Citations

Background: While myeloproliferative neoplasms (MPN), including essential thrombocythemia (ET), polycythemia vera (PV), and primary myelofibrosis (MF), are usually sporadic, adult-onset neoplasms, an increasing number of germline risk alleles have been described (e.g. EGLN1, ETV6, SH2B3, and ATM) in these disorders. DDX41MT Germline Predisposition Syndrome (GPS) is the most common myeloid GPS in adults and while there is extensive data on MDS/AML, little is known regarding MPN occurring in this context. We carried out this study to define the prevalence and characteristics of DDX41MT-GPS associated MPN. Methods: After IRB approval, we retrospectively assessed the Mayo Clinic cohort of 174 patients with DDX41MT-GPS, which included both pathogenic and clinically relevant germline variants of undetermined significance (VUS), based on our previous analysis (Badar et al Haematologica 2023). Standard statistical measures were applied. Results: We identified 12 (6.9%) patients with MPN (ET-5, PV-2, PMF-4, MPN-NOS-1). The median age at MPN diagnosis was 61.2 years (range, 8.-70.4); 58.3% (n=7) were male, and 83.3% (n=10) were Caucasian. A family history of hematologic malignancy was present in 16.7% (n=2, AML and T-LGL), while 50% (n=6) had a family history of visceral malignancies and 41.7% (n=5) had no family history of malignancies. Among ET patients (n=5) with DDX41MT-GPS, JAK2V617F was the MPN driver in 4 (80%) while type 1-CALR (L367fs*46) was a driver in 1 (20%). This included a 9-year-old child diagnosed with JAK2V617FMT ET. The DDX41 variant was classified as pathogenic in 40% (n=2; E113Kfs*14, D140Gfs*2) and VUS in 60% (n=3; V544L, V591I, P38L). Bone marrow (BM) aspirates in the ET patients were hypercellular in 40% (n=2), normocellular in 40% (n=2) and hypocellular in 20% (n=1), and none had increased blasts, or reticulin fibrosis (RF). In addition to JAK2V617F, somatic mutations seen included SF3B1 (K666T, VAF 16%) in 1 patient and IDH2 (R140Q, VAF 6%) and DNMT3A (R882H, VAF 7%) in 1 patient, respectively. With a median follow-up from diagnosis of 3.9yrs (range 2.9-8.9), there were no thrombotic events and no disease progressions was documented. There were 2 patients with JAK2V167FMT PV in whom the DDX41MT were clinically significant VUS (c.138+5G>T and M155I). Both patients had hypercellular BM, with no increase in blasts, no RF, normal karyotypes and no additional somatic mutations. With a median follow up of 7.5yrs (range, 2.1-12.9), 1 patient developed a deep vein thrombosis (DVT) and there were no fibrotic or leukemic transformations. There were 4 patients with PMF; 3 (75%) with JAK2V617F and 1(25%) with a type 1-CALR driver mutation (L367fs*46). DIPPS-plus scores ranged from 1 to 4 (median 2.5). The DDX41 variants were pathogenic in 50% (n=2, E256K and P78Qfs*3) and VUS in 50% (n=2, P510S and M155I). The median grade of RF at PMF diagnosis was grade 2 (range, 2-3). BM were hypercellular in 75% (n=3) and hypocellular in 25% (n=1), and 1 patient had 3% peripheral blasts (and no BM blasts). Somatic co-mutations included TET2 in 1 patient with a JAK2V617F, and CBL, EZH2 and SRSF2 in 1 patient with a CALR driver-mutation, respectively. PMF patients were treated with ruxolitinib (n=3), stem cell transplant (n=1), and pIFNα (n=1). With a median follow up of 3.9yrs (range,1.1-21.9), all patients were alive, and none had leukemia transformation. There was 1 patient with a JAK2V617F MPN-NOS with trisomy 9, where the DDX41MT-GPS was a VUS (I215L). There were no somatic co-mutations and at last follow up (3.1 years), there was no evidence for progression. Conclusions: While associations between late onset MDS/AML and DDX41MT-GPS has been well established, we systematically describe the MPN landscape seen in this context. MPN was diagnosed in 7% of our cohort, with JAK2V617F being the most common driver mutation. Most importantly, unlike in AML/MDS, where somatic DDX41 mutations are frequently associated with neoplastic transformation (30-50%; R525H being most common), none of our MPN patients had a somatic DDX41 mutation. Our work underscores the importance of germline mutation testing in patients with MPN.

Background: JAK2 mutations are invariably associated with polycythemia vera (PV); more than 50% of affected patients also harbor non-JAK2 mutations, some considered prognostically relevant (BJH 2020;189:291). We queried a large single institutional database of patients with PV, in order to examine the incidence and distribution of non-JAK2 mutations, across different disease stages, in order to assess their impact on disease phenotype and prognosis, in the context of other risk factors. Methods: Mayo Clinic databases (1998-2023) were searched to identify next-generation sequencing (NGS)-annotated patients with PV, with diagnosis retrospectively fitted to meet the 2022 International Consensus Classification (ICC) criteria (Blood 2022; 140:1200). NGS was performed either through research-based targeted capture assays or a clinically ordered 42-gene panel. Conventional statistical methods were used for group comparisons and survival analyses. Results: i) Mutational frequencies in chronic vs. transformed disease phases 319 patients with PV were considered; NGS was performed at time of i) diagnosis or before fibrotic or leukemic transformation (N=270; 84.6%), ii) fibrotic progression (N=37; 11.6%), or iii) leukemic transformation (N=12; 3.8%). Mutational frequencies in newly-diagnosed/chronic phase PV were 19% for TET2, 10% for ASXL1, 4% for SRSF2, ⁓3% each for SF3B1, DNMT3A, and SH2B3, and 1-2% each for TP53 and IDH2. Significant differences in mutation distribution were apparent for TP53/SRSF2/IDH1/U2AF1 in blast (50%/25%/17%/8%) vs. fibrotic (8%/0%/0%/5%) vs. chronic (2%/4%/2%/0.4%) phase (p<0.01, <0.01, =0.03, and =0.03, respectively). ii) Phenotypic correlates of specific mutations among patients with NGS information obtained during chronic phase (N=270) Median age was 61.4 years (51% males) and incidence rates included 22% for leukocytosis ( ≥15 x 10(9)/L) and 25%/14% for arterial/venous thrombosis history. Numerically prevalent or prognostically relevant mutations were selected for comparison of clinical or laboratory characteristics: TET2, ASXL1, SRSF2, TP53, IDH2. Significant associations were apparent for ASXL1 (younger age distribution), SRSF2 (older age distribution, leukocytosis), and TP53 (leukocytosis) mutations. Median age was 66.4, 58.7, 76.8, 63.9, and 68.6 years for TET2, ASXL1, SRSF2, TP53, IDH2 mutations, respectively (p<0.01). The corresponding median leukocyte counts were 12.1, 11.4, 14.4, 16.7, and 11.5 x 10(9)/L (p<0.01). iii) Prognostic impact of mutations detected at diagnosis or chronic phase (N=270) At median follow-up of 9.5 years (range 0.1-42.4), 115 (43%) deaths, 12 (4%) leukemic transformations, and 53 (20%) fibrotic progressions were documented. In univariate analysis of mutations, overall survival (OS) was adversely affected by SRSF2 and IDH2 mutations, leukemia-free survival (LFS) by ASXL1, SRSF2, IDH2, RUNX1, and CEBPA mutations, and myelofibrosis-free survival (MFS) by SRSF2 mutation. Age-adjusted (p<0.01) multivariable analysis, including mutations and other risk variables, identified SRSF2 (HR 4.2, 95% CI 1.9-9.5), ASXL1 (HR 2.0, 1.1-3.7), IDH2 (HR 5.3, 1.8-15.3) mutations and leukocytosis ≥15 x 10(9)/L (HR 2.0, 1.3-3.1) as independent predictors of inferior OS. SRSF2 and ASXL1 mutations were also independently associated with inferior LFS (p=0.02 and 0.06, respectively) and SRSF2 (p<0.01) and karyotype (p<0.01) with inferior MFS (p<0.01). Median survival for 235 patients without any adverse mutation (ASXL1, SRSF2, or IDH2) was 17.8 years vs. 8.8 years for 35 patients with any one of the three adverse mutations (p=0.01; HR 1.8, 95% CI 1.1-2.9). The number of non-JAK2 mutations, in general, was also associated with significantly different survival outcomes: median OS was 20, 15.1, and 9.3 years for patients with non-JAK2 mutations numbering zero, one, or two or more, respectively (p<0.01) Conclusions: SRSF2 mutations in PV cluster with older and ASXL1 with younger age distribution. SRSF2 and TP53 mutational frequencies were higher in blast-phase disease. SRSF2, ASXL1, and IDH2 mutations were significantly associated with inferior OS, independent of each other and other risk factors. SRSF2 mutations were also detrimental to LFS and MFS and ASXL1 to LFS. Such information might allow further refinement of current risk models for PV, which in future studies should also account for variant allele frequency.

Here we review the ‘what and how’ of molecular techniques used in the context of haematopathological diagnostics of both lymphoid and myeloid neoplasms. Keeping in mind that the required resources for molecular testing are not universally available, we will not only discuss novel and emerging techniques that allow more high‐throughput and sophisticated analyses of lymphoid and myeloid neoplasms, but also the more classical, low‐cost alternatives and even some workarounds for molecular testing approaches. In this review we also address other key aspects around molecular techniques for haematopatholgy diagnostics, including preanalytics, data interpretation, and data management, bioinformatics, and interlaboratory precision and performance evaluation.

Abstract Background In complex automated clinical laboratory Next Generation Sequencing (NGS) workflows, numerous opportunities exist for contamination events to occur. For oncology testing applications, detection of these events is crucial for accurate results reporting. A contamination detection module (MICon) using microhaplotype (MH) regions and an in-house designed analysis model was developed for use in a NGS assay for myeloid neoplasms (NGSHM) [1]. Variant detection for NGSHM has a validated analytical sensitivity of 2% variant allele frequency (VAF). Gross contamination events can potentially cause erroneous false positive variant detection whereas true low VAF mutations may be masked and evade detection. The following study was performed to evaluate MICon module performance on samples processed over the course of a year. Methods MH regions contain highly conserved tandem single nucleotide polymorphisms (SNPs) with high global heterogeneity occurring within a 300-nucleotide span. From the work of Kidd et al [2], 27 MH regions covering 92 SNPs and spanning 16 chromosomes were selected for inclusion in the 47 gene NGSHM target-capture panel. Sequencing was performed on a NovaSeq 6000 and analyzed through an internal bioinformatics pipeline, which incorporates the MICon module. MICon uses a binary classification model incorporating VAFs from MH regions, number of MH genotypes, and the contamination estimation score from verifyBamID to compute a single value on a 0-100 scale. Scores <50 are classified as non-contaminated and scores ≥50 require further investigation. Results The dataset was comprised of 10,990 samples. A total of 10,232 patient cases (93.1%) had non-contaminated MICon scores <50. Control replicates accounted for 261 samples (2.4%). There were 497 patient cases (4.5%) with MICon scores ≥50. Of the 497 patient cases, 137 (27.6%) had undergone hematopoietic stem cell transplantation (HSCT) and 114 (22.9%) contained gross chromosomal abnormalities, representing iatrogenic or tumor biological factors. An additional 135 (27.2%) of cases were contaminated from laboratory processing errors, 45 (9.1%) occurred due to chemistry failures during run processing, and 66 (13.2%) had an undetermined cause for a high score, representing laboratory-related and unknown factors. Overall, the 135 laboratory processing errors detected accounted for 1.3% of patient cases analyzed by the laboratory. These cases were repeated, and the non-contaminated results were accurately reported. Conclusions Herein it was shown the implementation of MICon has improved patient safety over the course of a year. The 1.3% of patient cases identified as arising from laboratory processing errors were successfully reprocessed. While the overall rate of laboratory processing errors appears low, the absolute number can be significant in a high-volume test setting, despite reliance on highly automated processes. Value is added by MICon through identifying errors that could result in the release of inaccurate patient results. By detecting previously unrealized errors, MICon has become an invaluable asset to the NGSHM assay by enhancing patient laboratory testing safety. References: [1] Balan J, et al. MICon Contamination Detection Workflow for Next-Generation Sequencing Laboratories Using Microhaplotype Loci and Supervised Learning. J Mol Diagn. 2023;25(8):602-610. doi:10.1016/j.jmoldx.2023.05.001. [2] Kidd KK, et al. Selecting microhaplotypes optimized for different purposes. Electrophoresis. 2018;39(21):2815-2823. doi:10.1002/elps.201800092.

Abstract The ZRSR2 gene is a member of the spliceosome gene family which are frequently mutated in myeloid neoplasms. ZRSR2 mutations (ZRSR2m) occur in less than 5% of MDS, CMML, and AML. Our study included 164 ZRSR2m patients (98.8% males) and 98 ZRSR2wt MDS control cohort. In the ZRSR2m group, there were 53 MDS (32%), 39 CCUS (24%), 33 MPN (20%), 23 MDS/MPN overlap (14%), 15 AML (9%), and 1 MPAL (0.6%). Most MDS patients were the low blast subtype (n=37, 70%). Twenty-seven MDS patients (51%), and 23 CCUS patients (59%) had absolute monocyte count ≥0.5 x109/L and 18 of 23 MDS/MPN overlap were CMML (78%). Mutations in ZRSR2 were spread across the entire gene. The median number of co-mutations was 2, with TET2 (51%) and ASXL1 (32%) being the most common. U2AF1 and SRSF2, previously described as mutually exclusive with ZRSR2, were found in 10.4% of patients. Median overall survival (OS) was 51 months, and significantly varied among MNs (p=0.004). ZRSR2m MDS patients had better mOS than the MDS control cohort with ZRSR2wt (35 vs 22 months, p=0.013). ZRSR2m patients with isolated TET2 co-mutation and higher hemoglobin showed improved survival, while patients with RUNX1m, higher WBC count showed worse OS.

Abstract Heterozygous germline variants in DDX41 are identified in ~5% of patients with Myelodysplastic Syndrome (MDS) or Acute Myeloid Leukemia (AML). Recognition of the hereditary nature of such cancers and a better understanding of the factors that affect progression to malignancy has deep implications for health surveillance of patients and relatives that share a pathogenic DNA variant. DDX41 has a role in ribosome biogenesis and in opposing R-loop accumulation at promoters, but the mechanisms through which DDX41 loss drives cancer development are poorly understood. In a collaboration between Cambridge, UK and Mayo Clinic, USA we identified 85 patients with germline DDX41 variants [73/85 with germline pathogenic variants (GPV) and 12 with variants of uncertain significance (VUS)]. The majority were identified through targeted myeloid NGS upon presentation with AML (30/85) or MDS (44/85). Average age at diagnosis was 65 (35-93) with male predominance (57/85). The most common GPV was the NM_016222.4(DDX41):c.415_418dup; p.D140Gfs*2 (15/85). The majority (53.4% 39/73), also acquired a somatic variants in the other DDX41 allele (referred to as GPV+Som). The most common somatic variant (82% 32/39) was the R525H, a variant predicted to reduce the ATPase function of the helicase domain. We hypothesise that the markedly reduced DDX41 activity in cells with biallelic variants, is a key cause of progression to overt malignancy. In our cohort, we observed that somatic variants occurred at a similar frequency in association with start loss, truncating, splice, in-frame deletion, and missense GPV. However, whereas MDS was the predominant diagnosis within GPV (67.6% 23/34, AML 26.4% 9/34), AML was the most frequent diagnosis within GPV+Som (AML 51%.2 20/39, MDS 38.4% 15/39). Overall, there was a significantly higher likelihood of AML in the presence of a somatic variant (p<0.05), suggesting that there might be a dosage effect on the phenotype. This pattern was observed across all the GPV, with the exception of missense, suggesting that many might be benign polymorphysms. In addition, although somatic variants are typically subclonal (overall mean variant allele fraction VAF=9.87%, 3-27.8%), we observed a higher somatic VAF in AML over MDS cases (12.4% vs 7.7% respectively p<0.05). A lower bone marrow cellularity was also characteristic of GPV+Som vs GPV alone (mean observed/expected cellularity for age 0.9 vs 1.32 respectively p<0.05). In two cases, serial bone marrow morphology and NGS data were available, and we observed marked reduction in bone marrow cellularity upon acquisition of the R525H clone. The mechanisms of AML evolution appear different in DDX41 HMMS compared to sporadic cases. Interestingly, over half of our patients (21/34 GPV and 23/39 GPV+Som) did not exhibit additional somatic drivers. Our work suggests that acquisition of a somatic variant is a critical event in disease progression. Furthermore, the near universally subclonal nature of somatic variants suggest that they may affect disease phenotype through non-cell autonomous mechanisms. Citation Format: Ludovica Marando, Talha Badar, Yael Kusne, Audrey Morris, Terra Lasho, Abhishek Mangaonkar, Christy Finke, Carles Crawley, James M. Foran, Aref Al-Kali, Andrew King, Hassan Alkhateeb, Naseema Gangat, Chi Wong, Rong He, David Viswanatha, Faisal Basheer, Mark Litzow, Alejandro Ferrer, George Vassiliou, Mrinal Patnaik. Investigating the role of the somatic DDX41 variant in the context of DDX41 hereditary myeloid malignancy syndromes (HMMS) [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr A037.

Abstract Objectives VEXAS syndrome is an adult-onset autoinflammatory disease caused by a somatic pathogenic mutation in the UBA1 (ubiquitin-like modifier activating enzyme 1) gene. Patients present with rheumatologic manifestations and cytopenias and may have an increased predisposition to myelodysplastic syndrome (MDS) and plasma cell neoplasms. Prior studies have reported on the peripheral blood and bone marrow findings in patients with VEXAS syndrome. Due to the protean clinical presentation and lack of specificity of morphologic features (eg, vacuoles in early erythroid and granulocytic precursors), an optimal screening methodology to identify these patients in a timely fashion is desirable. Methods To further evaluate and describe the salient diagnostic morphologic features in VEXAS syndrome, we carried out a comprehensive study of the largest single-institution cohort to date. Diagnostic and follow-up bone marrow biopsy specimens from 52 male patients with molecularly identified VEXAS syndrome underwent central review. Results Cytopenias were common in all cases, primarily macrocytic anemia, monocytopenia, and thrombocytopenia. Bone marrow aspirate and biopsy were often hypercellular, with an increased myeloid/erythroid ratio, granulocytic hyperplasia with left shift, erythroid left shift, and megakaryocyte hyperplasia, which exhibited a range of striking morphologic findings. Distinctly vacuolated myeloid and erythroid precursors were seen in more than 95% of cases. Conclusions Our data reveal potential novel diagnostic features, such as a high incidence of monocytopenia and distinct patterns of atypical megakaryopoiesis, that appear different from dysmegakaryopoiesis typically associated with MDS. In our experience, those findings are suggestive of VEXAS, in the appropriate clinical context.