- Cancer Biology & Biomarkers
- Chromatography & Mass Spectrometry
- Contract Research, Clinical Trials and Outsourcing
- Drug Discovery
- Drug Targets
- Flow Cytometry
- Informatics & Lab Automation
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- Microbiology & RMMs
- NIR, PAT & QbD
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MIQE guidelines - Articles and news items
Molecular diagnostics and biomarker discovery are gaining increasing attraction in clinical research. This includes all fields of diagnostics, such as risk assessment, disease prognosis, treatment prediction and drug application success control. The detection of molecular clinical biomarkers is very widespread and can be developed on various molecular levels, like the genome, the epi-genome, the transcriptome, the proteome or the metabolome. Today, numerous high-throughput laboratory methods allow rapid and holistic screening for such marker candidates. Regardless of which molecular level is analysed, in order to detect biomarker candidates, high sample quality and a standardised and highly reproducible quantification workflow are prerequisites. This article describes an optimal and approved development strategy to discover and validate ‘transcriptional biomarkers’ in clinical diagnostics, which are in compliance with the recently developed MIQE guidelines. We focus on the importance of sample quality, RNA integrity, available screening and quantification methods, and biostatistical tools for data interpretation…
RNA levels can be measured with very high specificity, sensitivity and accuracy with techniques such as real-time quantitative PCR (qPCR), microarray analysis and next generation sequencing. This makes messenger (m) RNAs and potentially microRNAs and other non-coding RNAs popular as biomarkers. But RNA is less stable and more dynamic than DNA, and assays are not always specific for RNA, so can we trust measured expression values?
A biomarker is a biological molecule found in blood, other body fluids or tissues, and is a sign of a normal or abnormal process, or of a condition or disease1. The biomarker may be used to see how well the body responds to a treatment for a disease or condition. Most popular and common molecular biomarkers are DNA, RNA and proteins. While proteins and in particular DNA are quite stable molecules and can be analysed for many properties such as sequence years after being removed from their natural biological environment, RNA molecules are not (Table 1). The extra 2’-hydroxyl group on the ribose in RNA that is absent in DNA is a nucleophile. It confers catalytic activity to ribozymes, but also makes RNA intrinsically unstable. In aqueous solution, RNA spontaneously degrades through self-cleavage catalysed by metal ions such as Mg2+, high (>9) or low (<2) pH, and temperature. EDTA or citrate is therefore typically added to RNA preserving solutions to chelate Mg2+2. Although RNA is more resistant to ultraviolet (UV) irradiation than DNA, it causes several types of damage including photochemical modification, cross - linking and oxidation.
Thermo Fisher Scientific and Science/AAAS Host Webinar on the Future of Quantitative PCR and the Importance of Standardization
Thermo Fisher Scientific, announced that it is sponsoring a webinar, “The Future of qPCR…
Cancer molecular pathology broadly relies on the comparison between diseased and normal tissues, with statistically validated differences revealing cancerassociated pathways. This approach, although comparatively one-dimensional, has been remarkably successful, enabling identification of many types of malignant biomarkers and providing the means to develop pharmaceutical agents directed against pertinent biological targets. Most typically during the progression of malignancies, pathologists employ morphological screening of cancerous tissues. However, this form of monitoring has significant limitations, particularly in the early stages of pre-treatment or during the clinical remission.
A diverse and widely applicable laboratory technique, qPCR is vital for the progression of drug discovery, enabling detection and quantification and commonly used for both diagnostic and basic research. This roundtable brings together experts from a wide range of pharmaceutical applications to discuss current technologies and future applications of qPCR for drug discovery and the pharmaceutical industry.
The deceptive simplicity of a typical qPCR assay is an important reason for the exponential growth in the adoption of qPCR-related technologies for both research and diagnostic applications. The only requirements for obtaining ostensibly quantitative data are a mixing of primers, DNA and a mastermix, their distribution into individual tubes or wells, turning on a qPCR instrument and collection of threshold cycles (Cqs). Indeed, it is remarkably difficult to make a reaction fail completely but alarmingly simple to produce poor quality data1. Furthermore, it is of great concern that many ready-to-run commercially available systems adopt protocols that discourage the user from performing assay optimisation or validation steps, resulting in the publication of vast volumes of potentially meaningless data. Inevitably this has lead to inaccurate conclusions and publication retractions2,3. Consequently, assay optimisation, validation and critical data evaluation are essential practice if the integrity of the scientific study is to be preserved4.
Real-time PCR (qPCR) data are reliable only if they result from a robust qPCR assay that has been carefully designed, validated and optimised. This process requires an extensive assay design procedure aimed at generating an optimum primer/probe/amplicon combination to allow accurate quantification of nucleic acids with minimum need for post-PCR analyses (see Figure 1).
The fluorescence-based quantitative real-time polymerase chain reaction (qPCR)1,2,3 has become firmly established as the preferred technology for the detection and quantification of nucleic acids in molecular diagnostics, life sciences, agriculture and medicine4,5.
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