A standardised methodology for the extraction and quantification of cell-free DNA in cerebrospinal fluid and application to evaluation of Alzheimer's disease and brain cancers.

Cerebrospinal fluid (CSF) is a source of diagnostic biomarkers for a range of neurological conditions. Cell-free DNA (cfDNA) is detected in CSF and differences in the concentration of cell-free mitochondrial DNA have been reported in studies of neurodegenerative disorders including Alzheimer's disease (AD). However, the influence of pre-analytical steps has not been investigated for cfDNA in CSF and there is no standardised approach for quantification of total cfDNA (copies of nuclear genome or mitochondria-derived gene targets). In this study, the suitability of four extraction methods was evaluated: QIAamp Circulating Nucleic Acid (Qiagen), Quick-cfDNA Serum & Plasma (Zymo), NucleoSnap® DNA Plasma (Macherey-Nagel) and Plasma/Serum Circulating DNA Purification Mini (Norgen) kits, for cfDNA extraction from CSF of controls and AD dementia patients, utilising a spike-in control for extraction efficiency and fragment size. One of the optimal extraction methods was applied to a comparison of cfDNA concentrations in CSF from control subjects, AD dementia and primary and secondary brain tumour patients. Extraction efficiency based on spike-in recovery was similar in all three groups whilst both endogenous mitochondrial and nucleus-derived cfDNA was significantly higher in CSF from cancer patients compared to control and AD groups, which typically contained < 100 genome copies/mL. This study shows that it is feasible to measure low concentration nuclear and mitochondrial gene targets in CSF and that normalisation of extraction yield can help control pre-analytical variability influencing biomarker measurements.

The performance of human cytomegalovirus digital PCR reference measurement procedure in seven external quality assessment schemes over four years.

A candidate digital PCR (dPCR)-based reference measurement procedure for quantification of human cytomegalovirus (hCMV) was evaluated in 10 viral load comparison schemes (seven external quality assessment (EQA) and three additional training schemes) organized by INSTAND e.V. over four years (between September 2014 and March 2018). Four metrology institutes participated in these schemes using the same extraction method and dPCR measurement procedure for the hCMV specific target sequence of UL54 gene. The calibration independent reference measurement procedure results from the metrology institutes were compared to the results of the clinical diagnostic laboratories applying hCMV qPCR measurement procedures calibrated to reference materials. While the criteria for the acceptable deviation from the target value interval for INSTAND's EQA schemes is from -0.8 log10 to +0.8 log10, the majority of dPCR results were between -0.2 log10 to +0.2 log10. Only 4 out of 45 results exceeded this interval with the maximum deviation of -0.542 log10. In the training schemes containing samples with lower hCMV concentrations, more than half of the results deviated less than ±0.2 log10 from the target value, while more than 95% deviated less than ±0.4 log10 from the target value. Evaluation of intra- and inter-laboratory variation of dPCR results confirmed high reproducibility and trueness of the method. This work demonstrates that dPCR has the potential to act as a calibration independent reference measurement procedure for the value assignment of hCMV calibration and reference materials to support qPCR calibration as well as ultimately for routine hCMV load testing.

Assessment of Digital PCR as a Primary Reference Measurement Procedure to Support Advances in Precision Medicine.

BACKGROUND: Genetic testing of tumor tissue and circulating cell-free DNA for somatic variants guides patient treatment of many cancers. Such measurements will be fundamental in the future support of precision medicine. However, there are currently no primary reference measurement procedures available for nucleic acid quantification that would support translation of tests for circulating tumor DNA into routine use. METHODS: We assessed the accuracy of digital PCR (dPCR) for copy number quantification of a frequently occurring single-nucleotide variant in colorectal cancer (KRAS c.35G>A, p.Gly12Asp, from hereon termed G12D) by evaluating potential sources of uncertainty that influence dPCR measurement. RESULTS: Concentration values for samples of KRAS G12D and wild-type plasmid templates varied by <1.2-fold when measured using 5 different assays with varying detection chemistry (hydrolysis, scorpion probes, and intercalating dyes) and <1.3-fold with 4 commercial dPCR platforms. Measurement trueness of a selected dPCR assay and platform was validated by comparison with an orthogonal method (inductively coupled plasma mass spectrometry). The candidate dPCR reference measurement procedure showed linear quantification over a wide range of copies per reaction and high repeatability and interlaboratory reproducibility (CV, 2%-8% and 5%-10%, respectively). CONCLUSIONS: This work validates dPCR as an SI-traceable reference measurement procedure based on enumeration and demonstrates how it can be applied for assignment of copy number concentration and fractional abundance values to DNA reference materials in an aqueous solution. High-accuracy measurements using dPCR will support the implementation and traceable standardization of molecular diagnostic procedures needed for advancements in precision medicine.

Control Materials and Digital PCR Methods for Evaluation of Circulating Cell-Free DNA Extractions from Plasma.

Cell-free DNA is an accessible source of genetic material found naturally in plasma that could be used in many diagnostic applications. Translation of cfDNA analysis methods from research laboratories into the clinic would benefit from controls for monitoring the efficiency of patient sample purification and for quality control of the whole workflow from extraction through to analysis. Here we describe two types of control materials that can be "spiked" into plasma samples to monitor and evaluate different aspects of the workflow. The first control material is an internal control that enables evaluation of extraction efficiency, fragment size bias, and sample inhibition. The second control material serves as a parallel quality control material for measurement of specific genetic targets such as tumor mutations.

International Interlaboratory Digital PCR Study Demonstrating High Reproducibility for the Measurement of a Rare Sequence Variant.

This study tested the claim that digital PCR (dPCR) can offer highly reproducible quantitative measurements in disparate laboratories. Twenty-one laboratories measured four blinded samples containing different quantities of a KRAS fragment encoding G12D, an important genetic marker for guiding therapy of certain cancers. This marker is challenging to quantify reproducibly using quantitative PCR (qPCR) or next generation sequencing (NGS) due to the presence of competing wild type sequences and the need for calibration. Using dPCR, 18 laboratories were able to quantify the G12D marker within 12% of each other in all samples. Three laboratories appeared to measure consistently outlying results; however, proper application of a follow-up analysis recommendation rectified their data. Our findings show that dPCR has demonstrable reproducibility across a large number of laboratories without calibration. This could enable the reproducible application of molecular stratification to guide therapy and, potentially, for molecular diagnostics.

Digital PCR dynamic range is approaching that of real-time quantitative PCR.

Digital PCR (dPCR) has been reported to be more precise and sensitive than real-time quantitative PCR (qPCR) in a variety of models and applications. However, in the majority of commercially available dPCR platforms, the dynamic range is dependent on the number of partitions analysed and so is typically limited to four orders of magnitude; reduced compared with the typical seven orders achievable by qPCR. Using two different biological models (HIV DNA analysis and KRAS genotyping), we have demonstrated that the RainDrop Digital PCR System (RainDance Technologies) is capable of performing accurate and precise quantification over six orders of magnitude thereby approaching that achievable by qPCR.

The use of digital PCR to improve the application of quantitative molecular diagnostic methods for tuberculosis.

BACKGROUND: Real-time PCR (qPCR) based methods, such as the Xpert MTB/RIF, are increasingly being used to diagnose tuberculosis (TB). While qualitative methods are adequate for diagnosis, the therapeutic monitoring of TB patients requires quantitative methods currently performed using smear microscopy. The potential use of quantitative molecular measurements for therapeutic monitoring has been investigated but findings have been variable and inconclusive. The lack of an adequate reference method and reference materials is a barrier to understanding the source of such disagreement. Digital PCR (dPCR) offers the potential for an accurate method for quantification of specific DNA sequences in reference materials which can be used to evaluate quantitative molecular methods for TB treatment monitoring. METHODS: To assess a novel approach for the development of quality assurance materials we used dPCR to quantify specific DNA sequences in a range of prototype reference materials and evaluated accuracy between different laboratories and instruments. The materials were then also used to evaluate the quantitative performance of qPCR and Xpert MTB/RIF in eight clinical testing laboratories. RESULTS: dPCR was found to provide results in good agreement with the other methods tested and to be highly reproducible between laboratories without calibration even when using different instruments. When the reference materials were analysed with qPCR and Xpert MTB/RIF by clinical laboratories, all laboratories were able to correctly rank the reference materials according to concentration, however there was a marked difference in the measured magnitude. CONCLUSIONS: TB is a disease where the quantification of the pathogen could lead to better patient management and qPCR methods offer the potential to rapidly perform such analysis. However, our findings suggest that when precisely characterised materials are used to evaluate qPCR methods, the measurement result variation is too high to determine whether molecular quantification of Mycobacterium tuberculosis would provide a clinically useful readout. The methods described in this study provide a means by which the technical performance of quantitative molecular methods can be evaluated independently of clinical variability to improve accuracy of measurement results. These will assist in ultimately increasing the likelihood that such approaches could be used to improve patient management of TB.

An international comparability study on quantification of mRNA gene expression ratios: CCQM-P103.1.

Measurement of RNA can be used to study and monitor a range of infectious and non-communicable diseases, with profiling of multiple gene expression mRNA transcripts being increasingly applied to cancer stratification and prognosis. An international comparison study (Consultative Committee for Amount of Substance (CCQM)-P103.1) was performed in order to evaluate the comparability of measurements of RNA copy number ratio for multiple gene targets between two samples. Six exogenous synthetic targets comprising of External RNA Control Consortium (ERCC) standards were measured alongside transcripts for three endogenous gene targets present in the background of human cell line RNA. The study was carried out under the auspices of the Nucleic Acids (formerly Bioanalysis) Working Group of the CCQM. It was coordinated by LGC (United Kingdom) with the support of National Institute of Standards and Technology (USA) and results were submitted from thirteen National Metrology Institutes and Designated Institutes. The majority of laboratories performed RNA measurements using RT-qPCR, with datasets also being submitted by two laboratories based on reverse transcription digital polymerase chain reaction and one laboratory using a next-generation sequencing method. In RT-qPCR analysis, the RNA copy number ratios between the two samples were quantified using either a standard curve or a relative quantification approach. In general, good agreement was observed between the reported results of ERCC RNA copy number ratio measurements. Measurements of the RNA copy number ratios for endogenous genes between the two samples were also consistent between the majority of laboratories. Some differences in the reported values and confidence intervals ('measurement uncertainties') were noted which may be attributable to choice of measurement method or quantification approach. This highlights the need for standardised practices for the calculation of fold change ratios and uncertainties in the area of gene expression profiling.

Highly reproducible absolute quantification of Mycobacterium tuberculosis complex by digital PCR.

Digital PCR (dPCR) offers absolute quantification through the limiting dilution of template nucleic acid molecules and has the potential to offer high reproducibility. However, the robustness of dPCR has yet to be evaluated using complex genomes to compare different dPCR methods and platforms. We used DNA templates from the pathogen Mycobacterium tuberculosis to evaluate the impact of template type, master mixes, primer pairs and, crucially, extraction methods on dPCR performance. Performance was compared between the chip (BioMark) and droplet (QX100) formats. In the absence of any external calibration, dPCR measurements were generally consistent within ∼2-fold between different master mixes and primers. Template DNA integrity could influence dPCR performance: high molecular weight gDNA resulted in underperformance of one master mix, while restriction digestion of a low molecular weight sample also caused underestimation. Good concordance (≤1.5-fold difference) was observed between chip and droplet formats. Platform precision was in agreement with predicted Poisson error based on partition number, but this was a minor component (<10%) of the total variance when extraction was included. dPCR offers a robust reproducible method for DNA measurement; however, as a predominant source of error, the process of DNA extraction will need to be controlled with suitable calibrators to maximize agreement between laboratories.

Standardization of Nucleic Acid Tests for Clinical Measurements of Bacteria and Viruses.

Nucleic acid-based tests for infectious diseases currently used in the clinical laboratory and in point-of-care devices are diverse. Measurement challenges associated with standardization of quantitative viral load testing are discussed in relation to human cytomegalovirus, BK virus, and Epstein-Barr virus, while the importance of defining the performance of qualitative methods is illustrated with Mycobacterium tuberculosis and influenza virus. The development of certified reference materials whose values are traceable to higher-order standards and reference measurement procedures, using, for instance, digital PCR, will further contribute to the understanding of analytical performance characteristics and promote clinical data comparability.

Quantification of epigenetic biomarkers: an evaluation of established and emerging methods for DNA methylation analysis.

BACKGROUND: DNA methylation is an important epigenetic mechanism in several human diseases, most notably cancer. The quantitative analysis of DNA methylation patterns has the potential to serve as diagnostic and prognostic biomarkers, however, there is currently a lack of consensus regarding the optimal methodologies to quantify methylation status. To address this issue we compared five analytical methods: (i) MethyLight qPCR, (ii) MethyLight digital PCR (dPCR), methylation-sensitive and -dependent restriction enzyme (MSRE/MDRE) digestion followed by (iii) qPCR or (iv) dPCR, and (v) bisulfite amplicon next generation sequencing (NGS). The techniques were evaluated for linearity, accuracy and precision. RESULTS: MethyLight qPCR displayed the best linearity across the range of tested samples. Observed methylation measured by MethyLight- and MSRE/MDRE-qPCR and -dPCR were not significantly different to expected values whilst bisulfite amplicon NGS analysis over-estimated methylation content. Bisulfite amplicon NGS showed good precision, whilst the lower precision of qPCR and dPCR analysis precluded discrimination of differences of < 25% in methylation status. A novel dPCR MethyLight assay is also described as a potential method for absolute quantification that simultaneously measures both sense and antisense DNA strands following bisulfite treatment. CONCLUSIONS: Our findings comprise a comprehensive benchmark for the quantitative accuracy of key methods for methylation analysis and demonstrate their applicability to the quantification of circulating tumour DNA biomarkers by using sample concentrations that are representative of typical clinical isolates.

Towards standardisation of cell-free DNA measurement in plasma: controls for extraction efficiency, fragment size bias and quantification.

Circulating cell-free DNA (cfDNA) is becoming an important clinical analyte for prenatal testing, cancer diagnosis and cancer monitoring. The extraction stage is critical in ensuring clinical sensitivity of analytical methods measuring minority nucleic acid fractions, such as foetal-derived sequences in predominantly maternal cfDNA. Consequently, quality controls are required for measurement of extraction efficiency, fragment size bias and yield for validation of cfDNA methods. We evaluated the utility of an external DNA spike for monitoring these parameters in a study comparing three specific cfDNA extraction methods [QIAamp circulating nucleic acid (CNA) kit, NucleoSpin Plasma XS (NS) kit and FitAmp plasma/serum DNA isolation (FA) kit] with the commonly used QIAamp DNA blood mini (DBM) kit. We found that the extraction efficiencies of the kits ranked in the order CNA kit > DBM kit > NS kit > FA kit, and the CNA and NS kits gave a better representation of smaller DNA fragments in the extract than the DBM kit. We investigated means of improved reporting of cfDNA yield by comparing quantitative PCR measurements of seven different reference gene assays in plasma samples and validating these with digital PCR. We noted that the cfDNA quantities based on measurement of some target genes (e.g. TERT) were, on average, more than twofold higher than those of other assays (e.g. ERV3). We conclude that analysis and averaging of multiple reference genes using a GeNorm approach gives a more reliable estimate of total cfDNA quantity.

Validation of high-throughput single cell analysis methodology.

High-throughput quantitative polymerase chain reaction (qPCR) approaches enable profiling of multiple genes in single cells, bringing new insights to complex biological processes and offering opportunities for single cell-based monitoring of cancer cells and stem cell-based therapies. However, workflows with well-defined sources of variation are required for clinical diagnostics and testing of tissue-engineered products. In a study of neural stem cell lines, we investigated the performance of lysis, reverse transcription (RT), preamplification (PA), and nanofluidic qPCR steps at the single cell level in terms of efficiency, precision, and limit of detection. We compared protocols using a separate lysis buffer with cell capture directly in RT-PA reagent. The two methods were found to have similar lysis efficiencies, whereas the direct RT-PA approach showed improved precision. Digital PCR was used to relate preamplified template copy numbers to Cq values and reveal where low-quality signals may affect the analysis. We investigated the impact of calibration and data normalization strategies as a means of minimizing the impact of inter-experimental variation on gene expression values and found that both approaches can improve data comparability. This study provides validation and guidance for the application of high-throughput qPCR workflows for gene expression profiling of single cells.

Application of next generation qPCR and sequencing platforms to mRNA biomarker analysis.

Recent years have seen the emergence of new high-throughput PCR and sequencing platforms with the potential to bring analysis of transcriptional biomarkers to a broader range of clinical applications and to provide increasing depth to our understanding of the transcriptome. We present an overview of how to process clinical samples for RNA biomarker analysis in terms of RNA extraction and mRNA enrichment, and guidelines for sample analysis by RT-qPCR and digital PCR using nanofluidic real-time PCR platforms. The options for quantitative gene expression profiling and whole transcriptome sequencing by next generation sequencing are reviewed alongside the bioinformatic considerations for these approaches. Considering the diverse technologies now available for transcriptome analysis, methods for standardising measurements between platforms will be paramount if their diagnostic impact is to be maximised. Therefore, the use of RNA standards and other reference materials is also discussed.

Comparison of reverse transcription-quantitative polymerase chain reaction methods and platforms for single cell gene expression analysis.

Single cell gene expression analysis can provide insights into development and disease progression by profiling individual cellular responses as opposed to reporting the global average of a population. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) is the "gold standard" for the quantification of gene expression levels; however, the technical performance of kits and platforms aimed at single cell analysis has not been fully defined in terms of sensitivity and assay comparability. We compared three kits using purification columns (PicoPure) or direct lysis (CellsDirect and Cells-to-CT) combined with a one- or two-step RT-qPCR approach using dilutions of cells and RNA standards to the single cell level. Single cell-level messenger RNA (mRNA) analysis was possible using all three methods, although the precision, linearity, and effect of lysis buffer and cell background differed depending on the approach used. The impact of using a microfluidic qPCR platform versus a standard instrument was investigated for potential variability introduced by preamplification of template or scaling down of the qPCR to nanoliter volumes using laser-dissected single cell samples. The two approaches were found to be comparable. These studies show that accurate gene expression analysis is achievable at the single cell level and highlight the importance of well-validated experimental procedures for low-level mRNA analysis.

Applicability of RNA standards for evaluating RT-qPCR assays and platforms.

The availability of diverse RT-qPCR assay formats and technologies hinder comparability of data between platforms. Reference standards to facilitate platform evaluation and comparability are needed. We have explored using universal RNA standards for comparing the performance of a novel qPCR platform (Fluidigm® BioMark™) against the widely used ABI 7900HT system. Our results show that such standards may form part of a toolkit to evaluate the key performance characteristics of platforms.

Evaluation of external RNA controls for the standardisation of gene expression biomarker measurements.

BACKGROUND: 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. RESULTS: 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. CONCLUSIONS: 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.

Validation of reference gene stability for APAP hepatotoxicity studies in different in vitro systems and identification of novel potential toxicity biomarkers.

Liver cell lines and primary hepatocytes are becoming increasingly valuable for in vitro toxicogenomic studies, with RT-qPCR enabling the analysis of gene expression profiles following exposure to potential hepatotoxicants. Supporting the accurate normalisation of RT-qPCR data requires the identification of reference genes which have stable expression during in vitro toxicology studies. Therefore, we performed a comprehensive analysis of reference gene stability in two routinely used cell types, (HepG2 cells and primary rat hepatocytes), and two in vitro culture systems, (2D monolayer and 3D scaffolds). A robust reference gene validation strategy was performed, consisting of geNorm analysis, to test for pair wise variation in gene expression, and statistical analysis using analysis of variance. This strategy identified stable reference genes with respect to acetaminophen treatment and time in HepG2 cells (GAPDH and PPIA), and with respect to acetaminophen treatment and culture condition in primary hepatocytes (18S rRNA and α-tubulin). Following the selection of reference genes, the novel target genes E2F7 and IL-11RA were identified as potential toxicity biomarkers for acetaminophen treatment. We conclude that accurate quantification of gene expression requires the use of a validated normalisation strategy for each species and experimental system employed.

Evaluation of a novel approach for the measurement of RNA quality.

BACKGROUND: Microarray data interpretation can be affected by sample RNA integrity. The ScreenTape Degradation Value (SDV) is a novel RNA integrity metric specific to the ScreenTape(R) platform (Lab901). To characterise the performance of the ScreenTape(R) platform for RNA analysis and determine the robustness of the SDV metric, a panel of intentionally degraded RNA samples was prepared. These samples were used to evaluate the ScreenTape(R) platform against an alternative approach for measuring RNA integrity (Agilent Bioanalyzer RIN value). The samples were also subjected to microarray analysis and the resulting data correlated to the RNA integrity metrics. FINDINGS: Measurement of SDV for a panel of intentionally degraded RNA samples ranged from 0 for intact RNA to 37 for degraded RNA, with corresponding RIN values ranging from 10 to 4 for the same set of samples. SDV and RIN scales both demonstrated comparable discrimination between differently treated samples (RIN 10 to 7, SDV 0 to 15), with the SDV exhibiting better discrimination at higher degradation levels. Increasing SDV values correlated with a decrease in microarray sample labelling efficiency and an increase in numbers of differentially expressed genes. CONCLUSIONS: The ScreenTape(R) platform is comparable to the Bioanalyzer platform in terms of reproducibility and discrimination between different levels of RNA degradation. The robust nature of the SDV metric qualifies it as an alternative metric for RNA sample quality control, and a useful predictor of downstream microarray performance.