Degree of Aberrant Antigen Expression in Myelodysplastic Syndromes Correlates with the Number of Molecular Mutations

Introduction: The diagnostic approach for suspected myelodysplastic syndromes (MDS) is evolving and flow cytometry and molecular genetics are increasingly considered to be applied in addition to cytomorphology and cytogenetics. While reports on comparisons of flow cytometric findings with results of cytomorphology and cytogenetics are available, data on comparisons between results obtained by flow cytometry and molecular genetics, however, have not yet been presented in detail.

Aims: 1) To assess the correlation between flow cytometric findings on MDS-specific aberrant antigen expression and the presence of molecular mutations in patients with cytomorphologically proven MDS. 2) To determine the respective impact of flow cytometric findings and of molecular mutations on survival in patients with MDS.

Patients and methods: In 256 patients (male/female, 161/95; median age 72 years, range 24-90) with proven MDS (137 low-risk MDS, 119 RAEB1/2) we compared data on aberrantly expressed antigens (AEA) determined according to ELN guidelines (Westers, Leukemia 2012) to the previously published mutational status of 104 genes (Haferlach, Leukemia 2014).

Results: Median numbers (ranges) of AEA were 0 (0-3) in myeloid progenitors, 2 (0-4) in granulocytes, 1 (0-5) in monocytes and 0 (0-1) in erythroid cells. Median number of mutation was 2 (0-7). The number of AEA in myeloid progenitors, granulocytes and monocytes increased with increasing number of mutations (r=0.257, p<0.001). Accordingly, in cases with ≥3 mutations the number of AEA in myeloid progenitors, granulocytes and monocytes was higher than in cases with ≤2 mutations (mean±SD, 3.9±1.9 vs. 3.0±2.0, p=0.001). This correlation was significant also when considering granulocytes as a single cell compartment (r=0.308, p<0.001) but non-significant trends only for myeloid progenitors and monocytes. No such correlation was observed for erythroid cells. Specifically, mutations in each of the genes TET2, ASXL1, SRSF2, STAG2, ZRSR2 or NF1 were associated with significantly higher numbers of AEA in ≥1 cell compartment. Cases with mutations in ≥1 of these genes (n=145), as compared to those without these 6 mutations (n=111), had higher numbers of AEA in myeloid progenitors (0.4±0.7 vs. 0.2±0.5, p=0.037), granulocytes (2.0±1.1 vs. 1.4±1.1, p<0.001) and monocytes (1.5±1.3 vs. 1.0±1.0, p=0.002). Consequently, the difference in the total of AEA was even larger (3.9±2.0 vs. 2.7±1.9, p<0.001). Regarding scoring points according to IPSS-R, there was a significant correlation with the number of AEA in granulocytes (r=0.189, p=0.004) as well as with the number of AEA in monocytes (r=0.159, p=0.017). Consequently, there was also a significant correlation between the IPSS-R scoring points and the number of AEA in myeloid progenitors, granulocytes and monocytes (r=0.227, p=0.001). Overall survival was impacted by the presence of mutations in ≥1 of the genes TP53, EZH2, ETV6, RUNX1 and ASXL1 (p<0.001, HR 2.9) published by Bejar (NEJM 2011) as well as by the presence of ≥3 AEA in myeloid progenitors, granulocytes and monocytes (p=0.015, HR 1.7) and by IPSS-R (p<0.001, HR 1.4). Multivariate analysis considering mutations and AEA revealed an independent significance for both of them (mutations, p<0.001, HR 2.9; AEA, p=0.017, HR 1.7). However, inclusion of also IPSS-R as a covariate resulted in a trend only for AEA (p=0.16, HR 1.4) and independent significance for mutations (p<0.001, HR 2.3) and IPSS-R (p<0.001, HR 1.3).

Conclusions: This data demonstrates that the degree of flow cytometric findings on MDS-related aberrant antigen expression correlates with the number of molecular mutations as well as with the IPSS-R. The present result therefore further support the consideration of both flow cytometry and molecular genetics for the diagnostic work-up of MDS in an integrated approach in combination with cytomorphology and cytogenetics.