How to get proteomics to the clinic? Issues in clinical proteomics, exemplified by CE-MS

Mass spectrometry-based proteomics as an emerging tool in clinical laboratories

Mass spectrometry (MS)-based proteomics have been increasingly implemented in various disciplines of laboratory medicine to identify and quantify biomolecules in a variety of biological specimens. MS-based proteomics is continuously expanding and widely applied in biomarker discovery for early detection, prognosis and markers for treatment response prediction and monitoring. Furthermore, making these advanced tests more accessible and affordable will have the greatest healthcare benefit.This review article highlights the new paradigms MS-based clinical proteomics has created in microbiology laboratories, cancer research and diagnosis of metabolic disorders. The technique is preferred over conventional methods in disease detection and therapy monitoring for its combined advantages in multiplexing capacity, remarkable analytical specificity and sensitivity and low turnaround time.Despite the achievements in the development and adoption of a number of MS-based clinical proteomics practices, more are expected to undergo transition from bench to bedside in the near future. The review provides insights from early trials and recent progresses (mainly covering literature from the NCBI database) in the application of proteomics in clinical laboratories.

Current state of the art for enhancing urine biomarker discovery

INTRODUCTION

Urine is a highly desirable biospecimen for biomarker analysis because it can be collected recurrently by non-invasive techniques, in relatively large volumes. Urine contains cellular elements, biochemicals, and proteins derived from glomerular filtration of plasma, renal tubule excretion, and urogenital tract secretions that reflect, at a given time point, an individual's metabolic and pathophysiologic state.

AREAS COVERED

High-resolution mass spectrometry, coupled with state of the art fractionation systems are revealing the plethora of diagnostic/prognostic proteomic information existing within urinary exosomes, glycoproteins, and proteins. Affinity capture pre-processing techniques such as combinatorial peptide ligand libraries and biomarker harvesting hydrogel nanoparticles are enabling measurement/identification of previously undetectable urinary proteins. Expert commentary: Future challenges in the urinary proteomics field include a) defining either single or multiple, universally applicable data normalization methods for comparing results within and between individual patients/data sets, and b) defining expected urinary protein levels in healthy individuals.

Recent advances in mass spectrometry-based proteomics of gastric cancer

The last decade has witnessed remarkable technological advances in mass spectrometry-based proteomics. The development of proteomics techniques has enabled the reliable analysis of complex proteomes, leading to the identification and quantification of thousands of proteins in gastric cancer cells, tissues, and sera. This quantitative information has been used to profile the anomalies in gastric cancer and provide insights into the pathogenic mechanism of the disease. In this review, we mainly focus on the advances in mass spectrometry and quantitative proteomics that were achieved in the last five years and how these up-and-coming technologies are employed to track biochemical changes in gastric cancer cells. We conclude by presenting a perspective on quantitative proteomics and its future applications in the clinic and translational gastric cancer research.

Proteomics in cancer research: Are we ready for clinical practice?

Although genomics has delivered major advances in cancer prognostics, treatment and diagnostics, it still only provides a static image of the situation. To study more dynamic molecular entities, proteomics has been introduced into the cancer research field more than a decade ago. Currently, however, the impact of clinical proteomics on patient management and clinical decision-making is low and the implementations of scientific results in the clinic appear to be scarce. The search for cancer-related biomarkers with proteomics however, has major potential to improve risk assessment, early detection, diagnosis, prognosis, treatment selection and monitoring. In this review, we provide an overview of the transition of oncoproteomics towards translational oncology. We describe which lessons are learned from currently approved protein biomarkers and previous proteomic studies, what the pitfalls and challenges are in clinical proteomics applications, and how proteomic research can be successfully translated into medical practice.

Advances in urinary proteome analysis and applications in systems biology

The urinary proteome is the focus of many studies due to the ease of urine collection and the relative proteome stability. Systems biology allows the combination of multiple omics studies, forming a link between proteomics, metabolomics, genomics and transcriptomics. In-depth data interpretation is achieved by bioinformatics analysis of -omics data sets. It is expected that the contribution of systems biology to the study of the urinary proteome will offer novel insights. The main focus of this review is on technical aspects of proteomics studies, available tools for systems biology analysis and the application of urinary proteomics in clinical studies and systems biology.

Multicentre prospective validation of a urinary peptidome-based classifier for the diagnosis of type 2 diabetic nephropathy

BACKGROUND

Diabetic nephropathy (DN) is one of the major late complications of diabetes. Treatment aimed at slowing down the progression of DN is available but methods for early and definitive detection of DN progression are currently lacking. The 'Proteomic prediction and Renin angiotensin aldosterone system Inhibition prevention Of early diabetic nephRopathy In TYpe 2 diabetic patients with normoalbuminuria trial' (PRIORITY) aims to evaluate the early detection of DN in patients with type 2 diabetes (T2D) using a urinary proteome-based classifier (CKD273).

METHODS

In this ancillary study of the recently initiated PRIORITY trial we aimed to validate for the first time the CKD273 classifier in a multicentre (9 different institutions providing samples from 165 T2D patients) prospective setting. In addition we also investigated the influence of sample containers, age and gender on the CKD273 classifier.

RESULTS

We observed a high consistency of the CKD273 classification scores across the different centres with areas under the curves ranging from 0.95 to 1.00. The classifier was independent of age (range tested 16-89 years) and gender. Furthermore, the use of different urine storage containers did not affect the classification scores. Analysis of the distribution of the individual peptides of the classifier over the nine different centres showed that fragments of blood-derived and extracellular matrix proteins were the most consistently found.

CONCLUSION

We provide for the first time validation of this urinary proteome-based classifier in a multicentre prospective setting and show the suitability of the CKD273 classifier to be used in the PRIORITY trial.

Long term metabolic syndrome induced by a high fat high fructose diet leads to minimal renal injury in C57BL/6 mice

Metabolic syndrome can induce chronic kidney disease in humans. Genetically engineered mice on a C57BL/6 background are highly used for mechanistic studies. Although it has been shown that metabolic syndrome induces cardiovascular lesions in C57BL/6 mice, in depth renal phenotyping has never been performed. Therefore in this study we characterized renal function and injury in C57BL/6 mice with long-term metabolic syndrome induced by a high fat and fructose diet (HFFD). C57BL/6 mice received an 8 months HFFD diet enriched with fat (45% energy from fat) and drinking water enriched with fructose (30%). Body weight, food/water consumption, energy intake, fat/lean mass ratio, plasma glucose, HDL, LDL, triglycerides and cholesterol levels were monitored. At 3, 6 and 8 months, renal function was determined by inulin clearance and measure of albuminuria. At sacrifice, kidneys and liver were collected. Metabolic syndrome in C57BL/6 mice fed a HFFD was observed as early 4 weeks with development of type 2 diabetes at 8 weeks after initiation of diet. However, detailed analysis of kidney structure and function showed only minimal renal injury after 8 months of HFFD. HFFD induced moderate glomerular hyperfiltration (436,4 µL/min vs 289,8 µL/min; p-value=0.0418) together with a 2-fold increase in albuminuria only after 8 months of HFFD. This was accompanied by a 2-fold increase in renal inflammation (p-value=0.0217) but without renal fibrosis or mesangial matrix expansion. In addition, electron microscopy did not show alterations in glomeruli such as basal membrane thickening and foot process effacement. Finally, comparison of the urinary peptidome of these mice with the urinary peptidome from humans with diabetic nephropathy also suggested absence of diabetic nephropathy in this model. This study provides evidence that the HFFD C57BL/6 model is not the optimal model to study the effects of metabolic syndrome on the development of diabetic kidney disease.

Screening for obstructive sleep apnoea in obesity and diabetes--potential for future approaches

BACKGROUND

It is recognised that sleep-disordered breathing (SDB), in particular, obstructive sleep apnoea (OSA) is associated with obesity and diabetes. The complications of OSA include dysregulation of metabolic and cardiovascular homeostasis. With the growing population of diabetes and obesity globally, it is becoming apparent that identifying and screening patients who are at risk is becoming increasingly crucial. Many patients may remain unaware of the potential diagnosis and continue to be undiagnosed. The high prevalence of OSA poses a demanding challenge to healthcare providers in order to provide sufficient resources and facilities for patient diagnosis and treatment.

DESIGN

In this article, we review the evidence in favour of screening populations deemed to be at increased risk of OSA, with particular reference to patients with obesity and diabetes. We consider the recent advances in potential screening methods that may allow new prognostic and predictive tools to be developed. A detailed search of Medline and Web of Science electronic databases for relevant articles in English was performed.

RESULTS

Apart from the use of screening tools such as questionnaires and clinical decision models, there is increasing evidence to suggest that there are differences in biological parameters in patients with OSA. Although further studies are required, there may be potential for such biomarkers to contribute to and augment the screening process. However, the significance of such biological tools remains to be elucidated.

CONCLUSIONS

A fundamental role for improved screening in patients with conditions such as obesity and diabetes can enable early interventions that may improve health outcomes relating to the adverse consequences of OSA. The future will see further research being carried out in the development of potential screening methods with emphasis on the selection of patients at risk of sleep disorders, thereby allowing more detailed physiological studies to be carried out where needed.

Proteomics and metabolomics in renal transplantation-quo vadis?

The improvement of long-term transplant organ and patient survival remains a critical challenge following kidney transplantation. Proteomics and biochemical profiling (metabolomics) may allow for the detection of early changes in cell signal transduction regulation and biochemistry with high sensitivity and specificity. Hence, these analytical strategies hold the promise to detect and monitor disease processes and drug effects before histopathological and pathophysiological changes occur. In addition, they will identify enriched populations and enable individualized drug therapy. However, proteomics and metabolomics have not yet lived up to such high expectations. Renal transplant patients are highly complex, making it difficult to establish cause-effect relationships between surrogate markers and disease processes. Appropriate study design, adequate sample handling, storage and processing, quality and reproducibility of bioanalytical multi-analyte assays, data analysis and interpretation, mechanistic verification, and clinical qualification (=establishment of sensitivity and specificity in adequately powered prospective clinical trials) are important factors for the success of molecular marker discovery and development in renal transplantation. However, a newly developed and appropriately qualified molecular marker can only be successful if it is realistic that it can be implemented in a clinical setting. The development of combinatorial markers with supporting software tools is an attractive goal.

Advances in proteomics of digestive juices for the diagnosis of digestive system malignancies

Body fluid proteomic analysis is a new technology and strategy for disease diagnosis and treatment. Blood is the most commonly used specimen in body fluid proteomics, but as a systemic fluid, it has limitations because of complex composition and low abundance of disease-related proteins. In contrast, local body fluids are closest to the lesions, contain more pathological information, and therefore are more valuable in clinical proteomics. In the digestive system, there are a variety of body fluids which are considered potential reservoirs of biomarkers for their quality and quantity of proteins will alter during lesions occurring in corresponding organs. In recent years, more and more clinical proteomic analyses of saliva, gastric juice, bile and pancreatic juice has been reported and the proteins related to digestive cancers have been found, and some proteins show application potentials in cancer diagnosis. However, the proteomic analyses of digestive juices are facing technical challenges in terms of the reproducibility of results and standardization of specimen handling.