COVID-19 vaccine race: watch your step for cancer patients.

Patients with cancer should benefit from COVID-19 vaccination. Some of the most advanced vaccine candidates are mRNAs encapsulated into lipid carriers, and small liposomes are expected to accumulate in tumour tissues through the enhanced and permeation retention effect. However, to what extent solid tumours could take up a significant part of the vaccine dose as well remains unknown. This calls for a careful evaluation of the efficacy of these promising mRNA COVID-19 vaccines administered as lipid carriers for patients with solid tumours, including a possible re-appraisal of the dosing for optimal protection of this specific and frail population.

Housekeeping gene validation for RT-qPCR studies on synovial fibroblasts derived from healthy and osteoarthritic patients with focus on mechanical loading.

Selection of appropriate housekeeping genes is essential for the validity of data normalization in reverse transcription quantitative PCR (RT-qPCR). Synovial fibroblasts (SF) play a mediating role in the development and progression of osteoarthritis (OA) pathogenesis, but there is no information on reliable housekeeping genes available. Therefore the goal of this study was to identify a set of reliable housekeeping genes suitable for studies of mechanical loading on SF from healthy and OA patients. Nine genes were evaluated towards expression stability and ranked according their relative stability determined by four different mathematical procedures (geNorm, NormFinder, BestKeeper and comparative ΔCq). We observed that RPLP0 (ribosomal protein, large, P0) and EEF1A1 (eukaryotic translation elongation factor 1 alpha 1) turned out to be the genes with the most stable expression in SF from non-OA or OA patients treated with or without mechanical loading. According to geNorm two genes are sufficient for normalization throughout. Expression of one tested target gene varied considerably, if normalized to different candidate housekeeping genes. Our study provides a tool for accurate and valid housekeeping gene selection in gene expression experiments on SF from healthy and OA patients with and without mechanical loading in consistent with the MIQE (Minimum Information for Publication of Quantitative Real-Time PCR Experiments) guidelines and additionally demonstrates the impact of proper housekeeping gene selection on the expression of the gene of interest.

Influence of microwave-assisted dehydration on morphological integrity and viability of cat ovarian tissues: First steps toward long-term preservation of complex biomaterials at supra-zero temperatures.

Ovarian tissue contains large pools of immature oocytes enclosed in primordial follicles, making it an attractive target for fertility preservation in female cancer patients, livestock and wild species. Compared to cryopreservation, desiccation and long-term storage of samples at supra-zero temperatures (using strategies inspired from small organisms to resist extreme environments) would be more cost-effective and convenient. The objective of the study was to characterize the influence of microwave-assisted dehydration on structural and functional properties of living ovarian tissues. While this method allows preservation of single cells (cat oocytes and sperm cells so far) using trehalose as the xeroprotectant, it has not been developed for multicellular tissues yet. Ovarian cortex biopsies were reversibly permeabilized, exposed to various concentrations of trehalose, and dried for different times using a commercial microwave under thermal control. Effective dehydration of samples along with proper trehalose retention were reached within 30 min of microwave drying. Importantly, the process did not affect morphology and DNA integrity of follicles or stromal cells. Moreover, transcriptional activity and survival of follicles were partially maintained following 10 min of drying, which already was compatible with storage at non-cryogenic temperatures. Present data provide critical foundation to develop dry-preservation techniques for long-term storage of living multicellular tissues.

Analysis of major BCR-ABL1 mRNA by digital polymerase chain reaction is useful for prediction of international scale.

BACKGROUND: Major BCR-ABL1 mRNA in patients with chronic myeloid leukemia (CML) has generally been analysed by real-time polymerase chain reaction (PCR). Application of the international scale (IS) for the quantification of major BCR-ABL1 mRNA has been recommended in several sets of guidelines, including those of the European LeukemiaNet. The aim of this study was to clarify the efficacy of digital PCR technology for the IS of BCR-ABL1 mRNA in the patients with CML by comparing with real-time PCR. METHODS: The analysis of BCR-ABL1 mRNA was carried out by the Ipsogen® BCR-ABL1 Mbcr IS-MMR DX Kit (Qiagen), and the QuantStudio 3D Digital PCR System (Thermo Fisher Scientific ) using 20 peripheral blood samples obtained from the 9 patients with CML at Sapporo Medical University Hospital. RESULTS: The correlation between the data obtained by digital PCR and by real-time PCR was really high at R = 0.96. The detection limit of digital PCR was up to 0.003% and was equal to IS with 0.01% or less in comparison with real-time PCR. CONCLUSIONS: Digital PCR technology is promising for predicting the IS value with similar efficacy to real-time PCR and should be useful for simple monitoring of the effects of tyrosine kinase inhibitor (TKI) treatments.

A cut-off of 2150 cytokeratin 19 mRNA copy number in sentinel lymph node may be a powerful predictor of non-sentinel lymph node status in breast cancer patients.

Since 2007, one-step nucleic acid amplification (OSNA) has been used as a diagnostic system for sentinel lymph node (SLN) examination in patients with breast cancer. This study aimed to define a new clinical cut-off of CK19 mRNA copy number based on the calculation of the risk that an axillary lymph node dissection (ALND) will be positive. We analyzed 1529 SLNs from 1140 patients with the OSNA assay and 318 patients with positive SLNs for micrometastasis (250 copies) and macrometastasis (5000 copies) underwent ALND. Axillary non-SLNs were routinely examined. ROC curves and Youden's index were performed in order to identify a new cut-off value. Logistic regression models were performed in order to compare OSNA categorical variables created on the basis of our and traditional cut-off to better identify patients who really need an axillary dissection. 69% and 31% of OSNA positive patients had a negative and positive ALND, respectively. ROC analysis identified a cut-off of 2150 CK19 mRNA copies with 95% sensitivity and 51% specificity. Positive and negative predictive values of this new cut-off were 47% and 96%, respectively. Logistic regression models indicated that the cut-off of 2150 copies better discriminates patients with node negative or positive in comparison with the conventional OSNA cut-off (p<0.0001). This cut-off identifies false positive and false negative cases and true-positive and true negative cases very efficiently, and therefore better identifies which patients really need an ALND and which patients can avoid one. This is why we suggest that the negative cut-off should be raised from 250 to 2150. Furthermore, we propose that for patients with a copy number that ranges between 2150 and 5000, there should be a multidisciplinary discussion concerning the clinical and bio-morphological features of primary breast cancer before any decision is taken on whether to perform an ALND or not.

Identification of reference genes for qPCR analysis during hASC long culture maintenance.

Up to now quantitative PCR based assay is the most common method for characterizing or confirming gene expression patterns and comparing mRNA levels in different sample populations. Since this technique is relative easy and low cost compared to other methods of characterization, e.g. flow cytometry, we used it to typify human adipose-derived stem cells (hASCs). hASCs possess several characteristics that make them attractive for scientific research and clinical applications. Accurate normalization of gene expression relies on good selection of reference genes and the best way to choose them appropriately is to follow the common rule of the "Best 3", at least three reference genes, three different validation software and three sample replicates. Analysis was performed on hASCs cultivated until the eleventh cell confluence using twelve candidate reference genes, initially selected from literature, whose stability was evaluated by the algorithms NormFinder, BestKeeper, RefFinder and IdealRef, a home-made version of GeNorm. The best gene panel (RPL13A, RPS18, GAPDH, B2M, PPIA and ACTB), determined in one patient by IdealRef calculation, was then investigated in other four donors. Although patients demonstrated a certain gene expression variability, we can assert that ACTB is the most unreliable gene whereas ribosomal proteins (RPL13A and RPS18) show minor inconstancy in their mRNA expression. This work underlines the importance of validating reference genes before conducting each experiment and proposes a free software as alternative to those existing.

Synthetic certified DNA reference material for analysis of human erythropoietin transgene and transcript in gene doping and gene therapy.

There is a recognised need for standardisation of protocols for vector genome analysis used in vector manufacturing, to establish dosage, in biodistribution studies and to detect gene doping in sport. Analysis of vector genomes and transgene expression is typically performed by qPCR using plasmid-based calibrants incorporating transgenic sequences. These often undergo limited characterisation and differ between manufacturers, potentially leading to inaccurate quantification, inconsistent inter-laboratory results and affecting clinical outcomes. Contamination of negative samples with such calibrants could cause false positive results. We developed a design strategy for synthetic reference materials (RMs) with modified transgenic sequences to prevent false positives due to cross-contamination. When such RM is amplified in transgene-specific assays, the amplicons are distinguishable from transgene's amplicons based on size and sequence. Using human erythropoietin as a model, we produced certified RM according to this strategy and following ISO Guide 35. Using non-viral and viral vectors, we validated the effectiveness of this RM in vector genome analysis in blood in vitro. The developed design strategy could be applied to production of RMs for other transgenes, genes or transcripts. Together with validated PCR assays, such RMs form a measurement tool that facilitates standardised, accurate and reliable genetic analysis in various applications.

Identification of appropriate reference genes for normalizing transcript expression by quantitative real-time PCR in Litsea cubeba.

Quantitative real-time PCR has emerged as a highly sensitive and widely used method for detection of gene expression profiles, via which accurate detection depends on reliable normalization. Since no single control is appropriate for all experimental treatments, it is generally advocated to select suitable internal controls prior to use for normalization. This study reported the evaluation of the expression stability of twelve potential reference genes in different tissue/organs and six fruit developmental stages of Litsea cubeba in order to screen the superior internal reference genes for data normalization. Two softwares-geNorm, and NormFinder-were used to identify stability of these candidate genes. The cycle threshold difference and coefficient of variance were also calculated to evaluate the expression stability of candidate genes. F-BOX, EF1α, UBC, and TUA were selected as the most stable reference genes across 11 sample pools. F-BOX, EF1α, and EIF4α exhibited the highest expression stability in different tissue/organs and different fruit developmental stages. Besides, a combination of two stable reference genes would be sufficient for gene expression normalization in different fruit developmental stages. In addition, the relative expression profiles of DXS and DXR were evaluated by EF1α, UBC, and SAMDC. The results further validated the reliability of stable reference genes and also highlighted the importance of selecting suitable internal controls for L. cubeba. These reference genes will be of great importance for transcript normalization in future gene expression studies on L. cubeba.

Validation of reference transcripts in strawberry (Fragaria spp.).

Contemporary methods to assay gene expression depend on a stable set of reference transcripts for accurate quantitation. A lack of well-tested reference genes slows progress in characterizing gene expression in high-value specialty crops. In this study, a set of strawberry (Fragaria spp.) constitutively expressed reference genes has been identified by merging digital gene expression data with expression profiling. Constitutive reference candidates were validated using quantitative PCR and hybridization. Several transcripts have been identified that show improved stability across tissues relative to traditional reference transcripts. Results are similar between commercial octoploid strawberry and the diploid model. Our findings also show that while some never-before-used references are appropriate for most applications, even the most stable reference transcripts require careful assessment across the diverse tissues and fruit developmental states before being adopted as controls.

AffyRNADegradation: control and correction of RNA quality effects in GeneChip expression data.

MOTIVATION: Gene expression experiments aim to accurately quantify thousands of transcripts in parallel. Factors posterior to RNA extraction can, however, impair their accurate representation. RNA degradation and differences in the efficiency of amplification affect raw intensity measurements using Affymetrix expression arrays. The positional intensity decay of specifically hybridized probes along the transcript they intend to interrogate is used to estimate the RNA quality in a sample and to correct probe intensities for the degradation bias. This functionality, for which no previous software solution is available, is implemented in the R/Bioconductor package AffyRNADegradation presented here. AVAILABILITY: The package is available via Bioconductor at the URL http://bioconductor.org/packages/release/bioc/html/AffyRNA Degradation.html

In vitro evidence for the brain glutamate efflux hypothesis: brain endothelial cells cocultured with astrocytes display a polarized brain-to-blood transport of glutamate.

The concentration of the excitotoxic amino acid, L-glutamate, in brain interstitial fluid is tightly regulated by uptake transporters and metabolism in astrocytes and neurons. The aim of this study was to investigate the possible role of the blood-brain barrier endothelium in brain L-glutamate homeostasis. Transendothelial transport- and accumulation studies of (3) H-L-glutamate, (3) H-L-aspartate, and (3) H-D-aspartate in an electrically tight bovine endothelial/rat astrocyte blood-brain barrier coculture model were performed. After 6 days in culture, the endothelium displayed transendothelial resistance values of 1014 ± 70 Ω cm(2) , and (14) C-D-mannitol permeability values of 0.88 ± 0.13 × 10(-6) cm s(-1) . Unidirectional flux studies showed that L-aspartate and L-glutamate, but not D-aspartate, displayed polarized transport in the brain-to-blood direction, however, all three amino acids accumulated in the cocultures when applied from the abluminal side. The transcellular transport kinetics were characterized with a K(m) of 69 ± 15 µM and a J(max) of 44 ± 3.1 pmol min(-1) cm(-2) for L-aspartate and a K(m) of 138 ± 49 µM and J(max) of 28 ± 3.1 pmol min(-1) cm(-2) for L-glutamate. The EAAT inhibitor, DL-threo-ß-Benzyloxyaspartate, inhibited transendothelial brain-to-blood fluxes of L-glutamate and L-aspartate. Expression of EAAT-1 (Slc1a3), -2 (Slc1a2), and -3 (Slc1a1) mRNA in the endothelial cells was confirmed by conventional PCR and localization of EAAT-1 and -3 in endothelial cells was shown with immunofluorescence. Overall, the findings suggest that the blood-brain barrier itself may participate in regulating brain L-glutamate concentrations.

Pitfalls of reverse transcription quantitative polymerase chain reaction standardization: Volume-related inhibitors of reverse transcription.

A large part of the reliability of reverse transcription quantitative polymerase chain reaction (RT-qPCR) data depends on technical variations. Such variations are mainly attributable to the reverse transcription step. Standardization is a key factor in decreasing the intersample variability. However, an ideal standardization is not always possible, and compromises must be found. Due to technical requirements, the current consensus is that a constant amount of total RNA should be used for the RT step (CA-RT). Because RNA isolation yields are variable, such a practice requires the use of variable volumes of nucleic acid extracts in RT reaction. We demonstrate that some RNA extracts contain both exogenous and endogenous inhibitors. These inhibitors induce a decrease in RT efficiency that significantly impairs the reliability of RT-qPCR data. Conversely, these inhibitors have a slight effect on the qPCR step. To overcome such drawbacks, we proposed to carry out the RT reaction with a constant volume of RNA extract by preserving a constant RNA amount through the supplementation of yeast transfer RNA (CV-RT). We show that CV-RT, compared with the usual CA-RT, allows us to decrease the RT-qPCR variability induced by intersample differences. Such a decrease is a prerequisite for the reliability of messenger RNA quantification.

Identification of housekeeping genes suitable for gene expression analysis in the zebrafish.

Housekeeping (HK) genes are constitutively expressed in order to maintain cellular function. They produce the minimal essential transcripts necessary for normal cellular physiology. Wide range expression, stable expression level and high expression level are independent features of a single gene expression and are all desirable for the definition of an "ideal" HK. Recent studies have questioned the possible existence of "ideal" HK mRNAs, mainly because of the wide expression conditions variability. This would imply that for each investigated organism the suitability of a putative HK should be verified. We perform a systematic analysis to identify "optimal" HK genes in Danio rerio (zebrafish), to be used in expression analyses conducted on embryos/larvae at different developmental stages, as well as on differentiated adult tissues from single donors. The expression pattern of candidate genes, selected on the basis of the literature available and of ad hoc bioinformatics analysis, was assessed by quantitative relative RT-PCR in an RNA panel, including six different embryo/larvae developmental stages and six adult tissues. Statistical analysis was performed to identify genes with the lowest expression standard deviation in the studied panel. Our results showed that beta-actin 2 (bactin2) is the mRNA with the lowest variability of expression.

Measurable impact of RNA quality on gene expression results from quantitative PCR.

Compromised RNA quality is suggested to lead to unreliable results in gene expression studies. Therefore, assessment of RNA integrity and purity is deemed essential prior to including samples in the analytical pipeline. This may be of particular importance when diagnostic, prognostic or therapeutic conclusions depend on such analyses. In this study, the comparative value of six RNA quality parameters was determined using a large panel of 740 primary tumour samples for which real-time quantitative PCR gene expression results were available. The tested parameters comprise of microfluidic capillary electrophoresis based 18S/28S rRNA ratio and RNA Quality Index value, HPRT1 5'-3' difference in quantification cycle (Cq) and HPRT1 3' Cq value based on a 5'/3' ratio mRNA integrity assay, the Cq value of expressed Alu repeat sequences and a normalization factor based on the mean expression level of four reference genes. Upon establishment of an innovative analytical framework to assess impact of RNA quality, we observed a measurable impact of RNA quality on the variation of the reference genes, on the significance of differential expression of prognostic marker genes between two cancer patient risk groups, and on risk classification performance using a multigene signature. This study forms the basis for further rational assessment of reverse transcription quantitative PCR based results in relation to RNA quality.

Identification of internal control genes for quantitative expression analysis by real-time PCR in bovine peripheral lymphocytes.

Gene expression studies in blood cells, particularly lymphocytes, are useful for monitoring potential exposure to toxicants or environmental pollutants in humans and livestock species. Quantitative PCR is the method of choice for obtaining accurate quantification of mRNA transcripts although variations in the amount of starting material, enzymatic efficiency, and the presence of inhibitors can lead to evaluation errors. As a result, normalization of data is of crucial importance. The most common approach is the use of endogenous reference genes as an internal control, whose expression should ideally not vary among individuals and under different experimental conditions. The accurate selection of reference genes is therefore an important step in interpreting quantitative PCR studies. Since no systematic investigation in bovine lymphocytes has been performed, the aim of the present study was to assess the expression stability of seven candidate reference genes in circulating lymphocytes collected from 15 dairy cows. Following the characterization by flow cytometric analysis of the cell populations obtained from blood through a density gradient procedure, three popular softwares were used to evaluate the gene expression data. The results showed that two genes are sufficient for normalization of quantitative PCR studies in cattle lymphocytes and that YWAHZ, S24 and PPIA are the most stable genes.

Housekeepers for accurate transcript expression analysis in Alzheimer's disease autopsy brain tissue.

BACKGROUND: Quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR) is a popular technique for mRNA expression studies. Normalization to an endogenous reference transcript (housekeeper) is widely used to correct for differences in loading and RNA quality. Alzheimer's disease (AD) alters brain metabolism. The stability of housekeeper transcript expression must be carefully validated. METHODS: qRT-PCR was used to assess eight putative housekeeper transcripts in four brain regions from 15 control, 12 AD, and 10 AD/Lewy body disease (LBD) cases. RESULTS: RNA quality is lower in AD and AD/LBD than in controls. Frequently used housekeepers such as glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and ß-actin had lower overall expression in AD and AD/LBD cases than in controls. RPL13 and 18S were the most stably expressed housekeepers tested. Synaptophysin and glial fibrillary acidic protein were used to evaluate normalized quantification. By using different housekeepers we confirmed that synaptophysin expression was down-regulated in AD cases, whereas glial fibrillary acidic protein expression was increased. CONCLUSIONS: Among all candidates tested, RPL13 was the best housekeeper for qRT-PCR studies in autopsy brain tissue samples from controls and AD cases. RNA quality should be assessed and data normalized on this index as well.

mRNA and microRNA quality control for RT-qPCR analysis.

The importance of high quality sample material, i.e. non-degraded or fragmented RNA, for classical gene expression profiling is well documented. Hence, the analysis of RNA quality is a valuable tool in the preparation of methods like RT-qPCR and microarray analysis. For verification of RNA integrity, today the use of automated capillary electrophoresis is state of the art. Following the recently published MIQE guidelines, these pre-PCR evaluations have to be clearly documented in scientific publication to increase experimental transparency. RNA quality control may also be integrated in the routine analysis of new applications like the investigation of microRNA (miRNA) expression, as there is little known yet about factors compromising the miRNA analysis. Agilent Technologies is offering a new lab-on-chip application for the 2100 Bioanalyzer making it possible to quantify miRNA in absolute amounts [pg] and as a percentage of small RNA [%]. Recent results showed that this analysis method is strongly influenced by total RNA integrity. Ongoing RNA degradation is accompanied by the formation of small RNA fragments leading to an overestimation of miRNA amount on the chip. Total RNA integrity is known to affect the performance of RT-qPCR as well as the quantitative results in mRNA expression profiling. The actual study identified a comparable effect for miRNA gene expression profiling. Using a suitable normalization method could partly reduce the impairing effect of total RNA integrity.

Resolving cell population heterogeneity: real-time PCR for simultaneous multiplexed gene detection in multiple single-cell samples.

Decoding the complexity of multicellular organisms requires analytical procedures to overcome the limitations of averaged measurements of cell populations, which obscure inherent cell-cell heterogeneity and restrict the ability to distinguish between the responses of individual cells within a sample. For example, defining the timing, magnitude and the coordination of cytokine responses in single cells is critical for understanding the development of effective immunity. While approaches to measure gene expression from single cells have been reported, the absolute performance of these techniques has been difficult to assess, which likely has limited their wider application. We describe a straightforward method for simultaneously measuring the expression of multiple genes in a multitude of single-cell samples using flow cytometry, parallel cDNA synthesis, and quantification by real-time PCR. We thoroughly assess the performance of the technique using mRNA and DNA standards and cell samples, and demonstrate a detection sensitivity of approximately 30 mRNA molecules per cell, and a fractional error of 15%. Using this method, we expose unexpected heterogeneity in the expression of 5 immune-related genes in sets of single macrophages activated by different microbial stimuli. Further, our analyses reveal that the expression of one 'pro-inflammatory' cytokine is not predictive of the expression of another 'pro-inflammatory' cytokine within the same cell. These findings demonstrate that single-cell approaches are essential for studying coordinated gene expression in cell populations, and this generic and easy-to-use quantitative method is applicable in other areas in biology aimed at understanding the regulation of cellular responses.

Consolidated strategy for the analysis of microarray spike-in data.

As the number of users of microarray technology continues to grow, so does the importance of platform assessments and comparisons. Spike-in experiments have been successfully used for internal technology assessments by microarray manufacturers and for comparisons of competing data analysis approaches. The microarray literature is saturated with statistical assessments based on spike-in experiment data. Unfortunately, the statistical assessments vary widely and are applicable only in specific cases. This has introduced confusion into the debate over best practices with regards to which platform, protocols and data analysis tools are best. Furthermore, cross-platform comparisons have proven difficult because reported concentrations are not comparable. In this article, we introduce two new spike-in experiments, present a novel statistical solution that enables cross-platform comparisons, and propose a comprehensive procedure for assessments based on spike-in experiments. The ideas are implemented in a user friendly Bioconductor package: spkTools. We demonstrated the utility of our tools by presenting the first spike-in-based comparison of the three major platforms--Affymetrix, Agilent and Illumina.