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Abstract Background Myeloid malignancies, including Acute Myeloid Leukemia (AML) and Myelodysplastic Syndromes (MDS), are characterized by a complex spectrum of genetic mutations. These mutations play a critical role in the pathogenesis of the diseases and are essential for accurate diagnosis, prognosis, and the development of personalized treatment strategies. This study aimed to compare the molecular profiles of AML and MDS by analyzing a database of comprehensive NGS myeloid panel results, which concurrently evaluates DNA variants and gene fusions, to identify distinct mutational patterns and differences between these conditions. Methods A retrospective analysis was conducted on a de-identified dataset from myeloid panel tests applied at the time of diagnosis for myeloid malignancies during 2023. Cases indicated for AML and MDS testing were identified, and relevant demographic, specimen, and test outcome data were retrieved from the database. The dataset was compiled from data obtained using the AmpliSeq for Illumina Myeloid Panel, performed on the MiSeq system (both from Illumina). This panel targets 40 DNA genes (17 full-length, 23 hotspots) and 29 RNA fusion genes, covering 629 potential fusions, with a limit of detection at a 5% allele frequency. Variants were classified according to the CAP/ASCO/AMP guidelines on the Frankling (Genoox) platform. Demographic, specimen, and test outcome data—including gene fusions, mutated genes grouped by biological function (epigenetic regulators, signaling and kinase pathway genes, tumor suppressors, transcription factors, and RNA spliceosome), and DNA variants (limited to tiers 1 and 2)—were analyzed and compared using the Mann-Whitney U test or chi-square test, as appropriate. Results A total of 106 cases were evaluated, comprising 53 AML (31 females) and 53 MDS (25 females). The average age was 56.15±21.62 years for AML and 64.79±18.18 years for MDS (p=0.026). Blood sample distribution was 26 for AML and 33 for MDS (p=0.24). Fusion genes, found exclusively in AML, appeared in 34% (18/53) of cases (p0.0001), with the most common being CBFB::MYH11 (50%, 9/18) and RUNX1::RUNX1T1 (22%, 4/18). Somatic DNA variants were more prevalent in AML cases at 87% (46/53) compared to 64% (34/53) in MDS cases (p=0.012). There were 87 Tier 1/2 DNA variants in AML and 53 in MDS, with a median (min-max) of 2 (1-7) variants per case for AML and 1 (1-5) for MDS (p=0.02). For AML versus MDS, the distribution of DNA variants by mutated gene biological function was as follows: epigenetic regulators 29.88% (26/87) versus 33.96% (18/53), p=0.75, signaling and kinase pathway genes 31.03% (27/87) versus 5.66% (3/53), p=0.0008, tumor suppressors 16.09% (14/87) versus 11.32% (6/53), p=0.59, transcription factors 17.24% (15/87) versus 20.75% (11/53), p=0.76, and RNA spliceosome 5.75% (5/87) versus 28.30% (15/53), p=0.0005. Conclusions Our study underscored distinct molecular profiles for AML and MDS when both DNA variants and gene fusions are analyzed. AML cases were younger, displayed a higher frequency of gene fusions, and a greater diversity of DNA variants compared to MDS. AML cases also showed a higher prevalence of mutations in signaling and kinase pathway genes. MDS was characterized by a higher prevalence of mutations in RNA spliceosome genes.
Barra et al. (Tue,) studied this question.