Oligomonocytic chronic myelomonocytic leukemia (OM-CMML) is defined as those myelodysplastic syndromes (MDSs) or myelodysplastic/myeloproliferative neoplasms, unclassifiable with relative monocytosis (≥10% monocytes) and a monocyte count of 0.5 to <1 × 109/L. These patients show clinical and genomic features similar to those of overt chronic myelomonocytic leukemia (CMML), although most of them are currently categorized as MDS, according to the World Health Organization 2017 classification. We analyzed the clinicopathologic features of 40 patients with OM-CMML with well-annotated immunophenotypic and molecular data and compared them to those of 56 patients with overt CMML. We found similar clinical, morphological, and cytogenetic features. In addition, OM-CMML mirrored the well-known complex molecular profile of CMML, except for the presence of a lower percentage of RAS pathway mutations. In this regard, of the different genes assessed, only CBL was found to be mutated at a significantly lower frequency. Likewise, the OM-CMML immunophenotypic profile, assessed by the presence of >94% classical monocytes (MO1s) and CD56 and/or CD2 positivity in peripheral blood monocytes, was similar to overt CMML. The MO1 percentage >94% method showed high accuracy for predicting CMML diagnosis (sensitivity, 90.7%; specificity, 92.2%), even when considering OM-CMML as a subtype of CMML (sensitivity, 84.9%; specificity, 92.1%) in our series of 233 patients (39 OM-CMML, 54 CMML, 23 MDS, and 15 myeloproliferative neoplasms with monocytosis and 102 reactive monocytosis). These results support the consideration of OM-CMML as a distinctive subtype of CMML.

INTRODUCTION The 2017 WHO classification requires the presence of ≥1x109/L and ≥10% of monocytes in peripheral blood (PB) for the diagnosis of CMML. Recently, Geyer et al. defines oligomonocytic CMML (O-CMML) as those MDS cases with relative monocytosis (≥10% monocytes) and monocyte count 0.5<1x109/L. The authors showed that clinicopathologic and mutational profile of OCMML were similar to overt CMML. The study of PB monocyte subsets by flow cytometry (FC) has gained interest for CMML diagnosis. As showed by Selimoglu-Buet et al, the increase of classical monocytes (Mo1) >94% is a highly sensitive and specific diagnostic marker for CMML. In the extent of our knowledge, there are no data about PB monocyte subset distribution by FC in O-CMML. Moreover, CD2 and CD56 expression is common in CMML and rarely observed in MDS, the group where O-CMML are currently included. Furthermore, we compared: the molecular profile; cytogenetic abnormalities; cytopenias; BM dysplasia; BM blast and monocyte percentage; PB monocyte percentage, and monocyte and leukocyte counts. METHODS 50 CMML and 33 O-CMML from a single institution were prospectively studied from 02/2016 to date. Table 1 summarizes morphologic, cytogenetic, molecular and clinical findings. We studied PB monocyte subsets by FC: Mo1 (CD14bright/CD16-), Mo2 (CD14bright/CD16+) and Mo3 (CD14dim or -/CD16bright). In addition, we assessed the expression of CD56 and CD2 in monocytes (positivity ≥ 20%). Finally, targeted NGS of the entire exonic sequence of 25 genes recurrently mutated in myeloid malignancies was performed (VAF sensitivity: 2%). Chi-Square, Fisher exact or Man-Whitney U tests were used as appropriate. RESULTS AND DISCUSSION The Mo1 percentage (%) was significantly inferior in O-CMML (P=0.007), but it is noteworthy that median and mean of Mo1% in O-CMML were upper the cutoff of 94% (median: 96.1 vs 98.1; mean: 94.7 vs 96.9). Moreover, the % of patients with >94% Mo1 was no significantly different when comparing O-CMML and CMML although a clear trend was observed (72% vs 90%; P=0.082). This result is impressive since, as previously reported, the specificity of the Mo1 >94% test is around 90-95% and only 5-10% of false positive rate (FP) should be expected. However, in O-CMML a 72% of FP was observed since following 2017 WHO recommendation these patients should be considered as MDS. No differences were observed neither in the % of patients showing CD56+ monocytes (65.6% vs 66.7%; P=0.923) nor in the % of them showing CD2+ (28.1% vs 37.5%; P=0.53) when comparing O-CMML and CMML. We observed no significant differences in platelet count, hemoglobin, BM dyserythropoiesis, BM dysgranulopoiesis, BM dysmegacaryopoiesis, BM blast %, percentage of abnormal karyotypes, and Spanish cytogenetic risk stratification. The main differences were observed in leukocyte count, monocyte count, PB monocyte %, BM monocyte %, and BM promonocyte percentage. Table 1. There were no differences in the number of mutated genes or in the number of mutations between CMML and O-CMML (Table 1). As expected, TET2 and SRSF2 were the most frequently mutated genes in both groups. Moreover, no significant difference was observed in the presence of TET2/SRSF2 co-mutation, the gene signature of CMML (32% vs 26% in CMML). The genes mutated at a frequency >10% in O-CMML were: TET2 (79%), SRSF2 (36%), SF3B1 (29%), ZRSR2 (25%), DNMT3A (15%), and ASXL1 (14%). The genes mutated at a frequency >10% in CMML were: TET2 (81%), SRSF2 (28%), ASXL1 (23%), CBL (23%), SF3B1 (16%), and NRAS (14%). Only two genes were mutated at a significant different frequency: CBL (4% vs 23% in CMML, P=0.041) and ZRSR2 (25% vs 7% in CMML, P=0.043). As expected, CMML showed a higher % of RAS pathway mutations (CBL, NRAS or KRAS) since these have been associated with proliferative features (4% vs 40%, P=0.001). This is especially evident in proliferative CMML in which genes associated with proliferation are present at higher frequencies: CBL (4% vs 39% in CMML, P=0.01), NRAS (0 vs 23% in CMML, P=0.029) and ASXL1 (14% vs 62% in CMML, P=0.004). A significant lower percentage of O-CMML with ZRSR2mut presented Mo1 >94% (33% vs 86%, P=0.024). As shown, O-CMML without ZRSR2mut showed this feature in a similar percentage than CMML (86% vs 90%). At a median follow-up of 31.2 months, 19% of O-CMML evolved to CMML showing a median time to evolution of 34 months. CONCLUSION Our data support the diagnosis of O-CMML as a distinctive subtype of CMML. Table 1 Disclosures Bellosillo: Qiagen: Consultancy, Speakers Bureau; TermoFisher Scientific: Consultancy, Speakers Bureau.

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Introduction The majority of prognostic indexes in CMML include information extracted from bone marrow (BM) evaluation. The blast count in BM in CMML includes the blast and promonocyte percentage. In the extent of our knowledge there are no data evaluating whether both cells have an equivalent prognostic weight for predicting survival. Recent data indicate that an accurate diagnosis of CMML could be established by assessing the monocyte population distribution by flow cytometry and by evaluating its molecular profile by targeted next-generation sequencing in PB. Our aim was to analyze which variables from our series had an independent prognostic value in order to assess if their addition to the most common prognostic scores for CMML, CPSS and Mayo prognostic model (Mayo), contributed to increase their predictive capacity; or if they allowed us to create a new one. Methods One hundred and fifty patients diagnosed with CMML from 1975 to 2019 from a single institution were evaluated. All patients met 2017 WHO criteria. Complete information was available for the following: BM blast percentage, BM promonocyte percentage, PB blast percentage, circulating immature myeloid cells (IMC), presence of Auer rods and complete blood count. The median overall survival (OS) was 35 months (CI 95%: 30-40). We performed univariate and multivariate survival analyses to establish the prognostic weight of each one. Both C-index and Somers'D (Dxy) were used to compare the prognostic accuracy of the different models. Results Patients characteristics are depicted in Table 1. The prognostic impact of the following items was reviewed: BM blasts; BM promonocytes; the sum of BM blasts and promonocytes; proliferative CMML (CMML-P); monocyte count ≥ 5 x 109/L; transfusional dependency; Hb < 100 g/L; platelets < 100 x 109/L; IMC; PB blasts; abnormal karyotype; spanish cytogenetic risk classification; sex, and dysmegacaryopoiesis, dysgranylopoiesis and dyserythropoiesis according to WHO criteria. In the univariate analysis for the OS only the following demonstrated an adverse impact: sex (women 50.7m vs men 33.4m, P=0.023), PB blasts (39m vs 11m, P<0.001), BM blasts ≥ 10% (35.7m vs 21.6m, P=0.033), Hb < 100 g/L (40.9m vs 21.7m, P=0.001), platelets < 100 x 109/L (40.9m vs 31.6m, P=0.004), abnormal karyotype (39.4m vs 31.6, P=0.01), spanish cytogenetic risk classification (37.5m vs 5.4m vs 9.2m, P=0.001), monocyte count ≥ 5 x 109/L (31.6m vs 35.7m, P=0.02), and leucocyte count ≥ 13 x 109/L (24.1m vs 39.8m, P=0.005). As shown, we did not observed an adverse impact on OS when assessing the percentage of promonocytes as continuous variable or categorized at 5% or 10% cut-offs. Only PB blasts, Hb < 100 g/L and platelets < 100 x 109/L maintained their adverse impact in a multivariate cox regression analysis including all the variables that showed an impact in the univariate analysis. These variables maintained their independent prognostic impact when adjusted for sex and age. The Hazard Ratios (HR) were: 2.9, 1.9, 1.7 for PB blasts, Hb and platelets The CPSS and Mayo prognostic model accurately stratified the prognosis in our series, having the last one a higher predictive capacity for the OS (C-index: 0.62 vs 0.65; Dxy: 0.24 vs 0.3). The prognostic accuracy of the CPSS improved when the platelets were added (CPSS-P) (C-index 0.63; Dxy: 0.26). Given the prognostic weight of the three values described, we developed a score based on these: platelets < 100 x 109/L, 0.5 points; Hb < 100g/L, 1 point, and PB blasts, 2 points. The MAR score (Figure 1) segmented the series in three risk categories with significant differences in OS: low (0 points), median OS 54m; intermediate (0.5-1 points), median OS 33m; and high (1.5-3.5 points), median OS 15m. The MAR score showed a better value for C-index (0.66) and Dxy (0.32) than the rest of scores assessed. Conclusions The variables with an independent adverse prognostic value for OS in our series were: Hb < 100 g/L, platelets 100 x 109/L and the presence of blasts in PB. The MAR score, a model based on them showed the best predictive capacity for OS in our series. Disclosures No relevant conflicts of interest to declare.