Proteomics and personalized medicine: a focus on kidney disease

ABSTRACT

Introduction: Inter-individual variability in response to drug treatment has induced an increased demand for decisions via personalize medicine. Also, the contribution of proteomics to the era of personalized medicine would seem to be vital in improving therapeutic outcomes.

Areas covered: We review validated biomarkers discovered by proteomics techniques and their use in personalized medicine with the focus on kidney diseases. We discuss this topic with a special emphasis on recent publications and relevant initiatives and depict some limitations that remain for personalized medicine.

Expert opinion: The development of highly accurate biomarkers is essential for optimizing the management of kidney diseases. Various biomarkers of kidney diseases have been identified using proteomic techniques. However, only a few of these biomarkers showed the potential to be used in clinical practice concerning personalized medicine. Therefore, it becomes evident that the combination of multiple biomarkers confers higher accuracy and the ability to depict complex pathophysiological conditions, a prerequisite for personalized treatment. CKD273, a multimarker panel for early CKD detection may serve as a first example for personalized medicine in nephrology. Based on this successful example, proteomics is expected to develop into the key technology to guide personalized intervention.     

Anatomy promotes neutral coexistence of strains in the human skin microbiome

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临床蛋白质组学———蛋白质组学在临床研究中的应用

临床蛋白质组学是将蛋白质组学技术应用于临床医学研究,它主要围绕疾病的预防、早期诊断和治疗等方面开展研究,其中,恶性肿瘤是临床蛋白质组学研究的一个重点研究对象.由于肿瘤生物标志物对早期诊断具有重要价值,所以临床蛋白质组学的主要目标之一是寻找合适的肿瘤生物标志物,多分子生物标志物已成为寻找肿瘤生物标志物的一个研究趋势.简要介绍了临床蛋白质组学的基本概念,实验设计,临床样本收集与预处理以及蛋白质组学技术在临床研究中的应用与进展.     

Direct tissue proteomics in human diseases: potential applications to melanoma research

Although the rates of cancer are stabilizing, the number of new invasive melanoma continues to rise. Melanoma represents only 4% of all skin cancers, but nearly 80% of skin cancer deaths. In loss of potential productive life-years, it is second only to adult leukemia. Once melanoma spreads to regional and distant sites, the chance of cure decreases significantly. Unfortunately, current diagnostic and prognostic methods are often inadequate. More precise staging and disease characterization will lead to new and more rational approaches to treatment. Proteomics is a fast-growing discipline in biomedicine that can be defined as the global characterization and differential expression of the entire protein complement of a cell, tissue or organism. Despite major advances in molecular approaches to the diagnosis and prognostication of human diseases such as melanoma, there remain significant obstacles in applying the proteomic technologies to clinical samples to extract important biological information. The application of a shotgun-based technique termed direct tissue proteomics with improved extraction protocol of proteins from formalin-fixed paraffin-embedded tissue would enable retrospective biomarker investigations of the vast archive of pathologically characterized clinical samples that exist worldwide. Combination of this direct tissue proteomics method with laser-capture microdissection may assist in the discovery of new biomarkers and may lead to new diagnostic tests, risk assessment and staging tools as well as improvement in therapeutics. In addition, these tools can provide a molecular characterization of melanoma, which may enable individualized molecular therapy.     

Adaptive landscape genetics: pitfalls and benefits

Landscape genetics offers a promising framework for assessing the interactions between the environment and adaptive genetic variation in natural populations. A recent workshop held at the University of Neuchatel brought together leading experts in this field to address current insights and future research directions in adaptive landscape genetics. Considerable amounts of genetic and/or environmental data can now be collected, but the forthcoming challenge is to do more with such manna. This requires a markedly better understanding of the genetic variation that is adaptive and prompts for advances in information management together with the development of a balance between theory and data. Moreover, showing the links between landscapes and adaptive genetic variation will ultimately move the field beyond association studies.     

Targeted and Untargeted Proteomics Approaches in Biomarker Development

An enormous amount of research effort has been devoted to biomarker discovery and validation. With the completion of the human genome, proteomics is now playing an increasing role in this search for new and better biomarkers. Here, what leads to successful biomarker development is reviewed and how these features may be applied in the context of proteomic biomarker research is considered. The “fit‐for‐purpose” approach to biomarker development suggests that untargeted proteomic approaches may be better suited for early stages of biomarker discovery, while targeted approaches are preferred for validation and implementation. A systematic screening of published biomarker articles using MS‐based proteomics reveals that while both targeted and untargeted technologies are used in proteomic biomarker development, most researchers do not combine these approaches. i) The reasons for this discrepancy, (ii) how proteomic technologies can overcome technical challenges that seem to limit their translation into the clinic, and (iii) how MS can improve, complement, or replace existing clinically important assays in the future are discussed.     

Power law analysis of the human microbiome

Taylor's (1961, Nature, 189:732) power law, a power function (V = am^b) describing the scaling relationship between the mean and variance of population abundances of organisms, has been found to govern the population abundance distributions of single species in both space and time in macroecology. It is regarded as one of few generalities in ecology, and its parameter b has been widely applied to characterize spatial aggregation (i.e. heterogeneity) and temporal stability of single‐species populations. Here, we test its applicability to bacterial populations in the human microbiome using extensive data sets generated by the US‐NIH Human Microbiome Project (HMP). We further propose extending Taylor's power law from the population to the community level, and accordingly introduce four types of power‐law extensions (PLEs): type I PLE for community spatial aggregation (heterogeneity), type II PLE for community temporal aggregation (stability), type III PLE for mixed‐species population spatial aggregation (heterogeneity) and type IV PLE for mixed‐species population temporal aggregation (stability). Our results show that fittings to the four PLEs with HMP data were statistically extremely significant and their parameters are ecologically sound, hence confirming the validity of the power law at both the population and community levels. These findings not only provide a powerful tool to characterize the aggregations of population and community in both time and space, offering important insights into community heterogeneity in space and/or stability in time, but also underscore the three general properties of power laws (scale invariance, no average and universality) and their specific manifestations in our four PLEs.     

Genetic Profile and Functional Proteomics of Anal Squamous Cell Carcinoma: Proposal for a Molecular Classification

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Highlights

• •Two molecular groups in anal squamous carcinoma according proteomic profile.
• •Differences in possible targeted processes such as metabolism or immune response.
• •Different percentage of tumor lymphocyte infiltration.
• •Difference in the frequency of ATM variants, related to PPAR inhibitors.

     

Functional microbiome deficits associated with ageing: Chronological age threshold

Composition of the gut microbiota changes during ageing, but questions remain about whether age is also associated with deficits in microbiome function and whether these changes occur sharply or progressively. The ability to define these deficits in populations of different ages may help determine a chronological age threshold at which deficits occur and subsequently identify innovative dietary strategies for active and healthy ageing. Here, active gut microbiota and associated metabolic functions were evaluated using shotgun proteomics in three well‐defined age groups consisting of 30 healthy volunteers, namely, ten infants, ten adults and ten elderly individuals. Samples from each volunteer at intervals of up to 6 months (n = 83 samples) were used for validation. Ageing gradually increases the diversity of gut bacteria that actively synthesize proteins, that is by 1.4‐fold from infants to elderly individuals. An analysis of functional deficits consistently identifies a relationship between tryptophan and indole metabolism and ageing (p < 2.8e^?8). Indeed, the synthesis of proteins involved in tryptophan and indole production and the faecal concentrations of these metabolites are directly correlated (r² > .987) and progressively decrease with age (r² > .948). An age threshold for a 50% decrease is observed ca. 11–31 years old, and a greater than 90% reduction is observed from the ages of 34–54 years. Based on recent investigations linking tryptophan with abundance of indole and other “healthy” longevity molecules and on the results from this small cohort study, dietary interventions aimed at manipulating tryptophan deficits since a relatively “young” age of 34 and, particularly, in the elderly are recommended.     

LncRNAs as potential diagnostic and prognostic biomarkers in gastric cancer: A novel approach to personalized medicine

Gastric cancer is the third leading cause of cancer death with 5-year survival rate of about 30–35%. Since early detection is associated with decreased mortality, identification of novel biomarkers for early diagnosis and proper management of patients with the best response to therapy is urgently needed. Long noncoding RNAs (lncRNAs) due to their high specificity, easy accessibility in a noninvasive manner, as well as their aberrant expression under different pathological and physiological conditions, have received a great attention as potential diagnostic, prognostic, or predictive biomarkers. They may also serve as targets for treating gastric cancer. In this review, we highlighted the role of lncRNAs as tumor suppressors or oncogenes that make them potential biomarkers for the diagnosis and prognosis of gastric cancer. Relatively, lncRNAs such as H19, HOTAIR, UCA1, PVT1, tissue differentiation-inducing nonprotein coding, and LINC00152 could be potential diagnostic and prognostic markers in patients with gastric cancer. Also, the impact of lncRNAs such as ecCEBPA, MLK7-AS1, TUG1, HOXA11-AS, GAPLINC, LEIGC, multidrug resistance-related and upregulated lncRNA, PVT1 on gastric cancer epigenetic and drug resistance as well as their potential as therapeutic targets for personalized medicine was discussed.     

Proteomics in biomarker discovery and drug development

Proteomics is a research field aiming to characterize molecular and cellular dynamics in protein expression and function on a global level. The introduction of proteomics has been greatly broadening our view and accelerating our path in various medical researches. The most significant advantage of proteomics is its ability to examine a whole proteome or sub-proteome in a single experiment so that the protein alterations corresponding to a pathological or biochemical condition at a given time can be considered in an integrated way. Proteomic technology has been extensively used to tackle a wide variety of medical subjects including biomarker discovery and drug development. By complement with other new technique advances in genomics and bioinformatics, proteomics has a great potential to make considerable contribution to biomarker identification and to revolutionize drug development process. This article provides a brief overview of the proteomic technologies and their application in biomarker discovery and drug development.     

Proteomics in atherothrombosis: a future perspective

Atherothrombosis is the primary cause of death in Western countries. The cellular and molecular mechanisms underlying atherosclerosis remain widely unknown. The complex nature of atherosclerotic cardiovascular diseases demands the development of novel technologies that enable discovery of new biomarkers for early disease detection and risk stratification, which may predict clinical outcome. In this review, we outline potential sources and recent proteomic approaches that could be applied in the search of novel biomarkers of cardiovascular risk. In addition, we describe some issues raised in relation to the application of proteomics to blood samples, as well as two novel emerging concepts, such as peptidomics and population proteomics. In the future, the use of high-throughput techniques (proteomic, genomics and metabolomics) will potentially identify novel patterns of biomarkers, which, along with traditional risk factors and imaging techniques, could help to target vulnerable patients and monitor the beneficial effects of pharmacological agents.     

Cancer Proteomics and the Elusive Diagnostic Biomarkers

Despite progress in genomic and proteomic technology and applications, the validation of cancer biomarkers of use as clinical early detection diagnostics has remained elusive. As described in this brief viewpoint, there are now recognized to be many types of clinical biomarkers and proteomic analyses, particularly when combined with other ‘omic analyses, have been effective in many such biomarker identifications. However, in the area of early diagnosis of cancers, the problems associated with the conversion from identification to diagnostic have largely not been overcome. Notably, the Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute (NCI), has been particularly successful in refining the analytical steps needed to tackle this challenging issue and has provided positive insight into how to solve many of the underlying problems. The potential for developing clinical diagnostics for early detection of highly lethal cancers and possible new therapeutic strategies through proteomic analyses, as seen through these CPTAC successes, is more promising than ever.     

人体微生物组计划

人体微生物组计划又称第二人类基因组计划。由美国国立卫生研究院立项资助,2007年正式启动。计划用5年时间耗资1.5亿美元完成900个人体微生物基因组测序。其目标是探索研究人类微生物组的可行性;研究人体微生物组变化与疾病健康的关系;同时为其它科学研究提供信息和技术支持。     

Proteomics in cardiovascular disease: recent progress and clinical implication and implementation

Introduction: Although multiple efforts have been initiated to shed light into the molecular mechanisms underlying cardiovascular disease, it still remains one of the major causes of death worldwide. Proteomic approaches are unequivocally powerful tools that may provide deeper understanding into the molecular mechanisms associated with cardiovascular disease and improve its management.

Areas covered: Cardiovascular proteomics is an emerging field and significant progress has been made during the past few years with the aim of defining novel candidate biomarkers and obtaining insight into molecular pathophysiology. To summarize the recent progress in the field, a literature search was conducted in PubMed and Web of Science. As a result, 704 studies from PubMed and 320 studies from Web of Science were retrieved. Findings from original research articles using proteomics technologies for the discovery of biomarkers for cardiovascular disease in human are summarized in this review.

Expert commentary: Proteins associated with cardiovascular disease represent pathways in inflammation, wound healing and coagulation, proteolysis and extracellular matrix organization, handling of cholesterol and LDL. Future research in the field should target to increase proteome coverage as well as integrate proteomics with other omics data to facilitate both drug development as well as clinical implementation of findings.     

Proteomics and syndrome of Chinese medicine

Syndrome of Chinese medicine is an understanding of the regularity of disease occurrence and development and its performance of symptoms. Syndrome is the key to recognize diseases and the foundation to treat them. However, because of the complexity of the concept and the limitation of present investigations, the research of syndrome is hard to go further. Proteomics has been received extensive attention in the area of medical diagnosis and drug development. In the holistic and systemic context, proteomics have a convergence with traditional Chinese medicine (TCM) syndrome, which could overcome the one-sidedness and singleness of TCM and avoid the complication and tedious processes. Chinese medicine has a wealth of experience and proteomics has a substantial research potential, the integration of the two aspects will bring a great enhancement of our knowledge of disease.     

Proteomics in uveal melanoma research: opportunities and challenges in biomarker discovery

Uveal melanoma (UM) is the most frequent primary intraocular tumor in adult humans. Despite the significant advances in diagnosis and treatment of UM in the last decades, the prognosis of UM sufferers is still poor. Metastatic liver disease is the leading cause of death in UM and can develop after a long disease-free interval, suggesting the presence of occult micrometastasis. Proteomics technology has opened new opportunities for elucidating the molecular mechanism of complex diseases, such as cancer. This article will review the recent developments in biomarker discovery for UM research by proteomics. In the last few years, the first UM proteomics-based analyses have been launched, yielding promising results. An update on recent developments on this field is presented.