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Todisco G, Creignou M, Bernard E, Björklund AC, Moura PL, Tesi B, Mortera-Blanco T, Sander B, Jansson M, Walldin G, Barbosa I, Reinsbach SE, Hofman IJ, Nilsson C, Yoshizato T, Dimitriou M, Chang D, Olafsdottir S, Venckute Larsson S, Tobiasson M, Malcovati L, Woll P, Jacobsen SEW, Papaemmanuil E, Hellström-Lindberg E. Integrated Genomic and Transcriptomic Analysis Improves Disease Classification and Risk Stratification of MDS with Ring Sideroblasts. Clin Cancer Res 2023; 29:4256-4267. [PMID: 37498312 PMCID: PMC10570683 DOI: 10.1158/1078-0432.ccr-23-0538] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 05/12/2023] [Accepted: 07/25/2023] [Indexed: 07/28/2023]
Abstract
PURPOSE Ring sideroblasts (RS) define the low-risk myelodysplastic neoplasm (MDS) subgroup with RS but may also reflect erythroid dysplasia in higher risk myeloid neoplasm. The benign behavior of MDS with RS (MDSRS+) is limited to SF3B1-mutated cases without additional high-risk genetic events, but one third of MDSRS+ carry no SF3B1 mutation, suggesting that different molecular mechanisms may underlie RS formation. We integrated genomic and transcriptomic analyses to evaluate whether transcriptome profiles may improve current risk stratification. EXPERIMENTAL DESIGN We studied a prospective cohort of MDSRS+ patients irrespective of World Health Organization (WHO) class with regard to somatic mutations, copy-number alterations, and bone marrow CD34+ cell transcriptomes to assess whether transcriptome profiles add to prognostication and provide input on disease classification. RESULTS SF3B1, SRSF2, or TP53 multihit mutations were found in 89% of MDSRS+ cases, and each mutation category was associated with distinct clinical outcome, gene expression, and alternative splicing profiles. Unsupervised clustering analysis identified three clusters with distinct hemopoietic stem and progenitor (HSPC) composition, which only partially overlapped with mutation groups. IPSS-M and the transcriptome-defined proportion of megakaryocyte/erythroid progenitors (MEP) independently predicted survival in multivariable analysis. CONCLUSIONS These results provide essential input on the molecular basis of SF3B1-unmutated MDSRS+ and propose HSPC quantification as a prognostic marker in myeloid neoplasms with RS.
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Affiliation(s)
- Gabriele Todisco
- Department of Medicine, Center for Hematology and Regenerative Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Molecular Medicine, University of Pavia, Pavia, Italy
- Unit of Precision Hematology Oncology, IRCCS S. Matteo Hospital Foundation, Pavia, Italy
| | - Maria Creignou
- Department of Medicine, Center for Hematology and Regenerative Medicine, Karolinska Institutet, Stockholm, Sweden
- Phase I Unit, Center for Clinical Cancer Studies, Karolinska University Hospital, Stockholm, Sweden
| | - Elsa Bernard
- Computational Oncology Service, Department of Epidemiology & Biostatistics and Center for Hematologic Malignancies, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Ann-Charlotte Björklund
- Department of Medicine, Center for Hematology and Regenerative Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Pedro Luis Moura
- Department of Medicine, Center for Hematology and Regenerative Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Bianca Tesi
- Department of Medicine, Center for Hematology and Regenerative Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Laboratory, Karolinska University Hospital, Stockholm, Sweden
| | - Teresa Mortera-Blanco
- Department of Medicine, Center for Hematology and Regenerative Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Birgitta Sander
- Division of Pathology, Department of Laboratory Medicine, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden
| | - Monika Jansson
- Department of Medicine, Center for Hematology and Regenerative Medicine, Karolinska Institutet, Stockholm, Sweden
- Medical Unit Hematology, Karolinska University Hospital, Stockholm, Sweden
| | - Gunilla Walldin
- Department of Medicine, Center for Hematology and Regenerative Medicine, Karolinska Institutet, Stockholm, Sweden
- Medical Unit Hematology, Karolinska University Hospital, Stockholm, Sweden
| | - Indira Barbosa
- Department of Medicine, Center for Hematology and Regenerative Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Susanne E. Reinsbach
- Department of Biology and Biological Engineering, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Chalmers University of Technology, Gothenburg, Sweden
| | - Isabel Juliana Hofman
- Department of Medicine, Center for Hematology and Regenerative Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Christer Nilsson
- Department of Medicine, Center for Hematology and Regenerative Medicine, Karolinska Institutet, Stockholm, Sweden
- Medical Unit Hematology, Karolinska University Hospital, Stockholm, Sweden
| | - Tetsuichi Yoshizato
- Department of Medicine, Center for Hematology and Regenerative Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Marios Dimitriou
- Department of Medicine, Center for Hematology and Regenerative Medicine, Karolinska Institutet, Stockholm, Sweden
| | - David Chang
- Department of Medicine, Center for Hematology and Regenerative Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Svannildur Olafsdottir
- Department of Medicine, Center for Hematology and Regenerative Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Sigita Venckute Larsson
- Department of Medicine, Center for Hematology and Regenerative Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Magnus Tobiasson
- Department of Medicine, Center for Hematology and Regenerative Medicine, Karolinska Institutet, Stockholm, Sweden
- Medical Unit Hematology, Karolinska University Hospital, Stockholm, Sweden
| | - Luca Malcovati
- Department of Molecular Medicine, University of Pavia, Pavia, Italy
- Unit of Precision Hematology Oncology, IRCCS S. Matteo Hospital Foundation, Pavia, Italy
| | - Petter Woll
- Department of Medicine, Center for Hematology and Regenerative Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Sten Eirik W. Jacobsen
- Department of Medicine, Center for Hematology and Regenerative Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Cell and Molecular Biology, Karolinska Institutet, Stockholm, Sweden
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, United Kingdom
| | - Elli Papaemmanuil
- Computational Oncology Service, Department of Epidemiology & Biostatistics and Center for Hematologic Malignancies, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Eva Hellström-Lindberg
- Department of Medicine, Center for Hematology and Regenerative Medicine, Karolinska Institutet, Stockholm, Sweden
- Medical Unit Hematology, Karolinska University Hospital, Stockholm, Sweden
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El Hussein S, Loghavi S. The Impact of Clonal Hierarchy and Heterogeneity on Phenotypic Manifestations of Myelodysplastic Neoplasms. Cancers (Basel) 2022; 14:5690. [PMID: 36428782 PMCID: PMC9688198 DOI: 10.3390/cancers14225690] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 10/30/2022] [Accepted: 11/15/2022] [Indexed: 11/22/2022] Open
Abstract
Until recently, conventional prognostication of myelodysplastic neoplasms (MDS) was performed using the revised International Prognostic Scoring System (IPSS-R), with additional adverse prognoses conferred by select mutations. Nonetheless, the clonal diversity and dynamics of coexisting mutations have been shown to alter the prognosis and treatment response in patients with MDS. Often in the process of clonal evolution, various initial hits are preferentially followed by a specific spectrum of secondary alterations, shaping the phenotypic and biologic features of MDS. Our ability to recapitulate the clonal ontology of MDS is a necessary step toward personalized therapy and the conceptualization of a better classification system, which ideally would take into consideration all genomic aberrations and their inferred clonal architecture in individual cases. In this review, we summarize our current understanding of the molecular landscape of MDS and the role of mutational combinations, clonal burden, and clonal hierarchy in defining the clinical fate of the disease.
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Affiliation(s)
- Siba El Hussein
- Department of Pathology, University of Rochester Medical Center, Rochester, NY 14607, USA
| | - Sanam Loghavi
- Department of Hematopathology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
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