MS-based clinical proteomics: biomarker discovery in men’s cancer

Importance of biomarker discovery in men’s cancer diagnosis and prognosis Each year around 10,000 men in the UK die as a result of prostate cancer (PCa) making it the 3rd most common cancer behind lung and breast cancer; worldwide more than 670,000 men are diagnosed every year with the disease [1]. Current methods of diagnosis of PCa mainly rely on the detection of elevated prostate-specific antigen (PSA) levels in serum and/or physical examination by a doctor for the detection of an abnormal prostate. PSA is a glycoprotein produced almost exclusively by the epithelial cells of the prostate gland [2]. Its role is not fully understood, although it is known that it forms part of the ejaculate and its function is to solubilise the sperm to give them the mobility to swim. Raised PSA levels in serum are thought to be due to both an increased production of PSA from the proliferated prostate cells, and a diminished architecture of affected cells, allowing an easier distribution of PSA into the wider circulatory system.

The cell cycle and drug discovery: The promise and the hope

In recent years, there have been major developments in the understanding of the cell cycle. It is now known that normal cellular proliferation is tightly regulated by the activation and deactivation of a series of proteins that constitute the cell cycle machinery. The expression and activity of components of the cell cycle can be altered during the development of a variety of diseases where aberrant proliferation contributes to the pathology of the illness. Apart from yielding a new source of untapped therapeutic targets, it is likely that manipulating the activity of such proteins in diseased states will provide an important route for treating proliferative disorders, and the opportunity to develop a novel class of future medicines.

Biomarker discovery and redundancy reduction towards classification using a multi-factorial MALDI-TOF MS T2DM mouse model dataset

Diabetes like many diseases and biological processes is not mono-causal. On the one hand multifactorial studies with complex experimental design are required for its comprehensive analysis. On the other hand, the data from these studies often include a substantial amount of redundancy such as proteins that are typically represented by a multitude of peptides. Coping simultaneously with both complexities (experimental and technological) makes data analysis a challenge for Bioinformatics.

An overview of interactive visual data mining techniques for knowledge discovery

n the past decade, the analysis of data has faced the challenge of dealing with very large and complex datasets and the real-time generation of data. Technologies to store and access these complex and large datasets are in place. However, robust and scalable analysis technologies are needed to extract meaningful information from these datasets. The research field of Information Visualization and Visual Data Analytics addresses this need. Information visualization and data mining are often used complementary to each other. Their common goal is the extraction of meaningful information from complex and possibly large data. However, though data mining focuses on the usage of silicon hardware, visualization techniques also aim to access the powerful image-processing capabilities of the human brain. This article highlights the research on data visualization and visual analytics techniques. Furthermore, we highlight existing visual analytics techniques, systems, and applications including a perspective on the field from the chemical process industry.

Price discovery of credit spreads in tranquil and crisis periods

In this paper we investigate the price discovery process in single-name credit spreads obtained from bond, credit default swap (CDS), equity and equity option prices. We analyse short term price discovery by modelling daily changes in credit spreads in the four markets with a vector autoregressive model (VAR). We also look at price discovery in the long run with a vector error correction model (VECM). We find that in the short term the option market clearly leads the other markets in the sub-prime crisis (2007-2009). During the less severe sovereign debt crisis (2009-2012) and the pre-crisis period, options are still important but CDSs become more prominent. In the long run, deviations from the equilibrium relationship with the option market still lead to adjustments in the credit spreads observed or implied from other markets. However, options no longer dominate price discovery in any of the periods considered. Our findings have implications for traders, credit risk managers and financial regulators.

MALDI mass spectrometry in prostate cancer biomarker discovery

Matrix-assisted laser desorption/ionisation (MALDI) mass spectrometry (MS) is a highly versatile and sensitive analytical technique, which is known for its soft ionisation of biomolecules such as peptides and proteins. Generally, MALDI MS analysis requires little sample preparation, and in some cases like MS profiling it can be automated through the use of robotic liquid-handling systems. For more than a decade now, MALDI MS has been extensively utilised in the search for biomarkers that could aid clinicians in diagnosis, prognosis, and treatment decision making. This review examines the various MALDI-based MS techniques like MS imaging, MS profiling and proteomics in-depth analysis where MALDI MS follows fractionation and separation methods such as gel electrophoresis, and how these have contributed to prostate cancer biomarker research. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge.

Information analytics for healthcare service discovery

The concept of being ‘patient-centric’ is a challenge to many existing healthcare service provision practices. This paper focuses on the issue of referrals, where multiple stakeholders, i.e. general practitioners and patients, are encouraged to make a consensual decision based on patient needs. In this paper, we present an ontology-enabled healthcare service provision, which facilitates both patients and GPs in jointly deciding upon the referral decision. In the healthcare service provision model, we define three types of profile, which represents different stakeholders’ requirements. This model also comprises of a set of healthcare service discovery processes: articulating a service need, matching the need with the healthcare service offerings, and deciding on a best-fit service for acceptance. As a result, the healthcare service provision can carry out coherent analysis using personalised information and iterative processes that deal with requirements change over time.

Hierarchical clustering based web service discovery

This paper presents a hierarchical clustering method for semantic Web service discovery. This method aims to improve the accuracy and efficiency of the traditional service discovery using vector space model. The Web service is converted into a standard vector format through the Web service description document. With the help of WordNet, a semantic analysis is conducted to reduce the dimension of the term vector and to make semantic expansion to meet the user’s service request. The process and algorithm of hierarchical clustering based semantic Web service discovery is discussed. Validation is carried out on the dataset.

Discovery of a mammalian splice variant of myostatin that stimulates myogenesis

Myostatin plays a fundamental role in regulating the size of skeletal muscles. To date, only a single myostatin gene and no splice variants have been identified in mammals. Here we describe the splicing of a cryptic intron that removes the coding sequence for the receptor binding moiety of sheep myostatin. The deduced polypeptide sequence of the myostatin splice variant (MSV) contains a 256 amino acid N-terminal domain, which is common to myostatin, and a unique C-terminus of 65 amino acids. Western immunoblotting demonstrated that MSV mRNA is translated into protein, which is present in skeletal muscles. To determine the biological role of MSV, we developed an MSV over-expressing C2C12 myoblast line and showed that it proliferated faster than that of the control line in association with an increased abundance of the CDK2/Cyclin E complex in the nucleus. Recombinant protein made for the novel C-terminus of MSV also stimulated myoblast proliferation and bound to myostatin with high affinity as determined by surface plasmon resonance assay. Therefore, we postulated that MSV functions as a binding protein and antagonist of myostatin. Consistent with our postulate, myostatin protein was co-immunoprecipitated from skeletal muscle extracts with an MSV-specific antibody. MSV over-expression in C2C12 myoblasts blocked myostatin-induced Smad2/3-dependent signaling, thereby confirming that MSV antagonizes the canonical myostatin pathway. Furthermore, MSV over expression increased the abundance of MyoD, Myogenin and MRF4 proteins (P,0.05), which indicates that MSV stimulates myogenesis through the induction of myogenic regulatory factors. To help elucidate a possible role in vivo, we observed that MSV protein was more abundant during early post-natal muscle development, while myostatin remained unchanged, which suggests that MSV may promote the growth of skeletal muscles. We conclude that MSV represents a unique example of intra-genic regulation in which a splice variant directly antagonizes the biological activity of the canonical gene product.