Cell-lineage level-targeted sequencing to identify acute myeloid leukemia with myelodysplasia-related changes

Abstract

Acute myeloid leukemia (AML) is a clonal myeloid neoplasm that typically arises de novo; however, some cases evolve from a preleukemic state, such as myelodysplastic syndrome (MDS). Such secondary AMLs and those with typical MDS-related clinical features are known as AMLs with myelodysplasia-related changes (AML-MRC). Because patients with AML-MRC have poor prognosis, more accurate diagnostic approaches are required. In this study, we performed targeted sequencing of 54 genes in 3 cell populations (granulocyte, blast, and T-cell fractions) using samples from 13 patients with MDS, 16 patients with clinically diagnosed AML-MRC, 4 patients with suspected AML-MRC but clinically diagnosed as AML not otherwise specified (AML-NOS), and 11 patients with de novo AML. We found that overlapping mutations, defined as those shared at least by the blast and granulocyte fractions, were significantly enriched in patients with MDS and AML-MRC, including those with suspected AML-MRC, indicating a substantial history of clonal hematopoiesis. In contrast, blast-specific nonoverlapping mutations were significantly enriched in patients with de novo AML. Furthermore, the presence of overlapping mutations, excluding DNMT3A, TET2, and ASXL1, effectively segregated patients with MDS and AML-MRC or suspected AML-MRC from patients with de novo AML. Additionally, the presence of ≥3 mutations in the blast fraction was useful for distinguishing patients with AML-MRC from those with MDS. In conclusion, our approach is useful for classifying clinically diagnosable AML-MRC and identifying clinically diagnosed AML-NOS as latent AML-MRC. Additional prospective studies are needed to confirm the utility of this approach.

Graphical abstract

Figure 1.

Frequency of mutations detected in the blast fraction among patients (n = 44) with MDS, clinically diagnosed AML-MRC, suspected AML-MRC, and de novo AML. A breakdown of the number of mutations within the different disease subsets also separated by mutational status (overlapping or nonoverlapping) within each disease subset is also shown. s/o, suspected of.

Figure 2.

Number of mutations in blast fraction identified in each disease subset. Each dot represents the number of mutations in the blast fraction in each patient. *P < .05, **P < .01.

Figure 3.

Overlapping mutational characteristics identified in the 3 cell fractions by targeted sequencing. Mutations present in blast cells (Bla), granulocytes (Gra), and T cells (Tc) in each of the 44 patients (UPN is shown in the second column from the left). Overlapping and nonoverlapping mutations are shown as red and yellow rectangles, respectively. When multiple mutations were identified in the same gene, only a representative mutation is shown for each case. The variant allele frequency (VAF) of each mutation is indicated by the horizontal width of the rectangle, with a maximum value set to 50%. Patient diagnosis (Dx) is shown in the far left-hand panel and is color coded according to the disease subset. The DNMT3A mutation in R882 residue is indicated by asterisks.

Figure 4.

Overlapping status of the same mutation between the blast fraction and granulocytes fraction (Granulo) based on disease subset. Shown are the VAFs of the same mutation from each patient in the blast fraction (x-axis) and in the granulocyte fraction (y-axis). In de novo AML, the green asterisks indicate mutations detected in AML with t(8;21), t(15;17), and inv16, whereas the green dots indicate mutations detected in NPM1-AML.

Figure 5.

Overlapping mutations are significantly enriched in MDS and AML-MRC. Each dot represents the number of overlapping mutations (A) and overlapping mutations except for DNMT3A, TET2, and ASXL1 (B) in each patient. Asterisks indicate the number of mutations detected in NPM1-AML. *P < .05, **P < .01. NS, not significant.

Figure 6.

Nonoverlapping mutations are significantly enriched in de novo AML. Each dot represents the number of blast-specific nonoverlapping mutations in each patient. Green asterisks indicate mutations detected in NPM1-AML. *P < .05, **P < .01.

Figure 7.

Disease classification model according to 2 mutational indices identified by targeted sequencing. (A) Shown is a hierarchical classification model for 3 disease-enriched subsets including de novo AML, AML-MRC, and MDS based on recursive partitioning analysis. Data from all 44 patients were analyzed to identify the optimal mutational indices that could best segregate patients within these 3 subsets. In each subset generated by partitioning analysis, the enriched diseases are highlighted in blue. (B) Shown is a receiver operating characteristic curve depicting the accuracy of classification based on this model. AUC, area under the curve.