Gene expression profiling based identifications of potential prognostic molecular markers in decitabine treated acute myeloid leukemia
InstitutionsUKU. Klinik für Innere Medizin III
UKU. Klinik für Innere Medizin II
Introduction: The hypomethylating agent decitabine (DAC) represents a therapeutic option for acute myeloid leukemia (AML) patients who are not eligible for an intensive treatment regime. However, there are no reliable biomarkers available yet that can predict patients who will likely benefit from this epigenetic therapy. Therefore, we executed a gene expression analysis prior to the treatment of patients with DAC in order to evaluate gene expression patterns associated with response to DAC that ultimately might be used to predict DAC outcome. Patients had been entered in a multicenter phase II trial of DAC as first-line treatment of older AML patients judged unfit for induction chemotherapy (NCT00866073). Material and Methods: Specimens: Blood or bone marrow AML samples were collected from elderly patient who had been entered in a multicenter phase II trial of DAC as first-line treatment of older AML patients judged unfit for induction chemotherapy (NCT00866073). Cytogenetic and molecular genetic analyses: Samples were studied centrally by the lab of the AMLSG at the University Hospital of Ulm by conventional cytogenetic analysis and reverse transcriptase polymerase chain reaction (RT-PCR) for the recurring gene fusions resulting from t(8;21)(q22;q22), inv16(p13q22)/t(16;16)(p13;q22), t(15;17)(q22;q12-21), and t(9;11)(p22;q23), and all diagnostic samples were screened for mutations in FLT3 (FMS like tyrosine kinase 3), NPM1 (nucleophosmin), CEBPA (enhancer binding protein alpha) and DNMT3a (DNA methyltranferase). Gene expression profiling: A gene expression profiling analysis in clinically well annotated specimens (n=36) was executed using Affymetrix microarrays (Human Genome U133 Plus 2.0 Arrays; 3`IVT Express Kit) according to the manufacturer’s recommendations (Affymetrix, Santa Clara, CA). Filtering the fluorescence ratios JustRMA algorithm was applied. We investigated significant different gene expression patterns between responders and no responders DAC treatment. qRT-PCR: For Validation of the gene expression profiling results, we performed a quantitative RT-PCR analysis of randomly picked genes using the TaqMan 7900HT. Statistical Analysis: Supervised analyses including gene and pathway class comparison were carried out using BRB-Array Tools Version 4.3.0 Beta_3, and further statistical calculations were performed using SPSS, version 19 and Graph Prad-Prism version 5. Results and conclusion: While the study cohort comprised a heterogeneous group of AML patients, a class comparison analysis nevertheless could reveal a DAC response associated gene pattern comprising 301 genes at a significance level of p<0.05. This signature was enriched for genes belonging to pathways that are essential in immune response and tumor suppressor function such as the Notch pathway. While genes associated with DAC response including: ASCL2, INPP5D, MSI2, SLC24A3, PRAME, TNSFS9, MLL and several homoebox genes might be used as novel biomarkers, along genes that were significantly higher expressed in patients who did not respond to DAC treatment, such as IFI27, IFI44L reflecting an insufficient immune system, several TSG like THBS1, FAS, MX1 or genes involved in the Notch pathway including TRPS1, RBPJ, NOTCH2. The clinical implementation of findings warrants additional studies. In the future integrative analysis also taking epigenetic changes into account might further improve the value of transcriptomic based predictors and lead the way to improved patient management.
Subject HeadingsAkute myeloische Leukämie [GND]
Acute myeloid leukemia [MeSH]
Gene expression [MeSH]