Validation of a mouse xenograft model system for gene expression analysis of human acute lymphoblastic leukaemia.

BACKGROUND: Pre-clinical models that effectively recapitulate human disease are critical for expanding our knowledge of cancer biology and drug resistance mechanisms. For haematological malignancies, the non-obese diabetic/severe combined immunodeficient (NOD/SCID) mouse is one of the most successful models to study paediatric acute lymphoblastic leukaemia (ALL). However, for this model to be effective for studying engraftment and therapy responses at the whole genome level, careful molecular characterisation is essential. RESULTS: Here, we sought to validate species-specific gene expression profiling in the high engraftment continuous ALL NOD/SCID xenograft. Using the human Affymetrix whole transcript platform we analysed transcriptional profiles from engrafted tissues without prior cell separation of mouse cells and found it to return highly reproducible profiles in xenografts from individual mice. The model was further tested with experimental mixtures of human and mouse cells, demonstrating that the presence of mouse cells does not significantly skew expression profiles when xenografts contain 90% or more human cells. In addition, we present a novel in silico and experimental masking approach to identify probes and transcript clusters susceptible to cross-species hybridisation. CONCLUSIONS: We demonstrate species-specific transcriptional profiles can be obtained from xenografts when high levels of engraftment are achieved or with the application of transcript cluster masks. Importantly, this masking approach can be applied and adapted to other xenograft models where human tissue infiltration is lower. This model provides a powerful platform for identifying genes and pathways associated with ALL disease progression and response to therapy in vivo.

Evaluation of automated and conventional microarray hybridization: a question of data quality and best practice?

Microarray is a widely used technique to study gene expression. The increasing interest in the technology has resulted in increased availability of commercial accessory reagents and instrumentation. In principle, commercial advances in reagents, kits and equipment should greatly improve assay performance, since they each bring a measure of quality assurance and uniformity to the data above that which may be obtained from the original manual hybridization processes. However, independent validation of this perceived benefit remains an essential part of the adoption process and, in microarrays, this has often been overlooked for want of immediate convenience. We describe here the comparative evaluation of two automated hybridization instruments, namely the MAUI(R) (microarray user interface) hybridization system and the GeneTAC HybStation, against the conventional manual coverslip hybridization methodology. Our results show that there is a significant advantage in using automated hybridization instrumentation over the diffusion-based coverslip methodology. We observed an enhancement of the mean signal, signal-to-noise ratio, and reproducibility between replicates when using both the MAUI(R) hybridization system and the GeneTAC HybStation. Automation further reduced labour time, offered simplicity and greater reproducibility and accuracy in the results. The present study has independently validated the benefits automation brings to the microarray hybridization process and highlights the differences between the instruments examined. We further comment on the higher quality of spot morphology when hybridization is performed at a lower temperature in combination with our buffer of choice.

Comparison of Alexa Fluor and CyDye for practical DNA microarray use.

Microarrays are a powerful tool for comparison and understanding of gene expression levels in healthy and diseased states. The method relies upon the assumption that signals from microarray features are a reflection of relative gene expression levels of the cell types under investigation. It has previously been reported that the classical fluorescent dyes used for microarray technology, Cy3 and Cy5, are not ideal due to the decreased stability and fluorescence intensity of the Cy5 dye relative to the Cy3, such that dye bias is an accepted phenomena necessitating dye swap experimental protocols and analysis of differential dye affects. The incentive to find new fluorophores is based on alleviating the problem of dye bias through synonymous performance between counterpart dyes. Alexa Fluor 555 and Alexa Fluor 647 are increasingly promoted as replacements for CyDye in microarray experiments. Performance relates to the molecular and steric similarities, which will vary for each new pair of dyes as well as the spectral integrity for the specific application required. Comparative analysis of the performance of these two competitive dye pairs in practical microarray applications is warranted towards this end. The findings of our study showed that both dye pairs were comparable but that conventional CyDye resulted in significantly higher signal intensities (P < 0.05) and signal minus background levels (P < 0.05) with no significant difference in background values (P > 0.05). This translated to greater levels of differential gene expression with CyDye than with the Alexa Fluor counterparts. However, CyDye fluorophores and in particular Cy5, were found to be less photostable over time and following repeated scans in microarray experiments. These results suggest that precautions against potential dye affects will continue to be necessary and that no one dye pair negates this need.

Comparison of commercial probe labeling kits for microarray: towards quality assurance and consistency of reactions.

Microarray technology is readily available to scientists interested in gene expression. Commensurate with this availability is the growing market in accessory products offering convenience but potentially variable performance. Here we evaluate seven commercial kits for probe labeling against a human apoptosis oligonucleotide array. All kits were found to label probes successfully using the manufacturers' instructions. The Stratagene Fairplay Microarray Labeling Kit was the most sensitive, with an overall call rate of 74% and the lowest rate of indeterminant calls for the HEK and HepG2 cell lines. The Invitrogen SuperScript Indirect cDNA Labeling System showed the most reproducible gene expression pattern and the least technical variation, both in terms of signal strength and between replicates on each array. The Promega Pronto! Plus System showed the least dye bias however, a higher level of variation between replicates was observed. Pairwise comparisons revealed that the Promega Pronto! Plus System and Invitrogen SuperScript Indirect cDNA Labeling System had the most similarity in their patterns of gene expression. Results obtained suggest variability in the performance of commercial kits between different manufacturers. This study supports the need to conduct comparative evaluations of commercial microarray probe labeling kits and the need for validation prior to use.