Menghrajani, Kamal

Abstract Background Myeloproliferative neoplasms (MPNs) can progress from chronic phase to accelerated or blast phase (MPN-AP/BP), a transition with poor prognosis and limited treatment options. While some abnormalities have been described, the genomic and clonal drivers of transformation remain poorly defined. We characterized mutational and structural alterations in MPN-AP/BP, leveraging paired samples to trace clonal evolution. Methods We profiled 186 samples from 160 individuals, including 159 MPN-AP/BP and 27 chronic-phase MPN samples (26 MF, 1 PV), using targeted sequencing of a 588 gene panel (mean depth: 709x). Paired pre- and post-transformation samples were available for 26 patients (n= 52). A consensus pipeline was used to detect somatic mutations, copy number variations (CNVs), and copy-neutral loss of heterozygosity (cnLOH). Clinical cytogenetic data were integrated when available. Single-cell validation is ongoing. Results Genomic complexity was widespread: 99% of patients harbored ≥1 oncogenic mutation (median 4; range 1–10). In total, 859 mutations were identified, most commonly in JAK2 (68%), ASXL1 (28%), TET2 (26%), SRSF2 (24%), TP53 (22%), and RUNX1 (22%). 684 structural alterations were identified in 86% of patients (median 3; range 1-20), including arm-level (22.5%), segmental (>5 Mb; 60%), and focal (<2 Mb; 9%) alterations. Recurrent events included 9p cnLOH (16%), del(5q) (13%), del(17p) (10%), and focal deletion of 21q22.12 involving RUNX1 (10%). Complex karyotypes (≥3 abnormalities) were observed in 55% of patients. Biallelic mutations accounted for 21% (183/859) of mutations, affecting 58% of patients across 21 genes, most frequently JAK2 V617F (28%), TP53 (17%) and TET2 (14%). Patients with biallelic mutations in these genes had significantly higher blast percentages compared to those with monoallelic mutations (p<0.05), highlighting an association with aggressive disease. In 26 patients with longitudinal samples (chronic phase MPN and MPN-AP/BP), 87% (125/144) of mutations were already detectable during the chronic phase, on average more than 7 years prior to transformation. Only 11% (16/144) of mutations were newly acquired, including additional RUNX1 and TP53 hits, or structural changes that converted pre-existing JAK2 V617F and TP53 R248Q mutations from monoallelic to biallelic via 9p cnLOH or 17p loss, respectively. These findings suggest transformation is often driven by outgrowth of pre-existing high-risk clones, indicating that these clones likely have a competitive advantage and that the mutations within these clones have a cooperative biological interaction which underlies this competitive advantage. To investigate this hypothesis, we examined whether patterns of recurrent co-mutations were identifiable in this cohort. We identified recurrent co-occurring mutations in SRSF2-IDH2, ASXL1-SRSF2, and ASXL1-EZH2, which were enriched at transformation (p < 0.05; Fisher exact test). Importantly, presence of these co-mutations was consistently associated with a higher transformation risk in two independent cohorts of MF patients from Mayo Clinic (n= 405) and University of Florence (n= 518). Clonal architecture analysis revealed that these co-mutations frequently arose within the same malignant clone: 100% for SRSF2-IDH2, 80% for ASXL1-SRSF2, and 85% for ASXL1-EZH2, and are often within the dominant clone. Prior studies have demonstrated mechanistic interplay between SRSF2 and IDH2 (Yoshimi et al.), as well as ASXL1 and SRSF2 (Sui et al.) mutations in myeloid malignancies. We assessed functional synergy of ASXL1-EZH2 using a murine model and identified that dual deletion caused a rapidly fatal myeloid neoplasm with shorter survival than single-gene loss. These results reinforce that functional synergy emerges within a shared cellular context, supporting clonal co-dependence as a driver of progression. Single-cell RNA sequencing of ASXL1-EZH2 mutant cases is ongoing and will be presented. Conclusions Transformation to MPN-AP/BP is driven by gradual clonal remodeling and expansion of pre-existing high-risk abnormalities. Biallelic and multi-hit alterations in TP53, JAK2, TET2, and RUNX1 promote clonal dominance and blast progression. Recurrent co-mutations such as IDH2-SRSF2 and ASXL1-EZH2 arise within the same clone, exhibit functional synergy, and are linked to poor outcomes. These findings support the clinical utility of early clonal and co-mutational profiling to guide risk-adapted intervention.

Abstract Philadelphia chromosome-negative myeloproliferative neoplasms (MPNs) have a propensity to transform to an accelerated or blast phase (MPN-AP/BP). The resulting disease has clinically similar manifestations to Acute Myeloid Leukemia (AML) but worse clinical outcomes. Here we present the first comprehensive description of the transcriptomic characteristics of MPN-AP/BP. Our analysis incorporates data from 261 patients of the BeatAML cohort and 56 MPN-AP/BP patients, 11 of whom had paired samples from before and after transformation. We establish that transformed MPN is a transcriptionally distinct entity from de novo AML and chronic phase MPNs. Genomic pathways traditionally associated with MPN pathogenesis, such as IL2/STAT5 signaling and IL6/JAK/STAT3 signaling were enriched in chronic-phase MPNs but are absent in transformed disease, suggesting JAK2 directed therapy may be less effective in this disease phase. We also discovered that gene expression signatures associated with doxorubicin resistance are highly enriched in transformed MPNs, which may explain the lack of efficacy of standard AML therapies. In addition, we identify that lineage composition at the time of transformation may define distinct subsets of MPN-AP/BP patients, which may assist in the future development of novel treatment strategies.

Abstract Little is known about whether risk classification at diagnosis predicts post-hematopoietic cell transplantation (HCT) outcomes in patients with acute myeloid leukemia (AML). We evaluated 8709 patients with AML from the CIBMTR database, and after selection and manual curation of the cytogenetics data, 3779 patients in first complete remission were included in the final analysis: 2384 with intermediate-risk, 969 with adverse-risk, and 426 with KMT2A-rearranged disease. An adjusted multivariable analysis detected an increased risk of relapse for patients with KMT2A-rearranged or adverse-risk AML as compared to those with intermediate-risk disease (hazards ratio [HR], 1.27; P = .01; HR, 1.71; P < .001, respectively). Leukemia-free survival was similar for patients with KMT2A rearrangement or adverse risk (HR, 1.26; P = .002, and HR, 1.47; P < .001), as was overall survival (HR, 1.32; P < .001, and HR, 1.45; P < .001). No differences in outcome were detected when patients were stratified by KMT2A fusion partner. This study is the largest conducted to date on post-HCT outcomes in AML, with manually curated cytogenetics used for risk stratification. Our work demonstrates that risk classification at diagnosis remains predictive of post-HCT outcomes in AML. It also highlights the critical need to develop novel treatment strategies for patients with KMT2A-rearranged and adverse-risk disease.

Abstract Background: JAK2 inhibition improves splenomegaly and symptoms in patients with myelofibrosis (MF), and the JAK2 inhibitor ruxolitinib has been shown to improve both bone marrow fibrosis and survival in MF patients (Cervantes et al., 2013; Verstovsek et al., 2013). Current prognostic models such as DIPSS plus (Gangat et al., 2011) predict survival in MF based on clinical, laboratory, and cytogenetic information, but predate the era of JAK2 inhibitor use in MF. As such, their value in predicting clinical response or survival during treatment with JAK2 inhibitors remains unknown. We hypothesized that features not considered by DIPSS plus, including bone marrow fibrosis and splenomegaly, have independent effects on therapy response. We therefore conducted a retrospective analysis to create a new model to risk stratify patients with respect to their likelihood of achieving a > 50% reduction in splenic size by palpation with JAK2-inhibitor therapy. Methods: We studied a cohort of 418 patients with bone marrow biopsy-proven MF who were treated with ruxolitinib or one of four other JAK2 inhibitors. An initial cohort of 203 patients seen at University of Michigan, Stanford University, and Mayo Clinic in Scottsdale, AZ was used identify factors that would predict a clinical response to therapy. Response to therapy was evaluated at an early time point (3-4 mos) in 167 patients and at a late time point (5-12 mos) in 138 patients, with 127 patients overlapping between the two. We constructed a multivariable logistic regression model, with Bayesian variable selection, for predicting the probability of early or late splenic response to JAK2 inhibitor therapy. The model was developed with this initial group of 203 patients. The model was then validated with a cohort of 215 patients from the PERSIST1 trial (data supplied by CTI Biopharma). Results: Conclusion: We identified several factors that play a role in predicting whether or not patients with MF are likely to respond to JAK2 inhibitor therapy. The interaction between spleen size and WBC at the time of therapy initiation plays the strongest role in predicting which patients will have an early response to therapy. Additionally, our model suggests that patients who do not have a response to JAK2 inhibitor therapy by about 4 months of treatment are unlikely to develop a later response. Our model is able to discriminate between those likely to benefit after several months of therapy and those for whom a change in therapy should be considered early in their treatment course. Figure 1 The following characteristics were selected for inclusion in the prognostic model based on the data collected from our 418-patient cohort. Spleen size and white blood cell count at the time of therapy initiation were the strongest predictors of early response to JAK2 inhibitor therapy. Achievement of an early response was used to further enhance the model for the late time point (third column) and was the strongest predictor of late response. Interaction terms looked at the interdependence of variables on splenic response. Log odds ratios are provided with 95% credible intervals in parentheses. Figure 1. The following characteristics were selected for inclusion in the prognostic model based on the data collected from our 418-patient cohort. Spleen size and white blood cell count at the time of therapy initiation were the strongest predictors of early response to JAK2 inhibitor therapy. Achievement of an early response was used to further enhance the model for the late time point (third column) and was the strongest predictor of late response. Interaction terms looked at the interdependence of variables on splenic response. Log odds ratios are provided with 95% credible intervals in parentheses. Figure 2 An example of the predicted response for a hypothetical patient. The curves show the interaction of a high initial WBC (red) or a low initial WBC (green) with baseline spleen size (depicted along the X-axis) in predicting whether or not the patient will have a late response to therapy (depicted along the Y-axis). The solid lines show the probability that the patient will respond at the later time point if they had an early response. The dashed lines show the probably of a late response if the patient had not achieved a response by the early time point. Overall, a patient with a higher initial WBC and a larger baseline spleen size is less likely to respond to JAK2 inhibitor therapy. Additionally, the curves clearly separate to show that, for a given baseline WBC and spleen size, a patient who has an early response to therapy is much more likely to have a late response to therapy, whereas a patient who fails to respond early in their treatment course is much less likely to respond with further treatment. Figure 2. An example of the predicted response for a hypothetical patient. The curves show the interaction of a high initial WBC (red) or a low initial WBC (green) with baseline spleen size (depicted along the X-axis) in predicting whether or not the patient will have a late response to therapy (depicted along the Y-axis). The solid lines show the probability that the patient will respond at the later time point if they had an early response. The dashed lines show the probably of a late response if the patient had not achieved a response by the early time point. Overall, a patient with a higher initial WBC and a larger baseline spleen size is less likely to respond to JAK2 inhibitor therapy. Additionally, the curves clearly separate to show that, for a given baseline WBC and spleen size, a patient who has an early response to therapy is much more likely to have a late response to therapy, whereas a patient who fails to respond early in their treatment course is much less likely to respond with further treatment. Disclosures Boonstra: CTI Biopharma: Research Funding. Gowin:Incyte: Membership on an entity's Board of Directors or advisory committees. Mesa:Novartis: Consultancy; Ariad: Consultancy; Promedior: Research Funding; Celgene: Research Funding; Galena: Consultancy; Incyte: Research Funding; CTI Biopharma: Research Funding; Gilead: Research Funding. Talpaz:Ariad: Other: Expense reimbursement, travel accomodation expenses, Research Funding; Novartis: Research Funding; Incyte Corporation: Other: Travel expense reimbursement, Research Funding; Pfizer: Consultancy, Other: travel accomodation expenses, Research Funding.

Abstract Myeloproliferative neoplasms (MPN), including polycythemia vera, essential thrombocythemia, and primary myelofibrosis, have a propensity to evolve into accelerated and blast-phase disease (MPN-AP/BP), carrying a dismal prognosis. Conventional antileukemia therapy has limited efficacy in this setting. Thus, MPN-AP/BP is an urgent unmet clinical need. Modest responses to hypomethylating agents and single-agent ruxolitinib have been reported. More recently, combination of ruxolitinib and decitabine has demonstrated synergistic in vitro activity in human and murine systems. These observations led us to conduct a phase 1 study to explore the safety of combined decitabine and dose-escalated ruxolitinib in patients with MPN-AP/BP. A total of 21 patients were accrued to this multicenter study. Ruxolitinib was administered at doses of 10, 15, 25, or 50 mg twice daily in combination with decitabine (20 mg/m2 per day for 5 days) in 28-day cycles. The maximum tolerated dose was not reached. The most common reasons for study discontinuation were toxicity/adverse events (37%) and disease progression (21%). Fourteen patients died during study treatment period or follow-up. The median overall survival for patients on study was 7.9 months (95% confidence interval, 4.1-not reached). Among evaluable patients, the overall response rate by protocol-defined criteria (complete remission with incomplete count recovery + partial remission) was 9/17 (53%) and by intention-to-treat analysis was 9/21 (42.9%). The combination of decitabine and ruxolitinib was generally well tolerated by patients with MPN-AP/BP and demonstrates potentially promising clinical activity. A phase 2 trial evaluating the efficacy of this combination regimen is ongoing within the Myeloproliferative Disorder Research Consortium.