Literature DB >> 21362264

[Research progress on mechanism of MDS transformation into AML].

Lin-Lin Wang1, Chong Gao, Bao-An Chen.   

Abstract

Myelodysplastic syndrome (MDS) is a clonal hematopoietic stem cell disorder characterized by ineffective hematopoiesis and a risk of transformation into acute leukemia. Approximately 30% of patients with MDS will progress and develop into acute myeloid leukemia (AML), especially in the patients with high-risk MDS, which can be named as secondary acute myeloid leukemia (sAML or MDS/AML). Generally, chemotherapy for sAML hardly has any efficacy. The only way to cure the patients with sAML is allogeneic hematopoietic stem cell transplantation, but unfortunately, only few patients are appropriate for transplantation. So it is important to study the mechanisms of progression of MDS to AML and to explore the potent drug for clinical use. This review summarizes the mechanism of MDS transformation into AML from chromosomal abnormality, aberrant DNA methylation and gene mutation, such as AML1/RUNX1 mutations, FLT3 mutations and PI-PLCβ1 mono-allelic deletion.

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Mesh:

Year:  2011        PMID: 21362264

Source DB:  PubMed          Journal:  Zhongguo Shi Yan Xue Ye Xue Za Zhi        ISSN: 1009-2137


  4 in total

1.  Association between RAD51 gene polymorphism (-135G/C) and susceptibility of myelodysplastic syndrome and acute leukemia: evidence based on a meta-analysis.

Authors:  Ya-zhou He; Xin Hu; Xiao-sa Chi; Yuan-chuan Zhang; Xiang-Bing Deng; Ming-tian Wei; Zi-qiang Wang; Yan-hong Zhou
Journal:  Tumour Biol       Date:  2013-08-17

Review 2.  Therapeutic applications of mesenchymal stroma cells in pediatric diseases: current aspects and future perspectives.

Authors:  Hamid S Habib; Taher F Halawa; Hazem M Atta
Journal:  Med Sci Monit       Date:  2011-11

3.  Community-acquired infections and their association with myeloid malignancies.

Authors:  Glen J Titmarsh; Mary Frances McMullin; Charlene M McShane; Mike Clarke; Eric A Engels; Lesley A Anderson
Journal:  Cancer Epidemiol       Date:  2013-11-22       Impact factor: 2.984

4.  Applications of Bayesian network models in predicting types of hematological malignancies.

Authors:  Rupesh Agrahari; Amir Foroushani; T Roderick Docking; Linda Chang; Gerben Duns; Monika Hudoba; Aly Karsan; Habil Zare
Journal:  Sci Rep       Date:  2018-05-03       Impact factor: 4.379

  4 in total

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