Myelodysplastic Syndromes Cohort Research Articles

Molecular and clinical presentation of UBA1-mutated myelodysplastic syndromes

Mutations in UBA1, which are disease-defining for VEXAS syndrome, have been reported in patients diagnosed with myelodysplastic syndromes (MDS). Here, we define the prevalence and clinical associations of UBA1 mutations in a representative cohort of patients with MDS. Digital droplet PCR profiling of a selected cohort of 375 male patients lacking MDS disease-defining mutations or established WHO disease classification identified 28 patients (7%) with UBA1 p.M41T/V/L mutations. Using targeted sequencing of UBA1 in a representative MDS cohort (n=2,027), we identified an additional 27 variants in 26 patients (1%), which we classified as likely/pathogenic (n=12) and unknown significance (n=15). Among the total 40 patients with likely/pathogenic variants (2%), all were male and 63% were classified by WHO2016 as MDS-MLD/SLD. Patients had a median of one additional myeloid gene mutation, often in TET2 (n=12), DNMT3A (n=10), ASXL1 (n=3), or SF3B1 (n=3). Retrospective clinical review where possible showed that 83% (28/34) UBA1-mutant cases had VEXAS-associated diagnoses or inflammatory clinical presentation. The prevalence of UBA1-mutations in MDS patients argues for systematic screening for UBA1 in the management of MDS.

Kinome expression profiling improves risk stratification and therapeutic targeting in myelodysplastic syndromes

AbstractThe human kinome, which comprises >500 kinases, plays a critical role in regulating numerous essential cellular functions. Although the dysregulation of kinases has been observed in various human cancers, the characterization and clinical implications of kinase expressions in myelodysplastic syndromes (MDS) have not been systematically investigated. In this study, we evaluated the kinome expression profiles of 341 adult patients with primary MDS and identified 7 kinases (PTK7, KIT, MAST4, NTRK1, PAK6, CAMK1D, and PRKCZ) whose expression levels were highly predictive of compromised patient survival. We then constructed the kinase stratification score (KISS) by combining the weighted expressions of the 7 kinases and validated its prognostic significance in 2 external MDS cohorts. A higher KISS was associated with older age, higher peripheral blood and marrow blast percentages, higher Revised International Prognostic Scoring System (IPSS-R) risks, complex karyotype, and mutations in several adverse-risk genes in MDS, such as ASXL1, EZH2, NPM1, RUNX1, STAG2, and TP53. Multivariate analysis confirmed that a higher KISS was an independent unfavorable risk factor in MDS. Mechanistically, the KISS-high patients were enriched for genesets associated with hematopoietic and leukemic stem cell signatures. By investigating the Genomics of Drug Sensitivity in Cancer database, we identified axitinib and taselisib as candidate compounds that could potentially target the KISS-high myeloblasts. Altogether, our findings suggest that KISS holds the potential to improve the current prognostic scheme of MDS and inform novel therapeutic opportunities.

Prognosis and risk factors for ASXL1 mutations in patients with newly diagnosed acute myeloid leukemia and myelodysplastic syndrome.

The objective of the study was to determine the prognosis and risk factors for additional sex combs like 1 (ASXL1) mutations in patients with acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS). This retrospective study enrolled 219 adult patients with newly diagnosed AML and MDS, who were treated in West China Hospital from October 2018 to January 2022. The primary clinical outcome was evaluated by overall survival (OS) followed up to January 2023. Kaplan-Meier analysis and Cox multivariate regression analysis were performed to identify potential prognostic parameters in patients with ASXL1 mutations (mt). A total of 34 (15.53%) ASXL1mt were detected, which occurred more frequently in the elderly and MDS cohorts (p < 0.001). Significantly lower blasts% (p < 0.001) and higher frequencies of mutant RUNX1, SRSF2, STAG2, EZH2, and SETBP1 (p < 0.02) were observed in the ASXL1mt cohort. Patients with ASXL1mt manifested with a worse complete remission rate (p = 0.011), and an inferior OS was shown in subgroups with MDS, co-mutations of RUNX1, SRSF2, or NRAS, as well as mutations in G646W (p < 0.05). Multivariate analysis considering age, diagnosis, co-mutations, and mutation site confirmed an independently adverse prognosis of mutations in G646W (HR = 4.302, 95% CI: 1.150-16.097) or RUNX1 co-mutations (HR = 4.620, 95% CI: 1.385-15.414) in the ASXL1mt cohort. Our study indicated that mutations in G646W or RUNX1 co-mutations are closely associated with a dismal clinical outcome in patients with AML and MDS harboring ASXL1mt . Considering the poor prognosis and risk factors in patients with ASXL1mt , more available treatments should be pursued.

UBA1 Mutations Identify a Rare but Distinct Subtype of Myelodysplastic Syndromes

Background Mutations in UBA1 are associated with VEXAS (Vacuoles, E1 enzyme, X-linked, Autoinflammatory, Somatic) syndrome, an adult-onset inflammatory disorder (Beck DB et al. NEJM 2020). Approximately 40% of VEXAS patients are also diagnosed with myelodysplastic syndromes (MDS). We previously profiled UBA1 p.M41 mutations in a select subset of the International Working Group for MDS (IWG-PM) cohort (Bernard E et al. NEJM Evid 2022) including 375 male patients lacking disease-defining mutations or established disease classification by WHO guidelines, and identified 28 patients (7%) with UBA1 p.M41T/V/L mutations (Cohort A, Sirenko M et al. Blood 2022). However, the prevalence and characteristics of UBA1 mutations in MDS have not been systematically evaluated in a representative MDS population. Methods We used targeted next-generation sequencing of the full UBA1 locus to profile 2027 diagnostic and treatment-naive MDS samples (Cohort B, 61% male) ascertained through the IWG-PM (Figure 1). Clinical associations of UBA1 mutations were evaluated and clinical history was reviewed for inflammatory conditions when available. Results In Cohort B, 35 UBA1 mutations in 34 (1.7%) patients were identified, of which 20 (0.97%) had likely pathogenic variants and 14 had variants of unknown significance (VUS). Likely pathogenic variants included 13 p.M41T/V/L mutation (variant allele fraction [VAF] range 0.013-0.94), and 7 non-p.M41 mutations where 6/7 had VAF&amp;gt;0.35: 2 with p.S56F (VAF 0.87 and 0.93), 2 p.A478S (VAF 0.72 and 0.80), 2 p.S621C (VAF 0.80 and 0.82) and 1 p.Y55H (VAF 0.025). Three VUS were in female patients. 204 cases were profiled by both assays and of those, all 8 ddPCR positive cases were identified by NGS with concordant VAF (R2=0.999 p&amp;lt;0.0001). Integration of Cohort A and B (n=2,198) yielded 40 patients (all male, median age 72; range 44-89 years) with pathogenic UBA1 variants. The WHO 2016 classification (available for n=38 of 40) was MDS-SLD/MLD (25), MDS-EB1 (4), MDS-U (3), CMML (2), MDS-RS-MLD (1), aCML (1), MDS/MPN-RS-T (1), MDS/MPN-U (1). Patients had a median of 1 myeloid gene mutation in addition to UBA1 (range: 0-4) with most frequent co-occurring events in TET2 (n=12), DNMT3A (n = 10), ASXL1 (n=3), SF3B1 (n=3) and loss of the Y chromosome (n=5). In 8 patients with pathogenic UBA1 &amp;gt; 2% VAF and co-occurring DNMT3A mutations, DNMT3A and UBA1 VAF were correlated (slope = 0.88, r = 0.87, p = 0.0005), suggesting that co-mutation may lead to clonal expansion. Conversely, TET2 co-mutations were either subclonal (n=4) or clonal (n=8) to UBA1. Among patients with pathogenic UBA1 variants, the majority had IPSS-M Very-Low/Low risk (73% 27/37). In contrast, patients with VUS were more likely to have Moderate or High risk (64% 7/11). Partial clinical history was available for 33 cases with pathogenic UBA1 variants. 50% (9/18) had inflammatory-rheumatic disease (IRD) including psoriatic arthritis, relapsing polychondritis, Sweet syndrome, bronchiolitis obliterans with organizing pneumonia, ear chondritis, and rosacea. 3 patients had more than one IRD. 8 were treated for IRD with steroids (n=6) or methotrexate (n=2). 4 patients had MGUS. Other manifestations included vacuoles (4/8), thromboembolic disease (5/16), non-infection fever (5/14), weight loss (4/14), ocular symptoms (5/15), arthralgia (3/16), chondritis (5/15), and other inflammation (6/14). IRD diagnosis usually preceded MDS (average time 0.28 years; range 16.5 years prior to 1.4 years after). Three patients transformed to acute myeloid leukemia (AML). One patient had a low VAF UBA1 p.M41V (0.0002 by ddPCR) and TET2, SF3B1, FLT3, and ASXL2 co-mutations at baseline. The second had UBA1 p.S56F (VAF 0.868) and a Chr 7q deletion. The third had VUS UBA1 p.R869L (VAF 0.222) and IRF1, NFE2 and RRAS co-mutations. Among the other UBA1-mutant patients that died or were censored after 1 year (n=37), none transformed to AML. Conclusion Within the large, representative, diagnostic and well-characterized IWG-PM MDS cohort, we find likely pathogenic UBA1 mutations in 1% of patients, with enrichment in male patients with few or no mutations in myeloid driver genes (7%). UBA1-mutant patients were predominantly IPSS-M low risk with a median of 1 additional mutation, usually in DNMT3A or TET2. UBA1 mutations may define a distinct subset of MDS and its recognition in future guidelines will improve the management of patients with MDS/VEXAS overlap.

The Molecular Prognostic Scoring System for Normal Karyotype Myelodysplastic Syndromes

Purpose: Myelodysplastic syndromes (MDS), is characterized by clinical heterogeneity and varying prognoses. Reliable prognostic models are essential to stratify MDS patients and optimize clinical management. Although incorporating molecular information into MDS prognostic models improves their predictive ability, limitations of next-generation sequencing panels and potential heterogeneity among MDS patients with different karyotypes hinder their clinical translation. Methods: In total, 237 normal karyotype (NK) MDS patients from the First Affiliated Hospital of Zhejiang University School of Medicine were used as the derivation set to investigate the molecular frequency and prognostic spectrum. A parsimonious molecular-clinical model was developed with overall survival (OS) as the endpoint and compared with other models using the concordance index as the primary evaluation index. An external independent validation set from the International Working Group for Prognosis in MDS cohort(691 NK MDS patients) was used to evaluate the model generalization ability. Results: In NK MDS, the gene mutation frequency spectrum is similar to the overall MDS population, the differences mainly lie in the prognostic spectrum. Genes such as TP53, previously associated with MDS prognoses have lost their prognostic value. Therefore, a seven-parameter molecular-clinical prognostic model called the Molecular Prognostic Scoring System for NK MDS (NK-PSS-M) was developed based on a specific molecular prognostic spectrum of NK MDS. The model includes age, hemoglobin, platelet count, blast percentage, CEBPA, RUNX1, and U2AF1. The NK-PSS-M model allows for personalized risk assessment based on patient characteristics, with higher scores indicating a greater risk and poorer prognosis. In addition, we developed a five-class classification system based on these scores, which differentiates patients across risk categories and predicts outcomes, such as OS and LFS(Figure 1 A and B). The performance of NK-PSS-M was comparable to that of the Molecular International Prognostic Scoring System(IPSS-M), and it significantly outperformed IPSS-R and other molecular prediction models based on it. The above results were confirmed in the external independent validation cohort(Figure 1C). Our transcriptomics analysis revealed that the low-risk group defined by NK-PSS-M demonstrated significant activation of the inflammatory pathway, and immune activation, which is consistent with the current understanding of the immunological landscape of MDS. Conclusion: The NK-PSS-M model improved the risk stratification of non-molecular models and provided a reliable alternative to the IPSS-M. In addition, we demonstrated the molecular heterogeneity of MDS across different cytogenetics and emphasized the importance of developing cytogenetics-specific prognostic models.

Venetoclax+Azacytidine Followed By Modified BuCy Conditioning Regimen for High Risk or Refractory/Relapsed Acute Lymphoblastic Leukemia and High Risk Myelodysplastic Syndromes

Background:Allogeneic hematopoietic stem cell transplantation (allo-HSCT) is the only potential curable treatment for myelodysplastic syndromes (MDS) and acute lymphoblastic leukemia (ALL). However, for patients with high-risk or refractory relapsed (R/R) B-ALL with allo-HSCT, the three-year overall survival (OS) rate is only 5-10%, more worse in T-ALL. It is widely known that MDS patients in the high-risk group do not benefit from induction chemotherapy, the five-year OS rate is 23-39% when they received allo-HSCT. Nevertheless, relapse remains a significant cause of treatment failure after allo-HSCT, highlighting the urgent need for improved conditioning regimens that can improve prognosis and reduce relapse rates. Azacytidine (AZA) combined with Venetoclax (VEN), showed a synergistic anti-tumor activity against several hematological malignancies, Therefore, we explored AZA+VEN (VA) combined with modified BuCy(mBuCy) (semustine, cytarabine, busulfan, and cyclophosphamide) conditioning regimen and assessed the safety and effectiveness. Aims ：The aim of this study is to assess the safety, and effectiveness of the VA treatment regimen followed by mBuCy as conditioning regimen for high-risk or R/R ALL(NCT05809167) and high-risk MDS(NCT03256071) . Methods:Patients diagnosed with high-risk or R/R ALL or high-risk MDS (IPSS-R score), undergoing VA+mBuCy as conditioning regimen, and consolidation treatment with demethylating drugs every three months after transplantation, for a total of 8-12 cycles. Results:Patients diagnosed with high-risk or R/R ALL(n=11) or high-risk MDS (IPSS-R score)(n=8) were enrolled between January 13, 2022, and June 9, 2023. The ALL cohort comprised of 5 Ph-negative B-ALL, 2 Ph-positive B-ALL, 3 mixed phenotype leukemias (MPAL), and one T-lymphoblastic lymphoma/leukemia (T-ALL/LBL). There were 7 males and 4 females, with a median age of 33 years (17-54 years) (Table 1). Out of the eleven patients, four had previously undergone Chimeric Antigen Receptor T-Cell Immunotherapy (CAR-T) therapy, and one patient had received Blinatumomab. One patient experienced relapse, another patient was refractory, and 3 patients had extramedullary infiltration. All patients achieved morphological complete remission prior to transplantation, and 10 patients (90.9%) achieved a MRD negative remission. Additionally, all the transplantations successfully completed, with a median time to absolute neutrophil counts (ANC) recovery of 12 days (11-15 days) and platelet (PLT) recovery of 16 days (15-21 days). The median follow-up time was 6.4 months (2.4 -13.6 months), no patient experienced relapse or death, the OS and DFS are both 100%. There were no grade 3 or higher adverse events (AEs), hepatic veno-occlusive disease (VOD),and the transplant-related mortality (TRM). Four patients who developed acute graft-versus-host disease (aGVHD) post-transplantation, all cases involved grade I/II skin aGVHD, and one of them involved grade III GI aGVHD, and no chronic graft-versus-host disease (cGVHD) were observed during the follow-up period. By the endpoint of follow-up, Cytomegalovirus (CMV) activation was 45.4% (5/11) and Epstein-Barr virus (EBV) activation was 27.3% (3/11). The MDS cohort consisted of 7 cases of MDS-EB-I, 1 case of MDS-EB-II. There were 5 males and 3 females, with a median age of 42 years (23-57 years)(Table 2). Two patients received chemotherapy before transplantation, and the other six patients directly received allo-HSCT. In MDS cohort, the median recovery time for ANC was 12 days (11-13 days) and PLT was 17.5 days (16-20 days). The median follow-up was 14.3 months (1.2-18.3 months), no patient had relapsed or died, both OS and DFS are 100%. There were no grade 3 or higher AEs, and TRM. One patient developed VOD. Three patients developed aGVHD after transplantation, all involving degree I/II skin aGVHD, and there was one case of cGVHD during the follow-up period, where the patient developed a mild pulmonary cGVHD. By the endpoint of the follow-up, the rate of CMV activation was 37.5% (3/8) and EBV activation was 25% (2/8). Conclusion:The VA combined with the mBuCy proves to be a effective and safe conditioning regimen for high-risk ALL and MDS patients. However, more patients are needed for follow-up and validation.

Clinical, Cytogenetic and Molecular Characterization of a 96 MDS and AML Cohort with TP53 Mutation

Introduction The last European LeukamiaNet (ELN) recommendations (Döhner H. et al. Blood. 2022) and the International Consensus Classification (ICC, Hasserjian R.P. et al. Virchows Arch. 2023) described a new entity, called myelodysplastic syndrome (MDS)/ acute myeloid leukemia (AML) with TP53 mutation ( TP53mut), comprising high-risk MDS with an excess of bone marrow blasts cells (more than 10%) and a TP53 mutation (variant allele frequency VAF ≥ 10%). They suggested that MDS and AML represent a biologic continuum rather than two distinct diseases separated by a blast cutoff. Among teams who worked on that topic, T. Grob et al. ( Blood. 2022) studied the molecular characterization of high-risk AML and MDS with TP53mut and suggested that these two types of pathologies should be considered as a single entity, with no difference in molecular characteristics or survival. In this study, we describe the clinical, cytogenetic, and molecular characteristics of a cohort of 96 MDS and AMLs with TP53mut. Patients and methods We included all the patients with AML, MDS/AML, MDS with increased blasts (MDS-IB1) and MDS-low blast (MDS-LB) with at least one TP53mut (VAF ≥ 1%) received between Aug. 2020 and Dec. 2022 at the Institut Paoli-Calmettes (IPC, Marseille, France). Clinical and biological data were extracted retrospectively from the AML IPC database. Morphologic and cytogenetic data were analyzed by standard techniques. NGS was performed using a custom targeted panel of 60 genes (Custom Myeloid Lymphoid Solution, SOPHIA GENETICS). Results We registered 96 patients with a TP53 mutation (VAF ≥ 1%), divided into AML (n=60), MDS/AML (n=14), MDS-IB1 (n=12) and MDS-LB (n=10). Median age was 71 (range, 28-88). Thirty-eight patients had been treated for a prior solid malignancy and 26 patients had a history of myeloid malignancy. TP53mut was detected at diagnosis for 85 patients and at relapse or during follow-up for 12 patients (no NGS data available at diagnosis). We detected 142 mutations in the TP53 gene, mostly missense (73%) between exon 4 and exon 11 with a median VAF of 39% (Figure 1). We found 3 hotspots mutations in positions 273, 248 and 220 with respectively 9, 9 and 8 mutations. Biallelic status (presence of ≥ 2 mutations or a mutation + a deletion) was found in 66 patients (69%). Karyotypes were available for 95 patients. The karyotype was abnormal in 88% of cases, complex in 71% and unfavorable in 80% of cases according to ELN classification or Revised International Prognostic Scoring System (R-IPSS). Complete NGS analysis revealed at least one mutation in 59 of the other genes of the panel in 67 patients (70%), the most frequent being DNMT3A (22%), TET2 (17%), ASXL1 (13%) and PPM1D (11%) (Figure 2). In our cohort of TP53mut LB-MDS (n=10), we found that 9/10 patients had co-mutations in DNMT3A (n=4) , TET2 (n=6) and PPM1D (n=2) genes, 7/10 with biallelic status and 3/10 with complex karyotype. AML and MDS/AML patients with TP53mut detected at diagnosis (n=65) were treated with intensive chemotherapy (n=13), VEN-AZA (n=26), non-intensive therapy (n=14) or best supportive care (BSC, n=12). Seventeen patients were treated with allogeneic stem-cell transplantation (ASCT). With a median follow-up (FU) of 13 months, median overall survival (OS) of the whole cohort was 7 months (ranges, 1-41). Median OS in the AML and MDS/AML group was 6 months (ranges, 1-41). Patients treated with non-intensive approach had the longest median OS (15 months) compared to patients treated with intensive chemotherapy and VEN-based approaches (8 and 6 months, respectively) and patients treated with BSC (1 month, p=0.02). Patients with MDS-IB1 and MDS-LB had 11-months median OS (ranges, 1-28). The four patients treated with upfront ASCT were still alive at the last FU date and have an estimated median OS of 18.5 months (ranges, 6-26). Conclusion Our data confirm that MDS and AML with TP53 mutation are frequently associated with complex karyotypes and have a poor prognosis. nterestingly we identified mutations in PPM1D gene, involved in TP53 pathway, in 11% of cases. Patients with AML or MDS/AML treated with non-intensive approach seem to have the longest OS (15 months). Patients with MDS-IB1 or MDS-LB treated with upfront ASCT seem to have a prolonged OS (18.5 months). Clinical, functional and mechanistic studies are required to complete these findings.

Hypomethylating Agents Are Associated with High Rates of Hematologic Toxicity in Patients with Secondary MDS/AML That Develops after Acquired Aplastic Anemia

Acquired aplastic anemia (AA) is an autoimmune bone marrow failure (BMF) associated with depletion of hematopoietic stem and progenitor cells. Approximately 15-20% of AA patients treated with immunosuppressive therapy (IST) develop late complications of myelodysplastic syndrome (MDS) or acute myeloid leukemia (AML). Little is known about managing patients with post-AA myeloid neoplasms (MN). We hypothesized that patients with post-AA MN may be particularly susceptible to hematologic toxicities from cytotoxic therapy because of stem cell deficits. To investigate our hypothesis, we retrospectively analyzed post-AA MN patients treated at our 2 institutions over the past 15 years. Fourteen post-AA MN patients were identified: 11 with MDS, 1 with AML, and 2 with clonal cytopenia of undetermined significance (CCUS). Patients with inherited BMF or allogeneic stem cell transplant (SCT) prior to MN diagnosis were excluded. The median age at MN was 56.5 years (range 5-75) with a median time of 5 years (range 0.25-30) between AA diagnosis and MN. At MN diagnosis, 12 of 14 patients (86%) had a partial or complete response of AA with 5 receiving cyclosporine (CSA) maintenance. Two patients (14%) were on CSA within 6 months of IST without response. After MN diagnosis, CSA was discontinued. Ten adults received hypomethylating agents (HMA) as first-line treatment in preparation for SCT. Three pediatric patients were treated with SCT with no prior HMA. One patient died before receiving treatment. The 10 post-AA patients who received HMA were matched in a 3:1 ratio with a similarly aged, randomly selected non-AA MDS cohort treated with HMA at our center during the same period (Table 1). Compared to patients with non-AA MDS, post-AA MN patients tolerated HMA poorly with frequent, severe complications. Their median per-cycle duration of grade 4 neutropenia was longer (9 v. 1.5 days, p = 0.044), as was median duration of grade 4 thrombocytopenia (13 v. 0 days, p = 0.003). Post-AA patients notably had lower baseline platelets prior to HMA (median 36.5 v. 115 k/mL, p =0.007). Following HMA, the post-AA cohort had higher rates of febrile neutropenia (80% v. 17%, RR 4.8, p &amp;lt; 0.001) and infections ≥ grade 3 (90% v. 13%, RR 6.8, p &amp;lt; 0.001). They also had higher rates of ≥ grade 3 bleeding (40% v. 7%, RR 6.0, p = 0.026) with 2 patients (20%) experiencing intracranial hemorrhage on HMA; no such events occurred in the non-AA cohort. Post-AA patients had more hospital admissions - 18 in 25 total chemotherapy cycles (72%) compared to 12 in 207 cycles (6%) in the matched cohort (RR 12.4, p &amp;lt; 0.001). Post-AA MN patients had more treatment delays &amp;gt;2 weeks (28% v. 8% of planned treatment cycles, RR 3.4, p = 0.01) and dose reductions (40% v. 13%, RR 3.0, p = 0.089). HMA was discontinued due to treatment-emergent adverse events (TEAEs) in 70% of post-AA cases v. 3% of non-AA patients (RR 21.0, p &amp;lt; 0.001). Consequently, post-AA MN patients received fewer cycles of HMA compared to non-AA patients (median 2.5 v. 6, p = 0.021). Death occurred following TEAEs in 20% of post-AA MN patients; no deaths on HMA occurred in the non-AA cohort (RR 14.1, p = 0.058). Among surviving patients, SCT was delayed in 20% of the non-AA cohort due to TEAEs, while no delays occurred in the matched cohort. The median months from final chemotherapy cycle to SCT were 4 (range 1-12) in post-AA v. 1 (1-3) in non-AA, while median months from MN diagnosis to SCT were 8.5 (4-21) in post-AA v. 5 (4-15) in non-AA. For all 14 post-AA MN patients, including those not treated with HMA, overall survival (OS) from MN diagnosis was 71% (95% CI 51-99) at 1 year and 56% (95% CI 34-90) at 3 years. OS of post-AA MN patients differed significantly (p = 0.011) based on treatment with SCT. Among the 5 who did not receive SCT, 4 died within 3 years of MN, while 1 patient is alive 13 months from diagnosis receiving supportive care after intracranial hemorrhage during the first cycle of HMA. In contrast, 7 of 9 (78%) patients who received SCT were alive 3 years after MN diagnosis. Of the 6 patients treated with SCT after HMA, 5 stopped HMA due to toxicity, all had morphologic dysplasia at SCT, and 2 were transplanted with ≥ 5% marrow blasts. Our study shows that patients with MN following antecedent autoimmune AA are at high risk of severe toxicities with standard HMA regimens and have difficulty tolerating repeated cycles. Our results do not support routine use of HMA prior to SCT in this patient population and suggest that early SCT may be the most suitable strategy.

Full-Dose Azacitidine in 5 Days Versus 7 Days With a Weekend Break in Myelodysplastic Syndromes: A Retrospective Cohort Study

IntroductionApart from transplantation, only azacitidine demonstrated a survival benefit in a phase III study in higher-risk myelodysplastic syndromes (MDS). The approved regimen is 75 mg/m2/day for 7 consecutive days, imposing a logistic challenge for outpatient weekend administration. Schedules with 5 days and 7 days with a weekend break (5 + 2) have been used for convenience despite the lack of strong scientific support. Most studies of alternative schedules were performed in lower-risk MDS and with dose reduction in the 5-day schedules. MethodsWe performed a single-center, retrospective cohort study to compare full-dose azacitidine (7 × 75 mg/m2) administration in 5-day and 5 + 2-day schedules in a higher-risk MDS cohort. We evaluated 100 patients for overall survival and a subsample (49 patients) for acute myeloid leukemia-free survival (AMLFS), probability of infections and transfusion burden. Kaplan-Meier analysis and Cox models were used for survival analyses. Linear and logistic regressions were applied for univariate and multivariate assessment. ResultsAfter a median follow-up of 10.8 months, patients treated with a 5-day schedule had a median overall survival of 12.5 months versus 15.0 months in the 5+2 group: HR 0.95 (95% CI, 0.57-1.56); P= .83. AMLFS was also similar between groups: HR 1.70 (95% CI, 0.70-4.14); P = .24. Azacitidine schedules were not predictive of infections nor number of red blood cell or platelet transfusions in multivariate analyses. ConclusionsIn higher-risk MDS, full-dose azacitidine (7 × 75 mg/m2) can be administered both in 5 days and in 7 days with a weekend break with no significant difference in survival, infection or transfusional outcomes.

Decreased transthyretin predicts a poor prognosis in primary myelodysplastic syndrome.

This study aims to investigate the prognostic significance of transthyretin in newly diagnosed myelodysplastic syndromes (MDS). The clinical, laboratory, and follow-up data of 280 newly diagnosed patients with MDS were collected. The relationship between serum transthyretin levels and overall survival (OS) and leukemia-free survival (LFS) were analyzed by Kaplan-Meier analysis and Cox Regression Model. In the MDS cohort, there were 121 cases in the low transthyretin group and 159 cases in the normal transthyretin group. MDS patients with decreased transthyretin had a higher risk score on the Revised International Prognostic Scoring System (IPSS-R) (p = 0.004) and on the molecular IPSS (IPSS-M) (p = 0.005), a higher frequency of TP53 mutation (p < 0.0001), a shorter OS (p < 0.0001) and LFS (p < 0.0001). Multivariate analyses showed that higher IPSS-R and IPSS-M score were adverse factors for OS (p = 0.008 and p = 0.015, respectively) and LFS (p = 0.024 and p = 0.005, respectively). Mutations of TP53 and NRAS were also poor factors for LFS (p = 0.034 and p = 0.018, respectively). Notably, decreased transthyretin was an independent adverse predictor for OS (p = 0.009, HR = 0.097, 95%CI, 0.017-0.561) but not for LFS (p = 0.167) when IPSS-R was included in the Cox regression model and an independent poor one for OS (p = 0.033, HR = 0.267, 95%CI, 0.080-0.898) and LFS (p = 0.024, HR = 0.290, 95%CI, 0.099-0.848) while IPSS-M involved. The results indicate that decreased transthyretin could be an independent adverse prognostic factor in patients with MDS and may provide a supplement to IPSS-R and IPSS-M.

Synthetic Data Generation By Artificial Intelligence to Accelerate Translational Research and Precision Medicine in Hematological Malignancies

Background In hematological malignancies there is a growing demand for real-world, comprehensive data including clinical and genomic information to build powerful models to improve diagnosis, prognosis and personalized treatment choice. However, collecting such information in large patient populations is challenging and there are many issues concerning patient privacy that need to be accounted for. One approach that can circumvent these issues is the creation of synthetic data that captures the complexities of the original data set (distributions, non-linear relationships, and noise) without including any real patient information. Aims 1) Apply advanced synthetic data generation methods to real-world datasets of different hematological malignancies. 2) Develop a Synthetic Validation Framework to evaluate the quality of synthetic data and perform data augmentation. 3) Test the capability of synthetic data to accelerate translational research. Methods Here we implemented a Conditional Tabular Wasserstein Generative Adversarial Networks (GAN) architecture with Gradient Penalty to generate synthetic data. Use cases were different cohorts of patients with myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML) with available clinical and molecular features. We created a Synthetic Validation Framework to evaluate the quality of generated synthetic data: Clinical Synthetic Fitness (CSF) and Genomic Synthetic Fitness (GSF) scores were calculated as the average of multiple metric tests adopted. Patients were stratified by Hierarchical Dirichlet (HD) clustering. Explainability analysis was carried out by SHapley Additive exPlanations approach (SHAP). Survival analyses were performed by Kaplan-Meier curves and CoxPH models (Experimental plan is reported in Figure 1). Results We first created a synthetic copy of a MDS cohort (n=2,043) using all the real data for training the model. We compared synthetic vs. real data, obtaining high fitness performances for both clinical and genomic features (CSF=93%; GSF=90%). HD were then applied to define clusters capturing broad dependencies among genomic features, showing comparable results in synthetic vs. real data; SHAP analysis indicated that similar features drive patients’ classification in both datasets. Finally, synthetic patients had comparable survival with respect to real ones; when applying conventional scoring system (IPSS-R), the probability of survival of the 5 risk categories was comparable between synthetic and real data. In the second experiment setting, we analysed synthetic MDS datasets with different size generated with model trained on a real dataset. Interestingly, when generating a synthetic augmented dataset (200%) we obtained high fitness performance for both clinical and genomic features (CSF=91%; GSF=89%). Moreover, all the performances showed a similar trend when considering a cohort of 1,002 patients with AML (CSF=92%; GSF=89%) thus proving evidence for high generalizability of the model across different clinical settings. Finally, we investigated if the generation of synthetic data can accelerate translational research in hematology. Since the first publication on clinical relevance of gene mutations in MDS (Leukemia 2014;28:241), it took several years to collect data in large patient populations for generating a molecular classification (JCO 2021;39:1223) and prognostic score (IPSS-M, NEJM Evid 2022;1:7). Starting from the MDS cohort available in 2014 (n=944, Leukemia 2014;28:241), we generated 300% augmented synthetic dataset. HD were applied to synthetic data to define genomic-based clinical entities, resulting in the identification of the same 8 subgroups described in a real cohort of 2,043 patients many years later. Moreover, we applied a CoxPH model to the synthetic dataset to generate a molecular prognostic score (IPSS-M_Syn). The model was based on similar molecular features as the real IPSS-M and identified 6 risk categories in which the probability of survival was similar to that of IPSS-M risk groups (Figure 2). Conclusion GAN-generated synthetic data recapitulate statistical properties and complexity of clinical and genomic features in different hematological malignancies, replicate reliable survival estimates and allow effective data augmentation. The implementation of this technology seems to accelerate precision medicine research in hematology. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Correlation of Mutational Profiles and Cytogenetics with Morphologic Dysplasia in Myelodysplastic Syndromes

Introduction: Myelodysplastic syndromes (MDS) are a spectrum of clonal bone marrow failure disorders demonstrating cytopenias, dysplasia, and risk of progression. Although ~50% of MDS patients have normal karyotype (NK), a subset of MDS exhibits genetic alterations that result in an abnormal karyotype. However, the relationship between the molecular landscape and histologic features in MDS have not been well explored. Using next generation sequencing (NGS) and cytogenetics, we sought to correlate genetic abnormalities in MDS with morphologic dysplasia. Methods: After IRB approval, we retrospectively identified NGS studies performed with a 164 gene panel in patients with MDS at Stanford (2018-2021). Molecular and cytogenetic data were collected for 225 MDS patients. Peripheral blood and bone marrow (BM) slides were collected from 61 patients for histological review. As controls, 32 staging BMs were obtained from untreated lymphoma patients. A hematopathologist performed a blinded intense morphologic review. A subset of cases was reviewed by 2 other hematopathologists and the intraclass correlation coefficient (ICC) was calculated to evaluate concordance. The degree of dysplastic features and overall dysplasia was scored. The standardized mean difference (SMD) was calculated to quantify the degree of dysplasia between comparison groups. Statistical analysis was performed using R (3.6.3); p value < 0.05 was considered statistically significant. Results: MDS cases had higher degrees of dysplasia than control cases in megakaryocytic (median 37.5% vs 0%), granulocytic (median 20% vs 0%), and erythroid (median 10% vs 0%) lineages. To assess specificity, using a cutoff of 10%, 1/31 control cases (3.1%) showed megakaryocytic dysplasia, 2/32 (6.3%) had erythroid dysplasia, while none showed granulocytic dysplasia. Dysplasia in > 2 lineages in >10% of cells was specific for MDS, detected in 49/61 (80.3%) of MDS cases vs 0/32 control cases (Table 1). Within the MDS group, lack of multilineage dysplasia was more common in NK (8/25; 32%) vs non-NK (3/36; 8.3%), suggesting MDS-NK is morphologically subtle. Using a cutoff of 10%, 13/25 (52%) NK lacked granulocytic dysplasia vs 10/36 (27.8%) in non-NK, 8/25 (32%) of NK lacked erythroid dysplasia vs 10/36 (27.8%) in non-NK, and 5/25 (20%) NK lacked megakaryocytic dysplasia vs 3/35 (8.3%) in non-NK. The most strongly associated dysplastic features for MDS included erythroid megaloblastic change (SMD=1.25), erythroid nuclear features (SMD=1.041), atypical megakaryocyte nuclei (SMD=1.189), separated megakaryocyte nuclei (SMD=1.131), and hypogranulated granulocytes (SMD=1.096). Based on 10 MDS and 5 control cases, rough concordance on overall dysplasia was demonstrated among 3 hematopathologists. Granulocytic dysplasia showed the highest reproducibility (ICC for granulocytic = 0.948, erythroid = 0.547, megakaryocytic = 0.531). The percent of cells with dysplasia in the MDS cohort did not correlate with number of mutations. The overall number of mutations between MDS with NK and non-NK were relatively similar (Figure 1). The non-NK group exhibited a greater frequency of pathogenic TP53 variants than NK (31.5% vs 2.6%, p < 0.0001). Conversely, SF3B1 and TET2variants occurred more frequently in the NK cohort than non-NK (SF3B1: 32.5% vs 12.6%; TET2: 29.8% vs 12.6%, both p values < 0.003). In MDS cases with a TET2 variant, NK was associated with a significantly higher total number of mutations than non-NK cases (median [IQR]: 5[5-7] vs 4[3-6], p = 0.031). Using Random Forest models, exploratory multivariate analysis identified the presence of mutations in TP53, SF3B1, TET2, and overall megakaryocytic, granulocytic, and erythroid dysplasia as the prominent parameters that distinguished NK from non-NK MDS cases. There was no significant difference in age at diagnosis between NK and non-NK MDS in all NGS cases (median age 74 vs 70, p = 0.10) and morphologically scored cases (median age 70 in both groups). Conclusion: Our study demonstrates that granulocytic dysplasia was the most specific morphologic finding for MDS with high reproducibility among 3 hematopathologists. Detection of dysplasia in > 2 lineages in >10% cells was also specific for MDS, while MDS-NK appear morphologically subtle. Mutations in TET2 were more frequent in MDS-NK. Our findings highlight the importance of NGS and histopathology in helping establish a diagnosis of MDS-NK. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Molecular International Prognostic Scoring System (IPSS-M) in Myelodysplastic Syndromes Arising from Aplastic Anemia and Paroxysmal Nocturnal Hemoglobinuria

Clonal evolution to myelodysplastic syndromes (MDS) or acute myeloid leukemia represents the most serious late complication of patients with aplastic anemia (AA) and paroxysmal nocturnal hemoglobinuria (PNH). The majority of secondary MDS (sMDS) cases present high-risk features with chromosome 7 abnormalities and mutations in ASXL1, RUNX1, SETBP1, and RAS pathway genes as the most frequent molecular lesions. Other cases tend to show more favorable outcomes with distinct genomic architecture mainly driven by generally considered low-risk cytogenetic alterations (e.g., del(13q), del(20q)). Such heterogeneity of genomic makeup, the rarity of the disease, and the scarcity of information make the prognostication of sMDS challenging for routine clinical practice. In recognition of the growing role of somatic mutations, the Molecular International Prognostic Scoring System (IPSS-M) has been conceived to improve the precision of prognostication of prior schemes by adding objective molecular markers. Whereas validated on de novo and secondary/therapy-related cases, its applicability specifically on post-AA/PNH MDS has not yet been explored. Here, we applied IPSS-M to 69 sMDS with complete clinico-genomic information from a large multicenter dataset of 1008 AA/PNH patients, using a comparator cohort of primary MDS (n=1281). The median age at MDS progression was 63 years (IQR, 34-70), and most patients were male (M:F ratio 1.65). Despite low bone marrow blast percentages (median, 2; 0-7), 71% of patients showed high-risk features according to IPSS-R (scores >3.5), chiefly due to the enrichment of poor risk cytogenetics, most frequently monosomy 7. Overall, 48% of patients received disease-modifying treatments (DMT) with either HMA (28%), HSCT (60%) or both (12%). Leukemia progression was registered in 14% of cases after a median of 5.4 months (1-14) from sMDS onset. With a median follow-up of 55.6 months (95%CI, 42.5-75.8), the 60-month overall (OS) and leukemia free-survival (LFS) achieved 44% (32-60) and 42% (31-58), respectively. The IPSS-R distribution was as follows: Very Low (6%), Low (23%), Intermediate (30%), High (23%) and Very High (18%). By applying IPSS-M, patients were redistributed in Very Low (5%), Low (19%), Moderate Low (14%), Moderate High (14%), High (29%), and Very High (19%) risk categories. When comparing five-to-five (merging together the Moderate Low/High IPSS-M categories), 55% of cases were re-stratified, of which 63% up- and 37% down-staged (Fig.1A). Indeed, 77% of sMDS patients harbored at least 1 mutation with 43% presenting >2, thereby substantiating the differences observed between the two prognostication systems. Although according to IPSS-M the majority (62%) of sMDS cases still clustered in higher-risk categories, a non-negligible fraction (38%) was assigned to lower-risk groups. To further explore whether IPSS-M could be used to predict OS/LFS also in sMDS cases, we analyzed survival outcomes by taking advantage of a cohort of de novo cases. However, approximately half of sMDS received DMT, potentially generating a bias when using survival as a surrogate for outcomes comparisons, even in cases falling into equivalent risk categories. Therefore, we applied a propensity score matching by using age, gender and DMT as relevant covariates to reduce any possible confounder. As reported for others MDS subtypes in the original IPSS-M study, OS/LFS outcomes of sMDS paralleled those observed in the de novo group within the various IPSS-M risk categories (Fig.1B). We applied for the first time IPSS-M in a real-world cohort of sMDS, showing its potential for refining the assignment of patients into risk categories prognostic of disease outcomes. The actuarial survival of sMDS cases was not distinct from de novo patients matched for basic clinical features in equivalent IPSS-M risk groups. The complexity of the genomic landscape typical of AA/PNH clonal evolution makes sMDS a prototypic model whereby the incorporation of molecular information is of paramount importance to ensure adequate clinical management. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Vexas Syndrome: A Complex Necessarily Integrated Diagnosis That Can Benefit from the Help of Deep Learning

Introduction At the end of 2020, a novel entity dubbed VEXAS (for vacuoles, E1 enzyme, X-linked, auto-inflammatory, somatic) was described by Beck et al. (NEJM, 2020). This syndrome is defined molecularly by a mutation of the UBA1 gene that codes for the E1 enzyme, a major actor of ubiquitinylation. From a pathophysiological point of view, UBA1 mutations induce the transcription of a deficient enzyme. Affected cells display an altered ubiquitinylation of misfolded proteins and dysregulated autophagy. This leads in fine to an impairment of several pathways of innate immunity, overproduction of a range of pro-inflammatory cytokines and, more generally, systemic inflammation. Clinical manifestations are pleomorphic and patient-dependent, with reported cases of fever, vasculitis, ophthalmic lesions, chondritis, Sweet syndrome or pulmonary interstitial infiltration. From a hematological point of view, thromboses have also been described as well as several cytologic alterations. The latter include cytopenias of any lineage, myeloid hyperplasia with erythroblastic hypoplasia (M/E) and, notably, the presence of vacuoles essentially in granulocytes and erythroblasts precursors. Some cases are associated to myelodysplastic syndrome (MDS). Here, an in-depth morphological examination of VEXAS and non-VEXAS patients was performed, to delineate and quantify several anomalies. These data were then fed to a deep learning algorithm to evaluate the additional help provided by this artificial intelligence (AI) tool in predicting VEXAS syndrome and orienting further analyses towards the identification of the molecular anomaly. Patients, material and methods To identify diagnostic tools for VEXAS syndrome on blood and bone marrow smears, 4 patient cohorts were analyzed :i) patients with a diagnosis of VEXAS syndrome confirmed by genetic analysis (n=6), ii) MDS patients (n=4), iii) patients with an initial clinical suspicion of VEXAS invalidated by molecular analysis (UBA1 WT: n=3) and iv) 4 healthy controls. For each patient, morphological examination of blood and marrow smears was performed independently by two experts in a blind fashion. In order to guide the diagnosis of the syndrome on the blood smears, a deep learning method was trained in a multilabel classification setting to automatically evaluate the percentages of abnormal polymorphonuclears (PMN). The final dataset was therefore composed of PMN from healthy controls (n=5, 519 images) and from VEXAS syndrome (n=4, 938 images) (DI microscope, Cellavision ®). Results Among the 6 patients with VEXAS syndrome, the main clinical manifestations were: asthenia 100%; fever 83.3%; skin involvement 66.7%; thrombosis 66.7%, chondritis 33.3% and interstitial lung disease 33.3%. The most frequent cytopenia was macrocytic anemia in 66.7% of the patients. Upon morphological examination of blood smears, the following abnormalities were statistically associated with the diagnosis of VEXAS : percentage of pseudo-Pelger PMNs (p=0.003), percentage of PMNs with more than 4 nuclear projections (Barr bodies; p=0.0009), percentage of vacuolated PMNs (p=0.01). On bone marrow smears, compared to the MDS and UBA1 WT cohort, patients with VEXAS syndrome had significantly more PMNs with a pseudo-Pelger aspect (p<0.05), more vacuolization of granular (p<0.05) and erythroblastic (p<0.05) precursors. Different deep learning architectures were tested on blood smear images, with the objectives of distinguishing abnormal PMN from others. The trainings were conducted by cross-validation, and then the algorithm was evaluated on new patients. The metrics used to evaluate algorithm performance were precision, recall, F1-score and Hamming loss. These data allowed to establish a standardized computer aided diagnosis tool. Discussion/conclusion The diagnosis of VEXAS syndrome is complex. This analysis identified cytological features on blood smears leading to the development of a deep learning-based diagnosis algorithm. Promising leads are currently investigated to improve the efficiency and robustness of this deep learning algorithm such as the inclusion of other pathologies in order to train a disease agnostic anomaly detection algorithm, or leveraging data from other modalities as prior knowledge.

Incidence, Clinical Associations, and Co-Mutation Patterns of UBA1 Mutations in MDS

Background Mutations in UBA1 are associated with VEXAS (Vacuoles, E1 enzyme, X-linked, Autoinflammatory, Somatic) syndrome, an adult-onset inflammatory disorder (Beck DB et al. NEJM 2020). Approximately 40% of VEXAS patients are also diagnosed with myelodysplastic syndromes (MDS). However, the prevalence and characteristics of UBA1 mutations in MDS are unknown. We hypothesize that UBA1 mutations underlie a proportion of MDS cases with systemic inflammation. Methods Molecular data were reviewed from a representative diagnostic and treatment-naive MDS cohort (n= 3,328) ascertained through the International Working Group for MDS (Bernard E et al NEJM Evid 2022). We prioritized 375 cases for UBA1 genotyping based on: 1) male gender; and 2) no identified driver mutations or few mutations, enriched in DTA (DNMT3A, TET2, ASXL1) genes; or 3) unclassifiable (MDS-U or MDS/MPN-U) per 2016 WHO Classification. We identified UBA1 hotspot mutations (M41T/V/L) with digital droplet PCR. Resulting UBA1 status was integrated with cytogenetic and sequencing data from 121 genes involved in myeloid pathogenesis to identify patterns of co-mutation. Clinical associations of UBA1 mutations were evaluated and where available, clinical history was reviewed for inflammatory conditions. Results We identified 30 UBA1 M41T/V/L mutations (median number mutant droplets: 1301; range: 4-12166) in 8% of the cohort (n=28 of 375 patients). This included 15 patients with M41T (c.122T>C), 7 with M41V (c.121A>G), 4 with M41L (c.121A>C), and 2 patients with more than one mutation (1 with M41V/T, and 1 with M41L/V). In 79% of UBA1-mutant cases (22/28), the karyotype was normal. Loss of the Y chromosome was observed in 6 cases. Three cases had MDS-associated cytogenetic abnormalities: del(11q), del(13q) and focal del(20q). In 43% of UBA1-mutant cases (12/28), UBA1 mutations were the sole genetic abnormalities. For a further 43% we observed co-mutation with DTA genes (DNMT3A, TET2, ASXL1) with median variant allele fraction (VAF) of 0.21 (0.02-0.56). SF3B1 co-mutations with VAF >30% were observed in 3 cases. Most UBA1-mutant cases were classified per 2016 WHO as MDS-SLD/MLD (n=18), but two cases were MDS with excess blasts 1, and one case was CMML-1 with 9% blasts. The median age at diagnosis was 72 years (44-89). No significant difference was found when comparing clinical parameters (blast counts, complete blood counts, age) between UBA1 mutant and wildtype MDS MDS. Clinical history was readily available for 4 UBA1-mutant patients. Inflammatory symptoms were reported in 3 patients, localized in the lungs (n=2), skin (n=2) and cartilage (n=1). Two patients also had a diagnosis of inflammatory/rheumatological disease (vasculitis and relapsing polychondritis), two patients had thrombosis, one had a history of monoclonal gammopathy of undetermined significance. The 4th patient, without inflammatory symptoms, had a prior diagnosis of T-cell large granular lymphocytic leukemia. Follow-up for transformation to acute myeloid leukemia (AML) and overall survival was available for 310 and 339 patients, respectively. No UBA1-mutant patients transformed to AML (n=24; median follow-up 2.6 years). There was no difference in overall survival between UBA1-mutant (n=27) and wildtype (n=312) patients (log-rank test p = 0.7), however, when subsetting for patients with no mutations detected by targeted DNA sequencing (UBA1-mutant n=7; wildtype n=45), UBA1-mutant patients had worse overall survival (median 5.2 vs 7.3 years; log-rank test p = 0.03). ConclusionUBA1 mutation in isolation or in combination with other mutations implicated in myeloid pathogenesis account for a significant proportion (8%) of patients diagnosed and treated as MDS but without established disease classification. Ongoing work includes 1) clinical review of inflammatory symptoms for the remaining UBA1-mutant cases and 2) profiling a larger cross-section of MDS by a UBA1 targeted panel to characterize mutations beyond the M41 locus.

Development and validation of a novel prognosis prediction model for patients with myelodysplastic syndrome.

BackgroundSomatic mutations are widespread in patients with Myelodysplastic Syndrome (MDS) and are associated with prognosis. However, a practical prognostic model for MDS that incorporates somatic mutations urgently needs to be developed.MethodsA cohort of 201 MDS patients from the Gene Expression Omnibus (GEO) database was used to develop the model, and a single-center cohort of 115 MDS cohorts from Northwest China was used for external validation. Kaplan-Meier analysis was performed to compare the effects of karyotype classifications and gene mutations on the prognosis of MDS patients. Univariate and multivariate Cox regression analyses and Lasso regression were used to screen for key prognostic factors. The shinyapps website was used to create dynamic nomograms with multiple variables. The time-dependent receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA) were used to evaluate the model’s discrimination, accuracy and clinical utility.ResultsSix risk factors (age, bone morrow blast percentage, ETV6, TP53, EZH2, and ASXL1) were considered as predictor variables in the nomogram. The nomogram showed excellent discrimination, with respective the area under the ROC curve (AUC) values of 0.850, 0.839, 0.933 for the training cohort at 1 year, 3 years and 5 years; 0.715, 0.802 and 0.750 for the testing cohort at 1 year, 3 years and 5 years; and 0.668, 0.646 and 0.731 for the external validation cohort at 1 year, 3 years and 5 years. The calibration curves and decision curve showed that the nomogram had good consistency and clinical practical benefit. Finally, a stratified analysis showed that MDS patients with high risk had worse survival outcomes than patients with low risk.ConclusionWe developed a nomogram containing six risk factors, which provides reliable and objective predictions of prognosis for MDS patients.

Identification of a novel HOOK3-FGFR1 fusion gene involved in activation of the NF-kappaB pathway

BackgroundRearrangements involving the fibroblast growth factor receptor 1 (FGFR1) gene result in 8p11 myeloproliferative syndrome (EMS), which is a rare and aggressive hematological malignancy that is often initially diagnosed as myelodysplastic syndrome (MDS). Clinical outcomes are typically poor due to relative resistance to tyrosine kinase inhibitors (TKIs) and rapid transformation to acute leukemia. Deciphering the transcriptomic signature of FGFR1 fusions may open new treatment strategies for FGFR1 rearrangement patients.MethodsDNA sequencing (DNA-seq) was performed for 20 MDS patients and whole exome sequencing (WES) was performed for one HOOK3-FGFR1 fusion positive patient. RNA sequencing (RNA-seq) was performed for 20 MDS patients and 8 healthy donors. Fusion genes were detected using the STAR-Fusion tool. Fluorescence in situ hybridization (FISH), quantitative real-time PCR (qRT-PCR), and Sanger sequencing were used to confirm the HOOK3-FGFR1 fusion gene. The phosphorylation antibody array was performed to validate the activation of nuclear factor-kappaB (NF-kappaB) signaling.ResultsWe identified frequently recurrent mutations of ASXL1 and U2AF1 in the MDS cohort, which is consistent with previous reports. We also identified a novel in-frame HOOK3-FGFR1 fusion gene in one MDS case with abnormal monoclonal B-cell lymphocytosis and ring chromosome 8. FISH analysis detected the FGFR1 break-apart signal in myeloid blasts only. qRT-PCR and Sanger sequencing confirmed the HOOK3-FGFR1 fusion transcript with breakpoints located at the 11th exon of HOOK3 and 10th exon of FGFR1, and Western blot detected the chimeric HOOK3-FGFR1 fusion protein that is presumed to retain the entire tyrosine kinase domain of FGFR1. The transcriptional feature of HOOK3-FGFR1 fusion was characterized by the significant enrichment of the NF-kappaB pathway by comparing the expression profiling of FGFR1 fusion positive MDS with 8 healthy donors and FGFR1 fusion negative MDS patients. Further validation by phosphorylation antibody array also showed NF-kappaB activation, as evidenced by increased phosphorylation of p65 (Ser 536) and of IKBalpha (Ser 32).ConclusionsThe HOOK3-FGFR1 fusion gene may contribute to the pathogenesis of MDS and activate the NF-kappaB pathway. These findings highlight a potential novel approach for combination therapy for FGFR1 rearrangement patients.

Der(1;7)(q10;p10) Presents with a Unique Genetic Profile and Frequent ETNK1 Mutations in Myeloid Neoplasms

BackgroundDer(1;7)(q10;p10) (der(1;7) is an unbalanced translocation recurrently found in myeloid neoplasms, particularly in myelodysplastic syndromes (MDS) and related disorders. Caused by a recombination between two homologous alphoid sequencing D1Z7 and D7Z1 on chromosomes 1 and 7, respectively, it results in monosomy 7q and trisomy 1q, which is implicated in the pathogenesis of der(1;7)-positive myeloid neoplasms. Previous studies reported frequent co-occurrence of +8 and del(20q), as well as RUNX1 mutations, the genetic and clinical characteristics of this abnormality has not fully been elucidated.MethodsIn this study, we enrolled a total of 153 cases myeloid neoplasms positive for der(1;7) from Japanese and German cohorts, in which co-occurring genetic lesions were analyzed using whole exome and/or targeted-capture sequencing. An additional 3,223 MDS and related neoplasm cases were also analyzed using targeted-capture sequencing to identify der(1;7)-specific genomic features.ResultsEthnicity was evaluated comparing the frequency of der(1;7) in 944 German MDS cases and 763 Japanese MDS cases. Der(1;7) cases were observed at a higher frequency in Japanese MDS cohort compared to German MDS cohort (73/763 cases versus 4/944 cases, p < 0.00001). Der(1;7) cases showed a strong male predominance (86.3%) (p<0.001). Of 153 myeloid neoplasm patients harboring der(1;7), 114 were diagnosed with MDS, 28 with AML, 5 with MDS-MPN and 1 with MPN. Targeted-capture sequencing revealed mutations in common myeloid drivers (n=61) in 96% of der(1;7) cases. The most frequently mutated gene was RUNX1 with 46%, followed by ETNK1 (24.5%) and EZH2 (24.5%). Of interest, ETNK1 mutation was identified as the most unique to der(1;7) when compared to myeloid neoplasm cases without der(1;7) (n=3,066) [odds ratio (OR)=15.06], followed by ETV6 (OR=9.35) and EZH2 (OR=6.52). To further examine the uniqueness of this mutation profile, the mutational profile of der(1;7) was compared to those myeloid neoplasm cases harboring amp(1q) (n=52) and monosomy 7 (n=105). Highly frequent ETV6 and ETNK1 mutations were highly unique to der(1;7) cases when compared to amp(1q) cases (OR=3.72, OR=2.57, respectively). BCOR and ETNK1 mutations were highly unique to der(1;7) cases when compared to monosomy 7 cases (OR=35.88, OR=4.29, respectively). Both amp(1q) and monosomy 7 cases showed a higher mutation rate in TP53 compared to der(1;7) cases (49.1% and 51%, respectively, vs 3.5 %) . From these mutational characteristics, ETNK1 was identified as being the most unique to der(1;7) when compared to amp(1q), monosomy 7 and other myeloid neoplasm cases. ETNK1-mutated der(1;7) cases were featured with eosinophilia (p < 0.0005), a lack of RAS pathway mutations and trisomy 8 when compared to ETNK1-wild type der(1;7) cases.Survival analysis was conducted to elucidate the difference in survival in der(1;7) cases (n=65) versus myeloid neoplasm cases (n=2066). Der(1;7)-harboring myeloid neoplasm cases had a median overall survival of 6.8 months (95% CI, 3.5 to 11.9) and non-der(1;7) harboring myeloid neoplasm cases were 11.8 months (95% CI, 10.5 to 12.6). Thus, der(1;7)-harboring myeloid neoplasm cases had poorer prognosis (p<0.001).ConclusionIn conclusion, der(1;7) is an unbalanced translocation that occurs predominantly in males and is seen more frequently in Japanese than Caucasian populations. Der(1;7) cases present with a mutational profile that is distinct from other myeloid neoplasm cases such as those with amp(1q) and monosomy7/del(7q), showing frequency of ETNK1 mutations. DisclosuresNannya: Otsuka Pharmaceutical Co., Ltd.: Consultancy, Speakers Bureau; Astellas: Speakers Bureau. Kern: MLL Munich Leukemia Laboratory: Other: Part ownership. Haferlach: MLL Munich Leukemia Laboratory: Other: Part ownership. Atsuta: Astellas Pharma Inc.: Speakers Bureau; Mochida Pharmaceutical Co., Ltd.: Speakers Bureau; AbbVie GK: Speakers Bureau; Kyowa Kirin Co., Ltd: Honoraria; Meiji Seika Pharma Co, Ltd.: Honoraria. Handa: Ono: Honoraria; BMS: Honoraria; Janssen: Honoraria; Daiichi Sankyo: Research Funding; Celgene: Honoraria, Research Funding; Chugai: Research Funding; Kyowa Kirin: Research Funding; Takeda: Honoraria, Research Funding; Sanofi: Honoraria, Research Funding; Abbvie: Honoraria; MSD: Research Funding; Shionogi: Research Funding. Ohyashiki: Novartis Pharma: Other: chief clinical trial; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees. Haferlach: MLL Munich Leukemia Laboratory: Other: Part ownership. Ogawa: Otsuka Pharmaceutical Co., Ltd.: Research Funding; Eisai Co., Ltd.: Research Funding; Kan Research Laboratory, Inc.: Consultancy, Research Funding; Dainippon-Sumitomo Pharmaceutical, Inc.: Research Funding; ChordiaTherapeutics, Inc.: Consultancy, Research Funding; Ashahi Genomics: Current holder of individual stocks in a privately-held company.

Identification of Novel Prognostic Biomarkers DDX11 and CHD1 of Allogeneic Hematopoietic Cell Transplantation Outcomes for Patients with MDS: A CIBMTR Comprehensive Genomic Screening

BACKGROUNDMyelodysplastic syndromes (MDS) represent a heterogeneous group of myeloid malignancies characterized by cytopenia and increased risk of progression to acute myeloid leukemia (AML) driven by accumulated somatic mutations in hematopoietic stem cells (HSCs). While recurrent mutations are known to associate with adverse outcomes in myelodysplastic syndrome (MDS), 10% of MDS cases have no known genetic indicators for survival prognosis. Whole genome sequencing (WGS) detects comprehensive mutations on coding and non-coding regions that empowers discovery of novel genetic biomarkers.METHODSWe conducted WGS at 60x read depth on 494 MDS patient subjects and scanned genome-wide for novel somatic biomarkers associated with MDS post allogeneic hematopoietic cell transplantation (allo-HCT) outcomes. Forward and backward stepwise variable selection was performed, and important clinical covariables were integrated into multivariate Cox proportional hazard models for survival outcome association tests. To test for associations with overall survival (OS), we conducted burden tests of somatic variants by summing the number of somatic nonsynonymous (missense, nonsense, splice) mutations per gene and testing for association with OS. For non-coding regions, we applied a sliding window approach, summing somatic mutations within each 10kb window and testing for association with OS. Furthermore, to distinguish potentially novel biomarkers from mutations in known MDS prognostic genes, we re-ran our association analyses considering only those MDS subjects with no known mutations in previously-identified prognostic genes for post allo-HCT survival(including TP53, RAS, JAK2, TET2, EZH2, ETV6, RUNX1, DNMT3A and ASXL1).RESULTSGenome-wide analyses of somatic coding variants on OS identified two statistically significant associations (Figure 1A I); one at TP53 (hazard ratio [HR], 2.19; 95% confidence intervals [CI] 1.48-2.75; P = 1.51e-06) and the other at HCN2 (HR, 5.84; 95% CI 2.38-14.34; P=1.18E-04). When we restricted our analyses to those patients with no mutations in known prognostic genes (N=301), we found one statistically significant candidate at DDX11 (HR, 3.74; 95% CI 1.87-7.47; P=1.83E-04). When we expanded our analyses to include non-coding somatic variants, we observed five additional significant genes (Figure 1A II, IV) including CHD1 (HR, 7.31; 95% CI 3.33-16.08; P=7.45E-07) that was significantly associated with post allo-HCT OS in the patient subset with no known mutations. Meta-analyses of OS using TCGA lymphoma and AML/MDS data provided validation that DDX11 and CHD1 mutations are associated with poor overall survival in hematopoietic malignancies (data not shown).Interestingly, many of the candidates from these analyses (e.g., DDX11, CHD1, RASGRF1 and ARHGEF7) are involved in DNA repair pathways. Gene set enrichment analyses confirmed that our association results are enriched a TP53-centered networks (p value: 0.0042, Figure 1B).Besides the novel candidates, a known MDS prognostic gene TP53 was replicated by our nonbiased screening approach. Co-occurrence of TP53 mutation and complex karyotypes, as well as high VAF of TP53 mutations in our MDS cohort were highly associated with poor post allo-HCT OS (data not shown). MDS patients with TP53, DDX11 and CHD1 mutations were overrepresented in samples with complex karyotypes.CONCLUSIONSOverall, through WGS of samples obtained at the time of allo-HCT, we identified two novel genetic prognostic biomarkers, DDX11 and CHD1 mutations, which were associated with inferior post allo-HCT OS. These results once validated could contribute to personalized risk assessments of post HCT outcomes for MDS patients. [Display omitted] DisclosuresSaber: Govt. COI: Other.

Characterization of Somatic Mosaicism and Mutational Profiling of Clonal Hematopoiesis Compared to MDS and sAML Depicts Diversities of Clonal Evolution

Background:Clonal hematopoiesis (CH) describes the presence of genetic alterations and expansion of clonal cell populations in the peripheral blood (PB) of individuals without clinical manifestation of a hematologic malignancy. CH is a common, age-related state. However, individuals carrying CH are at greater risk for hematologic cancer. It has been shown that presence of TP53- and other high-risk mutations, variant allele frequency (VAF) >10% or multiple mutations in CH carriers may confer a higher risk of preleukemic development and transformation to myelodysplastic syndrome (MDS) or acute myeloid leukemia (AML). Nevertheless, further insights into the role of CH in clonal evolution towards leukemia and elaborating features that are predictive of leukemic progression are needed.Aims:We have recently shown that CH is common in individuals undergoing hip replacement surgery (Hecker, Hartmann et al., Blood 2021). Here, we compared mutational spectrum in these CH individuals to MDS and secondary AML (sAML) cohorts. Additionally, we analyzed spatial and lineage distribution of CH and longitudinally monitored CH and MDS clones over time.Methods:Samples from individuals without known hematologic disease undergoing hip replacement surgery (n=288 samples from 261 individuals), patients with MDS (n=92) or sAML (n=123) were screened for variants in 68 leukemia-associated genes using a targeted sequencing approach (VAF cut off, 1%). Follow-up (FU) PB samples were available for 21 individuals with CH and 16 untreated low-risk MDS patients, 6-24 months after screening. n=5 CH bone marrow (BM) samples carrying six ASXL1-mutations were sorted for seven different cell fractions.Results:At screening, variants were detected in 127/261 (49%) healthy individuals, 84/92 (91%) MDS and 117/123 (95%) sAML patients, with median VAFs of 2.7% (ranging from 1-44%), 18.8% (1.1-87%) and 37.1% (1-99%), respectively. Individuals with CH had a median number of 1 variant per individual, whereas median detected variants per patient increased with clonal evolution with 3 variants in the MDS and 4 variants per patient in the sAML cohort.CH, MDS and sAML showed entity-specific mutation profiles (Figure 1A). Most variants in CH affected epigenetic modifiers, while mutations in splicing factors, signaling pathways and transcription factors increased with clonal progression.During FU, untreated low-risk MDS patients more frequently gained additional mutations compared to CH individuals (7/16 vs 2/21, respectively; p=0.024). However, we did not observe significant changes in clone sizes over time.In 17 hip replacement individuals both femoral heads were removed simultaneously, allowing paired analysis of two different hematopoietic sites. CH prevalence in this subgroup was 70.6% (12/17). Ten individuals showed identical mutation patterns in BM obtained from the right and left femoral head, with little differences in VAFs (Table 1). In contrast, two other individuals showed significant differences in variant detection comparing one to the other side: ASXL1-mutations were only present in one hip sample, whereas all the other variants were detectable in both sides (p<0.001), indicating possible spatial heterogeneity of CH clones in the BM compartment.To further characterize ASXL1 mosaicism across hematopoietic lineages and differentiation stages, we sorted and sequenced n=5 CH BM samples carrying six ASXL1-mutations for seven different hematopoietic cell fractions. In all cases ASXL1-mutations were identified in CD34 +CD38 -CD90 + hematopoietic stem cells (HSC). VAFs of ASXL1-mutations were differentially distributed (p=0.0049, Kruskal Wallis test): detected VAFs were significantly higher in HSC and common myeloid progenitors (CMP) compared to VAFs in T-cells (p=0.045 and p=0.011, respectively; Dunn´s multiple comparison test; Figure 1B).Conclusions:CH, MDS and sAML show characteristic mutation profiles that remained stable over a 6-24-month period. Gains of additional variants and clonal expansion associated with disease progression. Cellular distribution analysis of ASXL1 CH variants revealed characteristic repartition patterns within the hematopoietic differentiation tree. Additionally, differences in variant detection between cellular BM compartments indicates spatial heterogeneity of CH clones warranting further investigation.J.S.H. and L.H. contributed equally. [Display omitted] DisclosuresPlatzbecker: Geron: Honoraria; Takeda: Honoraria; AbbVie: Honoraria; Celgene/BMS: Honoraria; Janssen: Honoraria; Novartis: Honoraria. Goetze: BMS/Celgene: Other: Advisory Board, Research Funding; Abbvie: Other: Advisory Board.