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Genetic predisposition to MDS: clinical features and clonal evolution

Kennedy, Alyssa L., Shimamura, Akiko·2019·Blood
DOI 10.1182/blood-2018-10-844662
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Abstract

Myelodysplastic syndrome (MDS) typically presents in older adults with the acquisition of age-related somatic mutations, whereas MDS presenting in children and younger adults is more frequently associated with germline genetic predisposition. Germline predisposition is increasingly recognized in MDS presenting at older ages as well. Although each individual genetic disorder is rare, as a group, the genetic MDS disorders account for a significant subset of MDS in children and young adults. Because many patients lack overt syndromic features, genetic testing plays an important role in the diagnostic evaluation. This review provides an overview of syndromes associated with genetic predisposition to MDS, discusses implications for clinical evaluation and management, and explores scientific insights gleaned from the study of MDS predisposition syndromes. The effects of germline genetic context on the selective pressures driving somatic clonal evolution are explored. Elucidation of the molecular and genetic pathways driving clonal evolution may inform surveillance and risk stratification, and may lead to the development of novel therapeutic strategies.

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Cited by

See all 133

Metadata

Authors
Kennedy, A. L., & Shimamura, A.
Affiliations
Dana Farber/Boston Children’s Cancer and Blood Disorders Center, Harvard Medical School, Boston, MA
ORCID
Venue
Blood
Publisher
American Society of Hematology
Published
2019-03-07
Volume
133
Issue
10
Pages
1071-1085
ISSN
  • 0006-4971
  • 1528-0020
DOI
10.1182/blood-2018-10-844662
Cited by
133
References
9
Language
en

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This page
CoChat. (2026). Citation check: Genetic predisposition to MDS: clinical features and clonal evolution. https://app.cochat.ai/papers/10.1182/blood-2018-10-844662
The paper
Kennedy, A. L., & Shimamura, A. (2019). Genetic predisposition to MDS: clinical features and clonal evolution. Blood. https://doi.org/10.1182/blood-2018-10-844662

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.