Available ribonucleic acid (RNA) amplification methods are extensively tested for reproducibility, but only a few studies additionally deal with potential amplification bias. On targeted arrays, we evaluated three amplification protocols, which are less time consuming than the commonly used T7-RNA polymerase based in vitro transcription protocols and therefore may be more suitable for clinical use: Template-switching polymerase chain reaction (PCR), Ribo-single primer isothermal amplification and a random primer-based PCR. Additionally, a more sensitive labelling method, Dendrimer labelling, was evaluated. All methods were compared to unamplified RNA labelled at reverse transcription. From our results, we conclude that RNA amplification with template-switching PCR is highly reproducible and results in a reliable representation of the starting RNA population. We then assessed whether RNA amplification of clinical breast and thyroid cancer samples with template-switching PCR showed robust performance when altered cycle numbers or partially degraded RNA were used. Template-switching PCR proved to be a very reliable method for global RNA amplification, even when starting from partially degraded RNA down to a RNA Integrity Number of 4.3. In conclusion, template-switching PCR amplification promises to help micro-array expression profiling of limited amounts of human samples on its way to a clinical routine.
"A major concern is the amplification method and how it affects the ability to maintain the relative amount of the starting RNA, the so called fidelity of amplification . This was evaluated by comparing the expression of eight genes, which included the three endogenous control genes (PPIA, TBP and GAPDH), three transcription factors involved in the late B-cell lymphopoiesis (XBP1, IRF4 and PRDM1), and two genes related to oncogenesis of MM (MGST1 and WHSC1) in six amplified and non-amplified CCLs [see Additional file 4]. "
[Show abstract][Hide abstract] ABSTRACT: This report describes a method for the generation of global gene expression profiles from low frequent B-cell subsets by using fluorescence-activated cell sorting and RNA amplification. However, some of the differentiating compartments involve a low number of cells and therefore it is important to optimize and validate each step in the procedure.
Normal lymphoid tissues from blood, tonsils, thymus and bone marrow were immunophenotyped by the 8-colour Euroflow panel using multiparametric flow cytometry. Subsets of B-cells containing cell numbers ranging from 800 to 33,000 and with frequencies varying between 0.1 and 10 percent were sorted, subjected to mRNA purification, amplified by the NuGEN protocol and finally analysed by the Affymetrix platform.
Following a step by step strategy, each step in the workflow was validated and the sorting/storage conditions optimized as described in this report. First, an analysis of four cancer cell lines on Affymetrix arrays, using either 100 ng RNA labelled with the Ambion standard protocol or 1 ng RNA amplified and labelled by the NuGEN protocol, revealed a significant correlation of gene expressions (r >= 0.9 for all). Comparison of qPCR data in samples with or without amplification for 8 genes showed that a relative difference between six cell lines was preserved (r >= 0.9). Second, a comparison of cells sorted into PrepProtect, RNAlater or directly into lysis/binding buffer showed a higher yield of purified mRNA following storage in lysis/binding buffer (p < 0.001). Third, the identity of the B-cell subsets validated by the cluster of differentiation (CD) membrane profile was highly concordant with the transcriptional gene expression (p-values <0.001). Finally, in normal bone marrow and tonsil samples, eight evaluated genes were expressed in accordance with the biology of lymphopoiesis (p-values < 0.001), which enabled the generation of a gene-specific B-cell atlas.
A description of the implementation and validation of commercially available kits in the laboratory has been examined. This included steps for cell sorting, cell lysis/stabilization, RNA isolation, RNA concentration and amplification for microarray analysis. The workflow described in this report will enable the generation of microarray data from minor sorted B-cell subsets.
[Show abstract][Hide abstract] ABSTRACT: Alternative concepts for a flexible radiometer system for Sun calibration were analyzed, imposing as few constraints as possible to the spacecraft system. The principal possibilities for the variation of the instantaneous field of view (FOV) were investigated in order to provide better data correlation for the wide FOV system. The influence of polarization on the system energy transfer function was calculated. Results make it possible to specify a system with higher performance concerning system calibration and geometrical data correlation. The theoretical limits of radiometric resolution due to polarization errors are given.
[Show abstract][Hide abstract] ABSTRACT: We present a novel approach for microarray analysis of RNA derived from microdissected cells of routinely formalin-fixed and paraffin-embedded (FFPE) cancer resection specimens. Subsequent to RNA sample preparation and hybridization to standard GeneChips (Affymetrix), RNA samples yielded 36.43 +/- 9.60% (FFPE), 49.90 +/- 4.43% (fresh-frozen), and 53.9% (cell line) present calls. Quality control parameters and Q-RT-PCR validation demonstrated reliability of results. Microarray datasets of FFPE samples were informative and comparable to those of fresh-frozen samples. A systematic measurement difference of differentially processed tissues was eliminated by a correction step for comparative unsupervised data analysis of fresh-frozen and FFPE samples. Within FFPE samples, unsupervised clustering analyses clearly distinguished between normal and malignant tissues as well as to further separate tumor samples according to histological World Health Organization (WHO) subtypes. In summary, our approach represents a major step towards integration of microarrays into retrospective studies and enables further investigation of the relevance of microarray analysis for clinico-pathological diagnostics.
Journal of Molecular Medicine 02/2009; 87(2):211-24. DOI:10.1007/s00109-008-0419-y · 5.11 Impact Factor
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