| Literature DB >> 28255022 |
Cassandra M Hirsch1,2, Bartlomiej P Przychodzen1, Tomas Radivoyevitch3, Bhumika Patel4, Swapna Thota4, Michael J Clemente1, Yasunobu Nagata1, Thomas LaFramboise2, Hetty E Carraway4, Aziz Nazha4, Mikkael A Sekeres4, Hideki Makishima1,5, Jaroslaw P Maciejewski6,4.
Abstract
Myelodysplastic syndromes are typically diseases of older adults. Patients in whom the onset is early may have distinct molecular and clinical features or reflect a demographic continuum. The identification of differences between "early onset" patients and those diagnosed at a traditional age has the potential to advance understanding of the pathogenesis of myelodysplasia and may lead to formation of distinct morphological subcategories. We studied a cohort of 634 patients with various subcategories of myelodysplastic syndrome and secondary acute myeloid leukemia, stratifying them based on age at presentation and clinical parameters. We then characterized molecular abnormalities detected by next-generation deep sequencing of 60 genes that are commonly mutated in myeloid malignancies. The number of mutations increased linearly with age and on average, patients >50 years of age had more mutations. TET2, SRSF2, and DNMT3A were more commonly mutated in patients >50 years old compared to patients ≤50 years old. In general, patients >50 years of age also had more mutations in spliceosomal, epigenetic modifier, and RAS gene families. Although there are age-related differences in molecular features among patients with myelodysplasia, most notably in the incidence of SRSF2 mutations, our results suggest that patients ≤50 years old belong to a disease continuum with a distinct pattern of early onset ancestral events. Copyright© Ferrata Storti Foundation.Entities:
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Year: 2017 PMID: 28255022 PMCID: PMC5451334 DOI: 10.3324/haematol.2016.159772
Source DB: PubMed Journal: Haematologica ISSN: 0390-6078 Impact factor: 9.941
Figure 1.Clinical features and demographics of patients with “early onset” myelodysplastic syndrome. (A) Distribution of Cleveland Clinic MDS patients by age and sex-related trends. (B) Distribution of age and sex in MDS SEER patients. (C) Mutational frequencies in patients ≤50, 51–79, and ≥80 years old detected by targeted deep sequencing and whole exome sequencing. (D) Average number of mutations in each MDS subtype in MDS patients ≤50 and >50 years old. (E) Age-related increase in number of mutations.
Figure 2.Typical somatic defects in myelodysplastic syndrome patients ≤50 and >50 years old. (A) Frequencies of somatic mutations in the most recurrently mutated genes in patients ≤50 and >50 years of age. (B) Frequencies of cytogenetic abnormalities in patients ≤ 50 and >50 years of age. (C) Percentages of somatic mutations according to age in selected genes. P-values correspond to the linear slope of mutation rates vs. age found using Poisson regression. Only the genes found to be significant are shown here. Epigenetic modifier genes include DNMT3A, EZH2, KDM6A, IDH1/2, and TET2. Spliceosomal gene mutations include SRSF2, SF3B1, LUC7L2, U2AF1, ZRSRS, PRPF8, and DDX41. (D) TET2 mutational frequency per age group in MDS as predicted by SEER data and actual TET2 mutation frequency in the Cleveland Clinic cohort. (E) Frequency of TET2 mutations in healthy individuals and MDS patients by age.
Figure 3.Molecular characteristics of patients with myelodysplastic syndrome. (A) Comparison of variant allele frequencies across patients ≤50 vs. >50 years old. (B) Distribution of dominant mutations in patients ≤50 vs. >50 years old. (C) Distribution of all mutations in patients ≤50 vs. >50 years old.