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Detection of Residual Tumor Cells by RT-PCR for Tyrosine Hydroxylase mRNA

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Abstract

Neuroblastoma is the most common extracranial solid tumor of young children. Despite advances in therapy the survival of disseminated neuroblastoma still carries a poor prognosis. Autologous transplantation of stem cells has become a promising treatment in such patients.

An accurate control of transplant is necessary to minimize the risk of tumor cell contamination.

For the detection of tumor cells in bone marrow, peripheral blood, and stem cell preparations, we established reverse transcriptase-polymerase chain reaction (RT-PCR) to amplify tyrosine hydroxylase (TH) mRNA.

Samples from 6 pediatric patients with stage IV neuroblastoma were studied. Urinary vanillyl mandelic acid, homovanillic acid and dopamine levels were analyzed at diagnosis in all cases. Secretion of catecholamines was shown in all patients (one of these with slightly elevated dopamine); TH expression was detectable in tumor tissues and/or bone marrow aspirates. At the time of leukapheresis in all cases no contaminating neuroblastoma cells were found in PBSCs.

The high sensitivity and specificity of the RT-PCR suggest that this method is of considerable clinical value in

  1. 1.

    detecting minimal bone marrow metastasis,

  2. 2.

    monitoring of MRD (minimal residual disease) following chemotherapy to evaluate the efficacy of treatment regimens, and

  3. 3.

    assessing the effectiveness of stem cell purging in the process of autologous stem cell transplantation in neuroblastoma.

The Study was supported by the Vereine Hilfe für Krebskranke Kinder Frankfurt eV

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© 2000 Springer-Verlag Berlin Heidelberg

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Niegemann, E. et al. (2000). Detection of Residual Tumor Cells by RT-PCR for Tyrosine Hydroxylase mRNA. In: Berdel, W.E., et al. Transplantation in Hematology and Oncology. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-59592-9_23

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  • DOI: https://doi.org/10.1007/978-3-642-59592-9_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-64041-4

  • Online ISBN: 978-3-642-59592-9

  • eBook Packages: Springer Book Archive

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