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ctt-journal > Gorbunova et al. (Abstract)

Gorbunova et al. (Abstract)

Cellular Therapy and Transplantation (CTT), Vol. 3, No. 12
doi: 10.3205/ctt-2011-No12-abstract51

© The Authors. This abstract is provided under the following license: Creative Commons Attribution 3.0 Unported

Abstract accepted for "5th Raisa Gorbacheva Memorial Meeting Hematopoietic Stem Cell Transplantation in Children and Adults", Saint Petersburg, Russia, September 18–20, 2011

Preliminary Program

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Meta-analysis of gene expression in acute myeloid leukemia

Anna V. Gorbunova, Nikolay N. Mamaev

R.M. Gorbacheva Memorial Institute of Children Hematology and Transplantation, St. Petersburg Pavlov State Medical University, St. Petersburg, Russia

Correspondence: Anna V. Gorbunova, R.M. Gorbacheva Memorial Institute of Children Hematology and Transplantation, St. Petersburg Pavlov State Medical University, 6/8, Tolstoy str., St. Petersburg, 197022, Russia, E-mail: gorbunova@spam is badnm.ru


Aim: The aim of this study was to identify potential therapeutic targets and prognostic markers for AML through meta-analysis of public microarray data.

Methods: To identify genes differentially expressed in AML, microarray data from 5372 human samples representing expression of 23000 genes in 369 different cell and tissue types, disease states and cell lines selected from experiments stored in the public microarray repository (ArrayExpress www.ebi.ac.uk/arrayexpress and GEO www.ncbi.nlm.nih.gov/gds) were analyzed with ANOVA-based approaches using the Bioconductor package limma with a bootstrapping procedure in the software package R (http://www.R-project.org).

Results: We identified 7072 up-regulated and 9510 down-regulated genes (p<0.05) in the AML samples, when compared with different normal and disease-specific cell and tissue types. Many of these genes are known to be implicated in leukemia. FLT3 and ATP8B4 are the most specifically overexpressed genes. In the top 20 up-regulated genes there are several oncogenes (ETV6, FES, RUNX1, MYB), cycline-dependent kinase CDK6, apoptosis inhibitor MDM4, and transcription factor TLE4. Since expression of these genes was generally low in normal tissues, they have the characteristics of potential candidates for molecular targeted therapy in AML and as potential biomarkers for disease prognosis and monitoring. Meta-analysis also revealed the down-regulation of genes from the same biological pathway: the respiratory electron transport pathway (11 of the top 20 down-regulated genes). The results indicate that hypoxia is a fundamentally important characteristic of AML cells and this could allow development of new therapeutic approaches for the selective action on leukemic cells.

Conclusions: Large amounts of gene expression data obtained from public repositories allows the comparison of gene expression patterns in a wide range of normal tissue types and can help to refine the identification of candidate genes for molecular targeted therapy and biomarkers for AML.

Keywords: acute myeloid leukemia, biomarker, targeted therapy, gene expression, microarray, meta-analysis