Genomic characterization and prognostication applied to a Brazilian cohort of patients with myelofibrosis.

Autor: Nonino A; Secretaria de Saude do Distrito Federal, Brasilia, Brazil. nonino@cettro.com.br.; Cettro - Centro de Cancer de Brasilia, Brasilia, Brazil. nonino@cettro.com.br., Campregher PV; Hospital Israelita Albert Einstein, São Paulo, Brazil., de Souza Santos FP; Hospital Israelita Albert Einstein, São Paulo, Brazil., Mazzeu JF; Faculdade de Medicina da Universidade de Brasilia, Brasilia, Brazil., Pereira RW; Escola de Saude e Medicina da Universidade Catolica de Brasilia, Brasilia, Brazil.
Jazyk: angličtina
Zdroj: International journal of hematology [Int J Hematol] 2020 Sep; Vol. 112 (3), pp. 361-368. Date of Electronic Publication: 2020 Jun 13.
DOI: 10.1007/s12185-020-02906-w
Abstrakt: Genomic characterization of patients with myeloproliferative neoplasms (MPN) may lead to better diagnostic classification, prognostic assessment, and treatment decisions. These goals are particularly important in myelofibrosis (MF). We performed target Next Generation Sequencing for a panel of 255 genes and Chromosome Microarray Analysis (CMA) in 27 patients with MF. Patients were classified according to genomic findings and we compared the performance of a personalized prognostication system with IPSS, MIPSS70 and MIPSS70 + v2. Twenty-six patients presented mutations: 11.1% had single driver mutations in either JAK2, CALR or MPL; 85.2% had mutations in non-restricted genes (median: 2 per patient). CMA was abnormal in 91.7% of the 24 cases with available data. Copy-Number-Neutral Loss-of-Heterozygosity was the most common finding (66.7%). Del13q was the most frequent copy number variation, and we could define a 2.4 Mb minimally affected region encompassing RB1, SUCLA2 and CLLS2 loci. The largest genomic subgroup consisted of patients with mutations in genes involved with chromatin organization and splicing control (40.7%) and the personalized system showed better concordance and accuracy than the other prognostic systems. Comprehensive genomic characterization reveals the striking genetic complexity of MF and, when combined with clinical data, led, in our cohort, to better prognostication performance.
Databáze: MEDLINE
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