Targeting intercellular signals for bone regeneration from bone marrow mesenchymal progenitors

There are tremendous unmet clinical needs for effective strategies to enhance bone regeneration in vivo. The sustained presence of multipotent mesenchymal progenitors in the bone marrow in aged and osteoporotic individuals offers the potential for therapeutic interventions to induce osteoblast production from the resident progenitors. Recent advances in understanding the intercellular signals governing osteogenic decisions may provide targets for developing novel bone-enhancing therapeutics.     

Clinical proteomics-driven precision medicine for targeted cancer therapy: current overview and future perspectives

Cancer is a common disease that is a leading cause of death worldwide. Currently, early detection and novel therapeutic strategies are urgently needed for more effective management of cancer. Importantly, protein profiling using clinical proteomic strategies, with spectacular sensitivity and precision, offer excellent promise for the identification of potential biomarkers that would direct the development of targeted therapeutic anticancer drugs for precision medicine. In particular, clinical sample sources, including tumor tissues and body fluids (blood, feces, urine and saliva), have been widely investigated using modern high-throughput mass spectrometry-based proteomic approaches combined with bioinformatic analysis, to pursue the possibilities of precision medicine for targeted cancer therapy. Discussed in this review are the current advantages and limitations of clinical proteomics, the available strategies of clinical proteomics for the management of precision medicine, as well as the challenges and future perspectives of clinical proteomics-driven precision medicine for targeted cancer therapy.     

Progress in mining the human proteome for disease applications

Currently available technologies allow in-depth analysis of multiple facets of the proteome that have clinical relevance and that complement current genomics-based approaches. Although some progress has been made in our knowledge of the human proteome in health and in disease, there is an urgent need to chart a coherent road map with clearly defined milestones to guide proteomics efforts. Areas of emphasis include: (1) building resources, (2) filling gaps in our understanding of biological variation, and (3) systematically characterizing proteome alterations that occur in well-defined disease states, all of which require an organized and collaborative effort.     

Proteomic profiling of pancreatic cancer for biomarker discovery

Pancreatic cancer is a uniformly lethal disease that is difficult to diagnose at early stage and even more difficult to cure. In recent years, there has been a substantial interest in applying proteomics technologies to identify protein biomarkers for early detection of cancer. Quantitative proteomic profiling of body fluids, tissues, or other biological samples to identify differentially expressed proteins represents a very promising approach for improving the outcome of this disease. Proteins associated with pancreatic cancer identified through proteomic profiling technologies could be useful as biomarkers for the early diagnosis, therapeutic targets, and disease response markers. In this article, we discuss recent progress and challenges for applying quantitative proteomics technologies for biomarker discovery in pancreatic cancer.     

Pharmacogenetic approaches to the treatment of alcohol addiction

Addictive disorders are partly heritable, chronic, relapsing conditions that account for a tremendous disease burden. Currently available addiction pharmacotherapies are only moderately successful, continue to be viewed with considerable scepticism outside the scientific community and have not become widely adopted as treatments. More effective medical treatments are needed to transform addiction treatment and address currently unmet medical needs. Emerging evidence from alcoholism research suggests that no single advance can be expected to fundamentally change treatment outcomes. Rather, studies of opioid, corticotropin-releasing factor, GABA and serotonin systems suggest that incremental advances in treatment outcomes will result from an improved understanding of the genetic heterogeneity among patients with alcohol addiction, and the development of personalized treatments.     

Proteome informatics for cancer research: from molecules to clinic

Proteomics offers the most direct approach to understand disease and its molecular biomarkers. Biomarkers denote the biological states of tissues, cells, or body fluids that are useful for disease detection and classification. Clinical proteomics is used for early disease detection, molecular diagnosis of disease, identification and formulation of therapies, and disease monitoring and prognostics. Bioinformatics tools are essential for converting raw proteomics data into knowledge and subsequently into useful applications. These tools are used for the collection, processing, analysis, and interpretation of the vast amounts of proteomics data. Management, analysis, and interpretation of large quantities of raw and processed data require a combination of various informatics technologies such as databases, sequence comparison, predictive models, and statistical tools. We have demonstrated the utility of bioinformatics in clinical proteomics through the analysis of the cancer antigen survivin and its suitability as a target for cancer immunotherapy.     

The Human Eye Proteome Project: Perspectives on an emerging proteome

There are an estimated 285 million people with visual impairment worldwide, of whom 39 million are blind. The pathogenesis of many eye diseases remains poorly understood. The human eye is currently an emerging proteome that may provide key insight into the biological pathways of disease. We review proteomic investigations of the human eye and present a catalogue of 4842 nonredundant proteins identified in human eye tissues and biofluids to date. We highlight the need to identify new biomarkers for eye diseases using proteomics. Recent advances in proteomics do now allow the identification of hundreds to thousands of proteins in tissues and fluids, characterization of various PTMs and simultaneous quantification of multiple proteins. To facilitate proteomic studies of the eye, the Human Eye Proteome Project (HEPP) was organized in September 2012. The HEPP is one of the most recent components of the Biology/Disease‐driven Human Proteome Project (B/D‐HPP) whose overarching goal is to support the broad application of state‐of‐the‐art measurements of proteins and proteomes by life scientists studying the molecular mechanisms of biological processes and human disease. The large repertoire of investigative proteomic tools has great potential to transform vision science and enhance understanding of physiology and disease processes that affect sight.     

Population proteomics: addressing protein diversity in humans

In the past several years, proteomics and its subdiscipline clinical proteomics have been engaged in the discovery of the next generation protein of biomarkers. As the effort and the intensive debate it has sparked continue, it is becoming apparent that a paradigm shift is needed in proteomics in order to truly comprehend the complexity of the human proteome and assess its subtle variations among individuals. This review introduces the concept of population proteomics as a future direction in proteomics research. Population proteomics is the study of protein diversity in human populations. High-throughput, top-down mass spectrometric approaches are employed to investigate, define and understand protein diversity and modulations across and within populations. Population proteomics is a discovery-oriented endeavor with a goal of establishing the incidence of protein structural variations and quantitative regulation of these modifications. Assessing human protein variations among and within populations is viewed as a paramount undertaking that can facilitate clinical proteomics’ effort in discovery and validation of protein features that can be used as markers for early diagnosis of disease, monitoring of disease progression and assessment of therapy. This review outlines the growing need for analyzing individuals’ proteomes and describes the approaches that are likely to be applied in such a population proteomics endeavor.     

Population proteomics: addressing protein diversity in humans

In the past several years, proteomics and its subdiscipline clinical proteomics have been engaged in the discovery of the next generation protein of biomarkers. As the effort and the intensive debate it has sparked continue, it is becoming apparent that a paradigm shift is needed in proteomics in order to truly comprehend the complexity of the human proteome and assess its subtle variations among individuals. This review introduces the concept of population proteomics as a future direction in proteomics research. Population proteomics is the study of protein diversity in human populations. High-throughput, top-down mass spectrometric approaches are employed to investigate, define and understand protein diversity and modulations across and within populations. Population proteomics is a discovery-oriented endeavor with a goal of establishing the incidence of protein structural variations and quantitative regulation of these modifications. Assessing human protein variations among and within populations is viewed as a paramount undertaking that can facilitate clinical proteomics' effort in discovery and validation of protein features that can be used as markers for early diagnosis of disease, monitoring of disease progression and assessment of therapy. This review outlines the growing need for analyzing individuals' proteomes and describes the approaches that are likely to be applied in such a population proteomics endeavor.     

Glioma proteomics: Status and perspectives

High grade gliomas are the most common brain tumors in adults and their malignant nature makes them the fourth biggest cause of cancer death. Major efforts in neuro-oncology research are needed to reach similar progress in treatment efficacy as that achieved for other cancers in recent years. In addition to the urgent need to identify novel effective drug targets against malignant gliomas, the search for glioma biomarkers and grade specific protein signatures will provide a much needed contribution to diagnosis, prognosis, treatment decision and assessment of treatment response. Over the past years glioma proteomics has been attempted at different levels, including proteome analysis of patient biopsies and bodily fluids, of glioma cell lines and animal models. Here we provide an extensive review of the outcome of these studies in terms of protein identifications (protein numbers and regulated proteins), with an emphasis on the methods used and the limitations of the studies with regard to biomarker discovery. This is followed by a perspective on novel technologies and on the potential future contribution of proteomics in a broad sense to understanding glioma biology.     

Current strategies and findings in clinically relevant post-translational modification-specific proteomics

Mass spectrometry-based proteomics has considerably extended our knowledge about the occurrence and dynamics of protein post-translational modifications (PTMs). So far, quantitative proteomics has been mainly used to study PTM regulation in cell culture models, providing new insights into the role of aberrant PTM patterns in human disease. However, continuous technological and methodical developments have paved the way for an increasing number of PTM-specific proteomic studies using clinical samples, often limited in sample amount. Thus, quantitative proteomics holds a great potential to discover, validate and accurately quantify biomarkers in body fluids and primary tissues. A major effort will be to improve the complete integration of robust but sensitive proteomics technology to clinical environments. Here, we discuss PTMs that are relevant for clinical research, with a focus on phosphorylation, glycosylation and proteolytic cleavage; furthermore, we give an overview on the current developments and novel findings in mass spectrometry-based PTM research.     

Role of proteomics in biomarker discovery and psychiatric disorders: current status,potentials, limitations and future challenges

Proteomic approaches have advanced clinical research towards more reliable, sensitive and specific biological diagnostic markers for diseases. Mood disorders are most difficult to diagnose and very much prevalent in society; hence, their proper diagnosis becomes essential. Despite tremendous research efforts to dissect the neurobiological basis of psychiatric disorders, the diagnosis and evaluation for such diseases is still poor. Biomarker discovery in psychiatry research has been accelerated by proteomic technologies, accepting the challenges in order to meet disease state-related investigations. Proteomics-based research for disease-specific protein signatures is expected to give a new direction in psychiatry research. Therefore, this may become a more powerful tool to predict the development, course and outcome of the disease towards personalized psychiatric ailments. The review discusses the role of proteomics in elucidating mechanisms of psychiatric disorders, current status, prospects, limitations and new possibilities towards a strong diagnostic tool in the clinical laboratory.     

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.     

Recovering circulating extracellular or cell-free RNA from bodily fluids

The presence of extracellular circulating or cell-free RNA in biological fluids is becoming a promising diagnostic tool for non invasive and cost effective cancer detection. Extracellular RNA or miRNA as biological marker could be used either for the early detection and diagnosis of the disease or as a marker of recurrence patterns and surveillance. In this review article, we refer to the origin of the circulating extracellular RNA, we summarise the data on the biological fluids (serum/plasma, saliva, urine, cerebrospinal fluid and bronchial lavage fluid) of patients suffering from various types of malignancies reported to contain a substantial amount of circulating extracellular (or cell-free) RNAs and we discuss the appropriate reagents and methodologies needed to be employed in order to obtain RNA material of high quality and integrity for the majority of the experimental methods used in RNA expression analysis. Furthermore, we discuss the advantages and disadvantages of the RT-PCR or microarray methodology which are the methods more often employed in procedures of extracellular RNA analysis.     

A Foundation for Reliable Spatial Proteomics Data Analysis

Quantitative mass-spectrometry-based spatial proteomics involves elaborate, expensive, and time-consuming experimental procedures, and considerable effort is invested in the generation of such data. Multiple research groups have described a variety of approaches for establishing high-quality proteome-wide datasets. However, data analysis is as critical as data production for reliable and insightful biological interpretation, and no consistent and robust solutions have been offered to the community so far. Here, we introduce the requirements for rigorous spatial proteomics data analysis, as well as the statistical machine learning methodologies needed to address them, including supervised and semi-supervised machine learning, clustering, and novelty detection. We present freely available software solutions that implement innovative state-of-the-art analysis pipelines and illustrate the use of these tools through several case studies involving multiple organisms, experimental designs, mass spectrometry platforms, and quantitation techniques. We also propose sound analysis strategies for identifying dynamic changes in subcellular localization by comparing and contrasting data describing different biological conditions. We conclude by discussing future needs and developments in spatial proteomics data analysis.     

Data merging for integrated microarray and proteomic analysis.

The functioning of even a simple biological system is much more complicated than the sum of its genes, proteins and metabolites. A premise of systems biology is that molecular profiling will facilitate the discovery and characterization of important disease pathways. However, as multiple levels of effector pathway regulation appear to be the norm rather than the exception, a significant challenge presented by high-throughput genomics and proteomics technologies is the extraction of the biological implications of complex data. Thus, integration of heterogeneous types of data generated from diverse global technology platforms represents the first challenge in developing the necessary foundational databases needed for predictive modelling of cell and tissue responses. Given the apparent difficulty in defining the correspondence between gene expression and protein abundance measured in several systems to date, how do we make sense of these data and design the next experiment? In this review, we highlight current approaches and challenges associated with integration and analysis of heterogeneous data sets, focusing on global analysis obtained from high-throughput technologies.     

Perspective: a program to improve protein biomarker discovery for cancer

Biomarkers for cancer risk, early detection, prognosis, and therapeutic response promise to revolutionize cancer management. Protein biomarkers offer tremendous potential in this regard due to their great diversity and intimate involvement in physiology. An effective program to discover protein biomarkers using existing technology will require team science, an integrated informatics platform, identification and quantitation of candidate biomarkers in disease tissue, mouse models of disease, standardized reagents for analyzing candidate biomarkers in bodily fluids, and implementation of automation. Technology improvements for better fractionation of the proteome, selection of specific biomarkers from complex mixtures, and multiplexed assay of biomarkers would greatly enhance progress.     

The use of biophysical proteomic techniques in advancing our understanding of diseases

The use of proteomic approaches in investigating diseases is continuing to expand and has started to provide answers to substantial gaps in our understanding of disease pathogenesis as well as in the development of effective strategies for the early diagnosis and treatment of diseases. Biophysical techniques form a crucial part of the advanced proteomic techniques currently used and include mass spectrometry and protein separation techniques, such as two-dimensional gel electrophoresis and liquid chromatography. The application of biophysical proteomic techniques in the study of disease includes delineation of altered protein expression, not only at the whole-cell or tissue levels, but also in subcellular structures, protein complexes, and biological fluids. These techniques are also being used for the discovery of novel disease biomarkers, exploration of the pathogenesis of diseases, development of new diagnostic methodologies, and identification of new targets for therapeutics. Proteomic techniques also have the potential for accelerating drug development through more effective strategies for evaluating a specific drug’s therapeutic effects and toxicity. This article discusses the application of biophysical proteomic techniques in delineating cardiovascular disease and other diseases, as well as the limitations and future research directions required for these techniques to gain greater acceptance and have a larger impact.     

Proteomic tools for biomedicine

Proteomic tools measure gene expression, protein activity and interactions of biological events at the protein level. Proteins are the major catalysts of biological functions and contain several dimensions of information that collectively indicate the actual rather than the potential functional state as indicated by mRNA analysis. Measurements can be made in terms of protein quantity, location, and time-point. For the future we see a further integration of existing and new technologies for proteomics from a wide range of areas of biochemistry, chemistry, physics, computing science and molecular biology. This will further advance our knowledge of how biological systems are built up and what mechanisms control these systems. However, the potential of proteomics to comprehensively answer all biological questions is limited as only protein activity is measured. A unification of genomics, proteomics, and other technologies is needed if we are to start to understand the complexity of biological function in the context of disease and health.     

Cryobanking of viable biomaterials: implementation of new strategies for conservation purposes

Cryobanking, the freezing of biological specimens to maintain their integrity for a variety of anticipated and unanticipated uses, offers unique opportunities to advance the basic knowledge of biological systems and their evolution. Notably, cryobanking provides a crucial opportunity to support conservation efforts for endangered species. Historically, cryobanking has been developed mostly in response to human economic and medical needs — these needs must now be extended to biodiversity conservation. Reproduction technologies utilizing cryobanked gametes, embryos and somatic cells are already vital components of endangered species recovery efforts. Advances in modern biological research (e.g. stem cell research, genomics and proteomics) are already drawing heavily on cryobanked specimens, and future needs are anticipated to be immense. The challenges of developing and applying cryobanking for a broader diversity of species were addressed at an international conference held at Trier University (Germany) in June 2008. However, the magnitude of the potential benefits of cryobanking stood in stark contrast to the lack of substantial resources available for this area of strategic interest for biological science — and society at large. The meeting at Trier established a foundation for a strong global incentive to cryobank threatened species. The establishment of an Amphibian Ark cryobanking programme offers the first opportunity for global cooperation to achieve the cryobanking of the threatened species from an entire vertebrate class.