Promise of multiphoton detection in discovery and diagnostic proteomics

Proteomics has lacked adequate methods for handling the complexity (hundreds of thousands of different proteins) and range of protein concentrations (> or =10(6)) of eukaryotic proteomes. New multiphoton-detection methods for ultrasensitive detection of proteins produce 10,000-fold gains in sensitivity and allow highly quantitative, linear detection of 50 zmol (30,000 molecules) to 500 fmol of proteins in complex samples. The potential of multiphoton detection in top-down proteomics analyses is illustrated with applications in monitoring proteomes in very small numbers of cells, in identifying and monitoring complex functional isoforms of cancer-related proteins, and in super-sensitive immunoassays of serum proteins for high-performance detection of cancer.     

Chemical proteomics and its impact on the drug discovery process

Despite the rapid growth of postgenomic data and fast-paced technology advancement, drug discovery is still a lengthy and difficult process. More effective drug design requires a better understanding of the interaction between drug candidates and their targets/off-targets in various situations. The ability of chemical proteomics to integrate a multiplicity of disciplines enables the direct analysis of protein activities on a proteome-wide scale, which has enormous potential to facilitate drug target elucidation and lead drug verification. Over recent years, chemical proteomics has experienced rapid growth and provided a valuable method for drug target identification and inhibitor discovery. This review introduces basic concepts and technologies of different popular chemical proteomic approaches. It also covers the essential features and recent advances of each approach while underscoring their potentials in drug discovery and development.     

Deep and quantitative top-down proteomics in clinical and translational research

It has long been understood that it is proteins, expressed and post-translationally modified, that are the primary regulators of both the fate and the function of cells. The ability to measure differences in the expression of the constellation of unique protein forms (proteoforms) with complete molecular specificity has the potential to sharply improve the return on investment for mass spectrometry-based proteomics in translational research and clinical diagnostics.     

Understanding protein trafficking in plant cells through proteomics

The functions of approximately one-third of the proteins encoded by the Arabidopsis thaliana genome are completely unknown. Moreover, many annotations of the remainder of the genome supply tentative functions, at best. Knowing the ultimate localization of these proteins, as well as the pathways used for getting there, may provide clues as to their functions. The putative localization of most proteins currently relies on in silico-based bioinformatics approaches, which, unfortunately, often result in erroneous predictions. Emerging proteomics techniques coupled with other systems biology approaches now provide researchers with a plethora of methods for elucidating the final location of these proteins on a large scale, as well as the ability to dissect protein-sorting pathways in plants.     

Blood biomarker discovery in drug-free schizophrenia: the contribution of proteomics and multiplex immunoassays

Introduction: Recent evidence supports an association between systemic abnormalities and the pathology of psychotic disorders which has led to the search for peripheral blood-based biomarkers.

Areas covered: Here, we summarize blood biomarker findings in schizophrenia from the literature identified by two methods currently driving biomarker discovery in the human proteome; mass spectrometry and multiplex immunoassay. From a total of 14 studies in the serum or plasma of drug-free schizophrenia patients; 47 proteins were found to be significantly altered twice or more, in the same direction. Pathway analysis was performed on these proteins, and the resulting pathways discussed in relation to schizophrenia pathology. Future directions are also discussed, with particular emphasis on the potential for high-throughput validation techniques such as data-independent analysis for confirmation of biomarker candidates.

Expert commentary: We present promising findings that point to a convergence of pathophysiological mechanisms in schizophrenia that involve the acute-phase response, glucocorticoid receptor signalling, coagulation, and lipid and glucose metabolism.     

蛋白质芯片在蛋白质组学研究中的作用

蛋白质芯片是以高度并行性、高通量、微型化和自动化为特点的蛋白质组检测技术。本文综述了蛋白质芯片在蛋白质组学研究中的多种作用,包括普通蛋白质芯片在微量蛋白质分离、蛋白质与蛋白质之间以及蛋白质与其他小分子间相互作用和蛋白质定量检测方面的作用,普通蛋白质芯片通过与质谱技术、生物传感器技术的结合而拓展其应用范围,以及蛋白质组芯片、活性的蛋白质芯片在蛋白质组学研究中应用的进展。     

Recent mass spectrometry-based proteomics for biomarker discovery in lung cancer,COPD, and asthma

Introduction: Lung cancer and related diseases have been one of the most common causes of deaths worldwide. Genomic-based biomarkers may hardly reflect the underlying dynamic molecular mechanism of functional protein interactions, which is the center of a disease. Recent developments in mass spectrometry (MS) have made it possible to analyze disease-relevant proteins expressed in clinical specimens by proteomic challenges.

Areas covered: To understand the molecular mechanisms of lung cancer and its subtypes, chronic obstructive pulmonary disease (COPD), asthma and others, great efforts have been taken to identify numerous relevant proteins by MS-based clinical proteomic approaches. Since lung cancer is a multifactorial disease that is biologically associated with asthma and COPD among various lung diseases, this study focused on proteomic studies on biomarker discovery using various clinical specimens for lung cancer, COPD, and asthma.

Expert commentary: MS-based exploratory proteomics utilizing clinical specimens, which can incorporate both experimental and bioinformatic analysis of protein-protein interaction and also can adopt proteogenomic approaches, makes it possible to reveal molecular networks that are relevant to a disease subgroup and that could differentiate between drug responders and non-responders, good and poor prognoses, drug resistance, and so on.     

Clinical proteomics and mass spectrometry profiling for cancer detection

A key challenge in the clinical proteomics of cancer is the identification of biomarkers that would enable early detection, diagnosis and monitoring of disease progression to improve long-term survival of patients. Recent advances in proteomic instrumentation and computational methodologies offer a unique chance to rapidly identify these new candidate markers or pattern of markers. The combination of retentate affinity chromatography and mass spectrometry is one of the most interesting new approaches for cancer diagnostics using proteomic profiling. This review presents two technologies in this field, surface-enhanced laser desorption/ionization time-of-flight and Clinprot?, and aims to summarize the results of studies obtained with the first of them for the early diagnosis of human cancer. Despite promising results, the use of the proteomic profiling as a diagnostic tool brought some controversies and technical problems, and still requires some efforts to be standardized and validated.     

Activity- and reactivity-based proteomics: Recent technological advances and applications in drug discovery

Activity-based protein profiling (ABPP) is recognized as a powerful and versatile chemoproteomic technology in drug discovery. Central to ABPP is the use of activity-based probes to report the activity of specific enzymes or reactivity of amino acid types in complex biological systems. Over the last two decades, ABPP has facilitated the identification of new drug targets and discovery of lead compounds in human and infectious disease. Furthermore, as part of a sustained global effort to illuminate the druggable proteome, the repertoire of target classes addressable with activity-based probes has vastly expanded in recent years. Here, we provide an overview of ABPP and summarise the major technological advances with an emphasis on probe development.     

Targeted proteomics: a bridge between discovery and validation

New technologies in mass spectrometry are beginning to mature and show unique advantages for the identification and quantitation of proteins. In recent years, one of the significant goals of clinical proteomics has been to identify biomarkers that can be used for clinical diagnosis. As technology has progressed, the list of potential biomarkers has grown. However, the verification and validation of these potential biomarkers is increasingly challenging and require high-throughput quantitative assays, targeting specific candidates. Targeted proteomics bridges the gap between biomarker discovery and the development of clinically applicable biomarker assays.     

Profiling proteoforms: promising follow-up of proteomics for biomarker discovery

Today, proteomics usually compares clinical samples by use of bottom-up profiling with high resolution mass spectrometry, where all protein products of a single gene are considered as an integral whole. At the same time, proteomics of proteoforms, which considers the variety of protein species, offers the potential to discover valuable biomarkers. Proteoforms are protein species that arise as a consequence of genetic polymorphisms, alternative splicing, post-translational modifications and other less-explored molecular events. The comprehensive observation of proteoforms has been an exclusive privilege of top-down proteomics. Here, we review the possibilities of a bottom-up approach to address the microheterogeneity of the human proteome. Special focus is given to shotgun proteomics and structure-based bioinformatics as a source of hypothetical proteoforms, which can potentially be verified by targeted mass spectrometry to determine the relevance of proteoforms to diseases.     

Progress and prospects for the discovery of biomarkers for gastric cancer: a focus on proteomics

Introduction: Patient outcomes from gastric cancer vary due to the complexity of stomach carcinogenesis. Recent research using proteomic technologies has targeted components of all of these systems in order to develop biomarkers to aid the early diagnosis of gastric cancer and to assist in prognostic stratification.

Areas covered: This review is comprised of evidence obtained from literature searches from PubMed. It covers the evidence of diagnostic, prognostic, and predictive biomarkers for gastric cancer using proteomic technologies, and provides up-to-date references.

Expert commentary: The proteomic technologies have not only enabled the screening of a large number of samples, but also enabled the identification of diagnostic, prognostic and predictive biomarkers for gastric cancer. While major challenges still remain, to date, proteomic studies in gastric cancer have provided a wealth of information in revealing proteome alterations associated with the disease.     

Nutrition proteomics and biomarker discovery

Baukje de Roos is a principal investigator at the University of Aberdeen, Rowett Institute of Nutrition and Health. She investigates mechanisms through which dietary fats and fatty acids, and also polyphenols, affect parameters involved in the development of heart disease in vivo. This is achieved not only by measuring their effect on conventional risk markers for heart disease but also by assessing their effect on new markers that are being developed through proteomic and mass spectrometry methods. She obtained her PhD in Human Nutrition at Wageningen University, The Netherlands, in January 2000, after which she was appointed as a post-doctoral research fellow at the Department of Vascular Biochemistry, Glasgow Royal Infirmary, in collaboration with GlaxoSmithKline. In June 2001 she joined the Rowett Research Institute in Aberdeen. She is currently working for the University of Aberdeen, where her research is funded by the Scottish Government Rural and Environment Research and Analysis Directorate (RERAD). She is an active member of the European Nutrigenomics Organisation (NuGO), an EU-funded Network of Excellence, which merges the nutrigenomics activities of its 23 partners across Europe.     

Structural proteomics in drug discovery

High-throughput, automated or semiautomated methodologies implemented by companies and structural genomics initiatives have accelerated the process of acquiring structural information for proteins via x-ray crystallography. This has enabled the application of structure-based drug design technologies to a variety of new structures that have potential pharmacologic relevance. Although there remain major challenges to applying these approaches more broadly to all classes of drug discovery targets, clearly the continued development and implementation of these structure-based drug design methodologies by the scientific community at large will help to address and provide solutions to these hurdles. The result will be a growing number of protein structures of important pharmacologic targets that will help to streamline the process of identification and optimization of lead compounds for drug development. These lead agonist and antagonist pharmacophores should, in turn, help to alleviate one of the current critical bottlenecks in the drug discovery process; that is, defining the functional relevance of potential novel targets to disease modification. The prospect of generating an increasing number of potential drug candidates will serve to highlight perhaps the most significant future bottleneck for drug development, the cost and complexity of the drug approval process.     

Uses and misuses of the fudge factor in quantitative discovery proteomics

Selecting proteins with significant differential abundance is the cornerstone of many relative quantitative proteomics experiments. To do so, a trade‐off between p‐value thresholding and fold‐change thresholding can be performed because of a specific parameter, named fudge factor, and classically noted s₀. We have observed that this fudge factor is routinely turned away from its original (and statistically valid) use, leading to important distortion in the distribution of p‐values, jeopardizing the protein differential analysis, as well as the subsequent biological conclusion. In this article, we provide a comprehensive viewpoint on this issue, as well as some guidelines to circumvent it.     

Cancer biomarker discovery and translation: proteomics and beyond

Introduction: Cancer is often diagnosed at late stages when the chance of cure is relatively low and although research initiatives in oncology discover many potential cancer biomarkers, few transition to clinical applications. This review addresses the current landscape of cancer biomarker discovery and translation with a focus on proteomics and beyond.

Areas covered: The review examines proteomic and genomic techniques for cancer biomarker detection and outlines advantages and challenges of integrating multiple omics approaches to achieve optimal sensitivity and address tumor heterogeneity. This discussion is based on a systematic literature review and direct participation in translational studies.

Expert commentary: Identifying aggressive cancers early on requires improved sensitivity and implementation of biomarkers representative of tumor heterogeneity. During the last decade of genomic and proteomic research, significant advancements have been made in next generation sequencing and mass spectrometry techniques. This in turn has led to a dramatic increase in identification of potential genomic and proteomic cancer biomarkers. However, limited successes have been shown with translation of these discoveries into clinical practice. We believe that the integration of these omics approaches is the most promising molecular tool for comprehensive cancer evaluation, early detection and transition to Precision Medicine in oncology.     

Microplate-based,label-free detection of biomolecular interactions: applications in proteomics

This review describes a new type of label-free optical biosensor that is inexpensively manufactured from continuous sheets of plastic film and incorporated into standard format microplates to enable highly sensitive, high-throughput detection of small molecules, proteins and cells. The biosensor and associated detection instrumentation are applied to review two fundamental limiting issues for assays in proteomics research and drug discovery: requirement for quantitative measurement of protein concentration and specific activity, and measurements made with complex systems in highly parallel measurements. SRU BIosystems, Inc.’s BIND? label-free detection will address these issues using data examples for hybridoma screening, epitope binning and mapping, small-molecule screening, and cell-based functional assays. The review describes several additional applications that are under development for the system, and the key issues that will drive adoption of the technology over the next 5 years.     

癌症差异蛋白质组学研究中样品分离和鉴定分析技术

随着人类基因组测序的完成,癌症研究的重点从基因组学转移到蛋白质组学研究中。癌症研究中的差异蛋白质组学技术也飞速发展,包括癌症样品制备、分离,蛋白质鉴定分析、蛋白质组定量研究和翻译后修饰研究等。这些技术极大地推动了与癌症相关的差异蛋白质组学研究,使蛋白质组学在癌症早期诊断、治疗,监测以及发现新药物治疗靶标方面发挥更大的作用。本文主要综述了近年来癌症差异蛋白质组学研究中样品分离和鉴定分析技术。     

蛋白质组研究中的化学"探针"

随着蛋白质组学概念的提出以及诸如血浆蛋白质组等有影响力的计划开展, 蛋白质组研究迅速发展起来, 这门基于分析化学和物理化学的领域也逐渐为广大生物学家所关注, 同时也相应地在细胞生物学、生物化学等领域的研究中崭露头角。蛋白质表达量的变化以及各种各样的修饰无不反映出机体对环境变化的应激和自身功能的需要。因此, 定量蛋白质组和修饰化的蛋白质组成为了目前蛋白质组研究的重要领域之一。文章着重从采用化学标记实现定量和修饰化研究这个角度来介绍近些年来在这方面取得的进展, 希望对生物学领域的研究有所借鉴。