Basal keratin expression in breast cancer by quantification of mRNA and by immunohistochemistry

Definitions of basal-like breast cancer phenotype vary, and microarray-based expression profiling analysis remains the gold standard for the identification of these tumors. Immunohistochemical identification of basal-like carcinomas is hindered with a fact, that on microarray level not all of them express basal-type cytokeratin 5/6, 14 and 17. We compared expression of cytokeratin 5, 14 and 17 in 115 patients with operable breast cancer estimated by real-time RT-PCR and immunohistochemistry

An optimized protocol for microarray validation by quantitative PCR using amplified amino allyl labeled RNA

<p>Abstract</p> <p>Background</p> <p>Validation of microarrays data by quantitative real-time PCR (qPCR) is often limited by the low amount of available RNA. This raised the possibility to perform validation experiments on the amplified amino allyl labeled RNA (AA-aRNA) leftover from microarrays. To test this possibility, we used an ongoing study of our laboratory aiming at identifying new biomarkers of graft rejection by the transcriptomic analysis of blood cells from brain-dead organ donors.</p> <p>Results</p> <p>qPCR for ACTB performed on AA-aRNA from 15 donors provided Cq values 8 cycles higher than when original RNA was used (P < 0.001), suggesting a strong inhibition of qPCR performed on AA-aRNA. When expression levels of 5 other genes were measured in AA-aRNA generated from a universal reference RNA, qPCR sensitivity and efficiency were decreased. This prevented the quantification of one low-abundant gene, which was readily quantified in un-amplified and un-labeled RNA. To overcome this limitation, we modified the reverse transcription (RT) protocol that generates cDNA from AA-aRNA as follows: addition of a denaturation step and 2-min incubation at room temperature to improve random primers annealing, a transcription initiation step to improve RT, and a final treatment with RNase H to degrade remaining RNA. Tested on universal reference AA-aRNA, these modifications provided a gain of 3.4 Cq (average from 5 genes, P < 0.001) and an increase of qPCR efficiency (from -1.96 to -2.88; P = 0.02). They also allowed for the detection of a low-abundant gene that was previously undetectable. Tested on AA-aRNA from 15 brain-dead organ donors, RT optimization provided a gain of 2.7 cycles (average from 7 genes, P = 0.004). Finally, qPCR results significantly correlated with microarrays.</p> <p>Conclusion</p> <p>We present here an optimized RT protocol for validation of microarrays by qPCR from AA-aRNA. This is particularly valuable in experiments where limited amount of RNA is available.</p

Model based analysis of real-time PCR data from DNA binding dye protocols

BACKGROUND: Reverse transcription followed by real-time PCR is widely used for quantification of specific mRNA, and with the use of double-stranded DNA binding dyes it is becoming a standard for microarray data validation. Despite the kinetic information generated by real-time PCR, most popular analysis methods assume constant amplification efficiency among samples, introducing strong biases when amplification efficiencies are not the same. RESULTS: We present here a new mathematical model based on the classic exponential description of the PCR, but modeling amplification efficiency as a sigmoidal function of the product yield. The model was validated with experimental results and used for the development of a new method for real-time PCR data analysis. This model based method for real-time PCR data analysis showed the best accuracy and precision compared with previous methods when used for quantification of in-silico generated and experimental real-time PCR results. Moreover, the method is suitable for the analyses of samples with similar or dissimilar amplification efficiency. CONCLUSION: The presented method showed the best accuracy and precision. Moreover, it does not depend on calibration curves, making it ideal for fully automated high-throughput applications

Early pregnancy peripheral blood gene expression and risk of preterm delivery: a nested case control study

<p>Abstract</p> <p>Background</p> <p>Preterm delivery (PTD) is a significant public health problem associated with greater risk of mortality and morbidity in infants and mothers. Pathophysiologic processes that may lead to PTD start early in pregnancy. We investigated early pregnancy peripheral blood global gene expression and PTD risk.</p> <p>Methods</p> <p>As part of a prospective study, ribonucleic acid was extracted from blood samples (collected at 16 weeks gestational age) from 14 women who had PTD (cases) and 16 women who delivered at term (controls). Gene expressions were measured using the GeneChip^®Human Genome U133 Plus 2.0 Array. Student's T-test and fold change analysis were used to identify differentially expressed genes. We used hierarchical clustering and principle components analysis to characterize signature gene expression patterns among cases and controls. Pathway and promoter sequence analyses were used to investigate functions and functional relationships as well as regulatory regions of differentially expressed genes.</p> <p>Results</p> <p>A total of 209 genes, including potential candidate genes (e.g. PTGDS, prostaglandin D2 synthase 21 kDa), were differentially expressed. A set of these genes achieved accurate pre-diagnostic separation of cases and controls. These genes participate in functions related to immune system and inflammation, organ development, metabolism (lipid, carbohydrate and amino acid) and cell signaling. Binding sites of putative transcription factors such as EGR1 (early growth response 1), TFAP2A (transcription factor AP2A), Sp1 (specificity protein 1) and Sp3 (specificity protein 3) were over represented in promoter regions of differentially expressed genes. Real-time PCR confirmed microarray expression measurements of selected genes.</p> <p>Conclusions</p> <p>PTD is associated with maternal early pregnancy peripheral blood gene expression changes. Maternal early pregnancy peripheral blood gene expression patterns may be useful for better understanding of PTD pathophysiology and PTD risk prediction.</p

Optimizing a qPCR Gene Expression Quantification Assay for S. epidermidis Biofilms: A Comparison between Commercial Kits and a Customized Protocol

Staphylococcus epidermidis biofilm-related infections are a current concern within the medical community due to their high incidence and prevalence, particularly in patients with indwelling medical devices. Biofilm gene expression analysis by quantitative real-time PCR (qPCR) has been increasingly used to understand the role of biofilm formation in the pathogenesis of S. epidermidis infections. However, depending on the RNA extraction procedure, and cDNA synthesis and qPCR master mixes used, gene expression quantification can be suboptimal. We recently showed that some RNA extraction kits are not suitable for S. epidermidis biofilms, due to sample composition, in particular the presence of the extracellular matrix. In this work, we describe a custom RNA extraction assay followed by the evaluation of gene expression using different commercial reverse transcriptase kits and qPCR master mixes. Our custom RNA extraction assay was able to produce good quality RNA with reproducible gene expression quantification, reducing the time and the costs associated. We also tested the effect of reducing cDNA and qPCR reaction volumes and, in most of the cases tested, no significant differences were found. Finally, we titered the SYBR Green I concentrations in standard PCR master mixes and compared the normalized expression of the genes icaA, bhp, aap, psmβ1 and agrB using 4 distinct biofilm forming S. epidermidis strains to the results obtained with commercially available kits. The overall results demonstrated that despite some statistically, but not biologically significant differences observed, the customized qPCR protocol resulted in the same gene expression trend presented by the commercially available kits used

Analysis of differential gene expression in human melanocytic tumour lesions by custom made oligonucleotide arrays

Melanoma is one of the most aggressive types of cancer and resection of the tumour prior to dissemination of tumour cells is still the most effective treatment. Therefore, early diagnosis of melanocytic lesions is important and identification of novel (molecular) markers would be helpful to improve diagnosis. Moreover, better understanding of molecular targets involved in melanocytic tumorigenesis could possibly lead to development of novel interventions. In this study, we used a custom made oligonucleotide array containing 298 genes that were previously found to be differentially expressed in human melanoma cell lines 1F6 (rarely metastasising) and Mel57 (frequently metastasising). We determined differential gene expression in human common nevocellular nevus and melanoma metastasis lesions. By performing nine dye-swap array experiments, using individual as well as pooled melanocytic lesions, a constant differential expression could be detected for 25 genes in eight out of nine or nine out of nine array analyses. For at least nine of these genes, namely THBD, FABP7, H2AFJ, RRAGD, MYADM, HR, CKS2, NCK2 and GDF15, the differential expression found by array analyses could be verified by semiquantitative and/or real-time quantitative RT–PCR. The genes that we identified to be differentially expressed during melanoma progression could be potent targets for diagnostic, prognostic and/or therapeutic interventions