Metagenomic biomarker discovery and explanation

This study describes and validates a new method for metagenomic biomarker discovery by way of class comparison, tests of biological consistency and effect size estimation. This addresses the challenge of finding organisms, genes, or pathways that consistently explain the differences between two or more microbial communities, which is a central problem to the study of metagenomics. We extensively validate our method on several microbiomes and a convenient online interface for the method is provided at .     

Glycoscience aids in biomarker discovery

The glycome consists of all glycans (or carbohydrates) within a biological system, and modulates a wide range of important biological activities, from protein folding to cellular communications. The mining of the glycome for disease markers represents a new paradigm for biomarker discovery; however, this effort is severely complicated by the vast complexity and structural diversity of glycans. This review summarizes recent developments in analytical technology and methodology as applied to the fields of glycomics and glycoproteomics. Mass spectrometric strategies for glycan compositional profiling are described, as are potential refinements which allow structure-specific profiling. Analytical methods that can discern protein glycosylation at a specific site of modification are also discussed in detail. Biomarker discovery applications are shown at each level of analysis, highlighting the key role that glycoscience can play in helping scientists understand disease biology.     

Proteomics: advances in biomarker discovery

The challenges encountered by proteomic researchers seeking diagnostic, prognostic and mechanistic markers were the subject of the 1-day meeting, Proteomics: Advances in Biomarker Discovery hosted by EuroSciCon. The speakers had a broad range of clinical and basic science interests, and presented data using a number of proteomic platforms to search for discriminant biomarkers of disease in easily accessible bodily fluids including serum and urine. Several potential pitfalls for proteomic researchers were mentioned and the potential of collaborative networks between research institutions to increase the size and power of clinical studies was discussed. Overall, the meeting highlighted the exciting opportunities that proteomic techniques offer for discovering not only diagnostic but also prognostic and mechanistic markers of a number of clinically important diseases.     

Proteomics in prostate cancer biomarker discovery

Despite advances in molecular medicine, genomics, proteomics and translational research, prostate cancer remains the second most common cause of cancer-related mortality for men in the Western world. Clearly, early detection, targeted treatment and post-treatment monitoring are vital tools to combat this disease. Tumor markers can be useful for diagnosis and early detection of cancer, assessment of prognosis, prediction of therapeutic effect and treatment monitoring. Such tumor markers include prostate-specific antigen (prostate), cancer antigen (CA)15.3 (breast), CA125 (ovarian), CA19.9 (gastrointestinal) and serum α-fetoprotein (testicular cancer). However, all of these biomarkers lack sensitivity and specificity and, therefore, there is a large drive towards proteomic biomarker discovery. Current research efforts are directed towards discovering biosignatures from biological samples using novel proteomic technologies that provide high-throughput, in-depth analysis and quantification of the proteome. Several of these studies have revealed promising biomarkers for use in diagnosis, assessment of prognosis, and targeting treatment of prostate cancer. This review focuses on prostate cancer proteomic biomarker discovery and its future potential.     

Autoantibody microarrays for biomarker discovery

Identification of autoantigens and the detection of autoantibody reactivity are useful in biomarker discovery and for explaining the role of important biochemical pathways in disease. Despite all of their potential advantages, the main challenge to working with autoantibodies is their sensitivity. Nevertheless, proteomics may hold the key to overcoming this limitation by providing the means to multiplex. Clearly, the ability to detect multiple autoantigens using a platform such as a high-density antigen microarray would improve sensitivity and specificity of detection for autoantibody profiling. The aims of this review are to: briefly describe the current status of antigen–autoantibody microarrays; provide examples of their use in biomarker discoveries; address current limitations; and provide examples and strategies to facilitate their implementation in the clinical setting.     

Autoantibody microarrays for biomarker discovery

Identification of autoantigens and the detection of autoantibody reactivity are useful in biomarker discovery and for explaining the role of important biochemical pathways in disease. Despite all of their potential advantages, the main challenge to working with autoantibodies is their sensitivity. Nevertheless, proteomics may hold the key to overcoming this limitation by providing the means to multiplex. Clearly, the ability to detect multiple autoantigens using a platform such as a high-density antigen microarray would improve sensitivity and specificity of detection for autoantibody profiling. The aims of this review are to: briefly describe the current status of antigen-autoantibody microarrays; provide examples of their use in biomarker discoveries; address current limitations; and provide examples and strategies to facilitate their implementation in the clinical setting.     

Imaging mass spectrometry in biomarker discovery and validation

Biomarker discovery and validation involves the consideration of many issues and challenges in order to be effectively used for translation from bench to bedside. Imaging mass spectrometry (IMS) is a new technology to assess spatial molecular arrangements in tissue sections, going far beyond microscopy in providing hundreds of different molecular images from a single scan without the need of target-specific reagents. The possibility to correlate distribution maps of multiple analytes with histological and clinical features makes it an ideal tool to discover diagnostic and prognostic markers of diseases. Some recently published studies that show the usefulness and advantages of this technology in the field of cancer research are highlighted.     

Place of pattern in proteomic biomarker discovery

The role of pattern in biomarker discovery and clinical diagnosis is examined in its historical context. The use of MS-derived pattern is treated as a logical extension of prior applications of non-MS-derived pattern. Criticisms pertaining to specific technology platforms and analytic methodologies are considered separately from the larger issues of pattern utility and deployment in biomarker discovery. We present a hybrid strategy that marries the desirable attributes of high-information content MS pattern with the capability to obtain identity, and explore the key steps in establishing a data analysis pipeline for pattern-based biomarker discovery.     

Advances in proteomic prostate cancer biomarker discovery

Prostate cancer is the most common non-cutaneous cancer in men in the United States. For reasons largely unknown, the incidence of prostate cancer has increased in the last two decades, in spite or perhaps because of a concomitant increase in serum prostate-specific antigen (PSA) screening. While PSA is acknowledged not to be an ideal biomarker for prostate cancer detection, it is however widely used by physicians due to lack of an alternative. Thus, the identification of a biomarker(s) that can complement or replace PSA represents a major goal for prostate cancer research. Screening complex biological specimens such as blood, urine, and tissue to identify protein biomarkers has become increasingly popular over the last decade thanks to advances in proteomic discovery methods. The completion of human genome sequence together with new development in mass spectrometry instrumentation and bioinformatics has been a major driving force in biomarker discovery research. Here we review the current state of proteomic applications as applied to various sample sources including blood, urine, tissue, and “secretome” for the purpose of prostate cancer biomarker discovery. Additionally, we review recent developments in validation of putative markers, efforts at systems biology approach, and current challenges of proteomics in biomarker discovery.     

Applications of urinary proteomics in biomarker discovery

Urine is an important source of biomarkers. This article reviews current advances, major challenges, and future prospects in the field of urinary proteomics. Because the practical clinical problem is to distinguish diseases with similar symptoms, merely comparing samples from patients of a particular disease to those of healthy individuals is inadequate for finding biomarkers with sufficient diagnostic power. In addition, the variation of expression levels of urinary proteins among healthy individuals and individuals under different physiological conditions adds to the difficulty in identifying biomarkers. We propose that establishing the natural variation in urinary protein expression among a healthy population can serve as a reference to help identify protein abundance changes that are caused by disease, not by individual variations or physiological changes. We also discuss that comparing protein expression levels between urine and plasma may reveal the physiological function of the kidney and that may facilitate biomarker discovery. Finally, we propose that establishing a data-sharing platform for data collection and integrating results from all urinary biomarker studies will help promote the development of urinary proteomics.     

Strategies for biomarker discovery in fibrotic disease

The discovery and development of biomarkers for fibrotic diseases have potential utility in clinical decision-making as well as in pharmaceutical research and development. This review describes strategies for identifying diagnostic, prognostic and theranostic biomarkers. A range of technologies and platforms for biomarker discovery are highlighted, including several with specific relevance for fibrosis. Some challenges specific to fibrotic diseases are outlined including; benchmarking biomarkers against imperfect clinical measures of fibrosis, the complexity resulting from diverse aetiologies and target organs, and the availability of samples (including biopsy) from well-characterised patients with fibrotic disease. To overcome these challenges collaboration amongst clinical specialities as well as between academia and industry is essential. This article is part of a Special Issue entitled: Fibrosis: Translation of basic research to human disease.     

iTRAQ标记技术与差异蛋白质组学的生物标志物研究

结合多维液相色谱和串联质谱分析,iTRAQ技术已成为差异蛋白质组学定量研究的主要工具之一。而寻找和发现区别于正常生理状态下的疾病特异表达蛋白质,有利于阐明疾病的发病机理,对疾病的预防、诊断、预后和疗效监测具有重要作用,并有助于用作新靶点来开发临床治疗药物。本文重点就该技术在医学领域中进行差异蛋白质组分析并寻找标记蛋白质的研究进行综述。     

High-performance proteomics as a tool in biomarker discovery

Biomarkers allowing early detection of disease or therapy control have a huge influence in curing a disease. A wide variety of methods were applied to find new biomarkers. In contrast to methods focused on DNA or mRNA techniques, approaches considering proteins as potential biomarker candidates have the advantage that proteins are more diverse than DNA or RNA and are more reflective of a biological system. Here, we present an approach for the identification of new biomarkers relying on our experience from the past 10 years of proteomics, outlining a concept of "high-performance proteomics" This approach is based on quantitative proteome analysis using a sufficient number of clinical samples and statistical validation of proteomics data by independent methods, such as Western blot analysis or immunohistochemistry.     

Human saliva proteome analysis and disease biomarker discovery

Human saliva is an attractive body fluid for disease diagnosis and prognosis because saliva testing is simple, safe, low-cost and noninvasive. Comprehensive analysis and identification of the proteomic content in human whole and ductal saliva will not only contribute to the understanding of oral health and disease pathogenesis, but also form a foundation for the discovery of saliva protein biomarkers for human disease detection. In this article, we have summarized the proteomic technologies for comprehensive identification of proteins in human whole and ductal saliva. We have also discussed potential quantitative proteomic approaches to the discovery of saliva protein biomarkers for human oral and systemic diseases. With the fast development of mass spectrometry and proteomic technologies, we are enthusiastic that saliva protein biomarkers will be developed for clinical diagnosis and prognosis of human diseases in the future.     

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.