Literature DB >> 12835720

DNA microarrays for comparison of gene expression profiles between diagnosis and relapse in precursor-B acute lymphoblastic leukemia: choice of technique and purification influence the identification of potential diagnostic markers.

F J T Staal1, M van der Burg, L F A Wessels, B H Barendregt, M R M Baert, C M M van den Burg, C van Huffel, A W Langerak, V H J van der Velden, M J T Reinders, J J M van Dongen.   

Abstract

Microarrays for gene expression profiling are rapidly becoming important research tools for the identification of novel markers, for example, for novel classification of leukemias and lymphomas. Here, we review the considerations and infrastructure for microarray experiments. These considerations are illustrated via a microarray-based comparison of gene expression profiles of paired diagnosis-relapse samples from patients with precursor-B acute lymphoblastic leukemia (ALL), who relapsed during therapy or after completion of treatment. Initial experiments showed that several seemingly differentially expressed genes were actually derived from contaminating non-leukemic cells, particularly myeloid cells and T-lymphocytes. Therefore, we purified the ALL cells of the diagnosis and relapse samples if their frequency was lower than 95%. Furthermore, we observed in earlier studies that extra RNA amplification leads to skewing of particular gene transcripts. Sufficient (non-amplified) RNA of purified and paired diagnosis-relapse samples was obtained from only seven cases. The gene expression profiles were evaluated with Affymetrix U95A chips containing 12 600 human genes. These diagnosis-relapse comparisons revealed only a small number of genes (n=6) that differed significantly in expression: mostly signaling molecules and transcription factors involved in cell proliferation and cell survival were highly upregulated at relapse, but we did not observe any increase in drug-resistance markers. This finding fits with the observation that tumors with a high proliferation index have a poor prognosis. The genes that changed between diagnosis and relapse are currently not in use as diagnostic or disease progression markers, but represent potential new markers for such applications. Leukemia (2003) 17, 1324-1332. doi:10.1038/sj.leu.2402974

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Year:  2003        PMID: 12835720     DOI: 10.1038/sj.leu.2402974

Source DB:  PubMed          Journal:  Leukemia        ISSN: 0887-6924            Impact factor:   11.528


  14 in total

1.  Integrated genomic analysis of relapsed childhood acute lymphoblastic leukemia reveals therapeutic strategies.

Authors:  Laura E Hogan; Julia A Meyer; Jun Yang; Jinhua Wang; Nicholas Wong; Wenjian Yang; Gregory Condos; Stephen P Hunger; Elizabeth Raetz; Richard Saffery; Mary V Relling; Deepa Bhojwani; Debra J Morrison; William L Carroll
Journal:  Blood       Date:  2011-09-14       Impact factor: 22.113

2.  Genome-wide expression profiling of human blood reveals biomarkers for Huntington's disease.

Authors:  F Borovecki; L Lovrecic; J Zhou; H Jeong; F Then; H D Rosas; S M Hersch; P Hogarth; B Bouzou; R V Jensen; D Krainc
Journal:  Proc Natl Acad Sci U S A       Date:  2005-07-25       Impact factor: 11.205

3.  S100A8 inhibition in leukemic lymphoblasts induces sensitivity to chemotherapy and inhibition of disease relapse.

Authors:  Mohamad Javad Hejazi; Gholamhossein Tamaddon; Narges Kohan; Mohammadreza Sharifi
Journal:  Med Oncol       Date:  2022-06-08       Impact factor: 3.064

Review 4.  Gene expression profiling in childhood acute leukemia: progress and perspectives.

Authors:  Yasuhide Hayashi
Journal:  Int J Hematol       Date:  2003-12       Impact factor: 2.490

Review 5.  The biology of relapsed acute lymphoblastic leukemia: opportunities for therapeutic interventions.

Authors:  Teena Bhatla; Courtney L Jones; Julia A Meyer; Nicholas A Vitanza; Elizabeth A Raetz; William L Carroll
Journal:  J Pediatr Hematol Oncol       Date:  2014-08       Impact factor: 1.289

Review 6.  Childhood Acute Leukemias in Developing Nations: Successes and Challenges.

Authors:  Marta Zapata-Tarrés; Juan Carlos Balandrán; Roberto Rivera-Luna; Rosana Pelayo
Journal:  Curr Oncol Rep       Date:  2021-03-23       Impact factor: 5.075

7.  Translational database selection and multiplexed sequence capture for up front filtering of reliable breast cancer biomarker candidates.

Authors:  Patrik L Ståhl; Magnus K Bjursell; Hovsep Mahdessian; Sophia Hober; Karin Jirström; Joakim Lundeberg
Journal:  PLoS One       Date:  2011-06-15       Impact factor: 3.240

8.  Gene expression profiles associated with pediatric relapsed AML.

Authors:  Costa Bachas; Gerrit Jan Schuurhuis; C Michel Zwaan; Marry M van den Heuvel-Eibrink; Monique L den Boer; Eveline S J M de Bont; Zinia J Kwidama; Dirk Reinhardt; Ursula Creutzig; Valérie de Haas; Gertjan J L Kaspers; Jacqueline Cloos
Journal:  PLoS One       Date:  2015-04-07       Impact factor: 3.240

9.  Dysregulated signaling, proliferation and apoptosis impact on the pathogenesis of TCRγδ+ T cell large granular lymphocyte leukemia.

Authors:  Martine J Kallemeijn; Dick de Ridder; Joyce Schilperoord-Vermeulen; Michèle Y van der Klift; Yorick Sandberg; Jacques J M van Dongen; Anton W Langerak
Journal:  PLoS One       Date:  2017-04-13       Impact factor: 3.240

10.  Pathway correlation profile of gene-gene co-expression for identifying pathway perturbation.

Authors:  Allison N Tegge; Charles W Caldwell; Dong Xu
Journal:  PLoS One       Date:  2012-12-20       Impact factor: 3.240

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