AYA-AML, E-AML cases harbored more complex karyotype (32% vs 13%, P=0.002) and other cytogenetic abnormalities e.g., -5/del(5q) (14% vs 2%, P<0.0001), -7/del(7q) (14% vs 5%, P=0.001), -17/del(17p) (5% vs 1%, P=0.02), del(20q) (4% vs <1%, P=0.01) and trisomy 8 (14% vs 5%, P=0.0007) while a significantly lower odd of -9/del(9q) (<1% vs 4%, P=0.006).
A total of 1092 somatic mutations were identified by next-generation sequencing of common myeloid genes. The AYA-AML cohort had a total of 249 mutations (ratio 1.25) while 843 mutations were reported in E-AML patients (ratio 2.04). Older patients, as compared to AYA-AML, had more mutations in age-related myeloid genes linked to clonal hematopoiesis, including mutations in DNMT3A (15% vs 6%, P=0.001), ASXL1 (14% vs 4%, P=0.0005), and TET2 (19% vs 7%, P=0.0002). As inferred from the cytogenetic comparisons, TP53 mutations were more frequently detected in E-AML (10% vs 2%, P=0.002) compared to AYA-AML, as they carried more chromosomal 5 and 17 abnormalities which are commonly associated with this genomic lesion. On the other hand, AYA-AML had a higher frequency of mutated WT1 gene (9% vs 2%, P=.0009). Multivariate Cox-Proportional hazard was performed to identify group-specific genomic lesions associated with survival in each cohort. In AYA-AML, normal karyotype (HR:0.59, P=0.02), t(15;17) translocation (HR:0.24, P=0.0001), inv(16)/t(8;21) (HR:0.52, P=0.02) and CEBPA biallelic (HR:0.50, P=0.02) were favorable lesions while complex karyotype had an adverse impact on survival (HR:3.0, P=0.0003). Moreover, while normal karyotype and t(15;17) translocation had a favorable impact in E-AML (HR:0.73, P=0.0001 and HR:0.28, P<0.0001, respectively), mutations in RUNX1 (HR:1.2, P=0.4), TET2 (HR:1.2, P=0.01), and TP53 (HR:1.97, P<0.0001) lead to worse outcomes.
In conclusion, we demonstrated that E-AML cases are typically characterized by mutations belonging to the genomic subgroups of DNA methylation and chromatin modifiers, which have been reported to occur in age-related hematopoiesis or CHIP. Moreover, the complexity of aberrations (including cytogenetics) emphasizes that in this group of patients AML arises from a stepwise mutation acquisition model. In contrast, AYA-AML are typically characterized by favorable cytogenetic translocations and less clonal instability, dominated by the enrichment in myeloid leukemia driver gene mutations such as WT1.
Disclosures: No relevant conflicts of interest to declare.