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Loghavi, Sanam

https://orcid.org/0000-0001-8980-3202

Mayo Clinic

The University of Texas MD Anderson Cancer Center

Citations 20

Real‐world, multi‐omics validation of the clinical relevance of molecular taxonomy for myelodysplastic syndromes (MDS)
Sauta, Elisabetta, Lanino, Luca, Bewersdorf, Jan P, Kewan, Tariq, Ali, Najla H. Al, Fenaux, Pierre, Platzbecker, Uwe, Santini, Valeria, Brunner, Andrew M., Kuykendall, Andrew T., Bennett, John M. , Buckstein, Rena, Bejar, Rafael, Carraway, Hetty E., DeZern, Amy E., Hasserjian, R., Loghavi, Sanam, Odenike, Olatoyosi, Padron, Eric , Patnaik, Mrinal M., Stahl, Maximilian, Sekeres, M., Steensma, David P., Savona, Michael R., Taylor, Justin, Xu, Mina L., Sallman, David A., Nimer, Stephen D. , Hourigan, Christopher S., Wei, Andrew H., Riva, Elena , Ventura, Denise, Pinocchio, Nicole, Buizza, Alessandro , Russo, Antonio, D'Amico, Saverio, Delleani, Mattia , Travaglino, Erica , Tentori, Cristina A., Ferrari, Ivan, Crespi, Alessandra, Figini, Giulia , Matteo, Maria Di, Milanesi, Chiara, Castellani, Gastone, Borate, Uma M., Gore, Steven D., Kim, Tae K., Loosdrecht, Arjan A. van de , Daver, N., Wang, Sa A. , Foucar, Kathryn, Iastrebner, Marcelo, Miyazaki, Yasushi, Al‐Kali, Aref, Mittelmann, Moshe, Cluzeau, Thomas , Ades, Lionel, Germing, Ulrich, Garcia‐Manero, Guillermo, Kordasti, Shahram, Haferlach, Torsten, Zeidan, Amer M., consortia, An international study on behalf of GenoMed4all, Synthema, and icMDS, Zeidan, Amer M. , Buizza, Alessandro , Ficara, Francesca , Efficace, Fabio , Diez-Campelo, Maria , Orfao, Alberto , Wang, Sa A , Cluzeau, Thomas , Komrokji, Rami S , Della Porta, Matteo Giovanni , Zeidan, Amer M , Maggioni, Giulia , Todisco, Gabriele , Sauta, Elisabetta , Lanino, Luca , Ball, Somedeb , Bewersdorf, Jan Philipp , Fenaux, Pierre , Platzbecker, Uwe , Santini, Valeria , Xie, Zhuoer , Brunner, Andrew M. , Kuykendall, Andrew , Buckstein, Rena , Bejar, Rafael , Carraway, Hetty E. , Dezern, Amy Elizabeth , Griffiths, Elizabeth A. , Halene, Stephanie , Hasserjian, Robert P. , List, Alan F. , Loghavi, Sanam , Odenike, Olatoyosi , Patnaik, Mrinal M. , Roboz, Gail J. , Sekeres, Mikkael A. , Steensma, David P. , Savona, Michael R. , Sallman, David A. , Hourigan, Christopher S. , Wei, Andrew H. , Campagna, Alessia , Ubezio, Marta , Ventura, Denise , Pinocchio, Nicole , Zampini, Matteo , Russo, Antonio , Pesce, Francesco , D'Amico, Saverio , Asti, Gianluca , Tentori, Cristina Astrid , Ferrari, Ivan , Matteo, Maria Di, Brindisi, Matteo , Manes, Nicla , Crisafulli, Laura , Ficara, Francesca , Castellani, Gastone , Borate, Uma , Efficace, Fabio , Gore, Steven D. , Díez‐Campelo, María , Rozman, Marı́a , Órfão, Alberto , Foucar, Kathryn , Iastrebner, Marcelo , Scheinberg, Phillip , Miyazaki, Yasushi , Madanat, Yazan F. , Al‐Kali, Aref , Mittelman, Moshe , Adès, Lionel , Germing, Ulrich , Garcia‐Manero, Guillermo , Kordasti, Shahram , Haferlach, Torsten , Komrokji, Rami S.

HemaSphere | June 22, 2026 | Volume: 10 | Issue: 6 | Pages: No page available

10.1002/hem3.70406 Get It

Abstract Myelodysplastic syndromes (MDS) are clinically and biologically diverse disorders, emphasizing the need for personalized treatment approaches. The International Working Group for Prognostication of MDS (IWG_PM) recently introduced a molecular classification, referred to as the MDS taxonomy, that categorizes patients into 16 subgroups based on 21 gene mutations, 6 cytogenetic abnormalities, and loss of heterozygosity (LOH) at TP53 and TET2 loci. This study sought to validate and enhance the clinical relevance of the MDS taxonomy by analyzing a large retrospective cohort ( n = 5136) and transcriptomic data from a prospective cohort ( n = 477). The taxonomy successfully identified subgroups with distinct clinical characteristics and disease progression patterns. However, incorporating gene interactions from taxonomy subgroups did not improve the prognostic performance of the Molecular International Prognostic Scoring System (IPSS‐M). We further assessed whether the taxonomy could guide management in patients receiving disease‐modifying therapies. Except for the “ TP53 ‐complex” subgroup, taxonomy classifications were not predictive of hypomethylating agent response or transplant outcomes. Nonetheless, they correlated with overall survival, suggesting that while both IPSS‐M and the taxonomy capture disease biology, other non‐genetic factors may influence treatment response. RNA sequencing confirmed the biological distinctiveness of the taxonomy groups. Transcriptomic profiling of CD34+ bone marrow cells revealed unique, homogeneous gene expression patterns, particularly within the AML‐like, bi TET2 , SF3B1 , and TP53 ‐complex subgroups. Further integration of multi‐omics data may refine MDS classification, improving clinical decision‐making and guiding the development of targeted therapies.
Incorporation of Genomic Determinants Improves Diagnostic Accuracy of Oligomonocytic Chronic Myelomonocytic Leukemia
Montalban-Bravo, Guillermo, Wu, Chong , Rodríguez‐Sevilla, Juan José , Wei, Yue , Chien, K., Bouligny, Ian , Kanagal‐Shamanna, Rashmi , Li, Ziyi , Natu, Anuya , Bazinet, Alexandre , Hammond, Danielle E., Bataller, Alex, Borthakur, Gautam, Short, Nicholas J., DiNardo, Courtney D., Kadia, Tapan M., Ravandi, Farhad, Daver, Naval, Pemmaraju, Naveen, Jabbour, Elias, Issa, Ghayas C., Wang, Sa A., Patel, Keyur P. , Tang, Guilin, Medeiros, L. Jeffrey, Finke, Christy M. , Al‐Kali, Aref , Alkhateeb, Hassan, Gangat, Naseema, Mangaonkar, Abhishek A., Román, David , Arenillas, Leonor , Tefferi, Ayalew, Kantarjian, Hagop M., Garcia-Manero, Guillermo, Calvo, Xavier , Patnaik, Mrinal M. , Loghavi, Sanam, Kantarjian, Hagop M. , Bravo, Guillermo Montalban , Chien, Kelly , Gurney, Mark , Bazinet, Alexandre , Hammond, Danielle , Bataller, Alex , Borthakur, Gautam , Short, Nicholas , DiNardo, Courtney , Kadia, Tapan M , Ravandi, Farhad , Daver, Naval , Pemmaraju, Naveen , Jabbour, Elias , Issa, Ghayas , Wang, Sa A , Patel, Keyur P , Tang, Guilin , Medeiros, L Jeffrey , Lasho, Terra L , Finke, Christy M , Al-Kali, Aref , Csizmar, Clifford , Alkhateeb, Hassan B , Gangat, Naseema , Mangaonkar, Abhishek A. , Roman-Bravo, David , Arenillas, Leonor , Tefferi, Ayalew , Kantarjian, Hagop , Garcia-Manero, Guillermo , Calvo, Xavier , Patnaik, Mrinal , Loghavi, Sanam , Kanagal-Shamanna, Rashmi , Rodríguez-Sevilla, Juan José , Montalban‐Bravo, Guillermo , Chien, Kelly S. , Gurney, Mark E. , Hammond, Danielle , Borthakur, Gautam , Short, Nicholas J. , DiNardo, Courtney D. , Kadia, Tapan M. , Daver, Naval , Pemmaraju, Naveen , Jabbour, Elias , Wang, Sa A. , Tang, Guilin , Medeiros, L. Jeffrey , Lasho, Terra L. , Csizmar, Clifford M. , Alkhateeb, Hassan B. , Gangat, Naseema , Mangaonkar, Abhishek A. , Tefferi, Ayalew , Garcia‐Manero, Guillermo , Loghavi, Sanam

Blood Cancer Discovery | January 26, 2026 | Volume: 7 | Issue: 3 | Pages: 414-430

10.1158/2643-3230.bcd-25-0264 Get It

Abstract Recent updates to monocyte count thresholds recognize oligomonocytic chronic myelomonocytic leukemia (OM-CMML) as an early form of CMML. However, the clinical validity of these changes remains uncertain without incorporating biological and genomic factors. In this study, we analyzed a cohort of 911 patients (249 with OM-CMML, 359 with overt CMML, and 303 with myelodysplastic syndromes) using unsupervised clustering to evaluate the role of genomic determinants in refining CMML diagnosis. Our findings show that CMML molecular signatures (biallelic TET2 mutations or SRSF2-TET2 comutations) are linked to a distinct transcriptome, monocytic bias, classical monocytosis, and a higher risk of progression to overt CMML in OM-CMML cases. We developed a weighted genomic model and diagnostic workflow showing that combining genomic signatures with bone marrow monocyte frequencies in OM-CMML more accurately predicts progression to overt CMML. These findings support integrating genomic determinants and our clinic-ready diagnostic workflow into the CMML diagnostic framework to improve accuracy. Significance: Through comprehensive clinical and genomic profiling of a large patient cohort, alongside immunophenotypic and transcriptional cellular analyses, this study provides evidence that incorporating genomic determinants into the diagnostic criteria for OM-CMML improves diagnostic accuracy and refines the identification of early-stage CMML, thereby preventing misclassification.
Myeloid malignancies molecular analysis for therapy choice (myeloMATCH): Rapid availability of clinical, pathologic and molecular features for treatment assignment in the first 550 patients.
Winer, Eric, Tsai, Stephanie, Osman, Afaf, Im, Annie , Moseley, Anna , Wood, Brent, Chen, Xueyan , Qu, Xiaoyu , Harris, Lyndsay N. , Ghatak, Sayak , Gore, Steven D. , Michaelis, Laura C. , Odenike, Olatoyosi , Stone, Richard M. , Luger, Selina M. , Assouline, Sarit, Litzow, Mark R. , Lachowiez, Curtis A. , Borate, Uma , Savoie, Mary Lynn , Roy, Ntasha, Radich, Jerald P. , Little, Richard F. , Othus, Megan , Atallah, Ehab , Tsai, Stephanie, Sabloff, Mitchell , Loghavi, Sanam , Fang, Min, Yeung, Cecilia C.S. , Uy, Geoffrey L. , Erba, Harry Paul , Litzow, Mark R. , Reagan, John L. , Jonas, Brian A. , Jiwani, Shahanawaz S.

Blood | December 5, 2025 | Volume: 146 | Issue: Supplement 1 | Pages: 5279-5279

10.1182/blood-2025-5279 Get It

Abstract Background: MyeloMATCH is an NCI-sponsored initiative for acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS) employing a Master Screening and Reassessment Protocol (MSRP) to assign patients (pts) to a pt and disease biology-specific clinical trial. Several trials evaluating initial therapies are currently open, while subsequent trials dedicated to eradicating measurable residual disease during consolidation and including stem cell transplant are being developed. A pt enrolled at diagnosis may be followed longitudinally and be eligible for trials in sequential tiers throughout the treatment course. We report key data concerning the first cohort of pts enrolled on the MSRP. Methods: After pts with suspected AML or MDS consent for the MSRP, blood and marrow are sent to the myeloMATCH Molecular Diagnostics Network (MDNet) of central CLIA labs operating under a single Investigational Device Exemption to rapidly define molecular, cytogenetic, and immunophenotypic characteristics. These data are catalogued by a bioinformatics team (MATCHBox) and reviewed daily to assign participants to an available trial based on pt and disease features. A Tier Advancement Pathway (TAP) allows standard of care therapy with potential for assignment to subsequent myeloMATCH trials. Since activation in May 2024, 550 patients age≥18 were enrolled on the MSRP from 76 institutions: 48 Academic, 14 NCORP, 11 community, 3 VA. There are currently 4 open randomized AML trials (≥age 60 or unfit with mutant FLT3, ≥age 60 IDH2 mutant AML, fit age<60 ELN 2017 intermediate-risk AML, fit age<60 ELN 2017 adverse risk) and 1 MDS trial(IDH2 mutant). Patients not eligible for an open protocol were assigned to TAP. Results: Of the 550 pts consented, 491 completed screening assays; 49 had no or incomplete samples; 10 withdrew before completed analysis. Median cytogenetic turnaround time (TAT) was 69 hours (91% within 72 hours), and median Next Generation Sequencing (NGS) TAT from receipt was 49 hours (95% within 72 hours). Seventy-six pts (of 491 with assay data) were not assigned due to non-AML or non-MDS diagnoses, the most common being: B-ALL [n=11], MPN [9], benign marrow [9], APML [7], and MPAL [6]. The AML/MDS verified cohort was 415 pts, 366 (89.2%) patients with AML (45% age <60) and 49 (11.8%) with MDS. The median age at screening was 63 years (range:18-95) and 186 (45%) were female. Eighty-two percent identified as White, 7.5% Black, 3% Asian, 7% unknown, and 9% as Hispanic. The most frequent mutations in the AML pts were NPM1 (24.0%), DNMT3A (22.7%), TET2 (19.9%), NRAS (18.0%), FLT3 (18.0% ITD, TKD 7.1%), TP53 (14.5%), and CEBPA (8.7%); IDH1/2 mutation rates were 8.2% and 13.7%, respectively. Co-mutations include FLT3/NPM1 (9.8%), NPM1/IDH2 (4.4%), IDH1/2 and any RAS (3.8%). Karyotypes were normal in 40.4%, complex 20.8%, inv(16) 6.0%, MLL/KMT2A 4.6% and t(8;21) 1.9%. 29% had favorable risk disease, 29% intermediate, and 42% adverse (ELN 2017). In MDS, mutations included: TP53 (36.7%), RUNX1 (20.4%) ASXL1 (20.4%), TET2 (18.4%), spliceosome mutations (SRSF2, SF3B1, U2AF1 and ZRSR2, 28.6%) andIDH1/2 in 4.1% and 6.1%, respectively. Karyotypes were normal in 24.5%; complex in 40.8%. By IPSS-R, 2.4% were low, 73.8% intermediate, 2.4% high, and 21.4% very high risk. 82/415 (20%) pts were assigned to initial therapy protocol, with an increase in assignment rate to 44% in the most recent two months. 71/415 pts (16%) were enrolled in one of the MyeloMATCH studies. Three-hundred forty-four pts (80%) were assigned and enrolled to TAP (296 AML, 48 MDS) for potential assignment to subsequent tier trials. In the TAP AML pts, 99 (33%) have completed initial treatment, including intensive chemotherapy (IC) in 62% of pts and hypomethylating agents/venetoclax (HMA/VEN) in 38%. In pts <60 years of age, 87% received IC v. 13% with HMA/VEN, in >60 34% IC v. 66% HMA/VEN and in age 60-75 42% IC v. 58% HMA/Ven. Conclusion: MyeloMATCH has screened over 500 pts from academic and community sites in the US and Canada in 14 months, meeting the TAT goal of sample acquisition to results of <72 hours. Assignment to treatment protocols has substantially increased recently. As additional trials open (12 in development) we expect the percentage of pts enrolled on MSRP who go on to therapeutic trials will markedly increase, thereby allowing a personalized medicine approach for a broad group of US and Canadian adult pts with AML and MDS.
Clinical and biological correlates of blast-transformed chronic myelomonocytic leukemia (CMML): A multicenter study of 493 paired cases at chronic phase and at blast transformation
Montalban‐Bravo, Guillermo , Cysique-Foinlan, Leila , Finke, Christy M. , Al‐Kali, Aref , Alsugair, Ali, Begna, Kebede, Fathima, Saubia, Gangat, Naseema , Mangaonkar, Abhishek A. , Tefferi, Ayalew , Morabito, Margot, Marzac, Christophe , Braun, Thorsten, Adès, Lionel, Bazinet, Alexandre , Chien, Kelly S. , Kadia, Tapan M. , Kanagal‐Shamanna, Rashmi , Pemmaraju, Naveen , Kantarjian, Hagop, Fenaux, Pierre , Garcia‐Manero, Guillermo , Patnaik, Mrinal M. , Kanagal-Shamanna, Rashmi , Csizmar, Clifford M. , Natu, Anuya , Lasho, Terra L. , Alkhateeb, Hassan B. , Fathima, Saubia , Saliba, Antoine N. , Droin, Nathalie , Quivoron, Cyril , Podvin, Benjamin , Duployez, Nicolas , Kosmider, Olivier , Thépot, Sylvain , Meunier, Mathieu , Berthon, Céline , Braun, Thorsten , Willekens, Christophe , Botton, Stéphane de , Adès, Lionel , Hammond, Danielle , DiNardo, Courtney D. , Loghavi, Sanam , Ravandi, Farhad , Sasaki, Koji , Solary, Éric , Renneville, Aline

Blood | December 5, 2025 | Volume: 146 | Issue: Supplement 1 | Pages: 2081-2081

10.1182/blood-2025-2081 Get It

Abstract Introduction Blast transformation (BT) in CMML occurs in 15-30% of patients (pts) with a median overall survival (OS) <6 months (mo). While clonal evolution can be observed, biological mechanisms of BT remain unknown for many pts. Using paired samples from chronic phase (CP) and at BT, this study defines the cytogenetic and molecular landscape of BT-CMML. Methods BT-CMML pts from Mayo Clinic (n=153, 31%), MD Anderson (n=195, 40%), and 7 centers of the Groupe Francophone des Myélodysplasies (n=145, 29%) were included after IRB approval. ICC 2022 criteria defined CMML and AML. Pt data were collected at initial diagnosis or referral at CP and again at BT. Clonal dominance was inferred from a natural log-fold difference of mutation variant allele fractions (VAF). OS was censored at allogeneic stem cell transplant (alloSCT). Single-cell multiomic analyses used the Tapestri platform (Mission Bio). Statistics used R. Results Among 1,883 cases of CMML with a median follow up of 96 mo, 493 (26%) underwent BT. The median age at CP and BT was 69 and 71 years, respectively. BT-CMML pts were predominantly male (69%) and had proliferative CMML (53%) or CMML-1 (69%) in CP; 39% and 33% were considered high-risk by CPSS-Mol and BLAST-Mol criteria, respectively. The median time to BT was 16 mo (interquartile range 7-35 mo) and was not different in males vs females (p=0.60). Compared to their CP parameters (p<0.001 each), pts at BT had lower median hemoglobin (10.8 vs 9.2 g/dL) and platelets (100 vs 44 x109/L) but higher leukocytes (13.9 vs 16.3 x109/L), peripheral blasts (0% vs 14%), and bone marrow blasts (6% vs 32%). Blasts exhibited mostly monocytic (57%) or immature myeloid (40%) differentiation. Abnormal karyotypes (AK) were more prevalent at BT (25% vs 62%, p<0.001). Among 318 pts with paired karyotype data, 221 (69%) had a normal karyotype (NK) in CP, of which 123 (56%) remained normal at BT and 98 (44%) acquired new abnormalities. Conversely, 97 (31%) pts had an AK in CP, of which 67 (69%) acquired abnormalities or increased clonal metaphases (6%), 23 (24%) remained stable, and 7 (7%) reverted to a NK at BT. Overall, 46% acquired and 8% lost a clonal cytogenetic abnormality, while 46% remained unchanged. Numeric (37%) and structural (30%) changes were most common. Complex (12% vs 3%) and monosomal (5% vs 2%) karyotypes were more frequent at BT than in CP. Only 6 (2%) pts acquired an AML-defining rearrangement at BT. Mutational data were available for 248 paired cases. The number of somatic mutations was higher at BT (median 3 vs 4, p<0.001). Mutations in RUNX1 (27% vs 39%), NRAS (23% vs 33%), KRAS (11% vs 17%), FLT3 (6% vs 15%), NPM1 (0% vs 11%), IDH2 (5% vs 11%), and CEBPA (3% vs 10%) were more frequent at BT (all p<0.05). At BT, the average VAF of the dominant clone increased in 32%, decreased in 35%, and remained unchanged (delta ≤5%) in 33%. The most frequent dominant clones both in CP and at BT had mutations in TET2 (8% vs 4%) or co-dominant mutations involving SRSF2-TET2 (7% vs 3%). Mutational clonal evolution was observed in 72%, with mutations gained in 45% and lost from the dominant clone in 19%. The most gained mutations at BT were in NRAS (15%) and RUNX1 (13%). Single cell proteogenomic analyses in 4 selected CP and BT pts shed light on the impact of NRAS and RUNX1 mutations on clonal hierarchies and differentiation. Among 196 fully evaluable cases, a new cytogenetic and/or molecular aberration was uniquely gained in 106 (54%) cases and lost in 9 (5%), with 40 (20%) both gaining and losing a genetic alteration. Forty-one (21%) patients had no identifiable genetic change between CP and BT, suggesting driver alterations outside of that detected by routine analyses. Median OS was 31 mo from CMML diagnosis and 5.6 mo from BT. Compared to supportive care, treatment in CP did not prolong median time to BT (14 vs 17 mo, p=0.91) or OS (35 vs 29 mo, p=0.05), regardless of intensity. After BT, median OS was 1.2 mo with supportive care (n=83), 8.7 mo with a hypomethylating agent (HMA, n=39), 10 mo with HMA plus venetoclax (n=37), 7.8 mo with chemotherapy (n=91), and 31 mo in pts who underwent alloSCT (n=57). Conclusions In this large BT-CMML cohort, cytogenetic (46% gained, 8% lost) or mutational (45% gained, 19% lost) driver events were identified in 79% of pts, with 21% having no identifiable changes by conventional testing. Whole genome/transcriptome analyses are underway in this subgroup to identify novel drivers of BT.
Consideration of genomic determinants improves the diagnostic accuracy of oligomonocytic chronic myelomonocytic leukemia
Montalban‐Bravo, Guillermo , Wei, Yue , Chien, Kelly S. , Kanagal‐Shamanna, Rashmi , Bazinet, Alexandre , Kadia, Tapan M. , Pemmaraju, Naveen , Issa, Ghayas C., Wang, Sa , Patel, Keyur P. , Lasho, Terra, Finke, Christy M. , Al‐Kali, Aref , Gangat, Naseema , Mangaonkar, Abhishek A. , Román, David , Tefferi, Ayalew , Kantarjian, Hagop, Garcia‐Manero, Guillermo , Patnaik, Mrinal M. , Kanagal-Shamanna, Rashmi , Wu, Chong , Rodríguez‐Sevilla, Juan José , Bouligny, Ian , Natu, Anuya , Gurney, Mark E. , Hammond, Danielle , Bataller, Alex , Borthakur, Gautam , Short, Nicholas J. , DiNardo, Courtney D. , Ravandi, Farhad , Daver, Naval , Jabbour, Elias , Issa, Ghayas , Tang, Guilin , Medeiros, L. Jeffrey , Lasho, Terra, Csizmar, Clifford M. , Alkhateeb, Hassan B. , Arenillas, Leonor , Calvo, Xavier , Loghavi, Sanam

Blood | December 4, 2025 | Volume: 146 | Issue: Supplement 1 | Pages: 3849-3849

10.1182/blood-2025-3849 Get It

Abstract Recent updates to the monocyte count thresholds for diagnosing chronic myelomonocytic leukemia (CMML) have recognized oligomonocytic CMML (OM-CMML) as an early stage within the CMML spectrum. However, the clinical validity of these revised criteria remains uncertain without considering biological factors and might misclassify myelodysplastic syndromes (MDS) with mild monocytosis as CMML. To characterize the genomic landscape of OM-CMML, we evaluated OM-CMML (n=249), MDS (n=304) and myelodysplastic CMML (MD-CMML, n=358) patients (pts) treated at three academic institutions. Targeted next-generation sequencing was performed on bone marrow (BM) at initial diagnosis or first referral. OM-CMML was characterized by lower frequencies of biallelic TET2 (biTET2) and RAS pathway (RASp) gene mutations (BRAF, CBL, KRAS, NF1, NRAS and PTPN11) compared to MD-CMML (p<0.001) but higher frequencies than MDS (p<0.001). BM monocyte frequencies, assessed morphologically, were higher in OM-CMML than in MDS (p<0.001) but lower than in MD-CMML (p<0.001), indicating that OM-CMML is a heterogenous group including true CMML and distinct MDS subsets. Unsupervised hierarchical clustering based on genomic alterations across all cases (n=911) identified three distinct clusters: 1) TP53 alterations (predominantly multihit TP53) and complex karyotype (TP53-complex); 2) biTET2 or TET2-SRSF2 co-mutation (biTET2/SRSF2); 3) a heterogenous group lacking these features (not otherwise specifiable [NOS]). Among OM-CMML pts, 11%, 34% and 55% belonged to these clusters, respectively. Model-based unsupervised clustering further identified 9 unique clusters that could be consolidated into 6 groups: 1) TP53-complex; 2) biTET2/SRSF2; 3) SF3B1 (without biTET2 or SRSF2); 4) SRSF2 without TET2 and frequent IDH2 mutations (SRSF2-IDH2); 5) ASXL1 and U2AF1 mutations and copy number alterations (CNA-ASXL1/U2AF1); 6) no somatic mutations (No mutation). biTET2/SRSF2 group exhibited monocytic bias with higher AMC, PB and BM monocyte % even among OM-CMML cases. This bias was not attributed to higher RAS pathway mutation frequencies, as biTET2/SRSF2 cases had similar RASp mutation frequencies but lower median variant allele frequencies for RASp mutations compared to NOS cases (9% vs. 21%, p=0.029). PB monocyte partitioning using flow cytometry (FC) in a subset of OM-CMML pts (n=50) demonstrated higher frequency of classical monocytosis (>94% CD14+/CD16- monocytes) in biTET2/SRSF2 vs other OM-CMML. To further determine if biTET2/SRSF2 genotype defines a distinct biological subgroup, we performed RNA-sequencing of BM CD34+ cells from healthy donors (n=15) and pts with OM-CMML (n=12), MD-CMML (n=14) and MDS (n=55). Unsupervised clustering based on gene expression profiles revealed that biTET2/SRSF2 clustered irrespective of their diagnostic group with greater dispersion being observed based on diagnosis. MDS and CMML with biTET2/SRSF2 had less differentially expressed genes compared to MDS and CMML with biTET2/SRSF2 relative to other MDS and CMML genotypes. Among 138 OM-CMML pts in whom progression to overt CMML was evaluable, 37 (27%) progressed to overt CMML of which 26 (70%) belonged to the biTET2/SRSF2 group. Competing risk analysis confirmed higher cumulative incidence and shorter time to CMML progression among biTET2/SRSF2 OM-CMML. Using ElasticNet regression we identified BM monocytosis and 14 genomic variables (including biTET2 and TET2-SRSF2) as predictors of overt CMML progression among OM-CMML. We developed a score-based model able to predict progression with high reliability (AUC 0.805, sensitivity 0.70, specificity 0.76). Model accuracy was confirmed by optimism-corrected bootstrap internal validation (AUC 0.668). Monocytic bias, BM classical monocytosis (>94% CD16- monocytes) and higher overt CMML progression in biTET2/SRSF2 was confirmed in a validation cohort (28, 66 and 22 pts with OM-CMML, MDS and MD-CMML, respectively). BM monocytosis of biTET2/SRSF2 was confirmed in this cohort with morphologic and FC monocyte frequency quantification having high concordance (r=0.737, p<0.001). Genomic subgroup analysis discriminated survival outcomes more reliably than diagnostic categories alone. Our findings suggest that the presence of biTET2 or TET2-SRSF2 co-mutations, combined with BM monocytosis, can more reliably identify true CMML cases within the OM-CMML spectrum. Integrating genomic determinants into the CMML diagnostic framework enhances diagnostic accuracy.
Wide variability and inconsistency in reporting of results of Myelodysplastic Syndromes/neoplasms (MDS) clinical trials: An icMDS systematic review of published manuscripts
Getz, Ted M. , Pugh, Kelly , Brunner, Andrew M. , Borate, Uma , Buckstein, Rena , Hasserjian, Robert P. , Fenaux, Pierre, Sallman, David A. , Nimer, Stephen D. , Little, Richard F. , Odenike, Olatoyosi , Greenberg, Peter L. , Xu, Mina L. , Bejar, Rafael, Patnaik, Mrinal M. , Padron, Eric , Gore, Steven D. , Bennett, John M. , Metzeler, Klaus H. , Pleyer, Lisa , Loosdrecht, Arjan van de, Cluzeau, Thomas , Mufti, Ghulam, Sébert, Marie , Götze, Katharina S. , Miyazaki, Yasushi , Al‐Kali, Aref , Yacoub, Abdulraheem , Li, Bing, Stahl, Maximilian , Götze, Katharina , Brunner, Andrew, Bewersdorf, Jan Philipp , Dezern, Amy Elizabeth , Kewan, Tariq Zuheir , Platzbecker, Uwe , Sekeres, Mikkael A. , Wei, Andrew H. , Kordasti, Shahram , Roboz, Gail J. , Savona, Michael R. , Loghavi, Sanam , Fenaux, Pierre , Hourigan, Christopher S. , Porta, Matteo Giovanni Della , Santini, Valeria , Efficace, Fabio , Taylor, Justin , Kim, Tae Kon , Halene, Stephanie , Komrokji, Rami S. , Griffiths, Elizabeth A. , Xie, Zhuoer , Bejar, Rafael , Sanz, Guillermo , Figueroa, María E. , Carraway, Hetty E. , Abdel‐Wahab, Omar , Starczynowski, Daniel T. , Boultwood, Jacqueline , Daver, Naval , Churpek, Jane E. , Majeti, Ravindra , List, Alan F. , Orgueira, Adrián Mosquera , Solé, Françesc , Steensma, David P. , Adès, Lionel , Lanino, Luca , Madanat, Yazan F. , Platzbecker, Anne Sophie , Lindsley, R Coleman , Gurnari, Carmelo , Li, Bing, Kotsianidis, Ιoannis , Zeidan, Amer M.

Blood | December 4, 2025 | Volume: 146 | Issue: Supplement 1 | Pages: 3852-3852

10.1182/blood-2025-3852 Get It

Abstract Introduction: Standardized reporting of clinical trials results for MDS is essential to improve clinical interpretation and cross-study comparison. However, reporting of patient characteristics, response criteria, and endpoints in publications is often inconsistent; there is no systemic analysis of MDS trial reporting available. We conducted a systematic review of published MDS trial manuscripts on behalf of the international consortium for MDS (icMDS) to assess variability in reporting practices. Methods We searched ClinicalTrials.gov to identify all clinical trials registered for adults (≥18 years) with MDS that reported results between 2015-2024. Clinical trials that included acute myeloid leukemia (AML) or MDS/myeloproliferative neoplasms (MPN) were included if they enrolled ≥5 MDS patients. We excluded trials without an MDS cohort; non-therapeutic trials; trials focused on transplant interventions; or those which enrolled solid malignancies or other hematologic malignancies (chronic myeloid leukemia or lymphoid diseases). Finally, trials were required to have a manuscript available on Larvol, PubMed, or Google Scholar. Trials were categorized by disease risk (lower-risk [LR] vs. higher-risk [HR]) and trial phase (early phase [EP] vs. late phase [LP]). Results We identified 502 MDS trials on ClinicalTrials.gov, of which 351 did not meet inclusion criteria and 79 lacked a manuscript. A total of 72 trials (32 EP, 40 LP) with 80 publications (34 EP, 46 LP) were analyzed. Frequently reported baseline characteristics included age (100% EP, 100% LP), disease risk (74% EP, 74% LP), Eastern Cooperative Oncology Group performance status (85% EP, 72% LP), prior treatments (71% EP, 67% LP), and RBC transfusion dependency (32% EP, 70% LP). Less frequently reported characteristics included blood counts (hemoglobin [Hb; 38% EP, 54% LP], platelet count [38% EP, 54% LP], neutrophil count [24% EP and LP]) and bone marrow blasts (29% EP, 43% LP). Although disease risk was widely reported, definitions varied: IPSS and IPSS-R were each reported in 54% of manuscripts, while IPSS-M appeared in only 3%. Cytogenetic risk was separately reported in 39% of manuscripts (38% EP, 39% LP), and mutational data in 45% (47% EP, 43% LP). Responses per IWG 2006 criteria were reported in 84% of manuscripts. The primary endpoint involved safety/tolerability in 85% of EP manuscripts, though definitions were variable; recommended phase 2 dose was the most common (26% of EP manuscripts). In LP trials, primary endpoints were risk-specific: transfusion independence (TI) in 77% of LR, overall response rate (ORR) in 28% of HR, and complete remission (CR) or overall survival (OS) in 22% of HR. In HR manuscripts, CR was reported in 100%, ORR in 73%, hematologic improvement (HI) in 48%, RBC-TI in 23%, and OS in 80%. However, seven different definitions were used for ORR: CR + marrow CR + partial remission + HI per IWG 2006 was most common (35%). Event-free survival was reported in 25%; progression-free survival and relapse-free survival in 13%; and leukemia-free survival in 5%. Early mortality rate was reported in 35% (18% EP, 56% LP) and transplant rate in 58% (50% EP, 67% LP). Only 47% of HR and 90% of LR manuscripts identified HI-eligible patients. In LR-MDS, RBC-TI was reported in 72% of manuscripts but used six definitions. The most common were RBC-TI ≥8 weeks at any time during treatment (24%), ≥8 weeks within 28 weeks of treatment (13%), ≥8 weeks with Hb increase ≥1.0 (4%), ≥12 weeks with Hb increase ≥1.5 (4%), and ≥16 weeks within 24 weeks of treatment (12%). The remainder did not report RBC-TI, did not define it, or used a custom definition not used in another trial. HI was reported in 80% of LR papers with most of those reporting HI using IWG 2006 criteria (90%). Conclusion Reporting of baseline characteristics, response criteria, and outcomes is inconsistent in MDS clinical trials, with wide variability in response definitions, including ORR and TI. This heterogeneity limits interpretability, hampers historical comparisons and may obscure efficacy signals. Our findings highlight the need for standardized reporting guidelines to ensure clarity and consistency in MDS trial publications. As a next phase of this effort, we will conduct a formal Delphi process among icMDS experts to establish consensus recommendations for minimal and optimal MDS clinical trial reporting in manuscripts by disease risk (LR/HR) and trial phase (EP/LP).
Landscape and clinicopathologic features of RAS pathway mutations in chronic myelomonocytic leukemia
Montalban‐Bravo, Guillermo , Loghavi, Sanam , Li, Ziyi , Chien, Kelly S. , Kanagal‐Shamanna, Rashmi , Natu, Anuya , Gurney, Mark E. , Bazinet, Alexandre , Sasaki, Koji , Kadia, Tapan M. , Ravandi, Farhad, Pemmaraju, Naveen , Finke, Christy M. , Al‐Kali, Aref , Gangat, Naseema , Mangaonkar, Abhishek A. , Bueso‐Ramos, Carlos E. , Tefferi, Ayalew, Kantarjian, H., Garcia‐Manero, Guillermo , Patnaik, Mrinal M. , Kantarjian, Hagop M. , Chien, Kelly , Gurney, Mark , Sasaki, Koji , DiNardo, Courtney , Daver, Naval , Short, Nicholas , Pemmaraju, Naveen , Issa, Ghayas , Al-Kali, Aref , Csizmar, Clifford , Gangat, Naseema , Patnaik, Mrinal , Loghavi, Sanam , Kanagal-Shamanna, Rashmi , Kantarjian, Hagop , Bataller, Alex , Hammond, Danielle , Borthakur, Gautam , Swaminathan, Mahesh , DiNardo, Courtney D. , Ravandi, Farhad , Daver, Naval , Short, Nicholas J. , Lasho, Terra L. , Csizmar, Clifford M. , Alkhateeb, Hassan B. , Tefferi, Ayalew

Blood Advances | July 11, 2025 | Volume: 9 | Issue: 19 | Pages: 5105-5117

10.1182/bloodadvances.2025016529 Get It

Abstract RAS pathway (RASp) mutations induce proliferative features, and promote transformation in chronic myelomonocytic leukemia (CMML). However, the unique clonal landscape and hierarchy of distinct RASp mutations remain unexplored. To characterize the landscape, architecture, and implications of unique RASp mutations in CMML, we evaluated a cohort of 814 patients with CMML. We identified 461 RASp mutations among 342 patients (42%). N/KRAS and CBL mutations were the most common, frequently involved the P-loop or RING domains, respectively, and frequently appeared as dominant events (63% and 65%, respectively). BRAF, NF1, and PTPN11 mutations spanned throughout the gene structure, and frequently appeared as subclonal events (75%, 64%, and 59%, respectively). CBL mutations frequently occurred in codominance with SRSF2 and multihit TET2, and were enriched for KIT mutations. PTPN11 mutations more frequently co-occurred with SETBP1 and DNMT3A mutations, and were infrequently codominant with TET2 or ASXL1. RASp mutations predicted for shorter overall survival (hazard ratio [HR], 1.55; 95% confidence interval [CI], 1.15-2.07; P = .0075) and leukemia-free survival (LFS; HR, 1.67; 95% CI, 1.26-2.20; P = .0011), influenced outcomes of myelodysplastic and TET2 mutant CMML, and cooperated with IDH2 and RUNX1 mutations to induce shorter LFS. These data set the bases for refined genomic classifications of CMML, and underscore the need to develop RAS-directed therapies for patients with CMML.
BLAST: A Globally Applicable and Molecularly Versatile Survival Model for Chronic Myelomonocytic Leukemia
Tefferi, Ayalew , Fathima, Saubia , Abdelmagid, Maymona, Alsugair, Ali, Aperna, Fnu, Rezasoltani, Mahsa , Yousuf, Muhammad , Natu, Anuya , Csizmar, Clifford M. , Gurney, Mark E. , Finke, Christy M. , Chien, Kelly S. , Bazinet, Alexandre , Kadia, Tapan M. , Mangaonkar, Abhishek A. , Pardanani, Animesh , Zepeda‐Mendoza, Cinthya , Reichard, Kaaren K. , He, Rong , Sasaki, Koji , Garcia‐Manero, Guillermo , Gangat, Naseema , Montalban‐Bravo, Guillermo , Patnaik, Mrinal M. , Alsugair, Ali Khalid A, Gurney, Mark , Kanagal-Shamanna, Rashmi , Hammond, Danielle , Chien, Kelly , DiNardo, Courtney , Daver, Naval , Zepeda-Mendoza, Cinthya, He, Rong , Loghavi, Sanam , Sasaki, Koji , Larson, Dirk , Onida, Francesco , Gangat, Naseema , Patnaik, Mrinal , Csizmar, Clifford , Fathima, Saubia , Lasho, Terra L. , Kanagal‐Shamanna, Rashmi , Hammond, Danielle , DiNardo, Courtney D. , Daver, Naval , Borthakur, Gautam , Loghavi, Sanam , Passamonti, Francesco , Ravandi, Farhad , Larson, Dirk R.

Blood Journal | May 7, 2025 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.1182/blood.2024027170 Get It

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.
Reducing clinical trial eligibility barriers for patients with MDS: an icMDS position statement
Borate, Uma , Pugh, Kelly , Waller, Allyson, Welkie, Rina Li , Huang, Ying , Stahl, Maximilian , Platzbecker, Uwe , Wei, Andrew H. , Buckstein, Rena , Hasserjian, Robert P. , Fenaux, Pierre , Sallman, David A. , Nimer, Stephen D. , Little, Richard F. , Garcia‐Manero, Guillermo , Odenike, Olatoyosi, Kim, Tae Kon , Greenberg, Peter L. , Xu, Mina L. , Patnaik, Mrinal M. , Padron, Eric , Gore, Steven D. , Churpek, Jane E. , Bennett, John M., Brunner, Andrew M. , Zeidan, Amer M., Zeidan, Amer M. , Platzbecker, Uwe , Sekeres, Mikkael A , Wei, Andrew H , Roboz, Gail J , Loghavi, Sanam , Hasserjian, Robert P , Sallman, David A , Hourigan, Christopher S , Della Porta, Matteo Giovanni , Little, Richard F , Santini, Valeria , Taylor, Justin , Kim, Tae Kon , Halene, Stephanie , Komrokji, Rami S , Griffiths, Elizabeth A. , Greenberg, Peter L , Xie, Zhuoer , Sanz, Guillermo F , Patnaik, Mrinal , Carraway, Hetty E. , Boultwood, Jacqueline , Daver, Naval , Zeidan, Amer M , Churpek, Jane E , Bewersdorf, Jan Philipp , Dezern, Amy Elizabeth , Sekeres, Mikkael A. , Roboz, Gail J. , Savona, Michael R. , Loghavi, Sanam , Hourigan, Christopher S. , Santini, Valeria , Efficace, Fabio , Odenike, Olatoyosi , Komrokji, Rami S. , Xie, Zhuoer , Bejar, Rafael , Sanz, Guillermo , Figueroa, María E. , Abdel‐Wahab, Omar , Starczynowski, Daniel T. , Boultwood, Jacqueline , Daver, Naval , Majeti, Ravindra , List, Alan F. , Brunner, Andrew M., Churpek, Jane

Blood | March 27, 2025 | Volume: 145 | Issue: 13 | Pages: 1369-1381

10.1182/blood.2023023717 Get It

Abstract Excessively restrictive inclusion and exclusion criteria in clinical trials are one of many barriers to clinical trial enrollment for patients with myelodysplastic syndromes/neoplasms (MDSs). Many organizations are developing efforts to increase clinical trial eligibility; yet, several recent publications focused on patients with MDS suggest that many patients with this disease may be excluded from clinical trials unnecessarily. Clinical trial eligibility should reflect the phase of the study and risks of the agent being studied. Phase 3 trials should be less restrictive than early-phase trials to represent the real-world population as closely as possible. We hypothesize that many clinical trials, particularly phase 3 trials, have unnecessarily restrictive eligibility criteria. This study aims to evaluate the most common eligibility criteria according to phase of trial and to determine whether criteria correspond with drug safety signals. We identified MDS clinical trials registered on ClinicalTrials.gov from 1 January 2000 to 1 September 2023 and analyzed the eligibility criteria of 191 therapeutic MDS trials. We found that categorical inclusion and exclusion criteria are remarkably similar in representation across trial phases. Additionally, only 13% of trials are concordant with drug safety signals, suggesting that the eligibility criteria are often arbitrary. On behalf of the icMDS (International Consortium for Myelodysplastic Syndromes), an association of international MDS experts, we provide a position statement on restrictive eligibility criteria for MDS clinical trials that should be avoided with the aim of removing barriers to clinical trial enrollment.
Predictors of Blast Transformation (BT) and Post-BT Survival in Chronic Myelomonocytic Leukemia (CMML)
Kanagal‐Shamanna, Rashmi , Bazinet, Alexandre , Chien, Kelly S. , Finke, Christy M. , Al‐Kali, Aref , Gangat, Naseema , Mangaonkar, Abhishek A. , Tefferi, Ayalew , Garcia‐Manero, Guillermo , Kantarjian, Hagop, Montalban‐Bravo, Guillermo , Patnaik, Mrinal M. , Kanagal-Shamanna, Rashmi , Natu, Anuya , Csizmar, Clifford M. , Lasho, Terra L. , Loghavi, Sanam , Hammond, Danielle , Alkhateeb, Hassan B. , Saliba, Antoine N.

Blood | December 6, 2024 | Volume: 144 | Issue: Supplement 1 | Pages: 4593-4593

10.1182/blood-2024-209236 Get It

Introduction Chronic myelomonocytic leukemia (CMML) is associated with a 15-30% risk for blast transformation (BT) over 3-5 years. Post-BT survival remains dismal with a median overall survival (mOS) of ~6 months (mo), even with intensive therapies. Although genetic drivers are identified in >40% of BT-CMML cases (Carr, 2021), mechanisms of BT remain to be elucidated. This multicenter study examines risk factors for BT in CMML and predictors of post-BT survival. Methods CMML patients at Mayo Clinic (n = 400, 47%) and MD Anderson Cancer Center (n = 449, 53%) were included with IRB approval. Analyses used clinical and molecular data at diagnosis or first referral in chronic phase (CP) and again at BT. Categorical variables were compared by Chi squared and continuous by Mann-Whitney U or Kruskal-Wallis tests. Multivariate analyses used Cox proportional hazards models with binarization via receiver operator curves. Kaplan-Meier analyses were censored at hematopoietic cell transplantation (HCT). P < 0.05 was considered significant. Calculations used BlueSky (v10.3.1) or Prism (v10.2.3). Results Of 849 CMML patients (median age 71 years, 32% female, 90% white) included in the study, 133 (16%) underwent BT. In comparison to CP-CMML without BT, those with BT were more likely (p < 0.05) to have had higher WBC counts (15.1 vs 11.4 x109/L), higher absolute monocyte counts (2.9 vs 2.2 x109/L), lower platelet counts (84 vs 102 x109/L), have circulating immature myeloid cells (52% vs 37%), and be classified as myeloproliferative (MP)-CMML (58% vs 44%) or CMML-2 (33% vs 17%) at diagnosis/first referral in CP. More mutations were detected in BT-CMML than in CP-CMML (mean 3.2 vs 2.8, p = 0.002). Mutations in RAS (NRAS, KRAS, BRAF, CBL, PTPN11; 51% vs 40%, p = 0.02) and signaling (CSF3R, FLT3, JAK2, SH2B3; 15% vs 7%, p = 0.004) pathway genes were more frequent in BT-CMML. Conversely, there were fewer BT-CMML patients with the favorable ASXL1WT/TET2MT genotype compared to CP-CMML (22% vs 33%, p = 0.004). Multivariate analysis identified MP-CMML (hazard ratio [HR] 1.5, p = 0.04), CMML-2 (HR 2.4, p < 0.001), and the presence of ≥4 somatic gene mutations (HR 1.8, p = 0.002) as risk factors for BT whereas the ASXL1WT/TET2MTgenotype was protective (HR 0.45, p = 0.002). The ASXL1WT/TET2MT genotype was also protective in the MP-CMML (HR 0.49, p = 0.04) and RAS-mutated (HR 0.35, p = 0.005) subgroups. Amongst BT-CMML cases, the median time to BT was 10 mo from diagnosis/referral. Compared to their CP assessment, patients in an overlapping Mayo Clinic BT-CMML cohort (n = 156, median age 69 years, 35% female) were more likely to have NPM1 (24% vs 3%, p < 0.001) and IDH2 (14% vs 1%, p = 0.01) mutations at BT. Amongst cases with paired molecular evaluations (n = 44), 7 (16%) acquired new mutations, including FLT3-ITD (n = 2) and NPM1 (n = 2). Conversely, 6 (14%) lost mutations, including TET2 (n = 3), SRSF2 (n = 2), CBL, NRAS, or PTPN11 (n = 1 each). There were no differences in variant allele fractions in driver genes present at CP and BT. Abnormal karyotypes were more prevalent at BT than in CP (60% vs 34%, p < 0.001), and 26 (25%) patients with a normal karyotype in CP acquired structural (65%) and/or numerical (69%) changes at BT, including 6 (23%) that acquired a complex karyotype. Acute myeloid leukemia defining translocations were seen in 4 (4%) cases: 2 with t(8;21) and 1 each with inv(3) and t(10;11)(KMT2A::TET1). After considering mutation and karyotype changes, only bone marrow blasts ≥30% (HR 1.7, p = 0.04) were independently prognostic for OS after BT (mOS 4 mo). Compared to supportive care (n = 50, mOS 1.3 mo), OS was improved by hypomethylating agents (HMA, n = 14, mOS 16 mo, HR 0.3, p < 0.001) or induction chemotherapy (n = 56, mOS 8 mo, HR 0.3, p < 0.001), but not by HMA + venetoclax (n = 11, mOS 6 mo, HR 0.7, p = 0.4). Allogeneic HCT (n = 28) improved mOS to 46 vs 3 mo (p < 0.001). Amongst 4 patients with paired whole genome sequencing before and after BT, 3 had increased copy number alterations (including 2 with loss of heterozygosity, 2 with gains, and 3 with deletions) while the 4th acquired novel likely pathogenic somatic mutations (MUC4, BAX, WNK2). Conclusions Survival in CMML after BT remains exceptionally poor. In this multicenter cohort, MP-CMML, CMML-2, and the presence of ≥4 somatic gene mutations were identified as risk factors for BT, with the ASXL1WT/TET2MT genotype being protective. Following BT, bone marrow blast burden ≥30% was an independent adverse predictor of survival.