Al‐Kali, Aref

Summary We describe our single institution experience with cladribine therapy in 42 patients with systemic mastocytosis (SM): 22 advanced (adv‐SM; median age 65 years, 68% males) and 20 indolent/smouldering SM (ISM/SSM; median age 56 years, 45% males); subcategories included eight aggressive, 13 associated with another haematological neoplasm, one mast cell leukaemia, 17 ISM and three SSM. Overall/major response rates were 77%/45% for adv‐SM and 70%/60% for ISM/SSM, and median (range) duration of response 10 (4–75) and 46 (4–140) months respectively. A >50% reduction in bone marrow mast cell burden and serum tryptase level was documented in 63% and 67% of patients with adv‐SM and 50% and 46% with ISM/SSM respectively. The presence of KIT proto‐oncogene, receptor tyrosine kinase ( KIT ) D816V predicted response in adv‐SM: 17 (90%) of 19 with and none of three without the mutation responded ( P < 0·01). Treatment‐emergent adverse events were mostly limited to transient cytopenias: Grade 3/4 neutropenia, thrombocytopenia, or lymphopenia occurred in 27%, 27% and 27% of patients with adv‐SM, and 5%, 5% and 30% with ISM/SSM respectively. The present study provides practical information that might be considered when making treatment choices between cladribine and newer KIT‐targeted therapies and identifies the absence of KIT D816V as a potential marker of cladribine resistance in advanced SM; the latter observation needs confirmation in a larger study.

Abstract DDX41 mutations (germline and somatic) are associated with late onset myelodysplastic syndromes/acute myeloid leukemia (MDS/AML). Myeloid neoplasms (MN) with germline predisposition was identified as a distinct category in the 2016 WHO classification revision, including MN with germline DDX41 mutation. We retrospectively analyzed the molecular findings and clinical characteristics of thirty-three DDX41-mutated (mDDX41) patients at our institution. We identified 14 distinct pathogenic DDX41 variants in 32 patients and 8 DDX41 variants of unknown significance (VUS) in 9 patients. Five (16%) patients had a second DDX41 somatic mutation p.R525H and 13 (40%) had at least one additional oncogenic co-mutation in other genes. The median age at the time of diagnosis was 66 years, with male predominance (72%) and the majority of patients had normal cytogenetics (91%). Two-year overall survival (OS) was 86% and 6 (21%) MDS/AML patients with relatively preserved hematopoietic function were observed without further intervention. In comparison to AML patients with prognostically more favorable subtypes [t(8;21), n=27 and inv(16), n=40], mDDX41 patients in our cohort showed similarly favorable OS. Our study highlights that mDDX41-MN patients often have an indolent course and mDDX41-AML has comparable OS to favorable-risk AML.

AbstractGermline predisposition syndromes (GPS) result from constitutional aberrations in tumor suppressive and homeostatic genes, increasing risk for neoplasia in affected kindred. In this study, we present clinical and genomic data on 144 Mayo Clinic patients with GPS; 59 evaluated prospectively using an algorithm‐based diagnostic approach in the setting of a dedicated GPS/ inherited bone marrow failure syndrome (IBMFS) clinic. Seventy‐two (50%) patients had IBMFS (telomere biology disorders‐32,Fanconi anemia‐18, Diamond Blackfan Anemia – 11, congenital neutropenia–5, Schwachman‐Diamond Syndrome‐5 and Bloom Syndrome‐1), 27 (19%) had GPS with antecedent thrombocytopenia (RUNX1‐FPD‐15, ANKRD26‐6, ETV6‐2, GATA1‐1, MPL‐3), 28 (19%) had GPS without antecedent thrombocytopenia (GATA2 haploinsufficiency‐16, DDX41‐10, CBL‐1 and CEBPA‐1) and 17 (12%) had general cancer predisposition syndromes (ataxia telangiectasia‐7, heterozygous ATM variants‐3, CHEK2‐2, TP53‐2, CDK2NA‐1, NF1‐1 and Nijmegen Breakage Syndrome‐1). Homozygous and heterozygous ATM pathogenic variants were exclusively associated with lymphoproliferative disorders (LPD), while DDX41 GPS was associated with LPD and myeloid neoplasms. The use of somatic NGS‐testing identified clonal evolution in GPS patients, with ASXL1, RAS pathway genes, SRSF2 and TET2 being most frequently mutated. Fifty‐two (91%) of 59 prospectively identified GPS patients had a change in their management approach, including additional GPS‐related screening in 42 (71%), referral for allogenic HSCT workup and screening of related donors in 16 (27%), medication initiation and selection of specific conditioning regimens in 14 (24%), and genetic counseling with specific intent of fertility preservation and preconceptual counseling in 10 (17%) patients; highlighting the importance of dedicated GPS screening, detection and management programs for patients with hematological neoplasms.

SummaryInstitutional database search (1999–2020) for acute myeloid leukaemia (AML) identified 109 cases of myeloid sarcoma (MS), of which 19 were isolated and presented de novo. The latter displayed longer survival (median 78 months), compared to MS with synchronous intramedullary AML (n = 32; median 16 months) and de novo AML without MS (n = 729; median 22 months; P = 0·13). However, the difference in survival was no longer apparent after accounting for bone marrow cytogenetic risk status (P = 0·67). Treatment‐induced MS tumour resolution was not affected by the presence of intramedullary disease (P = 0·61). The current study clarifies the prognosis of de novo isolated MS, in the context of AML.

The accurate diagnosis of chronic myelomonocytic leukemia (CMML) and acute myeloid leukemia (AML) subtypes with monocytic differentiation relies on the proper identification and quantitation of blast cells and blast-equivalent cells, including promonocytes. This distinction can be quite challenging given the cytomorphologic and immunophenotypic similarities among the monocytic cell precursors. The aim of this study was to assess the performance of convolutional neural networks (CNN) in separating monocytes from their precursors (i.e., promonocytes and monoblasts). We collected digital images of 935 monocytic cells that were blindly reviewed by five experienced morphologists and assigned into three subtypes: monocyte, promonocyte, and blast. The consensus between reviewers was considered as a ground truth reference label for each cell. In order to assess the performance of CNN models, we divided our data into training (70%), validation (10%), and test (20%) datasets, as well as applied fivefold cross validation. The CNN models did not perform well for predicting three monocytic subtypes, but their performance was significantly improved for two subtypes (monocyte vs. promonocytes + blasts). Our findings (1) support the concept that morphologic distinction between monocytic cells of various differentiation level is difficult; (2) suggest that combining blasts and promonocytes into a single category is desirable for improved accuracy; and (3) show that CNN models can reach accuracy comparable to human reviewers (0.78 ± 0.10 vs. 0.86 ± 0.05). As far as we know, this is the first study to separate monocytes from their precursors using CNN.