Quantitative real-time reverse-transcription PCR (RT-qPCR) is presently the method of choice for validating gene expression results from high-density microarrays. However, the low throughput of traditional gene-by-gene RT-qPCR makes this process labor intensive and time consuming. To accelerate this laborious task, the SuperArray RT²Profiler PCR Array combines SYBR Green–based real-time RT-qPCR technology with a multi-gene array plate format to simultaneously analyze a panel of genes related to a specific disease or biological pathway.
Each assay on the PCR array plate has been experimentally validated to insure gene-specific amplification. The reliability and reproducibility of the RT²Profiler PCR Array have been demonstrated by DNA sequencing and intra/inter-laboratory reproducibility comparisons. The DNA sequencing demonstrated 100% of the PCR products amplified from the correct target genes. In one laboratory, individual PCR assays produced a standard deviation of 0.24 cycles and a coefficient of variance of 0.92% in technical replicates. The correlation coefficient for Ct values between replicate runs was 0.997 and for fold changes (ΔΔCt) across thermocyclers was 0.976. Comparisons between two different laboratories using different thermocyclers showed correlation coefficients of 0.972 and 0.976 for ΔCt and ΔΔCt, respectively. Each PCR array also includes stringent controls to monitor RNA quality by assessing reverse transcription efficiency and genomic DNA contamination to ensure the reliability of the PCR array data.
A practical application for the PCR array was demonstrated by identifying human pancreatic tumor–associated genes using the Cancer PathwayFinder RT²Profiler PCR Array. Results showed 23 genes exhibiting a statistically significant threefold or greater change in expression between a human pancreatic tumor and normal pancreas, including many genes previously linked to pancreatic cancer. Hence, the RT2 Profiler PCR Array system offers a simple, reliable, and convenient tool for multi-gene profiling and microarray data validation.
The quantitative real time polymerase chain reaction (qPCR) has become a key molecular enabling technology with an immense range of research, clinical, forensic as well as diagnostic applications. Its relatively moderate instrumentation and reagent requirements have led to its adoption by numerous laboratories, including those located in the Arabian world, where qPCR, which targets DNA, and reverse transcription qPCR (RT-qPCR), which targets RNA, are widely used for region-specific biotechnology, agricultural and human genetic studies. However, it has become increasingly apparent that there are significant problems with both the quality of qPCR-based data as well as the transparency of reporting. This realisation led to the publication of the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines in 2009 and their more widespread adoption in the last couple of years. An analysis of the performance of biomedical research in the Arabian world between 2001–2005 suggests that the Arabian world is producing fewer biomedical publications of lower quality than other Middle Eastern countries. Hence we have analysed specifically the quality of RT-qPCR-based peer-reviewed papers published since 2009 from Arabian researchers using a bespoke iOS/Android app developed by one of the authors. Our results show that compliance with 15 essential MIQE criteria was low (median of 40%, range 0–93%) and few details on RNA quality controls (22% compliance), assays design (12%), RT strategies (32%), amplification efficiencies (30%) and the normalisation process (3%). These data indicate that one of the reasons for the poor performance of Arabian world biomedical research may be the low standard of any supporting qPCR experiments and identify which aspects of qPCR experiments require significant improvements.
Harmful algal blooms (HABs) are a global problem that affects both human and ecosystem health. One of the most serious and widespread HAB poisoning syndromes is paralytic shellfish poisoning, commonly caused by Alexandrium spp. dinoflagellates. Like many toxic dinoflagellates, Alexandrium produces resistant resting cysts as part of its life cycle. These cysts play a key role in bloom initiation and decline, as well as dispersal and colonization of new areas. Information on cyst numbers and identity is essential for understanding and predicting blooms, yet comprehensive cyst surveys are extremely time- and labor-intensive. Here we describe the development and validation of a quantitative real-time PCR (qPCR) technique for the enumeration of cysts of A. tamarense of the toxic North American/Group I ribotype. The method uses a cloned fragment of the large subunit ribosomal RNA gene as a standard for cyst quantification, with an experimentally determined conversion factor of 28,402±6152 LSU ribosomal gene copies per cyst. Tests of DNA extraction and PCR efficiency show that mechanical breakage is required for adequate cyst lysis, and that it was necessary to dilute our DNA extracts 50-fold in order to abolish PCR inhibition from compounds co-extracted from the sediment. The resulting assay shows a linear response over 6 orders of magnitude and can reliably quantify ≥10cysts/cc sediment.
For method validation, 129 natural sediment samples were split and analyzed in parallel, using both the qPCR and primulin-staining techniques. Overall, there is a significant correlation (p<0.001) between the cyst abundances determined by the two methods, although the qPCR counts tend to be lower than the primulin values. This underestimation is less pronounced in those samples collected from the top 1 cm of sediment, and more pronounced in those derived from the next 1–3 cm of the core. These differences may be due to the condition of the cysts in the different layers, as the top 1cm contains more recent cysts while those in the next 1–3cm may have been in the sediments for many years. Comparison of the cyst densities obtained by both methods shows that a majority (56.6%) of the values are within a two-fold range of each other and almost all of the samples (96.9%) are within an order of magnitude. Thus, the qPCR method described here represents a promising alternative to primulin-staining for the identification and enumeration of cysts. The qPCR method has a higher throughput, enabling the extraction and assay of 24 samples in the time required to process and count 8–10 samples by primulin staining. Both methods require prior expertise, either in taxonomy or molecular biology. Fewer person-hours per sample are required for qPCR, but primulin staining has lower reagent costs. The qPCR method might be more desirable for large-scale cyst mapping, where large numbers of samples are generated and a higher sample analysis rate is necessary. While the qPCR and primulin-staining methods generate similar data, the choice of counting method may be most influenced by the practical issue of the different relative costs of labor and materials between the two methods.
quantitative PCR; ribosomal; toxic dinoflagellate; saxitoxins; algal blooms; red tides
Quantitative PCR (qPCR) is a workhorse laboratory technique for measuring the concentration of a target DNA sequence with high accuracy over a wide dynamic range. The gold standard method for estimating DNA concentrations via qPCR is quantification cycle () standard curve quantification, which requires the time- and labor-intensive construction of a standard curve. In theory, the shape of a qPCR data curve can be used to directly quantify DNA concentration by fitting a model to data; however, current empirical model-based quantification methods are not as reliable as standard curve quantification.
We have developed a two-parameter mass action kinetic model of PCR (MAK2) that can be fitted to qPCR data in order to quantify target concentration from a single qPCR assay. To compare the accuracy of MAK2-fitting to other qPCR quantification methods, we have applied quantification methods to qPCR dilution series data generated in three independent laboratories using different target sequences. Quantification accuracy was assessed by analyzing the reliability of concentration predictions for targets at known concentrations. Our results indicate that quantification by MAK2-fitting is as reliable as standard curve quantification for a variety of DNA targets and a wide range of concentrations.
We anticipate that MAK2 quantification will have a profound effect on the way qPCR experiments are designed and analyzed. In particular, MAK2 enables accurate quantification of portable qPCR assays with limited sample throughput, where construction of a standard curve is impractical.
In a previous study PCR analysis of clinical samples from suspected cases of Buruli ulcer disease (BUD) from Togo and external quality assurance (EQA) for local microscopy were conducted at an external reference laboratory in Germany. The relatively poor performance of local microscopy as well as effort and time associated with shipment of PCR samples necessitated the implementation of stringent EQA measures and availability of local laboratory capacity. This study describes the approach to implementation of a national BUD reference laboratory in Togo.
Large scale outreach activities accompanied by regular training programs for health care professionals were conducted in the regions “Maritime” and “Central,” standard operating procedures defined all processes in participating laboratories (regional, national and external reference laboratories) as well as the interaction between laboratories and partners in the field. Microscopy was conducted at regional level and slides were subjected to EQA at national and external reference laboratories. For PCR analysis, sample pairs were collected and subjected to a dry-reagent-based IS2404-PCR (DRB-PCR) at national level and standard IS2404 PCR followed by IS2404 qPCR analysis of negative samples at the external reference laboratory.
The inter-laboratory concordance rates for microscopy ranged from 89% to 94%; overall, microscopy confirmed 50% of all suspected BUD cases. The inter-laboratory concordance rate for PCR was 96% with an overall PCR case confirmation rate of 78%. Compared to a previous study, the rate of BUD patients with non-ulcerative lesions increased from 37% to 50%, the mean duration of disease before clinical diagnosis decreased significantly from 182.6 to 82.1 days among patients with ulcerative lesions, and the percentage of category III lesions decreased from 30.3% to 19.2%.
High inter-laboratory concordance rates as well as case confirmation rates of 50% (microscopy), 71% (PCR at national level), and 78% (including qPCR confirmation at external reference laboratory) suggest high standards of BUD diagnostics. The increase of non-ulcerative lesions, as well as the decrease in diagnostic delay and category III lesions, prove the effect of comprehensive EQA and training measures involving also procedures outside the laboratory.
Buruli ulcer disease (BUD), the third most common mycobacterial disease worldwide, is treated with standardized antimycobacterial therapy. According to WHO recommendations at least 50% of cases should be laboratory confirmed by polymerase chain reaction (PCR). In a previous study PCR analysis of clinical samples from suspected BUD cases from Togo and external quality assurance (EQA) for local microscopy were conducted at an external reference laboratory in Germany. The relatively poor performance of local microscopy as well as time and effort associated with shipment of clinical samples abroad necessitated the availability of a local BUD reference laboratory and the implementation of stringent EQA measures. All processes in the laboratories as well as in the field were defined by standard operating procedures, microscopy conducted at regional facilities was subjected to EQA at national and external reference level, and PCR samples were analyzed in parallel at national and external reference laboratories. Inter-laboratory concordance rates of >90% and case confirmation rates of 50% (microscopy) and >70% (PCR) respectively suggest high standards of BUD diagnostics. Furthermore, an increase of non-ulcerative lesions and a decrease in diagnostic delay and category III lesions reflect the impact of comprehensive EQA measures also involving procedures outside the laboratory on the quality of BUD control.
RT-qPCR analysis is a widely used method for the analysis of mRNA expression throughout the field of mesenchymal stromal cell (MSC) research. Comparison between MSC studies, both in vitro and in vivo, are challenging due to the varied methods of RT-qPCR data normalization and analysis. Therefore, this study focuses on putative housekeeping genes for the normalization of RT-qPCR data between heterogeneous commercially available human MSC, compared with more homogeneous populations of MSC such as MIAMI and RS-1 cells.
Eight genes including; ACTB, B2M, EF1α, GAPDH, RPL13a, YWHAZ, UBC
were tested as possible housekeeping genes based on their expression level and variability. EF1α and RPL13a were validated for RT-qPCR analysis of MIAMI cells during expansion in varied oxygen tensions, endothelial differentiation, neural precursor enrichment, and during the comparison with RS-1 cells and commercially available MSC. RPL13a and YWHAZ were validated as normalization genes for the cross-species analysis of MIAMI cells in an animal model of focal ischemia. GAPDH, which is one of the most common housekeeping genes used for the normalization of RT-qPCR data in the field of MSC research, was found to have the highest variability and deemed not suitable for normalization of RT-qPCR data.
In order to make comparisons between heterogeneous MSC populations, as well as adult stem cell like MSC which are used in different laboratories throughout the world, it is important to have a standardized, reproducible set of housekeeping genes for RT-qPCR analysis. In this study we demonstrate that EF1α, RPL13a and YWHAZ are suitable genes for the RT-qPCR analysis and comparison of several sources of human MSC during in vitro characterization and differentiation as well as in an ex vivo animal model of global cerebral ischemia. This will allow for the comparative RT-qPCR analysis of multiple MSC populations with the goal of future use in animal models of disease as well as tissue repair.
Reverse transcription quantitative real-time PCR (RT-qPCR) tests support personalized cancer treatment through more clinically meaningful diagnosis. However, samples obtained through standard clinical pathology procedures are formalin-fixed, paraffin-embedded (FFPE) and yield small samples with low integrity RNA containing PCR interfering substances. RT-qPCR tests able to assess FFPE samples with quality control and inter-laboratory reproducibility are needed.
We developed an RT-qPCR method by which 1) each gene was measured relative to a known number of its respective competitive internal standard molecules to control for interfering substances, 2) two-color fluorometric hydrolysis probes enabled analysis on a real-time platform, 3) external standards controlled for variation in probe fluorescence intensity, and 4) pre-amplification maximized signal from FFPE RNA samples. Reagents were developed for four genes comprised by a previously reported lung cancer diagnostic test (LCDT) then subjected to analytical validation using synthetic native templates as test articles to assess linearity, signal-to-analyte response, lower detection threshold, imprecision and accuracy. Fitness of this method and these reagents for clinical testing was assessed in FFPE normal (N = 10) and malignant (N = 10) lung samples.
Reagents for each of four genes, MYC, E2F1, CDKN1A and ACTB comprised by the LCDT had acceptable linearity (R2>0.99), signal-to-analyte response (slope 1.0±0.05), lower detection threshold (<10 molecules) and imprecision (CV <20%). Poisson analysis confirmed accuracy of internal standard concentrations. Internal standards controlled for experimentally introduced interference, prevented false-negatives and enabled pre-amplification to increase signal without altering measured values. In the fitness for purpose testing of this two-color fluorometric LCDT using surgical FFPE samples, the diagnostic accuracy was 93% which was similar to that previously reported for analysis of fresh samples.
This quality-controlled two-color fluorometric RT-qPCR approach will facilitate the development of reliable, robust RT-qPCR-based molecular diagnostic tests in FFPE clinical samples.
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.
Microarray gene expression profiling; RNA purification; B-cell subpopulations; Fluorescence activated cell sorting
We hypothesized improved inter-laboratory comparability of estrogen receptor (ER) and progesterone receptor (PgR) across different assay methodologies with adjunctive statistical standardization, akin to bone mineral density (BMD) z-scores. We examined statistical standardization in MA.12, a placebo-controlled pre-menopausal trial of adjuvant tamoxifen with locally assessed hormone receptor +/- tumours, and in a cohort of post-menopausal British Columbia (BC) tamoxifen-treated patients.
ER and PgR were centrally assessed for both patient groups with real time quantitative reverse transcription polymerase chain reaction (qPCR) and immunohistochemistry (IHC). Effects on disease-free survival (DFS) were investigated separately for 345 MA.12 and 673 BC patients who had both qPCR and IHC assessments. Comparisons utilized continuous laboratory units and statistically standardized z-scores. Univariate categorization of ER/PgR was by number of standard deviations (SD) above or below the mean (z-score ≥1.0 SD below mean; z-score <1.0 SD below mean; z-score ≤1.0 SD above mean; z-score >1.0 SD above mean). Exploratory multivariate examinations utilized step-wise Cox regression.
Median follow-up for MA.12 was 9.7 years; for BC patients, 11.8 years. For MA.12, 101 of 345 (29%) patients were IHC ER-PgR-. ER was not univariately associated with DFS (qPCR, P = 0.19; IHC, P = 0.08), while PgR was (qPCR, P = 0.09; IHC, P = 0.04). For BC patients, neither receptor was univariately associated with DFS: for ER, PCR, P = 0.36, IHC, P = 0.24; while for PgR, qPCR, P = 0.17, IHC, P = 0.31. Multivariately, MA.12 patients randomized to tamoxifen had significantly better DFS (P = 0.002 to 0.005) than placebo. Meanwhile, jointly ER and PgR were not associated with DFS whether assessed by qPCR or by IHC in all patients, or in the subgroup of patients with IHC positive stain, for pooled or separate treatment arms. Different results by type of continuous unit supported the concept of ER level being relevant for medical decision-making. For postmenopausal BC tamoxifen patients, higher qPCR PgR was weakly associated with better DFS (P = 0.06).
MA.12 pre-menopausal patients in a placebo-controlled tamoxifen trial had similar multivariate prognostic effects with statistically standardized hormone receptors when tumours were assayed by qPCR or IHC, for hormone receptor +/- and + tumours. The BC post-menopausal tamoxifen cohort did not exhibit a significant prognostic association of ER or PgR with DFS. Adjunctive statistical standardization is currently under investigation in other NCIC CTG endocrine trials.
Accurate laboratory diagnosis of malaria species in returning travelers is paramount in the treatment of this potentially fatal infectious disease.
Materials and methods
A total of 466 blood specimens from returning travelers to Africa, Asia, and South/Central America with suspected malaria infection were collected between 2007 and 2009 at the reference public health laboratory. These specimens were assessed by reference microscopy, multipex real-time quantitative polymerase chain reaction (QPCR), and two rapid diagnostic immuno-chromatographic tests (ICT) in a blinded manner. Key clinical laboratory parameters such as limit of detection (LOD) analysis on clinical specimens by parasite stage, inter-reader variability of ICTs, staffing implications, quality assurance and cost analysis were evaluated.
QPCR is the most analytically sensitive method (sensitivity 99.41%), followed by CARESTART (sensitivity 88.24%), and BINAXNOW (sensitivity 86.47%) for the diagnosis of malaria in returning travelers when compared to reference microscopy. However, microscopy was unable to specifically identify Plasmodia spp. in 18 out of 170 positive samples by QPCR. Moreover, the 17 samples that were negative by microscopy and positive by QPCR were also positive by ICTs. Quality assurance was achieved for QPCR by exchanging a blinded proficiency panel with another reference laboratory. The Kappa value of inter-reader variability among three readers for BINAXNOW and CARESTART was calculated to be 0.872 and 0.898 respectively. Serial dilution studies demonstrated that the QPCR cycle threshold correlates linearly with parasitemia (R2 = 0.9746) in a clinically relevant dynamic range and retains a LOD of 11 rDNA copies/μl for P. falciparum, which was several log lower than reference microscopy and ICTs. LOD for QPCR is affected not only by parasitemia but the parasite stage distribution of each clinical specimen. QPCR was approximately 6-fold more costly than reference microscopy.
These data suggest that multiplex QPCR although more costly confers a significant diagnostic advantage in terms of LOD compared to reference microscopy and ICTs for all four species. Quality assurance of QPCR is essential to the maintenance of proficiency in the clinical laboratory. ICTs showed good concordance between readers however lacked sensitivity for non-falciparum species due to antigenic differences and low parasitemia.
Multiplex QPCR but not ICTs is an essential adjunct to microscopy in the reference laboratory detection of malaria species specifically due to the superior LOD. ICTs are better suited to the non-reference laboratory where lower specimen volumes challenge microscopy proficiency in the non-endemic setting.
Disseminated tumor cells (DTCs) have potential to predict the effect of adjuvant treatment. The purpose of this study was to compare two methods, reverse transcription quantitative PCR (RT-qPCR) and immunocytochemisty (ICC), for detecting breast cancer DTCs in bone marrow (BM) from early breast cancer patients.
We investigated a subset (n = 313) of BM samples obtained from 271 early breast cancer patients in the “Secondary Adjuvant Taxotere Treatment” (SATT)-trial. All patients in this study had node positive or intermediate/high-risk node negative non-metastatic disease. The DTCs were detected by ICC using AE1-AE3 anti-cytokeratin monoclonal antibodies. Patients with DTCs detected in their BM by ICC after standard adjuvant fluorouracil, cyclophosphamide, epirubicin (FEC) chemotherapy were offered docetaxel treatment. For comparison, 5 × 106 mononuclear cells from the aliquoted BM samples were also analyzed by RT-qPCR using a multimarker (MM) assay based on the tumor cell mRNA markers keratin 19 (KRT19), mammaglobin A (hMAM), and TWIST1. In the MM-assay, a sample was defined as positive for DTCs if at least one of the mRNA markers was positive.
The MM RT-qPCR assay identified DTCs in 124 (40%) of the 313 BM samples compared with 23/313 (7%) of the samples analyzed by ICC. The concordance between the MM RT-qPCR and ICC was 61% (Kappa value = 0.04) and twelve of the BM samples were positive by both methods. By RT-qPCR, 46/313 (15%) samples were positive for KRT19, 97/313 (31%) for TWIST1, and 3/313 (1%) for hMAM mRNA. There were no statistically significant associations between the individual mRNA markers.
The RT-qPCR based method demonstrated more DTC-positive samples than ICC. The relatively low concordance of positive DTC-status between the two different assessment methods suggests that they may be complementary. The clinical relevance of the methods will be evaluated based on future clinical outcome data.
Disseminated tumor cells; RT-qPCR; Immunocytochemistry; Breast cancer; Bone marrow
Quantitative Polymerase Chain Reaction (qPCR) is a well-established method for quantifying levels of gene expression, but has not been routinely applied to the detection of constitutional copy number alterations of human genomic DNA. Microdeletions or microduplications of the human genome are associated with a variety of genetic disorders. Although, clinical laboratories routinely use fluorescence in situ hybridization (FISH) to identify such cryptic genomic alterations, there remains a significant number of individuals in which constitutional genomic imbalance is suspected, based on clinical parameters, but cannot be readily detected using current cytogenetic techniques.
In this study, a novel application for real-time qPCR is presented that can be used to reproducibly detect chromosomal microdeletions and microduplications. This approach was applied to DNA from a series of patient samples and controls to validate genomic copy number alteration at cytoband 22q11. The study group comprised 12 patients with clinical symptoms of chromosome 22q11 deletion syndrome (22q11DS), 1 patient trisomic for 22q11 and 4 normal controls. 6 of the patients (group 1) had known hemizygous deletions, as detected by standard diagnostic FISH, whilst the remaining 6 patients (group 2) were classified as 22q11DS negative using the clinical FISH assay. Screening of the patients and controls with a set of 10 real time qPCR primers, spanning the 22q11.2-deleted region and flanking sequence, confirmed the FISH assay results for all patients with 100% concordance. Moreover, this qPCR enabled a refinement of the region of deletion at 22q11. Analysis of DNA from chromosome 22 trisomic sample demonstrated genomic duplication within 22q11.
In this paper we present a qPCR approach for the detection of chromosomal microdeletions and microduplications. The strategic use of in silico modelling for qPCR primer design to avoid regions of repetitive DNA, whilst providing a level of genomic resolution greater than standard cytogenetic assays. The implementation of qPCR detection in clinical laboratories will address the need to replace complex, expensive and time consuming FISH screening to detect genomic microdeletions or duplications of clinical importance.
Numerous models for use in interpreting quantitative PCR (qPCR) data are present in recent literature. The most commonly used models assume the amplification in qPCR is exponential and fit an exponential model with a constant rate of increase to a select part of the curve. Kinetic theory may be used to model the annealing phase and does not assume constant efficiency of amplification. Mechanistic models describing the annealing phase with kinetic theory offer the most potential for accurate interpretation of qPCR data. Even so, they have not been thoroughly investigated and are rarely used for interpretation of qPCR data. New results for kinetic modeling of qPCR are presented.
Two models are presented in which the efficiency of amplification is based on equilibrium solutions for the annealing phase of the qPCR process. Model 1 assumes annealing of complementary targets strands and annealing of target and primers are both reversible reactions and reach a dynamic equilibrium. Model 2 assumes all annealing reactions are nonreversible and equilibrium is static. Both models include the effect of primer concentration during the annealing phase. Analytic formulae are given for the equilibrium values of all single and double stranded molecules at the end of the annealing step. The equilibrium values are then used in a stepwise method to describe the whole qPCR process. Rate constants of kinetic models are the same for solutions that are identical except for possibly having different initial target concentrations. Analysis of qPCR curves from such solutions are thus analyzed by simultaneous non-linear curve fitting with the same rate constant values applying to all curves and each curve having a unique value for initial target concentration. The models were fit to two data sets for which the true initial target concentrations are known. Both models give better fit to observed qPCR data than other kinetic models present in the literature. They also give better estimates of initial target concentration. Model 1 was found to be slightly more robust than model 2 giving better estimates of initial target concentration when estimation of parameters was done for qPCR curves with very different initial target concentration. Both models may be used to estimate the initial absolute concentration of target sequence when a standard curve is not available.
It is argued that the kinetic approach to modeling and interpreting quantitative PCR data has the potential to give more precise estimates of the true initial target concentrations than other methods currently used for analysis of qPCR data. The two models presented here give a unified model of the qPCR process in that they explain the shape of the qPCR curve for a wide variety of initial target concentrations.
Quantitative polymerase chain reaction; qPCR; Kinetic model
EndoPredict (EP) is a clinically validated multianalyte gene expression test to predict distant metastasis in ER-positive, HER2-negative breast cancer treated with endocrine therapy alone. The test is based on the combined analysis of 12 genes in formalin-fixed, paraffin-embedded (FFPE) tissue by reverse transcription-quantitative real-time PCR (RT-qPCR). Recently, it was shown that EP is feasible for reliable decentralized assessment of gene expression. The aim of this study was the analytical validation of the performance characteristics of the assay and its verification in a molecular-pathological routine laboratory.
Gene expression values to calculate the EP score were assayed by one-step RT-qPCR using RNA from FFPE tumor tissue. Limit of blank, limit of detection, linear range, and PCR efficiency were assessed for each of the 12 PCR assays using serial samples dilutions. Different breast cancer samples were used to evaluate RNA input range, precision and inter-laboratory variability.
PCR assays were linear up to Cq values between 35.1 and 37.2. Amplification efficiencies ranged from 75% to 101%. The RNA input range without considerable change of the EP score was between 0.16 and 18.5 ng/μl. Analysis of precision (variation of day, day time, instrument, operator, reagent lots) resulted in a total noise (standard deviation) of 0.16 EP score units on a scale from 0 to 15. The major part of the total noise (SD 0.14) was caused by the replicate-to-replicate noise of the PCR assays (repeatability) and was not associated with different operating conditions (reproducibility). Performance characteristics established in the manufacturer’s laboratory were verified in a routine molecular pathology laboratory. Comparison of 10 tumor samples analyzed in two different laboratories showed a Pearson coefficient of 0.995 and a mean deviation of 0.15 score units.
The EP test showed reproducible performance characteristics with good precision and negligible laboratory-to-laboratory variation. This study provides further evidence that the EP test is suitable for decentralized testing in specialized molecular pathological laboratories instead of a reference laboratory. This is a unique feature and a technical advance in comparison with existing RNA-based prognostic multigene expression tests.
Breast cancer; Prognostic multigene expression test; Analytical validation; PCR; Pathology
Since its introduction quantitative real-time polymerase chain reaction (qPCR) has become the standard method for quantification of gene expression. Its high sensitivity, large dynamic range, and accuracy led to the development of numerous applications with an increasing number of samples to be analyzed. Data analysis consists of a number of steps, which have to be carried out in several different applications. Currently, no single tool is available which incorporates storage, management, and multiple methods covering the complete analysis pipeline.
QPCR is a versatile web-based Java application that allows to store, manage, and analyze data from relative quantification qPCR experiments. It comprises a parser to import generated data from qPCR instruments and includes a variety of analysis methods to calculate cycle-threshold and amplification efficiency values. The analysis pipeline includes technical and biological replicate handling, incorporation of sample or gene specific efficiency, normalization using single or multiple reference genes, inter-run calibration, and fold change calculation. Moreover, the application supports assessment of error propagation throughout all analysis steps and allows conducting statistical tests on biological replicates. Results can be visualized in customizable charts and exported for further investigation.
We have developed a web-based system designed to enhance and facilitate the analysis of qPCR experiments. It covers the complete analysis workflow combining parsing, analysis, and generation of charts into one single application. The system is freely available at
Cell-associated (CA) HIV-1 RNA is considered a potential marker for assessment of viral reservoir dynamics and antiretroviral therapy (ART) response in HIV-infected patients. Recent studies employed sensitive seminested real-time quantitative (q)PCR to quantify CA HIV-1 RNA. Digital PCR has been recently described as an alternative PCR-based technique for absolute quantification with higher accuracy compared to qPCR. Here, a comparison was made between the droplet digital PCR (ddPCR) and the seminested qPCR for quantification of unspliced (us) and multiply spliced (ms) CA HIV-1 RNA. Synthetic RNA standards and CA HIV-1 RNA from infected patients on and off ART (N = 34) were quantified with both methods. Correlations were observed between the methods both for serially diluted synthetic standards (usRNA: R2 = 0.97, msRNA: R2 = 0.92) and patient-derived samples (usRNA: R2 = 0.51, msRNA: R2 = 0.87). Seminested qPCR showed better quantitative linearity, accuracy and sensitivity in the quantification of synthetic standards than ddPCR, especially in the lower quantification ranges. Both methods demonstrated equally high detection rate of usRNA in patient samples on and off ART (91%), whereas ddPCR detected msRNA in larger proportion of samples from ART-treated patients (p = 0.13). We observed an average agreement between the methods for usRNA quantification in patient samples, albeit with a large standard deviation (bias = 0.05±0.75 log10). However, a bias of 0.94±0.36 log10 was observed for msRNA. No-template controls were consistently negative in the seminested qPCR, but yielded a positive ddPCR signal for some wells. Therefore, the false positive signals may have affected the detection power of ddPCR in this study. Digital PCR is promising for HIV nucleic acid quantification, but the false positive signals need further attention. Quantitative assays for CA HIV RNA have the potential to improve monitoring of patients on ART and to be used in clinical studies aimed at HIV eradication, but should be cross-validated by multiple laboratories prior to wider use.
MicroRNAs (miRNAs) represent a growing class of small non-coding RNAs that are important regulators of gene expression in both plants and animals. Studies have shown that miRNAs play a critical role in human cancer and they can influence the level of cell proliferation and apoptosis by modulating gene expression. Currently, methods for the detection and measurement of miRNA expression include small and moderate-throughput technologies, such as standard quantitative PCR and microarray based analysis. However, these methods have several limitations when used in large clinical studies where a high-throughput and highly quantitative technology needed for the efficient characterization of a large number of miRNA transcripts in clinical samples. Furthermore, archival formalin fixed, paraffin embedded (FFPE) samples are increasingly becoming the primary resource for gene expression studies because fresh frozen (FF) samples are often difficult to obtain and requires special storage conditions. In this study, we evaluated the miRNA expression levels in FFPE and FF samples as well as several lung cancer cell lines employing a high throughput qPCR-based microfluidic technology. The results were compared to standard qPCR and hybridization-based microarray platforms using the same samples.
We demonstrated highly correlated Ct values between multiplex and singleplex RT reactions in standard qPCR assays for miRNA expression using total RNA from A549 (R = 0.98; p < 0.0001) and H1299 (R = 0.95; p < 0.0001) lung cancer cell lines. The Ct values generated by the microfluidic technology (Fluidigm 48.48 dynamic array systems) resulted in a left-shift toward lower Ct values compared to those observed by ABI 7900 HT (mean difference, 3.79), suggesting that the microfluidic technology exhibited a greater sensitivity. In addition, we show that as little as 10 ng total RNA can be used to reliably detect all 48 or 96 tested miRNAs using a 96-multiplexing RT reaction in both FFPE and FF samples. Finally, we compared miRNA expression measurements in both FFPE and FF samples by qPCR using the 96.96 dynamic array and Affymetrix microarrays. Fold change comparisons for comparable genes between the two platforms indicated that the overall correlation was R = 0.60. The maximum fold change detected by the Affymetrix microarray was 3.5 compared to 13 by the 96.96 dynamic array.
The qPCR-array based microfluidic dynamic array platform can be used in conjunction with multiplexed RT reactions for miRNA gene expression profiling. We showed that this approach is highly reproducible and the results correlate closely with the existing singleplex qPCR platform at a throughput that is 5 to 20 times higher and a sample and reagent usage that was approximately 50-100 times lower than conventional assays. We established optimal conditions for using the Fluidigm microfluidic technology for rapid, cost effective, and customizable arrays for miRNA expression profiling and validation.
Gene expression profiling is an important approach for detecting diagnostic and prognostic biomarkers, and predicting drug safety. The development of a wide range of technologies and platforms for measuring mRNA expression makes the evaluation and standardization of transcriptomic data problematic due to differences in protocols, data processing and analysis methods. Thus, universal RNA standards, such as those developed by the External RNA Controls Consortium (ERCC), are proposed to aid validation of research findings from diverse platforms such as microarrays and RT-qPCR, and play a role in quality control (QC) processes as transcriptomic profiling becomes more commonplace in the clinical setting.
Panels of ERCC RNA standards were constructed in order to test the utility of these reference materials (RMs) for performance characterization of two selected gene expression platforms, and for discrimination of biomarker profiles between groups. The linear range, limits of detection and reproducibility of microarray and RT-qPCR measurements were evaluated using panels of RNA standards. Transcripts of low abundance (≤ 10 copies/ng total RNA) showed more than double the technical variability compared to higher copy number transcripts on both platforms. Microarray profiling of two simulated 'normal' and 'disease' panels, each consisting of eight different RNA standards, yielded robust discrimination between the panels and between standards with varying fold change ratios, showing no systematic effects due to different labelling and hybridization runs. Also, comparison of microarray and RT-qPCR data for fold changes showed agreement for the two platforms.
ERCC RNA standards provide a generic means of evaluating different aspects of platform performance, and can provide information on the technical variation associated with quantification of biomarkers expressed at different levels of physiological abundance. Distinct panels of standards serve as an ideal quality control tool kit for determining the accuracy of fold change cut-off threshold and the impact of experimentally-derived noise on the discrimination of normal and disease profiles.
Comparison studies between different analytical methodologies for circulating tumor cells (CTC) detection and molecular characterization are urgently needed, since standardization of assays is essential before their use in clinical practice.
We compared three different CTC molecular assays. To avoid discrepancies due to pre-analytical errors we used the same cDNAs throughout our study. CTC were isolated using anti-EpCAM and anti-MUC1 coated magnetic beads from 2 × 5 ml of peripheral blood of 254 early and 51 metastatic breast cancer patients and 30 healthy individuals. The same cDNAs were analyzed by: a) singleplex RT-qPCR assay for CK-19; b) multiplex RT-qPCR for CK-19, HER-2, MAGE- A3, and PBGD; and c) a commercially available molecular assay (AdnaTest BreastCancer) for GA733-2, MUC-1, HER-2 and beta-actin.
In early breast cancer, CK-19 RT-qPCR, multiplex RT-qPCR and the AdnaTest, were positive for the presence of CTC in 14.2%, 22.8% and 16.5% subjects, respectively. The concordance between the AdnaTest and CK-19 RT-qPCR was 72.4% while between the AdnaTest and multiplex RT-qPCR was 64.6%. In patients with overt metastasis, CK-19 RT-qPCR, multiplex RT-qPCR and the AdnaTest were positive in 41.2%, 39.2% and 54.9% patients, respectively. The concordance between the AdnaTest and CK-19 RT-qPCR was 70.6% while between the AdnaTest and multiplex RT-qPCR was 68.6%.
All CTC assays gave similar results in about 70% of cases. Better agreement was found in the metastatic setting, possibly explained by the higher tumor load in this group. Discordances could be attributed to the different gene transcripts used to evaluate CTC positivity. Our results indicate the importance of CTC heterogeneity for their detection by different analytical methodologies.
Whole transcriptome RNA-sequencing is a powerful tool, but is costly and yields complex data sets that limit its utility in molecular diagnostic testing. A targeted quantitative RNA-sequencing method that is reproducible and reduces the number of sequencing reads required to measure transcripts over the full range of expression would be better suited to diagnostic testing. Toward this goal, we developed a competitive multiplex PCR-based amplicon sequencing library preparation method that a) targets only the sequences of interest and b) controls for inter-target variation in PCR amplification during library preparation by measuring each transcript native template relative to a known number of synthetic competitive template internal standard copies. To determine the utility of this method, we intentionally selected PCR conditions that would cause transcript amplification products (amplicons) to converge toward equimolar concentrations (normalization) during library preparation. We then tested whether this approach would enable accurate and reproducible quantification of each transcript across multiple library preparations, and at the same time reduce (through normalization) total sequencing reads required for quantification of transcript targets across a large range of expression. We demonstrate excellent reproducibility (R2 = 0.997) with 97% accuracy to detect 2-fold change using External RNA Controls Consortium (ERCC) reference materials; high inter-day, inter-site and inter-library concordance (R2 = 0.97–0.99) using FDA Sequencing Quality Control (SEQC) reference materials; and cross-platform concordance with both TaqMan qPCR (R2 = 0.96) and whole transcriptome RNA-sequencing following “traditional” library preparation using Illumina NGS kits (R2 = 0.94). Using this method, sequencing reads required to accurately quantify more than 100 targeted transcripts expressed over a 107-fold range was reduced more than 10,000-fold, from 2.3×109 to 1.4×105 sequencing reads. These studies demonstrate that the competitive multiplex-PCR amplicon library preparation method presented here provides the quality control, reproducibility, and reduced sequencing reads necessary for development and implementation of targeted quantitative RNA-sequencing biomarkers in molecular diagnostic testing.
MicroRNAs (miRNAs) have critical functions in various biological processes. MiRNA profiling is an important tool for the identification of differentially expressed miRNAs in normal cellular and disease processes. A technical challenge remains for high-throughput miRNA expression analysis as the number of miRNAs continues to increase with in silico prediction and experimental verification. Our study critically evaluated the performance of a novel miRNA expression profiling approach, quantitative RT-PCR array (qPCR-array), compared to miRNA detection with oligonucleotide microchip (microarray).
High reproducibility with qPCR-array was demonstrated by comparing replicate results from the same RNA sample. Pre-amplification of the miRNA cDNA improved sensitivity of the qPCR-array and increased the number of detectable miRNAs. Furthermore, the relative expression levels of miRNAs were maintained after pre-amplification. When the performance of qPCR-array and microarrays were compared using different aliquots of the same RNA, a low correlation between the two methods (r = -0.443) indicated considerable variability between the two assay platforms. Higher variation between replicates was observed in miRNAs with low expression in both assays. Finally, a higher false positive rate of differential miRNA expression was observed using the microarray compared to the qPCR-array.
Our studies demonstrated high reproducibility of TaqMan qPCR-array. Comparison between different reverse transcription reactions and qPCR-arrays performed on different days indicated that reverse transcription reactions did not introduce significant variation in the results. The use of cDNA pre-amplification increased the sensitivity of miRNA detection. Although there was variability associated with pre-amplification in low abundance miRNAs, the latter did not involve any systemic bias in the estimation of miRNA expression. Comparison between microarray and qPCR-array indicated superior sensitivity and specificity of qPCR-array.
Identification of predictive markers of response to treatment is a major objective in breast cancer. A major problem in clinical sampling is the variability of RNA templates, requiring accurate management of tumour material and subsequent analyses for future translation in clinical practice. Our aim was to establish the feasibility and reliability of high throughput RNA analysis in a prospective trial.
This study was conducted on RNA from initial biopsies, in a prospective trial of neoadjuvant chemotherapy in 327 patients with inoperable breast cancer. Four independent centres included patients and samples. Human U133 GeneChips plus 2.0 arrays for transcriptome analysis and quantitative RT-qPCR of 45 target genes and 6 reference genes were analysed on total RNA.
Thirty seven samples were excluded because i) they contained less than 30% malignant cells, or ii) they provided RNA Integrity Number (RIN) of poor quality. Among the 290 remaining cases, taking into account strict quality control criteria initially defined to ensure good quality of sampling, 78% and 82% samples were eligible for transcriptome and RT-qPCR analyses, respectively. For RT-qPCR, efficiency was corrected by using standard curves for each gene and each plate. It was greater than 90% for all genes. Clustering analysis highlighted relevant breast cancer phenotypes for both techniques (ER+, PR+, HER2+, triple negative). Interestingly, clustering on trancriptome data also demonstrated a "centre effect", probably due to the sampling or extraction methods used in on of the centres. Conversely, the calibration of RT-qPCR analysis led to the centre effect withdrawing, allowing multicentre analysis of gene transcripts with high accuracy.
Our data showed that strict quality criteria for RNA integrity assessment and well calibrated and standardized RT-qPCR allows multicentre analysis of genes transcripts with high accuracy in the clinical context. More stringent criteria are needed for transcriptome analysis for clinical applications.
neoadjuvant setting; transcriptome; RT-qPCR; breast cancer; quality criteria
Transcriptome data from quantitative PCR (Q-PCR) and DNA microarrays are typically obtained from a fixed amount of RNA collected per sample. Therefore, variations in tissue cellularity and RNA yield across samples in an experimental series compromise accurate determination of the absolute level of each mRNA species per cell in any sample. Since mRNAs are copied from genomic DNA, the simplest way to express mRNA level would be as copy number per template DNA, or more practically, as copy number per cell.
Here we report a method (designated the "Percellome" method) for normalizing the expression of mRNA values in biological samples. It provides a "per cell" readout in mRNA copy number and is applicable to both quantitative PCR (Q-PCR) and DNA microarray studies. The genomic DNA content of each sample homogenate was measured from a small aliquot to derive the number of cells in the sample. A cocktail of five external spike RNAs admixed in a dose-graded manner (dose-graded spike cocktail; GSC) was prepared and added to each homogenate in proportion to its DNA content. In this way, the spike mRNAs represented absolute copy numbers per cell in the sample. The signals from the five spike mRNAs were used as a dose-response standard curve for each sample, enabling us to convert all the signals measured to copy numbers per cell in an expression profile-independent manner. A series of samples was measured by Q-PCR and Affymetrix GeneChip microarrays using this Percellome method, and the results showed up to 90 % concordance.
Percellome data can be compared directly among samples and among different studies, and between different platforms, without further normalization. Therefore, "percellome" normalization can serve as a standard method for exchanging and comparing data across different platforms and among different laboratories.
The use of malaria-specific quantitative real-time PCR (qPCR) is increasing due to its high sensitivity, speciation and quantification of malaria parasites. However, due to the lack of consensus or standardized methods in performing qPCR, it is difficult to evaluate and/or compare the quality of work reported by different authors for a cross-study and/or cross-platform assay analysis.
The performances of seven published qPCR assays that detect Plasmodium spp or Plasmodium falciparum were compared using standard DNA and samples from a clinical trial. Amplification and qPCR measurements were performed using the Applied Biosystems 7500 Fast Real-Time PCR System. All the analyses were automatically established using the default settings. For the TaqMan probe format, the assays were performed in the background of QuantiFast Probe Master Mix whereas in SYBR Green format, the assays were performed in the background of QuantiFast SYBR Green Master Mix and QuantiTect SYBR Green Master Mix background.
Assays with high PCR efficiencies outperformed those with low efficiencies in all categories including sensitivity, precision and consistency regardless of the assay format and background. With the exception of one assay, all assays evaluated showed lower sensitivity compared to what have been published. When samples from a malaria challenge study were analysed, the qPCR assay with the overall best performance detected parasites in subjects earliest and with most consistency.
The data demonstrate the need for increased consensus and guidelines that will encourage better experimental practices, allowing more consistent and unambiguous interpretation of qPCR results.
Over the past few years, there has been an increasing demand for rapid and simple diagnostic tools that can be applied outside centralized laboratories by using transportable devices. In veterinary medicine, such mobile test systems would circumvent barriers associated with the transportation of samples and significantly reduce the time to diagnose important infectious animal diseases. Among a wide range of available technologies, high-speed real-time reverse transcriptase quantitative PCR (RT-qPCR) and the two isothermal amplification techniques loop-mediated isothermal amplification (LAMP) and recombinase polymerase amplification (RPA) represent three promising candidates for integration into mobile pen-side tests. The aim of this study was to investigate the performance of these amplification strategies and to evaluate their suitability for field application. In order to enable a valid comparison, novel pathogen-specific assays have been developed for the detection of Schmallenberg virus and bovine viral diarrhea virus. The newly developed assays were evaluated in comparison with established standard RT-qPCR using samples from experimentally or field-infected animals. Even though all assays allowed detection of the target virus in less than 30 min, major differences were revealed concerning sensitivity, specificity, robustness, testing time, and complexity of assay design. These findings indicated that the success of an assay will depend on the integrated amplification technology. Therefore, the application-specific pros and cons of each method that were identified during this study provide very valuable insights for future development and optimization of pen-side tests.