- Cancer Biology & Biomarkers
- Chromatography & Mass Spectrometry
- Contract Research, Clinical Trials and Outsourcing
- Drug Discovery
- Drug Targets
- Flow Cytometry
- Informatics & Lab Automation
- Ingredients, Excipients and Dosages
- Microbiology & Rapid Micro Methods (RMMs)
- Process Analytical Technology (PAT) & Quality by Design (QbD)
- Raman Spectroscopy
- Screening, Assays & High-Content Analysis
- Thermal Processing
- Latest News
- Contact us
Biomarkers - Articles and news items
Issue 6 2014 / 23 December 2014 / Axel Ducret, Biochemist
This article will focus on some of the critical aspects of transition biomarkers discovered in classical (MS-based) proteomics workflows and on the challenges to be met before validated assays can become more routine in the clinical laboratory…
Issue 6 2014 / 23 December 2014 / The Society for Laboratory Automation & Screening (SLAS)
The Society for Laboratory Automation and Screening (SLAS) is proud to present SLAS2015, the Fourth Annual Conference and Exhibition of the Society…
There is an urgent need to predict which treatment will report the most benefit to a patient with cancer. To that end, scientists are exploring any possible biomolecule in the organism that can mark each individual for its adequate treatment. If achieved, it will open a personalised medicine era.
In recent years, mass spectrometry (MS) based proteomics has moved from being a qualitative tool (used to mainly identify proteins) to a more reliable analysis tool, allowing relative quantitation as well as absolute quantitation of a large number of proteins. However, the developed quantitative methods are either specific for certain types of samples or certain types of mass spectrometers. In some cases, developing expertise on how to use a given method may take a long time and the use of these methods is therefore limited to few laboratories. Other quantitative methods are suitable for simple standard protein mixes which are far from the complexity of real samples. As a consequence, the number of available quantitative methods is high and choosing the right one is challenging.
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.
Biomarkers are biological characteristics that are objectively measured and evaluated as indicators of normal biological processes, pathogenic processes or pharmacological responses to a therapeutic intervention. Biomarkers can be used to determine disease onset, progression, efficacy of drug treatment, patient susceptibility to develop a certain type of disease or predict efficacy of treatment at a particular disease stage. Protein molecular biomarkers are particularly popular due to the availability of a large range of analytical instrumentation, which can identify and quantify proteins in complex biological samples. Proteins are key compounds in biosynthesis, cell, tissue and organ signalling and provide cell and tissue structural stability in living organisms. The primary protein sequences are encoded in the genome; however, their complex posttranslational modifications (PTMs) and three dimensional structures are fairly unpredictable from genomic information. In this mini-review, we will provide an overview of the current state, challenge and important aspects of protein biomarker discovery and validation…
Issue 3 2012, Proteomics / 10 July 2012 / Paul C. Guest, Department of Chemical Engineering and Biotechnology, University of Cambridge and Sabine Bahn Department of Chemical Engineering and Biotechnology, University of Cambridge & Department of Neuroscience, Erasmus Medical Centre
Pharmaceutical companies are under increasing pressure to improve their efficiency and returns on drug discovery projects. This is a daunting task considering that the average drug costs approximately one billion US dollars to develop and takes around 12 years from initial discovery to reach the market1. In addition, approximately 70 per cent of drugs fail to recover their research and development costs and around 90 per cent fail to provide a satisfactory return on investment. Therefore, minimising risk is one of the most important aims in pharmaceutical discovery programs today.
There are now efforts to establish standard operating procedures to navigate through these problems and, at the same time, meet the regulatory demands. To facilitate this process, the regulatory health authorities have encour aged the incorporation of biomarkers into the drug discovery pipeline and the Food and Drug Administration (FDA) has called for efforts to modernise and standardise approaches for the delivery of more effective and safer drugs2.
Proteomics is the most applicable tech – nology for implementing biomarker app – roaches in drug discovery given that virtually all existing drug targets are proteins3. Proteomics is a systems approach for the global study of protein expression changes4.
Dr Nicholls has over 30 years’ experience of building international businesses…
Cancer Biology, Issue 1 2012 / 28 February 2012 / Janina Staub and Jochen Utikal, Department of Dermatology, Venereology and Allergology, University Medical Center Mannheim, University of Heidelberg & Skin Cancer Unit, German Cancer Research Center
During the last few years, significant improvements in the treatment of metastatic melanoma were reported, targeting molecules involved in the pathogenesis of melanoma. Different clinical trials were able to prove a prolonged overall survival by introducing new therapeutic agents. Hereby an imunomodulating therapy with the anti-CTLA-4 antibody ipilimumab has been established. Other promising treatment possibilities include targeted therapies for melanoma patients showing certain activating mutations in their tumour cells, e.g. BRAF V600 mutations and their selective inhibition by vemurafenib or the inhibition of the c-Kit receptor by drugs such as imatinib mesylate. This review will provide a brief overview of the latest therapeutic strategies and recent achievements in treating metastatic melanoma, as well as discuss the arising problems with resistance mechanisms to selective therapies. It will also highlight future approaches to combine specific treatments in an attempt to individualise melanoma treatment for every patient with the best possible efficacy and outcome…
Whitepapers / 1 February 2012 / Oxford Gene Technology
Download this free white paper for detailed insight into the advantages of autoantibodies as biomarkers, including a review of the current technology and best practices for identification of sensitive and specific autoantibody biomarkers.
Multiple Sclerosis (MS) is an autoimmune disease leading to a chronic inflammation and degeneration of the central nervous system. It is one of the major neurological diseases with approximately 2.5 million suffering patients worldwide. Until now, the underlying mechanisms have not been fully elucidated, but the cause of the disease can be modulated to limit progression and severity. Currently, there are no validated biomarkers available to predict the progression of MS or response to a clinical intervention apart from MRI. In order to identify protein biomarkers for MS as well as other diseases, significant infrastructure is required and this is discussed.
The term ‘biomarker’ has been defined as a “characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention”. The measurement of normal and dysfunctional biological processes and their changes in response to therapeutic intervention forms the basis of biomarkers. The advances in genetics and molecular biology leading to the sequencing of the human genome has resulted in the identification of a variety of novel targets implicated in different disease states. Further technological developments including high throughput profiling of various samples using genomics, transcriptomics and proteomics has led to the identification of gene and protein based markers that characterise disease states for a number of indications including breast cancer, colorectal cancer and cardiovascular diseases. Additional initiatives that have led to the identification of biomarkers with minimal invasive methods such as proteomics technologies and systems biology have proven extremely effective for discovering potential biomarkers and drug targets. These technologies tend to provide large data sets that can be difficult to deconvolute for biomarker discovery. This bottleneck can be reduced by using several strategies. The first is to constrict the number of potential biomarkers and drug targets by dividing the proteome into smaller, more biologically significant segments. The second is to widen the bottleneck with higheroutput and higher-throughput screening technologies. The third is to incorporate more preliminary validation into the discovery process. New and emerging technologies provide promise for each of these strategies.
In order to advance the identification of new drug targets and disease biomarkers, experimental tools for the systems-level analysis of signalling networks are required. Approaches for a targeted analysis of cellular proteomes have improved in recent years. Notably, the reverse phase protein microarray (RPPA) approach offers great advantages due to properties such as high sensitivity and high sample capacity. This review gives an overview of the principle of RPPA and summarises successful applications that illustrate the potential of RPPA for the analysis of clinical samples, systems biology and for drug discovery concepts. Numerous reports demonstrated the power of this approach to produce higher-order information than is currently possible with any other approach while requiring only minute amounts of sample.
Up-to-date, acquired experience on the application of targeted therapeutics revealed that patients benefit from drugs targeting molecules that are overexpressed by tumours. However, the percentage of patients truly benefiting from the targeted treatment depends largely on the type of tumour. In detail, clinical data obtained from the treatment of solid tumours suggests that our current knowledge is not sufficient to decide beforehand which patients will benefit from a certain treatment and which patients do not. This suggests that overexpression of a particular oncogenic protein by a tumour, such as EGFR, HER2, or oestrogen receptor, does not provide dependable information for treatment decisions. Considerable knowledge has been accumulated on the wiring of those pathways that convey information from cell surface receptors and neighbouring cells as well as the nutritional state and related physiological events. An obvious challenge for proteome research is to convert this knowledge into clinically and pharmaceutically relevant information. However, most drugs target proteins and therefore the realisation of personalised treatment concepts requires a systematic large-scale analysis of individual tumours to identify patterns of deregulation characteristic for subgroups of a certain type of cancer. The identification of reliable disease markers could then be translated into new treatment concepts which have been held back due to technological constraints.