Myeloid Neoplasms In Patients Research Articles

Comprehensive analysis of the HCK gene in myeloid neoplasms: Insights into biological functions, prognosis, and response to antineoplastic agents

Myeloid neoplasms result from molecular alterations in hematopoietic stem cells, with acute myeloid leukemia (AML) being one of the most aggressive and with a poor prognosis. Hematopoietic cell kinase (HCK) is a proto-oncogene that encodes a protein-tyrosine kinase of the Scr family, and it is highly expressed in AML. The present study investigated HCK expression in normal hematopoietic cells across myeloid differentiation stages and myeloid neoplasm patients. Within the AML cohort, we explored the impact of HCK expression on clinical outcomes and its correlation with clinical, genetic, and laboratory characteristics. Furthermore, we evaluated the association between HCK expression and the response to antineoplastic agents using ex vivo assay data from AML patients. HCK expression is higher in differentiated subpopulations of myeloid cells. High HCK expression was observed in patients with chronic myelomonocytic leukemia, chronic myeloid leukemia, and AML. In patients with AML, high levels of HCK negatively impacted overall and disease-free survival. High HCK expression was also associated with worse molecular risk groups and white blood cell count; however, it was not an independent prognostic factor. In functional genomic analyses, high HCK expression was associated with several biological and molecular processes relevant to leukemogenesis. HCK expression was also associated with sensitivity and resistance to several drugs currently used in the clinic. In conclusion, our analysis confirmed the differential expression of HCK in myeloid neoplasms and its potential association with unfavorable molecular risks in AML. We also provide new insights into HCK biological functions, prognosis, and response to antineoplastic agents.

High Prevalence of IDH Mutation in Myeloid Neoplasm with Concomitant Autoimmune Rheumatic Disorders

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

Cumulative Incidence of Myeloid Neoplasms in Patients with Nodal T-Follicular Helper Cell Lymphoma

Introduction: Certain T-cell lymphomas (TCL), in particular nodal T-follicular helper (TFH) cell lymphomas, including angioimmunoblastic TCL (AITL), commonly develop on a background of mutations identified in clonal hematopoiesis (CH). Divergent clonal evolution can result in both nodal TFH cell lymphomas and myeloid neoplasms (MN). As peripheral TCLs are commonly treated with combination and dose intensive chemotherapy, there is a risk that these therapies could promote an evolution to MN. The frequency at which this occurs is unclear. Methods: We conducted a retrospective search for any patient with an International Classification of Disease (ICD) code referring to a TCL. Then, we identified patients with a concomitant ICD code referring to either myelodysplastic syndromes (MDS), acutemyeloid leukemia (AML), or a myeloproliferative neoplasm (MPN). Once the initial query was performed, we individually reviewed each patient and included only patients meeting the following criteria: (1) A histologically-confirmed diagnosis of either peripheral TCL, not otherwise specified (PTCL-NOS) or nodal TFH cell lymphoma by an MSK hematopathologist between 1/1/02 and 7/1/23; (2) Presentation to MSK at lymphoma diagnosis; (3) At least 6 months of follow-up (unless death from lymphoma); (4) if relevant, a histologically-confirmed diagnosis of a MN by an MSK hematopathologist. Histological diagnoses were recorded as documented in the pathology electronic record in accordance with the WHO criteria in place at the time of diagnosis. In particular, at our center, prior to 2016, cases of PTCL-NOS were not routinely assessed for TFH phenotype, as nodal TFH cell lymphoma was only added to the WHO classification in 2016. Cases documented herein as PTCL-NOS were not re-reviewed to determine TFH phenotype. Only patients who received systemic treatment were included (systemic steroids were not considered systemic treatment). CI of MN was evaluated using the reverse Kaplan-Meier method treating death as a competing risk. Results: We identified a total of 376 patients with either PTCL-NOS (N=178) or nodal TFH cell lymphoma (N=198; AITL N=184; nodal TFH cell lymphoma, NOS N=13; nodal TFH cell lymphoma, follicular-type=1). In total, 24 patients with a MN and either PTCL-NOS or nodal TFH cell lymphoma were identified. Nine had a MN that preceded the TCL diagnosis (AML: 2; MDS: 1; myelofibrosis: 2; CMML: 2; MDS/MPN: 1; polycythemia vera: 1)-these patients were excluded for CI calculation. Fifteen patients were diagnosed with a MN subsequent to lymphoma diagnosis and treatment (AML: 5; MDS: 8; CMML: 1; chronic neutrophilic leukemia: 1). Of the 198 patients with nodal TFH cell lymphoma, nine developed a MN. The CI of developing a MN among all patients at 2, 5, 10, and 15 years was 1.1%, 4.4%, 4.8%, and 5.8%. The CI of developing a MN among those with known nodal TFH cell lymphoma at the same timepoints were 1.6%, 4.5%, 5.3% and 7.1%. The median follow up among survivors was 4.1 years (range: 0.5-18). The median age at MN diagnosis was 72.6 years (range: 45-81), and the median time from lymphoma diagnosis to MN diagnosis was 2.6 years (range: 0.3-10.4). Four patients had either prior RT or chemotherapy for non-lymphoma conditions. Prior to MN diagnosis, ten patients (67%) received etoposide and seven patients (47%) received autologous stem cell transplant (ASCT) (six with BEAM, one with cyclophosphamide plus total body irradiation). The median number of therapies (including ASCT) prior to MN diagnosis was 2 (range: 1-5). At the time of MN diagnosis, 10 patients had relapsed TCL and were receiving lymphoma therapy. No patients had undergone alloSCT prior to the diagnosis of a MN. Next generation mutational profiling with MSK-IMPACT-Heme had previously been performed for eight of the 15 patients (on lymphoma tissue). All except one had mutations in TET2 and/or DNMT3A. Conclusions: Herein we report the CI of MN in a cohort of patients with TCL, with particular attention to nodal TFH cell lymphomas given known CH mutations and the genotoxic stress of combination chemotherapy. As more patients have prolonged survival after initial therapy for TCL, further analysis, including baseline genetics and prospective characterization for clonal expansion and acquired mutations during therapy, could identify those at highest risk for developing a MN. Further characterization of our cohort and comparison to patients who did not develop a MN is ongoing.

Distinct SF3B1 Allele HEAT Repeat Location Is Associated with Co-Occurring Mutation Patterns in MDS

Background: In 2022, the WHO classified a new subtype of myelodysplastic neoplasms (MDS) with low blast count and SF3B1 mutation called MDS- SF3B1. SF3B1 is the major subunit of the SF3B spliceosome complex and is responsible for recognizing 3' splice sites in pre-mRNA for processing into mature mRNA. Mutations in SF3B1 have also been observed in other myeloid neoplasms. While MDS- SF3B1 has been associated with a better survival outcome, allelic variants such as SF3B1 K666N are associated with higher-risk MDS, transformation to AML and decreased OS. Additionally, SF3B1 E592K is more likely to be co-mutated with RUNX1, with a worse prognosis. Thus, not all SF3B1 allelic variants should be treated the same. The IPSS-M model incorporates SF3B1 mutations with different weights depending on co-mutations (i.e. isolated del(5q) or BCOR, BCORL1, RUNX1, NRAS, STAG2, SRSF2 mutations) but did not find a difference based on SF3B1 hotspot mutation. However, these and other studies have focused on specific amino acid substitutions but have not taken into consideration the protein domain structure of SF3B1. Using a large cohort of SF3B1-mutant myeloid malignancies, we determined whether HEAT repeat domain location was associated with differences between SF3B1-mutant myeloid neoplasms when comparing co-mutations and clinical characteristics. Methods: Bone marrow, peripheral blood, or FFPE tissue samples from a cohort of 2,996 unique patients with a suspected myeloid neoplasm from 6/30/2020-5/30/2023 were sequenced using a DNA 297 gene myeloid panel. We also analyzed a separate cohort of 112 patients from Sylvester Comprehensive Cancer Center (SCCC) and the University of Texas Southwestern Medical Center (UTSW) from 06/01/2017-06/30/2023 to validate the findings and assess for associations with clinical parameters such as blast count, time to disease progression, and survival. Statistics were performed using Chi-Square. SF3B1 has 22 HEAT repeats with SF3B1 mutations occurring predominately in HEAT Domains 2-6. For this study, we used UniProt definitions of amino acids 569-603 (HEAT2), 604-641 (HEAT3), 643-677 (HEAT4), 680-718 (HEAT5), and 763-801 (HEAT6) as shown in Figure 1. Results: Out of 2,996 myeloid neoplasm patients with SF3B1 mutations, the SF3B1 allele with the highest prevalence was K700E, which falls into HEAT repeat number 5, followed by K666N/R/T and H662Q in HEAT repeat number 4, and R635C in HEAT repeat number 3. Mutations in HEAT repeat 2 and 6 were less common. Several genes were significantly co-mutated in different SF3B1 heat domains, including ASXL1 (11%, p-value =<0.00001), CUX1 (4.7%, p-value = <0.00001), DNMT3A (22.5%, p-value = <0.00001), EZH2 (4.3%, p-value = 0.07), JAK2 (11.2%, p-value= <0.00001), RUNX1 (7.8%, p-value = <0.00001), STAG2 (3.2%, p-value = <0.00001), and TET2 (28.2%, p-value = 0.003) shown in Table 1. The most common co-mutations within each HEAT domain were: HEAT2- ASXL1 (80.0%), RUNX1 (55%), and STAG2 (25%); HEAT3- TET2 (29.5%), DNMT3A (17.5%), and ASXL1 (12.6%); HEAT4- TET2 (24%), D NMT3A (15.2%), and JAK2 (16.9%); HEAT5- TET2 (31.4%) and DNMT3A (31%);and HEAT6- TET2 (28.9%), ASXL1 (15.8%), DMNT3A (14.5%), and EZH2(10.5%). In a separate cohort of 112 patients with clinical follow-up, 97 were diagnosed with MDS- SF3B1: 53 (55%) were male and the average age at diagnosis of 70 years (range: 27-89 years old). A total of 88 patients had 297 gene myeloid panel information, which revealed a similar HEAT repeat distribution: HEAT3 (19%), HEAT4 (27%), HEAT5 (45%), and HEAT6 (6%). The median OS of the entire cohort was 10.5 years (CI 95% 4.93-NE). With a median follow-up of 2 years; 75, 81, 63 and 80% of patients were alive in HEAT 3, 4, 5 and 6, respectively. Conclusion: Distinct SF3B1 alleles defined by HEAT repeat location reflect distinct co-mutation patterns and may play a role in the biology of myeloid disorders. The relatively most enriched co-mutation patterns included: ASXL1 and RUNX1 in HEAT2, JAK2 in HEAT4, and EZH2 in HEAT6. Despite numerical differences in survival larger multicenter patient cohorts are needed to further define how distinct SF3B1 allelic variants and their HEAT repeat location correlate with prognosis and outcome in MDS and other myeloid neoplasms. In addition, further research is need into whether distinct SF3B1 alleles result in differences in RNA splicing signatures that may influence interactions with co-occurring mutations and disease biology.

Association of early antibiotic de-escalation with length of stay in patients with myeloid neoplasms and neutropenic fever.

425 Background: Neutropenic fever is a common complication in patients with myeloid neoplasms. While patients typically receive intravenous (IV) antibiotics until neutrophil recovery, a growing body of literature shows the safety of de-escalation prior to this endpoint. The impact of this early de-escalation on health care utilization remains unclear. Methods: We conducted a retrospective analysis of hospitalized myeloid neoplasm patients at our institution with neutropenic fever, assessing the impact of IV antibiotic de-escalation prior to neutrophil recovery on length of stay (LOS). Manual chart review was performed on this cohort to assess clinical outcomes. Multivariable linear regression was performed, adjusting for age, diagnosis, Charlson Comorbidity Index, intensity of chemotherapy received, positive bacterial culture result, last hospital day with fever, and last hospital day with neutropenia. Results: Patient characteristics are shown in Table 1. Most de-escalation patients (67.7%) were discharged within 72 hours of stopping IV antibiotics. After adjusting for the above variables, early antibiotic de-escalation was associated with lower LOS of 2.7 days (95% confidence interval [CI] 2.0–3.3 days, p < 0.001), an effect that appeared most pronounced in the high very risk chemotherapy group (3.6 day reduction, 95% CI 2.5–4.6 days, p = 0.007). Review of clinical outcomes of de-escalation patients showed 5 potentially preventable recurrent or worsening fever or infectious incidents. Conclusions: Early de-escalation of IV antibiotics was associated with a statistically and clinically significant reduction in LOS, with very few clinical complications. To our knowledge, our study is the first to demonstrate a significant reduction in length of stay, an important hospital quality metric. Further prospective data is needed to confirm this relationship.[Table: see text]

PB0738 Platelet Count and Its Correlation in Mutated Myeloid Neoplasm Patients; a Single Center Experience from Pakistan

PB0738 Platelet Count and Its Correlation in Mutated Myeloid Neoplasm Patients; a Single Center Experience from Pakistan

The immunome of mobilized peripheral blood stem cells is predictive of long-term outcomes and therapy-related myeloid neoplasms in patients with multiple myeloma undergoing autologous stem cell transplant

Upfront autologous stem cell transplant (ASCT) is the standard of care for newly diagnosed multiple myeloma (MM) patients. However, relapse is ubiquitous and therapy-related myeloid neoplasms (t-MN) post-ASCT are commonly associated with poor outcomes. We hypothesized that the enrichment of abnormal myeloid progenitors and immune effector cells (IEC) in the peripheral blood stem cells (PBSCs) is associated with a higher risk of relapse and/or development of t-MN. We performed a comprehensive myeloid and lymphoid immunophenotyping on PBSCs from 54 patients with MM who underwent ASCT. Median progression-free (PFS), myeloid neoplasm-free (MNFS), and overall survival (OS) from ASCT were 49.6 months (95% CI: 39.5-Not Reached), 59.7 months (95% CI: 55–74), and 75.6 months (95% CI: 62–105), respectively. Abnormal expression of CD7 and HLA-DR on the myeloid progenitor cells was associated with an inferior PFS, MNFS, and OS. Similarly, enrichment of terminally differentiated (CD27/CD28-, CD57/KLRG1+) and exhausted (TIGIT/PD-1+) T-cells, and inhibitory NK-T like (CD159a+/CD56+) T-cells was associated with inferior PFS, MNFS, and OS post-transplant. Our observation of abnormal myeloid and IEC phenotype being present even before ASCT and maintenance therapy suggests an early predisposition to t-MN and inferior outcomes for MM, and has the potential to guide sequencing of future treatment modalities.

A CASE OF MYELODYSPLASTIC SYNDROME WITH RARE TRANSLOCATION (2-11) (Q31 P15) SECONDARY TO CHEMOTHERAPY TREATMENT

Chromosomal translocations are common genetic alterations in myeloid neoplasia, and certain translocations have been specifically associated with secondary myeloid neoplasms following treatment with Topoisomerase II inhibitors. The most frequently observed translocations involve chromosomes 11q23 (MLL) and 21q22 (Runx1), and they typically occur early after chemotherapy. Here, we present a rare case of secondary myelodysplastic syndrome that occurred 14 years after chemotherapy, which included both alkylating agents and Topoisomerase II inhibitors. The patient presented with a translocation t (211) (q31 p15), which resulted in a rearrangement of the Nup98 gene with the HOXD13 gene. To our knowledge, this is the first reported case of this specific translocation in the literature. This case underscores the importance of continued vigilance for the development of secondary myeloid neoplasms in patients who have received chemotherapy and suggests the need for further research to better understand the genetic mechanisms underlying these rare translocations.

Identification and interpretation of TET2 noncanonical splicing site intronic variants in myeloid neoplasm patients.

Background: DNA hypermethylation and instability due to inactivation mutations in Ten-eleven translocation 2 (TET2) is a key biomarker of hematological malignancies. This study aims at characterizing two intronic noncanonical splice-site variants, c.3954+5_3954+8delGTTT and c.3954+5G>A. Methods: We used in silico prediction tools, reverse transcription (RT)-PCR, and Sanger sequencing on blood/bone marrow-derived RNA specimens to determine the aberrant splicing. Results: In silico prediction of both variants exhibited reduced splicing strength at the TET2 intron 7 splicing donor site. RT-PCR and Sanger sequencing identified a 62-bp deletion at the exon 7, producing a frameshift mutation, p.Cys1298*. Conclusion: This study provides functional evidence for two intronic TET2 variants that cause alternative splicing and frameshift mutation.

Abstract A50: Distinguishing Mosaic Li Fraumeni Syndrome, Clonal Hematopoiesis and Incidental Myeloid Neoplasms in Patients with Solid Tumors with Pathogenic TP53 Mutations Identified by Germline Testing or Cell-Free Circulating DNA Sequencing

Abstract The incorporation of panel-based germline genetic testing for assessment of pathogenic or likely pathogenic variants associated with increased risk of breast, ovarian, prostatic and pancreatic cancer in NCCN guidelines and wide adoption of cell-free circulating DNA sequencing (liquid biopsy) for patients with advanced solid tumors has increased the identification of pathogenic TP53 variants in blood of patients with solid tumors. The variant allelic frequency (VAF) of the pathogenic variant is often used to help infer the compartment of origin (germline vs somatic) with near heterozygous (~50%) VAF favoring germline; however, when VAF is low (sub heterozygous) potential considerations include mosaic Li Fraumeni syndrome, clonal hematopoiesis, or incidental myeloid neoplasms, and determining the origin of the TP53 mutation can be a challenge with important surveillance and treatment implications. We describe a cohort of patients with solid tumors or hematologic malignancies in whom pathogenic or likely pathogenic TP53 variants of uncertain origin were identified by clinical genetic testing of peripheral blood, next generation sequencing (NGS) using an 81 gene hematologic malignancy-based panel, or cell-free DNA sequencing/liquid biopsy. In a subset of patients for whom solid tumor, adjacent normal tissue and/or bone marrow (BM) was available, immunohistochemistry for p53 protein was performed. Patients (n= 17) included 11 (61%) women and 7 (39%) men with a median age of 54 years (range 8-7) at initial cancer diagnosis, with 17 unique TP53 variants with a median VAF of 16% (range, 2-50%). The most common indication for referral for additional investigation of the TP53 origin was sub-heterozygous VAF on germline testing of blood (8/47%) or saliva (1/6%); TP53 variant identified in plasma when the concurrent solid tumor was TP53 wild-type (3/18%) followed by presence of a pathogenic TP53 variant in remission BM of patients with history of hematologic malignancies (4/24%). Additional germline testing of skin fibroblasts and/or BM examination was performed in in 9 (53%) and 8 (47%) patients, respectively. p53 IHC was performed on 3 BM biopsies and 2 solid tumor tissues. A multimodality/multidisciplinary interpretation of these results allowed appropriate classification of the TP53 variants in 12/18 patients (67%). These included Li Fraumeni syndrome (5/12; 42%); clonal hematopoiesis (5/12; 42%); donor-derived clonal hematopoiesis (1/12;8%) and therapy-related myelodysplastic syndrome (1/12; 8%) patients. Appropriate awareness and distinction of clonal hematopoiesis and potential myeloid neoplasms from mosaic germline TP53 in the setting of subheterozygous VAF identified on peripheral blood or bone marrow analyses can be challenging. Multimodality testing and a multidisciplinary approach for accurate interpretation is required. Immunohistochemical staining for p53 can be useful in making this distinction in a subset of patients. Citation Format: Sanam Loghavi, Yoheved Gerstein, Mark J Routbort, Keyur P Patel, Koichi Takahashi, Molly Daniels, Julie Moskowitz, Danielle E Hammond, Kelly Chien, L. Jeffrey Medeiros, Farhad Ravandi, Hagop M Kantarjian, Guillermo Garcia-Manero, Banu Arun, Joseph D Khoury, Courtney D DiNardo. Distinguishing Mosaic Li Fraumeni Syndrome, Clonal Hematopoiesis and Incidental Myeloid Neoplasms in Patients with Solid Tumors with Pathogenic TP53 Mutations Identified by Germline Testing or Cell-Free Circulating DNA Sequencing [abstract]. In: Proceedings of the AACR Special Conference: Acute Myeloid Leukemia and Myelodysplastic Syndrome; 2023 Jan 23-25; Austin, TX. Philadelphia (PA): AACR; Blood Cancer Discov 2023;4(3_Suppl):Abstract nr A50.

Primary Cancer Matters in Therapy-related Myeloid Neoplasm Patients Receiving Allogeneic Hematopoietic Cell Transplantation: A Study From the Chronic Malignancies Working Party of the EBMT

Primary Cancer Matters in Therapy-related Myeloid Neoplasm Patients Receiving Allogeneic Hematopoietic Cell Transplantation: A Study From the Chronic Malignancies Working Party of the EBMT

Clinicopathologic Features of Therapy-Related Myeloid Neoplasms in Patients with Myeloma in the Era of Novel Therapies

The development of therapy-related myeloid neoplasms (t-MN) is a rare complication that can occur in myeloma patients treated primarily with novel therapies. To better understand t-MNs in this context, we reviewed 66 such patients and compared them with a control group of patients who developed t-MN after cytotoxic therapies for other malignancies. The study group included 50 men and 16 women, with a median age of 68 years (range, 48-86 years). Therapies included proteasome inhibitors, immunomodulatory agents, and high-dose melphalan-based autologous stem cell transplantation (HDM-ASCT) in 64 (97%), 65 (98.5%), and 64 (97%) patients, respectively; 29 (43.9%) patients were exposed to other cytotoxic drugs besides HDM. The latency interval from therapy to t-MN was 4.9 years (range, 0.6-21.9 years). Patients who received HDM-ASCT in addition to other cytotoxic therapies had a longer latency period to t-MN compared with patients who only received HDM-ASCT (6.1 vs 4.7 years, P = .009). Notably, 11 patients developed t-MN within 2 years. Therapy-related myelodysplastic syndrome was the most common type of neoplasm (n = 60), followed by therapy-related acute myeloid leukemia (n = 4) and myelodysplastic syndrome/myeloproliferative neoplasm (n = 2). The most common cytogenetic aberrations included complex karyotypes (48.5%), del7q/-7 (43.9%), and/or del5q/-5 (40.9%). The most frequent molecular alteration was TP53 mutation, in 43 (67.2%) patients and the sole mutation in 20 patients. Other mutations included DNMT3A, 26.6%; TET2, 14.1%; RUNX1, 10.9%; ASXL1, 7.8%; and U2AF1, 7.8%. Other mutations in less than 5% of cases included SRSF2, EZH2, STAG2, NRAS, SETBP, SF3B1, SF3A1, and ASXL2. After a median follow-up of 15.3 months, 18 patients were alive and 48 died. The median overall survival after the diagnosis of t-MN in the study group was 18.4 months. Although the overall features are comparable to the control group, the short interval to t-MN (<2 years) underscores the unique vulnerable status of myeloma patients.

Differential Impact on Survival in Myeloid Neoplasm Patients with U2AF1 Mutations

Introduction:U2AF1 mutations (m) are associated with abnormal splicing of genes involved in functionally important pathways, such as cell cycle progression and RNA processing. The U2AF1 gene has specific hotspots for mutations primarily involving the S34F and Q157P residues within the ZnF1 and ZnF2 causing mis-splicing of genes critical for hematopoiesis. Most recently in European Leukemia Net 2022 guidelines, U2AF1m is categorized as high-risk disease with inferior survival. We analyze outcome of U2AF1m in myeloid neoplasms and co-mutation patterns in large cohort of patients treated at Mayo Clinic. Methods: We reviewed our myeloid neoplasms patients (pts) database who underwent NGS (MC OncoHeme 42 genes panel) testing between October 2015 and August 2021. We identified 121 myeloid neoplasm pts with U2AF1m, and these were analyzed for clinical characteristics, co-mutational patterns, and outcomes using SPSS statistical software. An appropriate IRB approved was obtained. Results: The median age at diagnosis was 71 years (range [R], 19-92) (Table 1). Sixty-one (51%) pts were diagnosed with MDS, 29 (24%) pts with myeloproliferative neoplasms (MPN), 23 (19%) pts with acute myeloid leukemia (AML), 12 (10%) pts with MDS/MPN overlap and 3 (2.5%) pts with clonal cytopenia of unknown significance (CCUS). Out of 61 pts diagnosed with MDS, 59 pts had risk stratification information based on the revised international prognostic scoring system (IPSS-R): 20 (33.9%), 18 (30.5%), 17 (28.8%) and 4 (6.8%) patients were stratified into low, intermediate, high, and very high risk, respectively. Thirty-one out of 102 (30%) pts with MDS/MPN/MDS-MPN overlap progressed to AML with median time to AML progression 14.6 months (R, 1-118). Forty-four percent and 32% of pts had mutations involving the S34F and Q157P hotspots respectively, while the remaining had Q157R (12%), S34Y (6%), R156H (5%) and R35L (1%). The median variable allele frequency (VAF) was 38% (R, 2-49). Isolated U2AF1m was seen in 15 (12.4%) patients, 9 of these patients were diagnosed as MDS. The rest of the patients (87.6%) had at least 1 co-mutation, the most common ones being ASLX1 (46%), JAK2 (19%), TET2 (17.5%), RUNX1 (14%), DNMT3A (14%) and BCOR (14%). We did sub-group analysis for overall survival (OS) in advanced MDS and AML patients harboring most frequent U2AF1 mutations (S34F, Q157P and Q157R). The mOS was 31.3, 20.5 and 8.8 months (mo) in MDS/AML pts with S34F, Q157P and Q157R mutations, respectively (p= 0.005, Figure 1A). While VAF <40% (OS 21.5 mo) vs VAF >40% (OS 24.5 mo) had no differential impact on OS (p= 0.98, Figure 1B). Conclusion: In this study, we have demonstrated that U2AF1 gene with S34F hotspot have better OS, while Q157R had significantly inferior OS in pts with MDS/AML. Contrary to earlier reports we did not observe significant survival difference in MDS/AML patients with VAF cutoff of 40%. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Integrated Personalized Prediction Model Identifies a Subgroup of Wild-Type TP53therapy-Related Myeloid Neoplasm Patients with Poor Outcome

Background: Therapy-related myeloid neoplasm (t-MN), is a heterogenous entity that includes therapy-related myelodysplastic syndromes (t-MDS), myelodysplastic syndrome/myeloproliferative neoplasms (t-MDS/MPN), and acute myeloid leukemia (t-AML) phenotypes. TP53 mutations (TP53mut) are known to be associated with poor survival in myeloid neoplasms (MN), with the recently revised World Health Organization (WHO) and the International Consensus Classification recommending major changes to the MN classification based on TP53mut status. The aim of this study was to employ machine learning approach to risk-stratify t-MN using the variables available at the time of diagnosis. The secondary aim was to identify risk factors, with a focus on the TP53 wild-type (TP53wt) cohort. Methods: We retrospectively analyzed clinicopathological features and outcomes of 380 WHO-defined t-MN patients treated at Mayo Clinic, Rochester (US cohort, n=200) or South Australia MDS Registry (AU cohort, n=180) who had cytogenetics and NGS at diagnosis. Karyotypes were classified using the International System for Cytogenetic Nomenclature Criteria. Number of cytogenetic aberrancies were counted according to Hasse et al. Leukemia 2019. A random forest survival algorithm was used to build a prognostic model using the training cohort (US cohort). The model algorithm randomly bootstraps the original data into two thirds, where the model is developed, and one third, where the model is internally validated. The process is repeated multiple times to assure reproducibility of the final result. The model was subsequently validated in an independent cohort from South Australia. The risk score optimal cut-off was determined using the maximally selected rank statistics. Results: The median age for the entire cohort was 67.3 (59.7-74.2) years. The most common cytogenetic abnormalities were complex karyotype (CK, 47.7%), monosomal karyotype (MK, 44.7%), deletion 7q (del 7q, 33.2%), and deletion 5q (del5q, 23.6%). Most common somatic mutations were TP53 (n=141; 37%), ASXL1 (n=67; 18%), TET2 (n=66;17%) and DNMT3A (n=64;17%), SRSF2 (n=46; 12%), RAS (44; 12%) and RUNX1 (n=43; 11%). Haematological malignancy (53.5%) followed by solid cancer (40.0%) and autoimmune disease (3%) were the most common primary diseases. Despite differences in frequency of CK, MK, del 7q and 5q between the training and validation cohort, the median overall survival (OS) was not significantly different between the US and the AU cohorts (17 vs. 11 months, P=0.51). The US cohort was used to build a new prognostic model. A total of 88 variables available at t-MN diagnosis (15 clinical, 32 mutations, and 44 cytogenetic) were included. TP53mut was the most important variable driving poor survival. Other variables included absolute neutrophil count, number of chromosomal abnormalities, chromosome 18 abnormality, del 5q, platelets, the number of cytogenetic clones and hemoglobin. The concordance index of the model in the training cohort was 0.65. In the US cohort, 83 (41%) and 117 (58%) patients were TP53mut and TP53wt, respectively. Median survival for TP53mut patients was 9.9 months (Figure 1A). Within the TP53wt subcohort, the model designated 52 (44%) and 65 (56%) patients as high- and low-risk groups, respectively. Strikingly, the survival of high-risk TP53wt patients was comparable to TP53mut cohort, and significantly inferior compared to the low-risk group (11.1 vs. 40.6; P<0.0001). These results were validated in the AU cohort: the proportion of TP53mut, high-risk TP53wt, and low-risk TP53wt patients was 58 (32.2%), 61 (33.9%), and 61 (33.9%), respectively. Median survival of the 3 cohorts was 7.8 months, 11.3 months, and 27.9 months respectively (P<0.0001, Figure 1B). The c-index for AU cohort was 0.66. Conclusion: The integrated prognostic model that used only diagnostic information, stratified t-MN patients into 3 approximately equal categories: TP53mut, constituting a third of the cohort, was the principal driver for inferior survival. Importantly, TP53wt cohort could further be stratified into 2 halves: the high-risk TP53wt patients had survival comparable to TP53mut cohort, whereas the low-risk cohort had an estimated 5-year survival approaching 45%. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

AML-387 Clinical Characteristics of Secondary Myeloid Neoplasms (MNs) in Patients With Inflammatory Bowel Disease (IBD)

Patients with ulcerative colitis (UC) and Crohn's disease (CD) are at increased cancer risk. Very little data is available regarding the risk of secondary MN in patients with IBD. To describe the clinical characteristics of secondary MNs in patients with IBD. Retrospective study of patients with MNs previously treated for IBD. Between 2012 and 2020, 43 patients were identified as having developed secondary MN during or after IBD treatment; 63% were women, and 81% were of white ethnicity. In 70% (30/43) of cases, secondary MNs arose after CD therapy, whereas 30% (13/43) arose after UC therapy. The median age at the time of MN diagnosis was 59 years (23-83 years), and latency from IBD diagnosis was 16 years (0-56 years). At the time of MN diagnosis, 25 patients were on active treatment for IBD (9 biological agent, 11 mesalamine, and 2 azathioprine), whereas 18 were in remission. Additionally, 8 patients (19%) had secondary cancer before the MN diagnosis (2 lymphoma, 2 skin cancer, ovarian cancer, uterine cancer, schwannoma, and adrenal tumor), and 3 patients received therapy. Acute myeloid leukemia (AML) was diagnosed in 74% of MN cases, 9 (21%) were myelodysplastic syndrome (MDS), and one each was MDS/myeloproliferative neoplasm (MPN) and chronic myelomonocytic leukemia (CMML). Cytogenetic abnormalities were detected in 70%: 13 patients (30%) with complex karyotype and 6 patients (14%) with core-binding factor (CBF) abnormalities (5 inv16 and 1 t [8;21]). Most common mutations were TP53 (23%), FLT3 (16%), RAS (19%), TET2 (16%), and DNMT3A (14%). Interestingly, all patients with CBF-AML had prior history of CD, including two treated with anti-TNF-α. The median overall survival (OS) was 2.17 yrs for the whole cohort, with no difference in OS between MNs arising from CD and UC (2.35 and 2.08 yrs for CD and UC, respectively). Seventeen patients underwent allogeneic stem cell transplantation (ASCT), which resulted in IBD remission in 13 patients (76%). Secondary MNs after IBD therapy included higher than expected prevalence of CBF-AML and were strongly associated with prior history of CD. ASCT led to remission of both MNs and IBD.

Extracellular Vesicles in Myeloid Neoplasms.

Myeloid neoplasms arise from malignant primitive cells, which exhibit growth advantage within the bone marrow microenvironment (BMM). The interaction between these malignant cells and BMM cells is critical for the progression of these diseases. Extracellular vesicles (EVs) are lipid bound vesicles secreted into the extracellular space and involved in intercellular communication. Recent studies have described RNA and protein alterations in EVs isolated from myeloid neoplasm patients compared to healthy controls. The altered expression of various micro-RNAs is the best-described feature of EVs of these patients. Some of these micro-RNAs induce growth-related pathways such as AKT/mTOR and promote the acquisition of stem cell-like features by malignant cells. Another well-described characteristic of EVs in myeloid neoplasms is their ability to suppress healthy hematopoiesis either via direct effect on healthy CD34+ cells or via alteration of the differentiation of BMM cells. These results support a role of EVs in the pathogenesis of myeloid neoplasms. mainly through mediating the interaction between malignant and BMM cells, and warrant further study to better understand their biology. In this review, we describe the reported alterations of EV composition in myeloid neoplasms and the recent discoveries supporting their involvement in the development and progression of these diseases.

Aberrant EVI1 splicing contributes to EVI1-rearranged leukemia

AbstractDetailed genomic and epigenomic analyses of MECOM (the MDS1 and EVI1 complex locus) have revealed that inversion or translocation of chromosome 3 drives inv(3)/t(3;3) myeloid leukemias via structural rearrangement of an enhancer that upregulates transcription of EVI1. Here, we identify a novel, previously unannotated oncogenic RNA-splicing derived isoform of EVI1 that is frequently present in inv(3)/t(3;3) acute myeloid leukemia (AML) and directly contributes to leukemic transformation. This EVI1 isoform is generated by oncogenic mutations in the core RNA splicing factor SF3B1, which is mutated in >30% of inv(3)/t(3;3) myeloid neoplasm patients and thereby represents the single most commonly cooccurring genomic alteration in inv(3)/t(3;3) patients. SF3B1 mutations are statistically uniquely enriched in inv(3)/t(3;3) myeloid neoplasm patients and patient-derived cell lines compared with other forms of AML and promote mis-splicing of EVI1 generating an in-frame insertion of 6 amino acids at the 3′ end of the second zinc finger domain of EVI1. Expression of this EVI1 splice variant enhanced the self-renewal of hematopoietic stem cells, and introduction of mutant SF3B1 in mice bearing the humanized inv(3)(q21q26) allele resulted in generation of this novel EVI1 isoform in mice and hastened leukemogenesis in vivo. The mutant SF3B1 spliceosome depends upon an exonic splicing enhancer within EVI1 exon 13 to promote usage of a cryptic branch point and aberrant 3′ splice site within intron 12 resulting in the generation of this isoform. These data provide a mechanistic basis for the frequent cooccurrence of SF3B1 mutations as well as new insights into the pathogenesis of myeloid leukemias harboring inv(3)/t(3;3).

Therapy-related Myeloid Neoplasms in Patients With Chronic Lymphocytic Leukemia Who Received FCR/FC as Frontline Therapy.

Therapy-related Myeloid Neoplasms in Patients With Chronic Lymphocytic Leukemia Who Received FCR/FC as Frontline Therapy.

Automated analysers underestimate atypical basophil count in myeloid neoplasms

Recent data suggest basophils can adopt an atypical appearance in myeloid disorders including myeloproliferative neoplasms (MPNs) and myeloproliferative/myelodysplastic disease. We hypothesized that automated analysers may not accurately quantitate basophils in myeloid neoplasms based on scatter properties. This study examined basophil counts and properties in myeloid disorders by automated cell analyser, manual differential, and flow cytometry. Patients with myeloid neoplasms and control patients with no myeloid disorder diagnosis at a tertiary care centre were identified. Basophil percentage was compared for automated analyser counts (Sysmex XN9000), manual differential, and flow cytometry. Basophil scatter properties in MPNs were examined using flow cytometry. Thirty-one patients with myeloid neoplasms were included: 58% were male, mean age was 70.2 (±20.7) years, 32% had a diagnosis of chronic myeloid leukaemia with the remaining patients divided among various other forms of myeloid disease (including: essential thrombocythemia, polycythemia vera, unclassifiable MPN, myelodysplastic syndromes). For these patients, mean basophil percentage by automated analyser was significantly lower than manual differential (2.7 ± 2.9 vs. 7.1 ± 4.6, respectively, p< 0.001). No significant difference was found between automated versus manual differential for basophils in control subjects (p= 0.373). For myeloid neoplasm patients, mean basophil percentage was not significantly different between manual differential and flow cytometry (p= 0.116); mean basophil percentage by automated analyser was significantly lower than flow cytometry (2.7 ± 2.9 vs. 5.3 ± 3.7, respectively, p= 0.003). Automated analysers underestimate basophil counts in patients with myeloid neoplasms. Manual differential and flow cytometry are recommended for more accurate quantitation and characterization of aberrant basophils.

Clonal haematopoiesis as a risk factor for therapy-related myeloid neoplasms in patients with chronic lymphocytic leukaemia treated with chemo-(immuno)therapy.

Clonal haematopoiesis of indeterminate potential (CHIP) may predispose for the development of therapy-related myeloid neoplasms (t-MN). Using target next-generation sequencing (t-NGS) panels and digital droplet polymerase chain reactions (ddPCR), we studied the myeloid gene mutation profiles of patients with chronic lymphocytic leukaemia (CLL) who developed a t-MN after treatment with chemo-(immuno)therapy. Using NGS, we detected a total of 30 pathogenic/likely pathogenic (P/LP) variants in 10 of 13 patients with a t-MN (77%, median number of variants for patient: 2, range 0-6). The prevalence of CHIP was then backtracked in paired samples taken at CLL diagnosis in eight of these patients. Six of them carried at least one CHIP-variant at the time of t-MN (median: 2, range: 1-5), and the same variants were present in the CLL sample in five cases. CHIP variants were present in 34 of 285 patients from a population-based CLL cohort, which translates into a significantly higher prevalence of CHIP in patients with a CLL who developed a t-MN, compared to the population-based cohort (5/8, 62.5% vs. 34/285, 12%, p=0.0001). Our data show that CHIP may be considered as a novel parameter affecting treatment algorithms in patients with CLL, and highlight the potential of using chemo-free therapies in CHIP-positive cases.