Multimodal and Data-Driven Assessment of Myeloid Neoplasms Refines Classification across Disease States
Year: 2025
Type: article
Study design: Observational Study
Abstract: The World Health Organization fifth edition and International Consensus Classification for myeloid neoplasms both incorporate empirical numerical thresholds to morphologic and molecular features defining certain disease entities. However, the clinical implications of these thresholds remain unclear. We analyzed a large cohort (N = 6,976) of patients with myeloid neoplasms to evaluate the impact of proposed yet different numerical thresholds for variant allele frequency of genetic mutations or hematologic parameters set forth by the World Health Organization fifth edition and International Consensus Classification for classification of SF3B1-mutated myelodysplastic neoplasms, NPM1-mutated acute myeloid leukemia (AML), and oligomonocytic chronic myelomonocytic leukemia. Our analysis demonstrated that the clonal burden of SF3B1 mutation in myelodysplastic neoplasms informs classification and prognosis. Our findings support the notion that NPM1 mutation should be AML-defining regardless of blast percentage and highlight the adverse prognostic impact of the cumulative number of myelodysplasia-related mutations in NPM1-mutated AML. Finally, we provide evidence that integrating specific molecular signatures could improve the accuracy of oligomonocytic chronic myelomonocytic leukemia classification. SIGNIFICANCE: Using comprehensive clinical and molecular profiling, this study provides a data-driven approach for evaluating numerical thresholds of variant allele frequency or hematologic parameters (i.e., blast percentage and absolute monocyte count) included in current classification schemas across a spectrum of myeloid malignancies, enabling refinement of disease classification and prognostication.
Source: Blood Cancer Discovery
Authors: Curtis A. Lachowiez, Georgios Asimomitis, Elsa Bernard, Sean M. Devlin, Yanis Tazi, Maria Creignou, Ulrich Germing, Norbert Gattermann, Amanda Gilkes, Ian Thomas, Lars Bullinger, Konstanze Döhner, Luca Malcovati, Jad Othman, Richard Dillon, Ann-Kathrin Eisfeld, Deedra Nicolet, Ghayas C. Issa, Naval Daver, Tapan M. Kadia, Courtney D. DiNardo, Farhad Ravandi, Guillermo Garcia-Manero, Guillermo Montalban-Bravo, Nigel Russell, Mario Cazzola, Hartmut Döhner, Brian J.P. Huntly, Robert P. Hasserjian, Eva Hellström-Lindberg, Elli Papaemmanuil, Sanam Loghavi
Institutions: Oregon Health & Science University, OHSU Knight Cancer Institute, Memorial Sloan Kettering Cancer Center, Institut Gustave Roussy, Cornell University, Weill Cornell Medicine, Karolinska University Hospital, Karolinska Institutet, Düsseldorf University Hospital, Heinrich Heine University Düsseldorf, Cardiff University, Humboldt-Universität zu Berlin, Freie Universität Berlin, Charité – Universitätsmedizin Berlin, Universität Ulm, University Hospital Ulm, University of Pavia, Policlinico San Matteo Fondazione, The University of Sydney, King's College London, Guy's and St Thomas' NHS Foundation Trust, The Ohio State University Comprehensive Cancer Center – Arthur G. James Cancer Hospital and Richard J. Solove Research Institute, The Ohio State University, The University of Texas MD Anderson Cancer Center, University of Nottingham, Wellcome/MRC Cambridge Stem Cell Institute, University of Cambridge, Massachusetts General Hospital
Language: English
Subfield: Hematology
Field: Medicine
Domain: Health Sciences
Open Access status: green
Awards: G1320931994, Understanding Treatment Response Patterns And Therapy Resistance In IDH-Mutant AML, Cancer Center Support Grant, The role of inflammation in the regulation of immune response in acute myeloid leukemia, Institutional Career Development Core, Towards an inclusive genomic risk classification for acute myeloid leukemia (AML)
OpenAlex ID: W4411994987