Literature DB >> 15471219

Detection of minimal residual disease in acute leukemia.

V H J van der Velden1, N Boeckx, E R van Wering, J J M van Dongen.   

Abstract

Detection of minimal residual disease (MRD) has prognostic value in acute lymphoblastic leukemia and acute myeloid leukemia. Particularly the evaluation of early treatment response has high prognostic value, because this allows identification of true low-risk and high-risk patients, who may profit from treatment reduction or treatment intensification, respectively. Consequently, monitoring of MRD is now being incorporated in many clinical protocols. Analysis of MRD in acute leukemia is currently mainly performed using flowcytometric immunophenotyping, real-time quantitative (RQ-)PCR analysis of fusion gene transcripts, and RQ-PCR analysis of rearranged immunoglobulin and/or T-cell receptor genes. These three techniques differ in their applicability and sensitivity and it should be noted that MRD results obtained by one method cannot yet easily be compared with MRD results obtained by another method. Also between laboratories applying the same method, significant variations in MRD results can be present. Consequently, multicenter clinical studies with MRD-based treatment intervention need standardization of MRD techniques and quality control of MRD results.

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Year:  2004        PMID: 15471219

Source DB:  PubMed          Journal:  J Biol Regul Homeost Agents        ISSN: 0393-974X            Impact factor:   1.711


  3 in total

1.  Flow minimal residual disease monitoring of candidate leukemic stem cells defined by the immunophenotype, CD34+CD38lowCD19+ in B-lineage childhood acute lymphoblastic leukemia.

Authors:  Kerrie Wilson; Marian Case; Lynne Minto; Simon Bailey; Nick Bown; Jenny Jesson; Sarah Lawson; Josef Vormoor; Julie Irving
Journal:  Haematologica       Date:  2009-11-30       Impact factor: 9.941

2.  Establishment and validation of a standard protocol for the detection of minimal residual disease in B lineage childhood acute lymphoblastic leukemia by flow cytometry in a multi-center setting.

Authors:  Julie Irving; Jenny Jesson; Paul Virgo; Marian Case; Lynne Minto; Lisa Eyre; Nigel Noel; Ulrika Johansson; Marion Macey; Linda Knotts; Margaret Helliwell; Paul Davies; Liam Whitby; David Barnett; Jeremy Hancock; Nick Goulden; Sarah Lawson
Journal:  Haematologica       Date:  2009-04-18       Impact factor: 9.941

3.  Automated analysis of acute myeloid leukemia minimal residual disease using a support vector machine.

Authors:  Wanmao Ni; Beili Hu; Cuiping Zheng; Yin Tong; Lei Wang; Qing-Qing Li; Xiangmin Tong; Yong Han
Journal:  Oncotarget       Date:  2016-11-01
  3 in total

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