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Exploration of the role of gene mutations in myelodysplastic syndromes through a sequencing design involving a small number of target genes

Novel sequencing designs are necessary to supplement the recognized knowledge of myelodysplastic syndrome (MDS)-related genomic alterations. In this study, we sequenced 28 target genes in 320 Chinese MDS patients but obtained 77.2% of recall factors and 82.8% of genetic abnormalities (including kary...

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Detalles Bibliográficos
Autores principales: Xu, Feng, Wu, Ling-Yun, He, Qi, Wu, Dong, Zhang, Zheng, Song, Lu-Xi, Zhao, You-Shan, Su, Ji-Ying, Zhou, Li-Yu, Guo, Juan, Chang, Chun-Kang, Li, Xiao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5318910/
https://www.ncbi.nlm.nih.gov/pubmed/28220884
http://dx.doi.org/10.1038/srep43113
Descripción
Sumario:Novel sequencing designs are necessary to supplement the recognized knowledge of myelodysplastic syndrome (MDS)-related genomic alterations. In this study, we sequenced 28 target genes in 320 Chinese MDS patients but obtained 77.2% of recall factors and 82.8% of genetic abnormalities (including karyotype abnormalities). In addition to known relationships among mutations, some specific chromosomal abnormalities were found to link to specific gene mutations. Trisomy 8 tended to be linked to U2AF1 and ZRSR2 mutations, and 20q- exhibited higher SRSF2/WT1 and U2AF1 mutation frequency. Chromosome 7 involvement accounted for up to 50% of RUNX1 mutations and 37.5% of SETBP1 mutations. Patients carrying a complex karyotype were prone to present TP53 mutations (36.1%). However, individuals with normal karyotypes rarely possessed mutations in the TP53, RUNX1 and U2AF1. Moreover, DNMT3A, TP53, SRSF2, STAG2, ROBO1/2 and WT1 predicted poor survival and high AML transformation. By integrating these predictors into international prognostic scoring system (IPSS) or revised IPSS, we built a set of mutation-based prognostic risk models. These models could layer different degrees of risk in patients more satisfactorily. In summary, this sequencing design was able to detect a number of gene mutations and could be used to stratify patients with varied prognostic risk.