Next-generation sequencing with a 54-gene panel identified unique mutational profile and prognostic markers in Chinese patients with myelofibrosis View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-12-04

AUTHORS

Harinder Gill, Ho-Wan Ip, Rita Yim, Wing-Fai Tang, Herbert H. Pang, Paul Lee, Garret M. K. Leung, Jamilla Li, Karen Tang, Jason C. C. So, Rock Y. Y. Leung, Jun Li, Gianni Panagioutou, Clarence C. K. Lam, Yok-Lam Kwong

ABSTRACT

Current prognostication in myelofibrosis (MF) is based on clinicopathological features and mutations in a limited number of driver genes. The impact of other genetic mutations remains unclear. We evaluated for mutations in a myeloid panel of 54 genes using next-generation sequencing. Multivariate Cox regression analysis was used to determine prognostic factors for overall survival (OS) and leukaemia-free survival (LFS), based on mutations of these genes and relevant clinical and haematological features. One hundred and one patients (primary MF, N = 70; secondary MF, N = 31) with a median follow-up of 49 (1–256) months were studied. For the entire cohort, inferior OS was associated with male gender (P = 0.04), age > 65 years (P = 0.04), haemoglobin < 10 g/dL (P = 0.001), CUX1 mutation (P = 0.003) and TP53 mutation (P = 0.049); and inferior LFS was associated with male gender (P = 0.03), haemoglobin < 10 g/dL (P = 0.04) and SRSF2 mutations (P = 0.008). In primary MF, inferior OS was associated with male gender (P = 0.03), haemoglobin < 10 g/dL (P = 0.002), platelet count < 100 × 109/L (P = 0.02), TET2 mutation (P = 0.01) and CUX1 mutation (P = 0.01); and inferior LFS was associated with haemoglobin < 10 g/dL (P = 0.02), platelet count < 100 × 109/L (P = 0.02), TET2 mutations (P = 0.01) and CUX1 mutations (P = 0.04). These results showed that clinical and haematological features and genetic mutations should be considered in MF prognostication. More... »

PAGES

869-879

References to SciGraph publications

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s00277-018-3563-7

    DOI

    http://dx.doi.org/10.1007/s00277-018-3563-7

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1110371899

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/30515541


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