Patnaik, Mrinal M.

Introduction HMAs are the only approved therapy for CMML. In order to improve response rates and survival, the addition of VEN has been utilized in both CMML and after blast transformation (CMML-BT) with conflicting results in small single center studies. To clarify the role of upfront HMA+VEN in CMML and CMML-BT, we performed a large multicenter analysis. Methods We included patients with HMA-naïve CMML and CMML-BT treated with combination HMA and VEN from 4 academic centers. The primary outcome was overall survival (OS) with secondary outcomes including overall response rate (ORR) by 2015 MDS/MPN IWG criteria for CMML and 2022 ELN criteria for CMML-BT. To better appreciate the benefit of adding VEN to HMA treatment, we also performed 1:1 propensity score matched (PSM) analysis of patients treated with HMA alone as upfront therapy for CMML or CMML-BT. Matching was based on age, sex, ECOG performance status, CPSS-Mol, blood counts, peripheral and bone marrow blasts. Results Eighty-nine patients were treated with frontline HMA+VEN, 51 CMML and 38 CMML-BT (5 had received HMA alone for prior CMML). The median age was 71 years, 70% were male, and 83% had ECOG 0-1. Among CMML patients, 55% had MP-CMML subtype, 65% had CMML-2 and 12%, 30%, 58% were CPSS-mol intermediate-1, intermediate-2 and high risk, respectively. In the entire cohort, ASXL1 (63%), TET2 (47%), SRSF2 (39%) and RUNX1 (27%) were the most commonly mutated genes and 55% of patients harbored a RAS mutation ( KRAS [20%], NRAS [18%], CBL [13%], NF1 [11%], PTPN11 [9%]). For HMA combination partner, 46 (52%) were treated with azacitidine, 35 (39%) with decitabine, and 8 (9%) with both during their VEN course. During a median follow-up time of 15.8 months (mos) 52 patients (58%) died: 23 (45%) with CMML and 29 (76%) with CMML-BT. Among CMML patients, the ORR was 90%, including complete remission (CR) in 22%, complete cytogenic remission (CCR) in 4%, optimal marrow response (CMR) in 50%, and partial marrow response (PMR) in 6%. The OS of CMML patients was 25.1 mo (95% CI 15.7 - NR). A PSM population of HMA patients matched to HMA+VEN treated patients showing similar baseline characteristics. ORR was significantly higher with HMA+VEN (95%) as compared those treated with HMA alone (46%), p < 0.001. However, there was no significant OS difference between HMA+VEN vs HMA alone (19.1 mos vs 19.1 mos, p = 0.85, Figure 1). For CMML-BT patients, the ORR of HMA+VEN was 81% including CR in 17%, CR with partial hematologic recover (CRh) in 3%, CR with incomplete hematologic recovery (CRi) in 28%, morphologic leukemia-free state (MLFS) in 22% and partial response (PR) in 11%. The OS of CMML-BT patients was 8 mos (95% CI 4.6 - 26.2). A PSM population of CMML-BT patients treated with HMA alone showed a significantly increased ORR with HMA+VEN (82% vs 40%, p = 0.039). However, there was no difference in OS (7.49 mos vs 9.26 mos, p = 0.83, Figure 2). Among HMA-VEN treated patients, achievement of a CR was associated with an improved OS in the CMML (HR 0.31, 95% CI 0.13 - 0.75) and CMML-BT (HR 0.37, 95% CI 0.19 - 0.74). No predictors of response were identified, including the presence of a RAS mutation. In terms of safety, 7 patients (7.9%) had a grade 3/4 (G3/4) neutropenic infection and 2 patients (2.2%) had a G3/4 hemorrhagic event while being treated with HMA+VEN. A total of 29 patients went on to receive allogeneic transplant (alloSCT): 22 (43%) with CMML and 7 (18%) with CMML-BT. CMML patients who underwent alloSCT after HMA+VEN were younger as compared to non-transplanted patients (64 vs 74 years, p < 0.0001), but had otherwise similar baseline characteristics including stage, CPSS-mol category and prevalence of RAS mutations. Similarly, CMML-BT patients bridged to alloSCT were younger (66 vs 74 years, p < 0.002) and had a better ECOG performance status (p = 0.047). Of patients who received alloSCT, 10 patients (34%) died, 5 with CMML and 5 with CMML-BT. The median OS after alloSCT was 26.7 mo. Conclusions Although the use of VEN with HMA in the upfront treatment of CMML and AML secondary to CMML results in higher response rates compared to HMA alone, this combination does not improve survival based on this multi-center PSM analysis. The current sample size of CMML-BT may limit detection of OS differences between treatment groups. The role of VEN to reduce blasts and serve as a bridge to alloSCT, particularly after HMA failure, requires further investigation in larger studies in both the CMML and CMML-BT populations.

Background. The inclusion of gene mutations and chromosomal abnormalities in the 2022 WHO and ICC Classifications of MDS has enhanced diagnostic precision and is expected to improve clinical decision-making process. Although these two systems share similarities, clinically relevant discrepancies still exist and potentially cause inconsistency in their adoption in a clinical setting. In this study on behalf of the International Consortium for MDS (icMDS), we adopted a data-driven approach to provide a harmonization roadmap between the 2022 WHO and ICC classification for MDS. A modified Delphi Process consensus approach is currently ongoing among icMDS experts to finalize a harmonized MDS classification scheme. Methods. We analyzed retrospective international cohorts of patients with a diagnosis of MDS (n=7017) and AML (n=1002) according to WHO 2016 criteria. Hierarchical Dirichlet Processes were applied to define clusters capturing broad dependencies among all gene mutations and cytogenetic abnormalities. To investigate the features of importance and their impact on the clustering process, we employed the SHapley Additive exPlanations approach (SHAP). This allowed to define harmonized labels for each clinical entity. The clinical relevance of the unsupervised clustering was assessed through the analysis of phenotypic features and outcomes among each group. ( Blood 2022;140: 9828-9830) Results. Patients' characteristics are summarized in Table 1. We identified 9 clusters, defined by specific genomic features. The cluster of highest hierarchical importance was characterized by biallelic inactivation of TP53 (biTP53). According to SHAP analysis, bi TP53 was defined as 2 or more TP53 mutations, or 1 mutation with copy number loss or cnLOH. Most patients assigned to bi TP53 cluster had TP53 VAF>10% (77.9%) and complex karyotype (70.1%). Assignment to bi TP53 cluster was irrespective of blast count. Patients with monoallelic TP53 mutation segregated into other clusters. Hierarchically, the second cluster included patients with del(5q). SHAP analysis highlighted 5q deletion alone, or with one other chromosomal abnormality other than -7, and absence of bi TP53, as the most relevant features. Most of these patients had blast counts <5% (88.1%). The third distinct cluster included patients with SF3B1 mutations (in the absence of concurrent del(7q), abn3q26.2, complex karyotype or RUNX1 mutation). Most patients with MDS and SF3B1 mutation had <5% blasts (94.2%). Common co-mutated variants in the SF3B1 cluster included mutant DNMT3A (25.2%) and TET2 (38.3%). Morphologically defined MDS cases (i.e., not meeting criteria for bi TP53, del(5q) or SF3B1) were preferentially assigned to the following additional clusters: SF3B1 and concurrent higher-risk mutations (e.g., RUNX1 and ASXL1); SRSF2 and concomitant TET2 mutations; U2AF1 mutations with del(20q), del(7q) or -7; SRSF2 with TET2 mutations and co-mutational patterns including RUNX1 and ASXL1; and AML-like genomic signatures. Our analyses suggest that morphologically defined MDS is characterized by a large heterogeneity in terms of mutation profiles, not entirely captured by the presence of unilineage versus multilineage dysplasia, percentage of bone marrow blasts, and presence of hypocellularity and fibrosis. To better investigate the continuum between high risk MDS (i.e., patients with ≥10% blasts) and AML, an exploratory comparison was made using a cohort of AML (defined according to WHO 2016) patients analyzed using the same statistical methods. Only a partial overlap in genetic signatures was observed between MDS with ≥10% blasts and AML. However, similarities were observed between the AML-like MDS clusters (characterized by mutant NPM1, bZIP CEBPA, and Core Binding Factor abnormalities) and AML clusters defined by the same genetic signature, thus supporting the classification of these entities as AML, irrespective of blast count. Conclusion. Our study demonstrated the utility of a data-driven approach based on advanced statistical methods to generate a harmonized classification for MDS. Table 2 shows a provisional, hierarchical classification algorithm. Further refinement of entity labels and classification criteria is the subject of the ongoing modified Delphi Process consensus approach among icMDS experts.

BACKGROUND: The association between myeloid neoplasm (MN) and autoimmune rheumatological diseases (AIRD) is increasingly recognized. Furthermore, prolonged cytotoxic disease modifying anti-rheumatological drugs (DMARD) for AIRD may potentially induce therapy-related MN (t-MN), a lethal haematological malignancy with dismal outcomes. However, the genetic association and mechanism underpinning immune dysfunction in patients with between MN and AIRD is not fully elucidated. METHODS: In this collaborative study across the two disciplines and continents (Australia and USA), we assessed the burden of well-defined AIRD in a large cohort of MN (n=1702) that included myelodysplastic syndrome (MDS; n=861), acute myeloid leukaemia (AML; n=640), myeloproliferative neoplasm (MPN; n=89) and MDS/MPN overlap (n=112). We characterized the cytogenetic and mutational landscape of MN with AIRD (MN-AIRD) and without AIRD. In order to assess the mechanistic link between AIRD and MN, we investigated the bone marrow microenvironment in MN-AIRD vs. well-curated age matched controls. RESULTS: 132 (7.75%) of MN (n=1702) had concomitant AIRD. Although association of AIRD was observed across all subtypes of MN, enrichment of AIRD was observed in patients with MDS, MDS/MPN and MPN compared to AML (9.5% vs. 9.8% vs 10.1% vs. 4.67%; P <0.001). Inflammatory arthritis (n=65; 49.24%) followed by inflammatory connective tissue diseases (CTD, n=23; 17.42%), polymyalgia rheumatica (PMR, n=18; 13.63%) and vasculitis (n=16; 12.12%) were the most prevalent AIRD in the MN cohort. Notably, 87.7% of inflammatory arthritis were rheumatoid arthritis (RA; n=57). Striking survival differences were observed between t-MN without AIRD and MN-AIRD (14.0 vs. 33.7 months; P <0.0001) and t-MDS no-AIRD and MDS-AIRD (16.1 vs. 33.4 months, P =0.001). Chromosomal abnormalities including complex karyotype, monosomal karyotype, del 5q, del 7q, marker chromosome and TP53 mutations were enriched in t-MN following independent primary cancer (t-MN without AIRD). However striking enrichment of IDH1 and IDH2 (henceforth referred as IDH) mutations in MN with AIRD compared to MN without AIRD (20% vs. 11%, P =0.02), particularly in MDS-AIRD compared to MDS without AIRD (21% vs. 7%; P =0.001). The enrichment of IDH mutations were particularly prevalent in in MN cases with RA compared to other AIRD (34% vs. 11%; P =0.005). While IDH mutations were observed in only 8% and 6% of PMR and inflammatory CTD patients, respectively. Surprisingly higher frequency of IDH mutations was observed in evaluable seronegative compared to seropositive RA patients (62% vs. 0%; P =0.006). We also observed that majority of IDH mutations in seronegative RA were IDH1 (6/8; 75%) while IDH2 mutations were common other AIRD (6/6; 100%) ( P =0.009). We also assessed the impact of DMARDs on genomics of myeloid neoplasm. The majority of MN-AIRD patients treated with methotrexate did not harbor poor risk cytogenetic and mutation features such as complex karyotype, monosomal karyotype, del 5q, del 7q and/or TP53 mutation. In contrast, the majority of patients who had cyclophosphamide harbored high risk cytogenetic and molecular features. To assess pathogenic mechanisms linking MN and AIRD, we evaluated bone marrow microenvironment in myeloid neoplasm patients with and without AIRD. Bone marrow mesenchymal stromal cells (MSC) isolated from MN-AIRD were highly senescent compared to age matched healthy controls, MN without AIRD, with defective proliferating and differentiation capacity of MN-AIRD and secretion of highly proinflammatory cytokines and chemokines. CONCLUSIONS: In summary, our key findings include: 7.8% of MN were associated with AIRD with stronger association of AIRD with MDS and MDS/MPN compared to AML and striking enrichment of IDH mutations in MN with inflammatory arthritis compared to MN with other AIRD (29% vs 11%; P =0.02), especially in seronegative RA compared to seropositive RA (62% vs. 0%; P =0.006). In contrast to cyclophosphamide and azathioprine, majority of cases treated with methotrexate did not harbor poor risk cytogenetic and/or TP53 mutation. As methotrexate is widely used as an anchor drug in many rheumatology treatment regimens, this is a highly significant finding of clinical relevance.

Introduction: Germline DEAD-box RNA helicase-1 mutant (DDX41) predisposition syndrome ( DDX41-MT-GPS) is one of the most frequent hereditary predisposition syndromes in adults with myeloid neoplasms (MN-2-5%). Somatic mosaicism involving the unmutated DDX41 allele (e.g., R525H) as a potential mechanism for myeloid evolution has been reported in 39-50% of patients (pts). In addition, given the later age of onset, somatic mosaic states composed of age-related clonal hematopoiesis (ARCH) (e.g., DNMT3A, ASXL1, TET2, and TP53), with reported frequencies less than expected in MDS and AML, have been documented. We conducted this study to define the somatic mosaic landscape in DDX41-MT-GPS . Methods: After approval from the Mayo Clinic IRB the prospective GPS database was queried for pts with DDX41-MT GPS. Germline confirmation was conducted on skin fibroblast-, or hair follicle-derived DNA. Somatic CH testing was conducted using a targeted NGS panel as previously described. Given the high frequency of variants of undetermined significance (VUS), comparisons were made between pathogenic ( DDX41path) and DDX41VUS. Results: We identified 106 pts with DDX41-MT-GPS, of which 83 (78%) met criteria for MN, 16 (15%) for CH/CCUS (clonal cytopenias of undetermined significance), while 7 (6%) were unaffected carriers. Somatic mosaicism in DDX41-GPS patients without MN Sixteen DDX41-MT pts without MN met criteria for CH/CCUS ( DDX41path [n=4] and DDX41VUS [n=12]; median age 69 years (yrs) (range [R], 19-78) ( DDX41path [69 yrs] and DDX41VUS [67 yrs], p=0.85), with a male predilection (75%). Four (25%) pts had somatic DDX41 MT (R525H [n=3] and A376T [n=1]) with median variant allele frequency (VAF) 10.5% (R, 5-27); 2 (50%) pts with germline DDX41path had R525H (VAF; 5% and 13%) and 1 (8%) pt each with germline DDX41VUS had R525H (VAF 5%) and A376T (VAF 27%) somatic variants, respectively. Abnormal cytogenetics (CG) were observed in 2/13 evaluable (15%) pts ([+8 and del20q]) in the germline DDX41path group only (p= 0.05). ARCH co-mutations were observed in 11 (69%) pts, not significantly (NS) different between DDX41path (75%) and DDX41VUS (75%), p= 0.66. Individual co-mutations: DNMT3A (25% vs 16%, p= > 0.99), ASXL1 (25% vs 8%, p=0.71), TET2 (25% vs 8%, p= >0.99), and JAK2 (0% vs 8%, p= >0.99) were NS different between the two groups. Somatic mosaicism in DDX41-GPS patients with MN Eight-three pts met criteria for MN ( DDX41path [n=43] and DDX41VUS [n=40]; median age 67 yrs (range [R], 27-92), with a male predilection (58%). Fifty-four (65%) pts had MDS ( DDX41path [55%] and DDX41VUS [45%], p=0.55) and 29 (35%) had AML ( DDX41path [41%] and DDX41VUS [59%], p=0.65). Overall, 15 (18%) pts had somatic DDX41 MT; 12 (80%) pts with DDX41path and 3 (20%) pts with DDX41VUS (p= 0.003). The median VAF of somatic DDX41 MT was 12% (R, 5-37), NS different between DDX41path (10.5%) and DDX41VUS (12%) (p=0.08). The most common somatic DDX41 MT was R525H (66% [n=10]), significantly associated with DDX41path (9/10 [90%]), p=0.01. ARCH was observed in 17 (20%) pts, significantly higher in DDX41path (76%) compared to DDX41VUS (24%), p= 0.03. Abnormal CG were observed in 10/73 evaluable (14%) pts (-Y [n=2], del 20 [n=3], del 5q [n=2], del 7q [n=1], t (3;8) [n=1] and complex CG [n=1]), higher in DDX41path (70%) compared to DDX41VUS (30%) with p value >0.99. We compared the spectrum of CH between DDX41 MT CH/CCUS and MN pts ( Table 1) and found no difference in the proportion of pts with somatic DDX41 MT (p= 0.52) and ARCH/myeloid MT (p= 0.56). The individual occurrences of DNMT3A (p= 0.49), ASXL1 (p= 0.71), TET2 (p=0.59), JAK2 (p>0.99) and TP53 (p= 0.56) mutations were NS different between the two groups ( Figure 1). Conclusion: We define the somatic mosaic landscape in DDX41-MT GPS and demonstrate that somatic mutations involving the other allele, especially R525H, are seen in ~20% of pts (>80% of R525H present in MN). The frequency and composition of ARCH and myeloid driver mutations was lower than expected for the age of presentation, in comparison to de novo and secondary MDS/AML and occurred more frequently in DDX41path compared to DDX41VUS. Forty-two % (n=41), including 37% with MN, did not have somatic mosaicism, underscoring the fact that mechanisms of leukemia progression remain to be defined in subsets of affected pts.

Introduction Truncating ASXL1 mutations in chronic myelomonocytic leukemia (CMML) are associated with inferior overall survival (OS) and leukemia free survival (LFS). Conversely, loss-of-function mutations in TET2 are associated with better outcomes, with the ASXL1wt/ TET2mut genotype being associated with the best OS and LFS-rates (Coltro G, et al. Leukemia. 2020). Contemporary CMML prognostic scoring systems - such as the Mayo Molecular Model (MMM; Patnaik MM, et al. Leukemia. 2014) and the CPSS-Molecular Model (CMM; Elena C, et al. Blood. 2016) - do not consider concomitant ASXL1/ TET2 mutational status or mutational VAF. We hypothesized that the ASXL1/ TET2 genotype would better risk stratify patients in comparison to ASXL1 mutations alone, and that this effect would be proportional to the underlying mutational VAF. Methods After IRB approval, we compiled a large (n = 888), molecularly annotated database of CMML patients seen at two US medical centers (Mayo Clinic and MD Anderson) via retrospective chart review. All statistical analyses considered the clinical and laboratory parameters obtained at the time of presentation to the respective institution. Categorical variables were compared by Fisher exact or Pearson χ 2 tests and continuous variables by Mann-Whitney U tests. Univariate and multivariate analyses were performed using Cox proportional hazards regression models. Survival was assessed via the Kaplan-Meier method. P-values < 0.05 were considered significant. All statistical calculations were performed using the BlueSky Statistics (v10.3.1) interface for R. Results The median age of the cohort was 71 years (range 20 - 94), 67% were male, 46% had proliferative CMML (pCMML), and 19% had CMML-2. The distribution of low, intermediate-1, intermediate-2, and high-risk patients was 15%, 11%, 32%, and 42% by the MMM and 9%, 23%, 40%, and 28% by the CMM, respectively. The most frequently mutated genes were ASXL1 (45%), TET2 (43%), SRSF2 (41%), and RUNX1 (17%), while 40% harbored at least one RAS pathway mutation ( NRAS 16%, CBL 15%, KRAS 8%, PTPN11 4%, FLT3 2%). The median OS and LFS of the entire cohort were 31.8 months (95% CI 28.4 - 33.5 months) and 28.4 months (95% CI 24.6 - 32.1 months), respectively. Patients were stratified into ASXL1wt/ TET2wt (28%), ASXL1mut/ TET2wt (29%), ASXL1wt/ TET2mut (26%), and ASXL1mut/ TET2mut (17%) genotypes. Those with isolated TET2 mutations had the longest median OS (53.6 months; p < 0.02 for all comparisons) whereas those with isolated ASXL1 mutations had the shortest median OS (20.9 months; p < 0.04 for all comparisons); mutations in neither or both genes performed similarly (p = 0.9224; Figure 1A). The same trend was seen for LFS. We further hypothesized that the ASXL1 or TET2 mutation VAF would be more predictive of outcomes than a binary metric. The respective median VAFs were 37% (quartiles 28% - 45%) and 45% (quartiles 40% - 49%). When treated as a continuous variable, however, there was no correlation between either VAF and OS or LFS by both Pearson linear regression and Cox proportional hazard modeling. Unlike the overall cohort, the ASXL1/ TET2 genotypes did not further stratify patients with pCMML, CMML-2, or those considered high risk by the CMM in Kaplan-Meier analyses, suggesting that the high-risk features inherent in these subgroups outweigh the benefits of the TET2 mutation. In contrast, patients considered high-risk by the MMM were further stratified by the ASXL1/ TET2 genotypes. Incorporating TET2 mutations into the MMM as a protective factor (worth -1.5 points) improved detection of low- (≤ 1 point) and high-risk (≥ 4 points) patients, while intermediate-1 and intermediate-2 coalesced into a single intermediate risk category ( Figure 1B). A similar phenomenon was observed when TET2 was incorporated into the CMM (worth -1 point, yielding low- (0 points), intermediate- (1-2 points), and high-risk (≥ 3 points) groups with median OS of 83 months (95% CI 66.2 - 104.2), 34.3 months (95% CI 31.6 - 38.7), and 17.7 months (95% CI 15.7 - 20.2), respectively. Conclusions Truncating and hypomorphic TET2 mutations are associated with better outcomes in CMML, with the ASXL1mut/ TET2wt genotype being associated with improved risk stratification in comparison to ASXL1 mutational status alone. Counterintuitively, in our data set, this stratification was not impacted by mutational VAF, supporting binary mutational assessments in prognostic models.

BACKGROUND: Recently proposed World Health Organization (WHO, 5 th edition) and International Consensus Classification (ICC) recognized myeloid neoplasms (MN) harboring TP53-mutated ( TP53mut) as a separate entity. However, there are critical differences between the two classifications regarding allelic-status, variance allele frequency (VAF) cut-off and blast categories, that may lead to under- or overestimation of the risk. METHODS: We analyzed MN harboring TP53mut (VAF ≥2%, n=536) managed at Mayo Clinic (USA) and South Australia Health Network (Australia). ICC (Arber et al, Blood 2022) and WHO (Bluebook, Beta v2) definitions were used to stratify MN harboring TP53mut. RESULTS: Of 536 cases, 379 (71%) had myelodysplastic syndromes (MDS) (<20% blasts) and 157 (29%) had acute myeloid leukemia (AML). Using WHO, 160 (42%) of 379 were classified as MDS-bi TP53 as they harbored 2 TP53mut (n=115; 30%) or 1 TP53mut plus confirmed loss of heterozygosity (LOH) or copy neutral LOH (cnLOH) of TP53 locus (n=45; 12%). Sixty-two (16%) TP53mut MDS with VAF >49% were classified as presumptive MDS-bi TP53. Of the 157 cases with 1 TP53mut VAF ≤49%, 17 confirmed to have an intact wild-type TP53 copy and were classified as monoallelic. While 140 (89%) cases did not have copy number variation (CNV) analysis. We next evaluated the number of TP53mut cases classified differently by WHO and ICC. As WHO does not recognize TP53mut AML as a separate entity, 157 (29%) TP53mut AML were not classifiable. 46% (174/379) of the TP53mut MDS including 48 (30%), 12 (19%) and 79 (65%) of bi TP53, presumptive bi TP53 and monoallelic TP53mut MDS according to WHO were classified differently by ICC ( Figure 1A). Discordance between the two classifications were predominantly driven by: (i) The difference in VAF cut-off. Sixty patients (11%) with TP53mut VAF <10% were excluded from the ICC classification of TP53mut MN as it mandates TP53mut VAF cut-off ≥10%. 11 (18%) and 41 (68%) of these had bi TP53, monoallelic TP53mut MDS by WHO criteria while 8 (13%) had AML. Importantly, within the VAF <10% cohort, median overall survival (OS) of 2 TP53mut or 1 TP53mut with 17p13.1 (hereafter 17p) deletion or complex karyotype (CK, n=30) was significantly poor compared to 1 TP53mut VAF <10% (11.6 vs 32.4 months; P =0.002, Figure 1B), suggesting that ICC may underestimate the poor prognosis of multi-hit or multi-hit equivalent TP53mut MN with VAF <10%. (ii) The difference in bone marrow blast cut-off. The underlying assumption by WHO is that prognosis of bi TP53mut MDS is poor irrespective of blast percentage category (0-9% vs 10-19%). In contrast, ICC considers that TP53mut MDS/AML (blasts 10-19%) is associated with poor prognosis irrespective of TP53 allelic status. Median OS of TP53mut MDS with 10-19% blasts was significantly poor compared to blast 0-9% (6.4 vs 11.6 months, P <0.0001). Second, median OS of bi TP53mut was significantly poor than monoallelic TP53mut in MDS- blast 0-9% (10.1 vs 15.9 months; P =0.0001) but not in blasts 10-19% (6.8 vs 6.2 months; P =0.19). Hence, exclusion of monoallelic TP53mut MDS with blast 10-19% as TP53mut MN from the WHO classification may underestimate the poor prognosis. (iii) The difference in the definition of biallelic and multi-hit TP53 loss. 35 cases with 1 TP53mut VAF ≤49%, had 17p deletion but did not have CNV analysis to confirm the loss of TP53 locus and could not be classified further using WHO. ICC classified 18 (50%) of these cases as multi-hit. Median OS of 1 TP53mut VAF ≤49%, and 17p deletion on karyotype was significantly poor than 1 TP53mut (VAF ≤49%without 17p deletion on karyotype (6.4 vs 14.6 months, P =0.001). (iv) The difference in the definition of multi-hit equivalent. 32% (33/104) WHO defined monoallelic cases without available CNV data, were classified as multi-hit-equivalent by ICC as they harbored CK. However, WHO does not consider CK as presumptive evidence of bi TP53. Median OS of 1 TP53mut VAF ≤49% with CK was significantly poor compared to 1 TP53mut without CK (8.2 vs 26.9 months, P =0.0008). CONCLUSION: Our study provides evidence that poor prognosis of ‘multi-hit’ TP53 with VAF <10% is underestimated by ICC. On the other hand, poor prognosis of monoallelic TP53 MDS with 10-19% blasts as well as 1 TP53mut VAF ≤49% in the presence of CK is underestimated by WHO. These data suggest that both classifications can be further refined.

Abstract VEXAS (Vacuoles, E1 enzyme, X‐linked, Autoinflammatory, Somatic) syndrome is a newly identified disease caused by somatic alterations in UBA1 which produce a recalcitrant inflammatory state along with hematologic disturbances. Patients with VEXAS can have a wide spectrum of clinical symptoms and providers should be familiar with the heterogeneity of associated clinical features. While hematologic parameters may be generally non‐specific, peripheral blood features of macrocytosis, monocytopenia, and/or thrombocytopenia coupled with bone marrow vacuolization of erythroid or myeloid precursors should raise suspicion for this condition. Due to an increased mortality, prompt recognition and accurate diagnosis is paramount. Access to testing for confirmation of UBA1 variants is not yet universally available but clinicians should understand the current available options for genetic confirmation of this disease. Treatment options are limited due to lack of prospective clinical trials but cytokine directed therapies such as interleukin‐6 inhibitors and JAK–STAT inhibitors as well as hypomethylating agents such as azacitidine have shown evidence of partial effect. Though cases are limited, allogeneic stem cell transplantation holds promise for durable response and potential cure. The intent of this review is to outline the pathophysiology of VEXAS syndrome and to provide a practical approach to diagnosis and treatment.

Abstract Blastic plasmacytoid dendritic cell neoplasm (BPDCN) is a rare hematological malignancy with a poor prognosis and considered incurable with conventional chemotherapy. Small observational studies reported allogeneic hematopoietic cell transplantation (allo-HCT) offers durable remissions in patients with BPDCN. We report an analysis of patients with BPDCN who received an allo-HCT, using data reported to the Center for International Blood and Marrow Transplant Research (CIBMTR). We identified 164 patients with BPDCN from 78 centers who underwent allo-HCT between 2007 and 2018. The 5-year overall survival (OS), disease-free survival (DFS), relapse, and nonrelapse mortality (NRM) rates were 51.2% (95% confidence interval [CI], 42.5-59.8), 44.4% (95% CI, 36.2-52.8), 32.2% (95% CI, 24.7-40.3), and 23.3% (95% CI, 16.9-30.4), respectively. Disease relapse was the most common cause of death. On multivariate analyses, age of ≥60 years was predictive for inferior OS (hazard ratio [HR], 2.16; 95% CI, 1.35-3.46; P = .001), and higher NRM (HR, 2.19; 95% CI, 1.13-4.22; P = .02). Remission status at time of allo-HCT (CR2/primary induction failure/relapse vs CR1) was predictive of inferior OS (HR, 1.87; 95% CI, 1.14-3.06; P = .01) and DFS (HR, 1.75; 95% CI, 1.11-2.76; P = .02). Use of myeloablative conditioning with total body irradiation (MAC-TBI) was predictive of improved DFS and reduced relapse risk. Allo-HCT is effective in providing durable remissions and long-term survival in BPDCN. Younger age and allo-HCT in CR1 predicted for improved survival, whereas MAC-TBI predicted for less relapse and improved DFS. Novel strategies incorporating allo-HCT are needed to further improve outcomes.

AbstractThe World Health Organization (WHO) classification system categorizes advanced systemic mastocytosis (SM‐Adv) into aggressive SM (ASM), mast cell leukemia (MCL), and SM with associated hematological neoplasm (SM‐AHN). By contrast, the International Consensus Classification (ICC) requires “immature” MC cytomorphology for the diagnosis of MCL and limits SM‐AHN to myeloid neoplasms (SM‐AMN). The current study includes 329 patients with SM‐Adv (median age 65 years, range 18–88; males 58%): WHO subcategories SM‐AHN (N = 212; 64%), ASM (N = 99; 30%), and MCL (N = 18; 6%); ICC subcategories SM‐AMN (N = 190; 64%), ASM (N = 99; 33%), and MCL (N = 9; 3%); WHO‐defined MCL with “mature” MC cytomorphology and SM‐AHN associated with lymphoid neoplasms were operationally labeled as “MCL‐mature” (N = 9) and SM‐ALN (N = 22), respectively, and distinguished from ICC‐defined MCL and SM‐AMN. Multivariable analysis that included the Mayo alliance risk factors for survival in SM (age >60 years, anemia, thrombocytopenia, increased alkaline phosphatase) revealed more accurate survival prediction with the ICC versus WHO classification order: (i) survival was significantly worse with MCL‐immature versus MCL‐mature (hazard ratio [HR] 15; p < .01), (ii) prognostic distinction between MCL and SM‐AHN/AMN was confirmed in the context of ICC (HR 9.3; p < .01) but not WHO classification order (p = .99), (iii) survival was similar between MCL‐mature and SM‐AMN (p = .18), and (iv) SM‐AMN (HR 1.7; p < .01) but not SM‐ALN (p = .37) was prognostically distinct from ASM. The current study provides evidence for the independent prognostic contribution of both the ICC system for SM‐Adv and the Mayo alliance risk factors for survival in SM.