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Supplementary Table S2 from Integrated Genomic and Transcriptomic Analysis Improves Disease Classification and Risk Stratification of MDS with Ring Sideroblasts

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posted on 2023-10-13, 07:41 authored by Gabriele Todisco, Maria Creignou, Elsa Bernard, Ann-Charlotte Björklund, Pedro Luis Moura, Bianca Tesi, Teresa Mortera-Blanco, Birgitta Sander, Monika Jansson, Gunilla Walldin, Indira Barbosa, Susanne E. Reinsbach, Isabel Juliana Hofman, Christer Nilsson, Tetsuichi Yoshizato, Marios Dimitriou, David Chang, Svannildur Olafsdottir, Sigita Venckute Larsson, Magnus Tobiasson, Luca Malcovati, Petter Woll, Sten Eirik W. Jacobsen, Elli Papaemmanuil, Eva Hellström-Lindberg

Demographic and clinical features of cases and controls included into the study.

Funding

Cancerfonden (Swedish Cancer Society)

Radiumhemmets Forskningsfonder (Cancer Research Foundations of Radiumhemmet)

Vetenskapsrådet (VR)

Fondazione AIRC per la ricerca sul cancro ETS (AIRC)

Knut och Alice Wallenbergs Stiftelse (Knut and Alice Wallenberg Foundation)

History

ARTICLE ABSTRACT

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. 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. 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. 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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