He, Rong

ABSTRACTPolycythemia vera (PV) is invariably associated with a JAK2 mutation, with over 50% of patients harboring additional non‐JAK2 mutations. In the current study, 319 patients with PV underwent NGS at diagnosis or in chronic phase PV (Group A: N = 270, 85%) or at the time of fibrotic (Group B; N = 37, 12%) or leukemic (Group C; N = 12, 4%) transformation. Mutational frequencies involving TP53/SRSF2/IDH1/U2AF1 were significantly (p < 0.05) different between patients in the mutually exclusive Groups A (2%/4%/2%/0.4%), B (8%/0%/0%/5%), and C (50%/25%/17%/8%). Analyses on phenotype/genotype associations and prognostic impact on overall (OS), leukemia‐free (LFS), and myelofibrosis‐free (MFFS) survival were limited to Group A patients. ASXL1MUT was associated with younger age (p < 0.01), SRSF2MUT with older age and leukocytosis (p < 0.01), and TP53MUT with leukocytosis (p < 0.01). Mutation co‐segregation was apparent between ASXL1 and IDH2 (p < 0.01) or SRSF2 (p < 0.01), SRSF2 and IDH2 (p < 0.01), and TP53 and NRAS (p = 0.01). Multivariable analysis identified SRSF2MUT (p < 0.01; HR, 4.2, 1.9–9.5), IDH2MUT (p = 0.01; HR, 5.3, 1.8–15.3), ASXL1MUT (p = 0.04; HR, 2.0, 1.1–3.7), leukocyte count ≥ 15 × 109/L (p < 0.01; HR 2.0, 1.3–3.1), and advanced age (p < 0.01) as risk factors for OS. Median OS in the presence (N = 235; 87%) or absence (N = 35; 13%) of any adverse mutation (i.e., SRSF2MUT, ASXL1MUT, or IDH2MUT) was 8.8 versus 17.8 years (p = 0.01; HR 1.8, 1.1–2.9). In addition, ASXL1MUT (p = 0.02; HR, 1.6–24.9), SRSF2MUT (p = 0.06; HR, 11.9, 1.1–126.2), and advanced age (p = 0.04) were associated with inferior LFS, and SRSF2MUT (p < 0.01; HR, 24.0, 5.5–103.8) and abnormal karyotype (p < 0.01; HR 3.8, 1.6–8.9) with inferior MFFS. The number of non‐JAK2 mutations was significant in predicting outcome in univariate but not multivariable analysis. The observations from the current study highlight the prognostic significance of non‐JAK2 mutations in PV and the prospect of their inclusion in future prognostic models.

We sought to develop a survival model in chronic myelomonocytic leukemia (CMML) that is primarily based on clinical variables and examine additional impact from mutations and karyotype. 457 molecularly-annotated patients were considered. Multivariable analysis identified circulating Blasts ≥2% (1 point), Leukocytes ≥13 x 109/L (1 point), and severe (2 points) or moderate (1 point) Anemia as preferred risk variables in developing a clinical risk Stratification Tool for overall survival (OS), acronymized to "BLAST": low-risk (0 points; median 63 months); intermediate-risk (1 point; median 28 months; HR 2.2, 95% CI 1.6-3.0), and high-risk (2-4 points; median 13 months; 5.4, 4.1-7.3); the corresponding 3/5 year OS rates were 68%/53%, 43%/18%, and 12%/1%. BLAST model performance (AUC 0.77/0.85 at 3/5-years) was shown to be comparable to that of the molecular CMML-specific prognostic scoring system (CMML-mol; AUC 0.73/0.75) and the international prognostic scoring system-molecular (IPSS-M; AUC 0.73/0.74). Multivariable analysis of mutations and karyotype identified PHF6MUT and TET2MUT as being "favorable" and DNMT3AMUT, U2AF1MUT, BCORMUT, SETBP1MUT, ASXL1MUT, NRASMUT, PTPN11MUT, RUNX1MUT, TP53MUT, and adverse karyotype, "unfavorable". Molecular information was subsequently encoded in a combined clinical-molecular risk model (BLAST-mol; AUC 0.80/0.86 at 3/5-years) that included the aforementioned BLAST clinical risk variables and a 3-tiered molecular risk score. BLAST and BLAST-mol were subsequently validated by two separate external cohorts. Independent risk factors for blast transformation included DNMT3AMUT, ASXL1MUT, PHF6WT, leukocytes ≥13 x 109/L, and ≥2% circulating or ≥10% bone marrow blasts. The current study proposes an easy to implement, globally applicable, and molecularly adaptive risk model for CMML.

Abstract This retrospective analysis aimed to provide evidence-based risk stratification of TP53-mutated (TP53mut) myeloid neoplasms (MNs). Of 580 MNs harboring TP53mut with variant allele frequency (VAF) ≥2%, 219 (37.8%), 194 (33.4%), 92 (15.9%), and 75 (12.9%) were classified as acute myeloid leukemia (AML), myelodysplastic syndrome (MDS) with low blasts (MDS-LB), MDS with excess blasts (MDS-EB)-2, and -EB1 according to the revised fourth edition of the World Health Organization (WHO) classification, respectively. Hierarchical analysis identified the following 4 risk groups with distinct survival: (1) MDS-LB, (2) MDS-EB1/EB2/AML VAF &lt;10%, (3) MDS-EB1/EB2 VAF ≥10%, and (4) AML VAF ≥10%. We next evaluated the impact of allelic status, VAF, and complex karyotype (CK). In our cohort, the significance of biallelic status was limited to MDS with &lt;5% blasts and not for blasts 5% to 9%, as proposed by the International Consensus Classification (ICC), or 5% to 19%, as proposed by the fifth edition of the WHO (WHO-5). MDS-EB1 and -EB2 with VAF ≥10% had comparable survival (9.6 vs 7.2 months; P = .12), regardless of allelic status. Contrary to the ICC proposal, MDS-EB1/EB2 with VAF &lt;10% and CK had poor survival compared with those without CK, comparable to MDS-EB1/EB2 with VAF ≥10% (5.6 vs 26.2 vs 6.3 months; P = .003). Survival of TP53mut AML was poor (median 3.9 months) regardless of allelic/CK status. Thus, using ICC or WHO-5 may underestimate prognosis of MDS with blasts 5% to 19% and 5% to 9%, respectively. Collectively, the hierarchical model acknowledges poor survival of 91.9% TP53mut MDS and AML compared with 36.5% and 80.7% by WHO-5 and ICC, respectively.

ABSTRACTA total of 142 patients with myeloproliferative neoplasms (MPNs) or acute myeloid leukemia (AML) associated with multihit TP53 mutations (mTP53 MUT) were accessed from the Mayo Clinic database and included (i) chronic phase MPN (MPN‐CP; N = 19), (ii) accelerated phase MPN (MPN‐AP; N = 14), (iii) blast phase MPN (MPN‐BP; N = 28), and (iv) AML (N = 81). Concurrent ASXL1 MUT, EZH2 MUT, IDH1,MUT and IDH2 MUT were more common in MPN‐MUTBP‐mTP53 compared to AML‐mTP53 MUT. At median of 11.6 months follow‐up, 124 (87%) deaths and 19 (13%) allogeneic stem cell transplantations (ASCT) were documented. Overall survival (OS), calculated from the time of mTP53 MUT detection, was similar between MPN‐BP‐mTP53 MUT (median 4.6 months) and MPN‐AP‐mTP53 MUT (5.6 months; p = 0.5) but both were inferior to MPN‐CP‐mTP53 MUT (11.6 months, p < 0.01). OS in MPN‐CP‐mTP53 MUT was similar to that of AML‐mTP53 MUT (median 7.4 months, p = 0.07). In multivariable analysis, OS was favorably affected by ASCT (HR 0.4, p = 0.03) and disease stage (i.e., chronic phase disease) or achieving response to pre‐transplant chemotherapy (HR 0.2, p < 0.01) and unfavorably by the presence of concurrent TET2 MUT or DNMT3A MUT (HR 2.7, p < 0.01). Based on these risk factors, a 3‐tiered risk model was constructed: low (no risk factors; N = 18; median OS 23.8 months); intermediate (one risk factor; N = 44; 11.1 months); and high (two or more risk factors; N = 80; 4 months; p < 0.01). The current study highlights the equally detrimental impact of mTP53 MUT on long‐term survival in MPN and AML and identifies predictors of short‐term survival.

ABSTRACT The clinical relevance of TP53 mutations ( TP53 MUT ) in myeloproliferative neoplasms (MPN) and their prognostic interaction with MPN subtype designation has not been systematically studied. In the current study, 114 patients with MPN harboring TP53 MUT (VAF ≥ 2%) were evaluated for overall survival (OS), calculated from the time of TP53 MUT detection: chronic phase myelofibrosis (MF‐CP; N = 61); blast‐phase (MPN‐BP; N = 31) or accelerated‐phase (MPN‐AP; N = 16) MPN, and polycythemia vera/essential thrombocythemia (PV/ET; N = 6). Sixty‐five (57%) patients harbored International Consensus Classification (ICC)‐defined multihit TP53 MUT and 56 (49%) monosomal/complex karyotype (MK/CK). Majority of MPN‐BP (90%) and MPN‐AP (81%) while 39% of MF‐CP and none of PV/ET patients harbored multihit TP53 MUT . OS in MPN‐BP and MPN‐AP was equally dismal (median 6 vs. 4.5 months, respectively; p = 1.0), regardless of multihit configuration ( p = 0.44), while OS in TP53 MUT MPN‐BP/AP ( N = 47; median 4 months) was inferior to that of a separate cohort ( N = 49) with TP53 wild‐type MPN‐BP/AP (median 11 months; p < 0.01). OS in MF‐CP was significantly shorter with multihit versus non‐multihit TP53 MUT (median 10 vs. 35 months; HR 2.9; p < 0.01), independent of other MF‐relevant genetic risk factors, including ASXL1/SRSF2/U2AF1 mutations. Multihit TP53 MUT was also associated with inferior survival following allogeneic stem cell transplant (ASCT): median 9 months versus “not reached” in patients with ( N = 9) versus without ( N = 8) multihit TP53 MUT ( p < 0.01). The presence of multihit or non‐multihit TP53 MUT in MPN‐BP/AP or multihit TP53 MUT in MF‐CP is associated with exceptionally poor prognosis and justifies inclusion into the ICC category of “myeloid neoplasms with mutated TP53 .” By contrast, detection of non‐multihit TP53 MUT , by itself, might not endanger short‐term survival in MF‐CP, PV, or ET.

Multiple myeloma (MM), an incurable hematologic malignancy, presents significant challenges in managing its recurrence. The bone marrow tumor microenvironment (BM-TME) is critical to MM progression. However, classical immune checkpoint blockade (ICB) therapies, like anti-PD1, have shown limited efficacy in MM. Therefore, elucidating the compositional features and regulatory mechanisms of the TIME in MM is crucial for developing novel immunotherapeutic targets. Tissue-resident memory CD8+ T cells (CD8+ TRMs) reside indefinitely at multiple anatomical locations like the skin, intestine, and bone marrow, functioning as frontline responders against reencountered pathogens and tumors. Whether CD8+ TRMs within BM-TME are involved in the MM cell immune escape and pathogenesis has not been systematically elucidated. Firstly, we leverage single-cell RNA sequencing (scRNA-seq) to dissect the BM CD8+ T cells across patients at different stages of MM, and identify that CD69+CD8+ T subsets were BM residents, and the proportion of BM CD8+ TRMs between health donors and MM patients was comparable. Moreover, our findings indicated that BM CD8+ TRMs exhibit exhausted features and enrichment of NK genes with MM progresses. Importantly, we observed a considerable elevation of the NK gene KLRB1 and its encoded protein CD161 in BM CD8+ TRMs in MM patients. Immunofluorescence labeling of BM biopsy samples from MM patients confirmed the infiltration of the BM-TME with CD3+CD8+CD69+CD161+ cells. Then, we found that KLRB1 expression in BM CD8+ TRMs was higher than that of other classical inhibitory receptor genes (e.g., PDCD1, CTLA4, LAG3), and CLEC2D (encodes the ligand of CD161) was also markedly expressed in patients' MM cells, exhibiting considerably higher than classical immunosuppressive receptor ligand genes (e.g., PDL1, CD80, CD86). Moreover, patients with higher CLEC2D expression had unfavorable overall survival. We further found that the CD161 expression was higher in CD69+CD8+ TRMs compared to circulating CD69-CD8+ T cells, and the percentage of BM CD161+CD8+ TRMs in MM patients was significantly higher than in healthy donors, while there was no difference for PD-1, LAG3, and TIM3 expression. Notably, only a small fraction of BM CD8+ TRMs have mucosal-associated invariant T cell phenotypes (identified by CD161+TCR-Vα7.2+). Additionally, the CLEC2D expression of BM cells was analyzed, and the highest level of CLEC2D expression was observed in B cells from MM patients, followed by plasma cells. Importantly, CLEC2D expression in MM patients was significantly higher than in plasma cells from healthy donors. Next, to investigate whether the blockade of CD161 could restore the function of CD8+ TRMs, the primary BM cells from MM patients were isolated and stimulated ex vivo. Compared to the anti-PD-1 and isotype group, CD161 blocking presents enhanced CD8+ TRMs proliferation and cytokine secretion levels (TNF-α, IFN-γ, IL2), increasing MM cells apoptosis. Chimeric antigen receptor T (CAR-T) cell therapy has achieved impressive success in treating relapsed/refractory MM. How to prevent CAR-T cell exhaustion and enhance function remains a significant challenge. Therefore, we next set out to investigate the impact of CD161 on CAR-T cells. Our results demonstrated that CD161 was highly expressed in early peripheral blood (PB) CAR-T cells after infusion in MM patients but decreased with time. Moreover, the CD161 expression of CAR-T cells was considerably higher than endogenous T cells. Notably, BM-derived CAR-T cells have higher CD161 expression than PB counterparts for the same patient, suggesting CD161 may have BM-specific expression enrichment. After co-culturing MM and CAR-T cells in vitro for 24 hours, we found that blocking CD161 led to an augmented proportion of CAR-T cells, increased IFN-γ secretion, and a notable elevation in tumor cell apoptosis compared to the anti-PD-1 and isotype groups. Taken together, we demonstrated that CD8+ TRMs constitute a vital anti-tumor cell subset in the MM BM-TME, which exhibits a high expression of the inhibitory CD161 receptor, binding to the CLEC2D expressed by MM cells, thereby mediating the dysfunction of CD8+ TRMs. Blocking the CD161-CLEC2D pathway is expected to become a novel target for MM immunotherapy. The combination of CD161 inhibitors and CAR-T cell therapy can potentially enhance the anti-myeloma function of CAR-T cells.

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&lt;0.01, &lt;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&lt;0.01). The corresponding median leukocyte counts were 12.1, 11.4, 14.4, 16.7, and 11.5 x 10(9)/L (p&lt;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&lt;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&lt;0.01) and karyotype (p&lt;0.01) with inferior MFS (p&lt;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&lt;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.

Background: SETBP1 gene, located on 18q12.3, is a major oncogene in myeloid neoplasms. GATA2 gene, located on 3q21, is one of the six GATA transcription factors regulating gene expression via two conserved zinc finger domains (ZF). Previous data suggested that in patients with germline GATA2 mutation (m), acquisition of a somatic SETBP1 mutation (m) was associated with leukemic transformation among patients with excess blast MDS and CMML. Aim: To study the characteristics of patients with somatic SETBP1-GATA2 mutated myeloid neoplasms. Methods: This study is a retrospective study at Mayo Clinic. After obtaining IRB approval, we retrospectively reviewed the charts of patients who had myeloid NGS panel results between 2016-2023. All data were recorded at time of first NGS. Cohort 1 was defined as patients with SETBP1m and GATA2m, cohort 2; patients with SETBP1m and GATA2wt, and cohort 3; patients with SETBP1wt and GATA2m. Germline work-up was not performed in the majority of GATA2 cases. We stratified risk based on the European LeukemiaNet 2022 guidelines for AML, IPSS-M for MDS and MDS/MPN, and CPSS-M for CMML. Overall survival (OS) was calculated from date of NGS to date of last follow-up based on Kaplan-Meier estimates and Cox regression analysis. For statistical analysis, we used BlueSky Statistics V10.3.1. Results: General characteristics: 114 patients had SETBP1m (median VAF= 39%), and 63 patients had GATA2m (median VAF= 35%). Nine patients had co-occurring SETBP1m/GATA2m mutations (cohort 1). 4/9 patients in cohort 1 had MDS/MPN (44.4%), while only 13/105 in cohort 2 (12.4%) had MDS/MPN (P=0.02). AML was seen in 2 patients in cohort 1 (22.2%) compared to18 in cohort 2 (17.1%) (p=0.6). The median WBC count was 22.9 x 109 cells/L among cohort 1 compared to 9 x 109 cells/L among cohort 2 cases (p=0.09). BM blasts were higher in cohort 3 (7%) compared to cohort 1 (5%) and cohort 2 (3%) (p=0.09), while peripheral blasts tended to be lower in cohort 2 (1%) in comparison to cohort 1 (6%) and cohort 3 (4%) (p=0.48). Genetic characteristics: In cohort 1,7 GATA2m clustered in zinc finger 2 (ZF2) (77.8%), while the other two mutations were outside the ZF domains (22.2%). This was higher than the ZF2 mutated cases in cohort 3 (46.3%, p=0.1). Abnormal cytogenetics were seen in 66.7% of cohort 1 patients and 45% of cohort 2 (p= 0.3). Two cases with trisomy 8 were seen among patients in cohort 1 (22.2%), compared to only 4.9% in cohort 2 (p=0.09). Two incidences of isochromosome 17q [i(17q)] were seen in cohort 1 (22.2%), versus 5 cases in cohort 2 (4.8%) and 1 case in cohort 3 (1.9%) (p= 0.068). Co-mutations: The median number of co-mutationswas 3 in both cohort 1 and cohort 2 (p= 0.6). In cohort 1, ASXL1 and SRSF2 mutations were the most common (7/9, 77.8%) followed by NRAS (22.2%) and TET2 (22.2%). 77.8% of cohort 1 patients had SRSF2 co-mutation, compared to 44.8% in cohort 2 (p=0.08), and 27.8% in cohort 3 (p= 0.006). No isolated SETBP1m/GATA2m cases were found. Survival: Patients in cohort 1 had a numerically higher median OS compared to those in cohort 2 (19.4 vs 15.4 months, p= 0.3). When comparing with the cohort 3, patients in cohort 1 tended to have better outcomes (median OS= 19.4 vs 13.8 months, p=0.8). Among cohort 1, SRSF2 co-mutation was associated with worse survival outcomes compared to patients with SRSF2wt (median OS= 5.3 vs 19.4 months, p= 0.02); this association was not found in cohort 2 (12.5 vs 18.4 months, p= 0.3) and cohort 3 (13.2 vs 17.1 months, p= 0.4). Allogeneic hematopoietic cell transplantation was associated with favorable survival outcomes in all cohorts (cohort 1: 22.6 vs 7.8 months, p= 0.1; cohort 2: 20.9 vs 12.5 months, p= 0.04; cohort 3: 25.6 vs 13.1 months, p= 0.03). Conclusion: SETBP1m/GATA2m myeloid neoplasms included a significantly higher proportion of MDS/MPN overlap cases in comparison with the SETBP1m/GATA2wt group. The SETBP1m/GATA2m group had a higher proportion of ZF2 GATA2m and SRSF2 co-mutation compared to patients with SETBP1wt/GATA2m. Survival of SETBP1m/GATA2m patients was not worse compared to SETBP1wt/GATA2m or SETBP1m/GATA2wt.

Background A JAK2 mutation is detected in almost all patients with polycythemia vera (PV) and in ⁓50% of those with essential thrombocythemia (ET). The two diseases also share characteristic clinical and bone marrow morphological traits, suggesting they exist on a disease continuum rather than representing discrete entities. The objective of the current study was to compare clinical and genetic characteristics as well as long-term outcome between formally-defined PV vs. JAK2-mutated ET vs. JAK2-wild-type (WT) ET. Methods Study patients were retrospectively recruited from Mayo Clinic, USA databases (1967-2024). Diagnostic criteria were according to the International Consensus Classification (ICC; Blood 2022;140:1200). All study patients were fully annotated for JAK2, CALR, and MPL mutations while cytogenetic and additional next-generation sequencing (NGS)-derived mutation information was available in a subset of patients. Conventional statistical methods were employed for phenotypic comparisons and survival analysis. Results Among 2,010 study patients, 1,010 had PV, 617 (63%) JAK2-mutated ET, and 383 JAK2-WT ET (CALR 26%; MPL 3%; triple-negative 9%). Phenotypic comparisons revealed older age distribution in PV compared to JAK2-mutated ET (p=0.03) and the latter compared to JAK2-WT ET (p&lt;0.01). Females were represented more in JAK2-mutated ET (69%), compared to both PV (49%; p&lt;0.01) and JAK2-WT ET (54%; p&lt;0.01). The frequencies of leukocytosis, palpable splenomegaly, constitutional symptoms, diabetes, hypertension, and abnormal karyotype were all significantly higher in PV, compared to both groups of ET, while JAK2-mutated compared to JAK2-WT ET displayed higher leukocyte count and incidence of hypertension. The incidences of arterial thrombosis at/prior to diagnosis were 14%, 16%, and 10% in PV, JAK2-mutated and WT ET, respectively (P=0.03), and venous thrombosis 14%, 13%, and 6% (p&lt;0.01). After a median follow-up of 8.6 years, 632 (32%) deaths, 329 (16%) fibrotic progressions, 79 (4%) leukemic transformations, and 236 (12%) arterial and 202 (10%) venous thrombotic events were recorded, among all 2,010 study patients. Median overall survival was 19.3 years for PV vs. 17.8 years for JAK2-mutated ET vs. 23 years for JAK2-WT ET (p&lt;0.01); however, the significant difference in favor of JAK2-WT ET was no longer apparent when analysis was adjusted for age and sex (p=0.15) and subsequently for other risk factors (p=0.86). All-inclusive multivariable analysis identified older age (p&lt;0.01), male sex (p&lt;0.01), higher leukocyte count (p&lt;0.01), and arterial thrombosis history (p&lt;0.01), but not the distinction between PV, JAK2-mutated, and JAK2-WT ET (p=0.9), to be independently associated with shortened survival. Leukemia-free survival was similar between PV and either JAK2-mutated (p=0.5) or JAK2-WT (p=0.1) ET. On the other hand, myelofibrosis-free survival was shorter in PV, compared to both JAK2-mutated (HR 1.8, 1.4-2.4; p&lt;0.01) and JAK2-WT (HR 1.4. 1.0-1.8; p=0.03) ET. In multivariable analysis, older age (p&lt;0.01), higher leukocyte count (p&lt;0.01), PV vs. JAK2-mutated ET (HR 1.8; p&lt;0.01), and JAK2-WT vs. JAK2-mutated ET (HR 1.6; p=0.01) were associated with a higher risk of fibrotic progression, with no difference noted between PV and JAK2-WT ET (p=0.4). Arterial thrombosis-free survival was similar between PV and JAK2-mutated ET (p=0.8). In univariate analysis, JAK2-WT ET vs. PV was associated with superior arterial thrombosis-free survival (p=0.02), but significance was lost when analysis was adjusted for arterial thrombosis history (p=0.1). Venous thrombosis-free survival favored JAK2-WT ET vs. PV (HR 0.3; p&lt;0.01) and JAK2-mutated ET (HR 0.6; p=0.02) and the latter vs. PV (HR 0.6; p&lt;0.01); the significant differences between PV and both groups of ET were sustained when analysis was adjusted for age, sex, and venous thrombosis history. Conclusions The current study highlights significant demographic and phenotypic differences between PV and JAK2-mutated ET. However, risk factor-adjusted overall, leukemia-free, and arterial thrombosis-free survival was not inferior in PV, compared to ET, regardless of the presence or absence of a JAK2 mutation in the latter. JAK2-WT ET was distinctly associated with a lower risk of venous thrombosis while JAK2-mutated ET appeared to be less vulnerable to fibrotic progression.