Recent advances in targeted proteomics for clinical applications

MS-based approaches using targeted methods have been widely adopted by the proteomics community to study clinical questions such as the evaluation of biomarkers. At present, the most widely used targeted MS method is the SRM technique typically performed on a triple quadrupole instrument. However, the high analytical demands for performing clinical studies in combination with the extreme complexity of the samples involved are a serious challenge. The segmentation of the biomarker evaluation workflow has only partially alleviated these issues by differently balancing the analytical requirements and throughput at different stages of the process. The recent introduction of targeted high-resolution and accurate-mass analyses on fast sequencing mass spectrometers operated in parallel reaction monitoring (PRM) mode offers new avenues to conduct clinical studies and thus overcome some of the limitations of the triple quadrupole instrument. This article discusses the attributes and specificities of the PRM technique, in terms of experimental design, execution, and data analysis, and the implications for biomarker evaluation. The benefits of PRM on data quality and the impact on the consistency of results are highlighted and the definitive progress on the overall output of clinical studies, including high throughput, is discussed.     

A roadmap for successful applications of clinical proteomics

Despite over 30,000 publications on proteomics in the last decade, and the accumulation of extensive interesting information on the human proteome in diverse observations, the clinical translation of proteomics to-date has had major setbacks. I review here a roadmap for improving the success rate of clinical proteomics. The roadmap includes steps for improvements that need to be made in analytical tools, discovery, validation, clinical application, and post-clinical application appraisal. It is likely that most if not all of the components that are necessary for clinical success are either readily available, or should be possible to put in place with more rigorous research standards and concerted efforts of the research community, clinicians, and health agencies. Enthusiasm for the clinical impact of proteomics may need to be tempered currently until robust evidence can be obtained, but some clinical successes should eventually be feasible.     

Urine proteomics in kidney and urogenital diseases: Moving towards clinical applications

To date, multiple biomarker discovery studies in urine have been conducted. Nevertheless, the rate of progression of these biomarkers to qualification and even more clinical application is extremely low. The scope of this article is to provide an overview of main clinically relevant proteomic findings from urine focusing on kidney diseases, bladder and prostate cancers. In addition, approaches for promoting the use of urine in clinical proteomics including potential means to facilitate the validation of existing promising findings (biomarker candidates identified from previous studies) and to increase the chances for success for the identification of new biomarkers are discussed.     

Combining laser capture microdissection and proteomics: methodologies and clinical applications

Laser capture microdissection (LCM) has become an important tool for biomedical research. Various molecular biology techniques have been combined with LCM to reveal molecular profiles at an unprecedented tissue resolution. Proteomics is among those techniques that have proved fruitful in combination with LCM. This review provides an overview of the various proteomic techniques that have been developed for analyzing cells obtained using LCM. Methods for analyzing microdissected cells for various proteomic techniques are described and compared. In addition, various applications based on LCM and proteomics are discussed.     

Quantitative proteomics for identification of cancer biomarkers

Quantitative proteomics can be used for the identification of cancer biomarkers that could be used for early detection, serve as therapeutic targets, or monitor response to treatment. Several quantitative proteomics tools are currently available to study differential expression of proteins in samples ranging from cancer cell lines to tissues to body fluids. 2-DE, which was classically used for proteomic profiling, has been coupled to fluorescence labeling for differential proteomics. Isotope labeling methods such as stable isotope labeling with amino acids in cell culture (SILAC), isotope-coded affinity tagging (ICAT), isobaric tags for relative and absolute quantitation (iTRAQ), and (18) O labeling have all been used in quantitative approaches for identification of cancer biomarkers. In addition, heavy isotope labeled peptides can be used to obtain absolute quantitative data. Most recently, label-free methods for quantitative proteomics, which have the potential of replacing isotope-labeling strategies, are becoming popular. Other emerging technologies such as protein microarrays have the potential for providing additional opportunities for biomarker identification. This review highlights commonly used methods for quantitative proteomic analysis and their advantages and limitations for cancer biomarker analysis.     

Exploring the potential of platelet proteomics in children

Proteomics is a rapidly evolving ‘‘post-genomic’’ science utilizing advanced technologies in protein separation, identification, quantitation and heavily relying on bioinformatics. Proteomic research in pediatrics is important and most of the successes thus far are seen in research that utilize samples that require less invasive procedures and focus on prevailing childhood diseases such as acute lymphoblastic leukaemia and neuroblastoma. Recent advances in proteomics are helping to elucidate platelet processes that are relevant to bleeding and clotting disorders, as well as other important roles of platelets such as in angiogenesis and inflammation. Nevertheless, most of platelet proteome data obtained to date are derived from the adult population and the potential of platelet proteomic application in children has not yet been explored. As it happens in all research fields, there are additional challenges in studying children such as procuring sufficient biological samples and access to less common disease cohorts as compared to in adults. Furthermore, many of the prevalent platelet-mediated diseases in adults, such as coronary heart disease and atherosclerotic lesions, are believed to have origins during childhood. Hence, platelet proteomic research in children may reveal some important information on how platelet plays a role in the pathogenesis of disease. In this article, we refer to the current knowledge from platelet proteomic research strategies in adults and address the specific concerns in the study of pediatric samples.     

Quantitative proteomics in cardiovascular research: Global and targeted strategies

Extensive technical advances in the past decade have substantially expanded quantitative proteomics in cardiovascular research. This has great promise for elucidating the mechanisms of cardiovascular diseases and the discovery of cardiac biomarkers used for diagnosis and treatment evaluation. Global and targeted proteomics are the two major avenues of quantitative proteomics. While global approaches enable unbiased discovery of altered proteins via relative quantification at the proteome level, targeted techniques provide higher sensitivity and accuracy, and are capable of multiplexed absolute quantification in numerous clinical/biological samples. While promising, technical challenges need to be overcome to enable full utilization of these techniques in cardiovascular medicine. Here, we discuss recent advances in quantitative proteomics and summarize applications in cardiovascular research with an emphasis on biomarker discovery and elucidating molecular mechanisms of disease. We propose the integration of global and targeted strategies as a high-throughput pipeline for cardiovascular proteomics. Targeted approaches enable rapid, extensive validation of biomarker candidates discovered by global proteomics. These approaches provide a promising alternative to immunoassays and other low-throughput means currently used for limited validation.     

Mixed computation: potential applications and problems for study

Mixed computation is processing of an incomplete information. Its product are a partially processed information and a so-called residual program destined to complete in sequel the processing of the remaining information. Many kinds of practical work with programs are nothing more but obtaining a residual program. We demonstrate, as an example, the application of mixed computation to compilation. Under computational approach mixed computation generalizes the operational semantics of a language by inclusion of steps which generate residual program instructions. Under transformational approach the residual program is obtained as a result of a series of so-called basic transformations of the program text. We argue that the transformational approach is more fundamental, for it allows to describe mixed computation in all its variety and moreover, to relate mixed computation to other kinds of program manipulation: execution, optimization, macroprocessing, synthesis. Such an integrated approach leads us to a transformational machine concept.     

An innovative degraded adhesion model for multibody applications in the railway field

The simulation of the braking maneuver of a railway vehicle under degraded adhesion conditions is very important concerning the safety of railway operation. However, the implementation of a realistic friction law is comparatively difficult because of the complex and nonlinear behavior of the wheel-rail contact. Particularly under degraded adhesion conditions, very high creepages occur, which cause sliding in the contact. This sliding produces a high dissipation of energy, which has a cleaning effect on the rolling surfaces, and thereby strengthens the influence of the adhesion. In this work, this energetic criterion has been studied. The authors suggest implementing an innovative friction law to the simulation of railway multibody models with 3D multi-point contact detection algorithms. As a benchmark case, the braking of a coach equipped with a Wheel Slide Protection (WSP) system is simulated. The results are compared with experimental data available from previous testing activities by Trenitalia. The new friction law provides to match the experimental reference results and to carry out simulated braking tests, including the working WSP system, which comply with the current regulations (Railway applications, braking, wheel slide protection, UNI EN 15595, 2009).     

分子模拟在木素研究中的应用

分子模拟作为近年发展起来的一门综合性的计算化学技术,越来越受到油田化学、催化剂研制、高分子设计及化学工程等领域的广泛重视。它与实验技术一起成为研究木素分子结构、性质及生物合成机理的有效工具。文章介绍包含分子力学法、分子动力学法和量子力学法在内3种常用的分子模拟方法并综述其在木素研究中的应用,同时指出分子模拟的不足及其发展方向。     

Using data-independent,high-resolution mass spectrometry in protein biomarker research: Perspectives and clinical applications

In medicine, there is an urgent need for protein biomarkers in a range of applications that includes diagnostics, disease stratification, and therapeutic decisions. One of the main technologies to address this need is MS, used for protein biomarker discovery and, increasingly, also for protein biomarker validation. Currently, data-dependent analysis (also referred to as shotgun proteomics) and targeted MS, exemplified by SRM, are the most frequently used mass spectrometric methods. Recently developed data-independent acquisition techniques combine the strength of shotgun and targeted proteomics, while avoiding some of the limitations of the respective methods. They provide high-throughput, accurate quantification, and reproducible measurements within a single experimental setup. Here, we describe and review data-independent acquisition strategies and their recent use in clinically oriented studies. In addition, we also provide a detailed guide for the implementation of SWATH-MS (where SWATH is sequential window acquisition of all theoretical mass spectra)—one of the data-independent strategies that have gained wide application of late.     

Vascular proteomics and the discovery process of clinical biomarkers: The case of TWEAK

In the last years, big efforts are devoted to the search of novel biomarkers. Proteomic approaches in healthy and pathological samples may help us to discern differential protein expression patterns. These identified proteins include potential culprits in pathological pathways and/or clinical biomarkers to identify individuals at risk. However, extensively validation must be carried out before their implementation into the clinical practice. Biomarkers need to discriminate between health and disease, detect preclinical disease stages, have impact on survival prediction, and add predictive value beyond traditional risk factors and global risk algorithms. Now, we summarize the data of soluble tumor necrosis factor-like weak inducer of apoptosis (sTWEAK), a new cardiovascular biomarker identified by proteomic analysis. Decreased sTWEAK concentrations have been shown in patients with carotid atherosclerosis, coronary artery disease, congestive heart failure, peripheral artery disease, or chronic kidney disease (CKD). sTWEAK predicted adverse outcomes in patients with heart failure, myocardial infarction, and CKD. Finally, different drug regimens were able to modify sTWEAK plasma levels in patients with CKD. Although sTWEAK seems so far to fulfill the requisites in the development of a new biomarker, more large-scale studies are warranted to consolidate its usefulness.     

Challenges and opportunities for cell line secretomes in cancer proteomics

Cancer cell lines are the most widely used experimental models in cancer research. Their advantages of easy growth and manipulation are unfortunately paralleled by their limitations derived from long-term growth in isolation from the rest of the tumor, and hence, lack of tumor microenvironment. We are however currently witnessing novel and transformative advances that are making cell lines more reflective of the human biology and therefore, better experimental models for cancer research. Beyond the experimental model used, the choice of cellular proteome is key in proteomics-based biomarker discovery. Over the last decade, cell line secretomes have been proposed as an alternative for tumor biomarker discovery due to the difficulties posed by plasma in terms of complexity and low abundance of tumor-specific biomarkers. Cell line secretomes are enriched with proteins already linked to tumorigenesis, which also have a good chance of being present in biological fluids. In this review, we will provide an overview of the main technical and biological issues related to cell line secretome analysis, and briefly discuss both the challenges and opportunities in its use for tumor biomarker discovery.     

The long path towards implementation of clinical proteomics: Exemplified based on CKD273

Clinical proteomics aims at the development and the implementation of novel biomarkers that demonstrate a clear clinical benefit in the management of diseases. However, though the attention in the field is increasing and multiple articles on biomarker research are published, clinical implementation of these biomarkers is scarce. In this paper, we aim towards identifying the hurdles on the path towards implementation, and present one successful approach, based on capillary electrophoresis coupled with mass spectrometry. A panel of biomarkers identified and assessed using this approach, termed CKD273, has recently received a Letter‐of‐Support from the US‐Food and Drug Administration (FDA), and is now implemented in the (early) management of chronic kidney disease. Based on this experience in the process towards implementation of CKD273, issues associated with implementation and suggestions how to meet these challenges are given.     

Mobile asynchronous communication: Exploring the potential for converged applications

Trends in technological development show that devices of personal communication and information management are converging and penetrating to new user segments. Therefore, it is a question of interest how the convergence of applications should be managed. This article explores the current use of email and SMS, focussing on the differences in the ways they are used and understood among their users. It is argued that, since the systems are different and have been in use for some time, established practices in using them as well as systems applied to understanding them are different. Based on analysis of interview data, it is conluded that this is the case, and that the future converged systems should not be considered as replacements of the current ones, but rather that the systems need to supplement each other. For example, the need for a quick and dirty instant asynchronous media such as SMS seems to remain, and therefore it cannot be replaced simply by implementing email to mobile phones. The need for email and SMS seems to be different, and thus the development should be towards a better understanding of these needs rather than simple technological convergence.     

Considerations for powering a clinical proteomics study: Normal variability in the human plasma proteome

Proteomics is increasingly being applied to the human plasma proteome to identify biomarkers of disease for use in non‐invasive assays. 2‐D DIGE, simultaneously analysing thousands of protein spots quantitatively and maintaining protein isoform information, is one technique adopted. Sufficient numbers of samples must be analysed to achieve statistical power; however, few reported studies have analysed inherent variability in the plasma proteome by 2‐D DIGE to allow power calculations. This study analysed plasma from 60 healthy volunteers by 2‐D DIGE. Two samples were taken, 7 days apart, allowing estimation of sensitivity of detection of differences in spot intensity between two groups using either a longitudinal (paired) or non‐paired design. Parameters for differences were: two‐fold normalised volume change, α of 0.05 and power of 0.8. Using groups of 20 samples, alterations in 1742 spots could be detected with longitudinal sampling, and in 1206 between non‐paired groups. Interbatch gel variability was small relative to the detection parameters, indicating robustness and reproducibility of 2‐D DIGE for analysing large sample sets. In summary, 20 samples can allow detection of a large number of proteomic alterations by 2‐D DIGE in human plasma, the sensitivity of detecting differences was greatly improved by longitudinal sampling and the technology was robust across batches.     

新型生物传感器在蛋白质组学研究中应用进展

微技术和毫微技术的进展,使新技术的广泛领域包括具有毫微大小的机械设计成为可能．这类设计的新型传感器及其分析是蛋白质组学研究中的重要分析仪器和分析方法之一。文章讨论了新型生物传感器的类型,各种不同类型的生物传感器及非传感器生物检测技术对蛋白质敏感的检出限度和分析时间。综述了新型生物传感器在蛋白质分析鉴定、蛋白质组学研究中的应用进展。