Nature MedicineGenomicsPeer-reviewed journal article
Implications of TP53 Allelic State for Genome Stability, Clinical Presentation and Outcomes in Myelodysplastic Syndromes
Elsa BernardiD, Yasuhito NannyaiD, Robert Paul HasserjianiD, Sean M. DevliniD, Heinz TuechleriD, Juan Santiago Medina-MartineziD, Tetsuichi YoshizatoiD, Yusuke Shiozawa, Ryunosuke SaikiiD, Luca MalcovatiiD, Max Fine LevineiD, Juan E. Arango, Yangyu Zhou, Francesc Gessé SoléiD, Catherine A. CargoiD, Detlef Thomas Haase, Maria CreignouiD, Ulrich GermingiD, Yanming ZhangiD, Gunes GundemiD, Araxe Sarian, Arjan A. van de LoosdrechtiD, Martin JädersteniD, Magnus TobiassoniD, Olivier KosmideriD, , Elli PapaemmanuiliD
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Abstract
TP53 mutations are associated with poor clinical outcomes and treatment resistance in myelodysplastic syndromes. However, the biological and clinical relevance of the underlying mono- or bi-allelic state of the mutations is unclear. We analyzed 3,324 MDS patients for TP53 mutations and allelic imbalances of the TP53 locus and found that 1 in 3 TP53-mutated patients had mono-allelic targeting of the gene whereas 2 in 3 had multiple hits consistent with bi-allelic targeting. The established associations for TP53 with complex karyotype, high-risk presentation, poor survival and rapid leukemic transformation were specific to patients with multi-hit state only. TP53 multi-hit state predicted risk of death and leukemic transformation independently of the Revised International Prognostic Scoring System, while mono-allelic patients did not differ from TP53 wild-type patients. The separation by allelic state was retained in therapy-related MDS. Findings were validated in a cohort of 1,120 patients. Ascertainment of TP53 allelic state is critical for diagnosis, risk estimation and prognostication precision in MDS, and future correlative studies of treatment response should consider TP53 allelic state.
- organism: human
- assay: DNA methylation
- assay: whole-genome sequencing
- research focus: variant calling
- research focus: protein structure prediction
- approach: statistical model
- approach: benchmark study
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