Sample collection in clinical proteomics--proteolytic activity profile of serum and plasma

Tumor-On-A-Chip Models for Predicting In Vivo Nanoparticle Behavior

Nanosized drug formulations are broadly explored for the improvement of cancer therapy. Prediction of in vivo nanoparticle (NP) behavior, however, is challenging, given the complexity of the tumor and its microenvironment. Microfluidic tumor-on-a-chip models are gaining popularity for the in vitro testing of nanoparticle targeting under conditions that simulate the 3D tumor (microenvironment). In this review, following a description of the tumor microenvironment (TME), the state of the art regarding tumor-on-a-chip models for investigating nanoparticle delivery to solid tumors is summarized. The models are classified based on the degree of compartmentalization (single/multi-compartment) and cell composition (tumor only/tumor microenvironment). The physiological relevance of the models is critically evaluated. Overall, microfluidic tumor-on-a-chip models greatly improve the simulation of the TME in comparison to 2D tissue cultures and static 3D spheroid models and contribute to the understanding of nanoparticle behavior. Interestingly, two interrelated aspects have received little attention so far which are the presence and potential impact of a protein corona as well as nanoparticle uptake through phagocytosing cells. A better understanding of their relevance for the predictive capacity of tumor-on-a-chip systems and development of best practices will be a next step for the further refinement of advanced in vitro tumor models.

Description of an activity-based enzyme biosensor for lung cancer detection

BACKGROUND

Lung cancer is associated with the greatest cancer mortality as it typically presents with incurable distributed disease. Biomarkers relevant to risk assessment for the detection of lung cancer continue to be a challenge because they are often not detectable during the asymptomatic curable stage of the disease. A solution to population-scale testing for lung cancer will require a combination of performance, scalability, cost-effectiveness, and simplicity.

METHODS

One solution is to measure the activity of serum available enzymes that contribute to the transformation process rather than counting biomarkers. Protease enzymes modify the environment during tumor growth and present an attractive target for detection. An activity based sensor platform sensitive to active protease enzymes is presented. A panel of 18 sensors was used to measure 750 sera samples from participants at increased risk for lung cancer with or without the disease.

RESULTS

A machine learning approach is applied to generate algorithms that detect 90% of cancer patients overall with a specificity of 82% including 90% sensitivity in Stage I when disease intervention is most effective and detection more challenging.

CONCLUSION

This approach is promising as a scalable, clinically useful platform to help detect patients who have lung cancer using a simple blood sample. The performance and cost profile is being pursued in studies as a platform for population wide screening.

Tutorial review for peptide assays: An ounce of pre-analytics is worth a pound of cure

The recent increase in peptidomimetic-based medications and the growing interest in peptide hormones has brought new attention to the quantification of peptides for diagnostic purposes. Indeed, the circulating concentrations of peptide hormones in the blood provide a snapshot of the state of the body and could eventually lead to detecting a particular health condition. Although extremely useful, the quantification of such molecules, preferably by liquid chromatography coupled to mass spectrometry, might be quite tricky. First, peptides are subjected to hydrolysis, oxidation, and other post-translational modifications, and, most importantly, they are substrates of specific and nonspecific proteases in biological matrixes. All these events might continue after sampling, changing the peptide hormone concentrations. Second, because they include positively and negatively charged groups and hydrophilic and hydrophobic residues, they interact with their environment; these interactions might lead to a local change in the measured concentrations. A phenomenon such as nonspecific adsorption to lab glassware or materials has often a tremendous effect on the concentration and needs to be controlled with particular care. Finally, the circulating levels of peptides might be low (pico- or femtomolar range), increasing the impact of the aforementioned effects and inducing the need for highly sensitive instruments and well-optimized methods. Thus, despite the extreme diversity of these peptides and their matrixes, there is a common challenge for all the assays: the need to keep concentrations unchanged from sampling to analysis. While significant efforts are often placed on optimizing the analysis, few studies consider in depth the impact of pre-analytical steps on the results. By working through practical examples, this solution-oriented tutorial review addresses typical pre-analytical challenges encountered during the development of a peptide assay from the standpoint of a clinical laboratory. We provide tips and tricks to avoid pitfalls as well as strategies to guide all new developments. Our ultimate goal is to increase pre-analytical awareness to ensure that newly developed peptide assays produce robust and accurate results.

Quantitative protein mass-spectrometry requires a standardized pre-analytical phase

OBJECTIVES

Quantitative protein mass-spectrometry (QPMS) in blood depends on tryptic digestion of proteins and subsequent measurement of representing peptides. Whether serum and plasma can be used interchangeably and whether in-vitro anticoagulants affect the recovery is unknown. In our laboratory serum samples are the preferred matrix for QPMS measurement of multiple apolipoproteins. In this study, we investigated the effect of different matrices on apolipoprotein quantification by mass spectrometry.

METHODS

Blood samples were collected from 44 healthy donors in Beckton Dickinson blood tubes simultaneously for serum (with/without gel) and plasma (heparin, citrate or EDTA). Nine apolipoproteins were quantified according to standard operating procedure using value-assigned native serum calibrators for quantitation. Tryptic digestion kinetics were investigated in the different matrices by following formation of peptides for each apolipoprotein in time, up to 22 h.

RESULTS

In citrate plasma recovery of apolipoproteins showed an overall reduction with a bias of -14.6%. For heparin plasma only -0.3% bias was found compared to serum, whereas for EDTA-plasma reduction was more pronounced (-5.3% bias) and variable with >14% reduction for peptides of apoA-I, A-II and C-III. Digestion kinetics revealed that especially slow forming peptides showed reduced formation in EDTA-plasma.

CONCLUSIONS

Plasma anticoagulants affect QPMS test results. Heparin plasma showed comparable results to serum. Reduced concentrations in citrate plasma can be explained by dilution, whereas reduced recovery in EDTA-plasma is dependent on altered proteolytic digestion efficiency. The results highlight the importance of a standardized pre-analytical phase for accurate QPMS applications in clinical chemistry.

Assessment of the Stability of Midregional Proadrenomedullin in Different Biological Matrices

Midregional proadrenomedullin (MR-proADM) has been shown to play a key role in endothelial dysfunction, with increased levels helping to prevent early stages of organ dysfunction. Recent clinical evidence has demonstrated MR-proADM to be a helpful biomarker to identify disease severity in patients with sepsis as well as pneumonia. This biomarker is helpful at triage in emergency departments to assess risk level of patients. The aim of this study is to evaluate the stability of MR-proADM in different biological matrices. The results, obtained by Bland-Altman and scatter plot analyses, demonstrate that deviation of MR-proADM concentration in serum compared to EDTA plasma unequivocally shows that serum should not be used as a sample matrix. Instead, the excellent correlation of heparin plasma vs EDTA plasma samples shows that heparin plasma can be used without reservation in clinical routine and emergency samples.

Determination of amino acids in human biological fluids by high-performance liquid chromatography: critical review

The quantitation and qualification of amino acids are most commonly used in clinical and epidemiological studies, and provide an excellent way of monitoring compounds in human fluids which have not been monitored previously, to prevent some diseases. Because of this, it is not surprising that scientific interest in evaluating these compounds has resurfaced in recent years and has precipitated the development of a multitude of new analytical techniques. This review considers recent developments in HPLC analytics on the basis of publications from the last few years. It helps to update and systematize knowledge in this area. Particular attention is paid to the progress of analytical methods, pointing out the advantages and drawbacks of the various techniques used for the preparation, separation and determination of amino acids. Depending on the type of sample, the preparation conditions for HPLC analysis change. For this reason, the review has focused on three types of samples, namely urine, blood and cerebrospinal fluid. Despite time-consuming sample preparation before HPLC analysis, an additional derivatization technique should be used, depending on the detection technique used. There are proposals for columns that are specially modified for amino acid separation without derivatization, but the limit of detection of the substance is less beneficial. In view of the fact that amino acid analyses have been performed for years and new solutions may generate increased costs, it may turn out that older proposals are much more advantageous.

The heparin-binding proteome in normal pancreas and murine experimental acute pancreatitis

Acute pancreatitis (AP) is acute inflammation of the pancreas, mainly caused by gallstones and alcohol, driven by changes in communication between cells. Heparin-binding proteins (HBPs) play a central role in health and diseases. Therefore, we used heparin affinity proteomics to identify extracellular HBPs in pancreas and plasma of normal mice and in a caerulein mouse model of AP. Many new extracellular HBPs (360) were discovered in the pancreas, taking the total number of HBPs known to 786. Extracellular pancreas HBPs form highly interconnected protein-protein interaction networks in both normal pancreas (NP) and AP. Thus, HBPs represent an important set of extracellular proteins with significant regulatory potential in the pancreas. HBPs in NP are associated with biological functions such as molecular transport and cellular movement that underlie pancreatic homeostasis. However, in AP HBPs are associated with additional inflammatory processes such as acute phase response signalling, complement activation and mitochondrial dysfunction, which has a central role in the development of AP. Plasma HBPs in AP included known AP biomarkers such as serum amyloid A, as well as emerging targets such as histone H2A. Other HBPs such as alpha 2-HS glycoprotein (AHSG) and histidine-rich glycoprotein (HRG) need further investigation for potential applications in the management of AP. Pancreas HBPs are extracellular and so easily accessible and are potential drug targets in AP, whereas plasma HBPs represent potential biomarkers for AP. Thus, their identification paves the way to determine which HBPs may have potential applications in the management of AP.

Pre-fractionation of Noncirculating Biological Fluids to Improve Discovery of Clinically Relevant Protein Biomarkers

Nowadays, significant difficulties remain in the diagnosis and/or prognosis of many diseases, leading to an unsatisfactory patient management and a counterproductive increase in time and costs. It is therefore crucial to bridge the gap between basic and applied research by complying with clinical requirements, notably from the design stage of the experimental workflow. In this chapter we provide key suggestions for selecting appropriate biological samples and reducing pre-analytical and analytical variabilities to improve the discovery of clinically relevant protein biomarkers.

Characterization of the Blister Fluid Proteome for Pediatric Burn Classification

Blister fluid (BF) is a novel and viable research matrix for burn injury study, which can reflect both systemic and local microenvironmental responses. The protein abundance in BF from different burn severities were initially observed using a 2D SDS-PAGE approach. Subsequently, a quantitative data independent acquisition (DIA) method, SWATH, was employed to characterize the proteome of pediatric burn blister fluid. More than 600 proteins were quantitatively profiled in 87 BF samples from different pediatric burn patients. These data were correlated with clinically assessed burn depth and time until complete wound re-epithelialization through several different statistical analyses. Several proteins from these analyses exhibited significant abundance change between different burn depth or re-epithelialization groups, and can be considered as potential biomarker candidates. Further gene ontology (GO) enrichment analysis of the significant proteins revealed the most significant burn related biological processes (BP) that are altered with burn depth, including homeostasis and oxygen transport. However, for wounds with re-epithelialization times more or less than 21 days, the significant GO annotations were related to enzyme activity. This quantitative proteomics investigation of burn BF may enable objective classification of burn wound severity and assist with clinical decision-making. Data are available via ProteomeXchange with identifier PXD011102.

Direct Assessment of Plasma/Serum Sample Quality for Proteomics Biomarker Investigation

Blood proteome analysis for biomarker discovery represents one of the most challenging tasks to be achieved through clinical proteomics due to the sample complexity, such as the extreme heterogeneity of proteins in very dynamic concentrations, and to the observation of proper sampling and storage conditions. Quantitative and qualitative proteomics profiling of plasma and serum could be useful both for the early detection of diseases and for the evaluation of pathological status. Two main sources of variability can affect the precision and accuracy of the quantitative experiments designed for biomarker discovery and validation. These sources are divided into two categories, pre-analytical and analytical, and are often ignored; however, they can contribute to consistent errors and misunderstanding in biomarker research. In this chapter, we review critical pre-analytical and analytical variables that can influence quantitative proteomics. According to guidelines accepted by proteomics community, we propose some recommendations and strategies for a proper proteomics analysis addressed to biomarker studies.

The Impact of Pre-Analytical Conditions on Human Serum Peptidome Profiling

The successful use of proteomic technology for the discovery of clinically relevant, new candidate biomarkers, especially in the low molecular weight range (peptidome), calls for a careful consideration of standardized operating procedures (SOP) for pre-analytical variables, including samples handling and storage. The current lack of standardization, widely considered a relevant source of random and systematic errors, underlies the uncertainty of analytical results and poor comparability, especially in multi-centric or inter-laboratory studies. In their recent study, Tsuchida et al. used the MALDI-TOF/MS technique to investigate the effect of long-term storage at -20 °C, -80 °C, and in liquid nitrogen on serum samples obtained for peptidomic analyses. The authors have also evaluated the effects of different sample thawing modalities. By including results from the same series as that reported on in a previous publication, they have effectively defined some important requirements for the peptidomic analysis of serum samples (e.g., maximum time intervals between venepuncture and serum separation [1 h], minimum temperature for long-term sera storage temperature [-80 °C], ideal conditions for sample thawing).

Analysis of anticoagulants for blood-based quantitation of amyloid β oligomers in the sFIDA assay

Early diagnostics at the preclinical stage of Alzheimer's disease is of utmost importance for drug development in clinical trials and prognostic guidance. Since soluble Aβ oligomers are considered to play a crucial role in the disease pathogenesis, several methods aim to quantify Aβ oligomers in body fluids such as cerebrospinal fluid (CSF) and blood plasma. The highly specific and sensitive method surface-based fluorescence intensity distribution analysis (sFIDA) has successfully been established for oligomer quantitation in CSF samples. In our study, we explored the sFIDA method for quantitative measurements of synthetic Aβ particles in blood plasma. For this purpose, EDTA-, citrate- and heparin-treated blood plasma samples from five individual donors were spiked with Aβ coated silica nanoparticles (Aβ-SiNaPs) and were applied to the sFIDA assay. Based on the assay parameters linearity, coefficient of variation and limit of detection, we found that EDTA plasma yields the most suitable parameter values for quantitation of Aβ oligomers in sFIDA assay with a limit of detection of 16 fM.

Differential stability of therapeutic peptides with different proteolytic cleavage sites in blood, plasma and serum

Proteolytic degradation of peptide-based drugs is often considered as major weakness limiting systemic therapeutic applications. Therefore, huge efforts are typically devoted to stabilize sequences against proteases present in serum or plasma, obtained as supernatants after complete blood coagulation or centrifugation of blood supplemented with anticoagulants, respectively. Plasma and serum are reproducibly obtained from animals and humans allowing consistent for clinical analyses and research applications. However, the spectrum of active or activated proteases appears to vary depending on the activation of proteases and cofactors during coagulation (serum) or inhibition of such enzymes by anticoagulants (plasma), such as EDTA (metallo- and Ca²⁺-dependent proteases) and heparin (e.g. thrombin, factor Xa). Here, we studied the presumed effects on peptide degradation by taking blood via cardiac puncture of CD-1 mice using a syringe containing a peptide solution. Due to absence of coagulation activators (e.g. glass surfaces and damaged cells), visible blood clotting was prevented allowing to study peptide degradation for one hour. The remaining peptide was quantified and the degradation products were identified using mass spectrometry. When the degradation rates (half-life times) were compared to serum derived freshly from the same animal and commercial serum and plasma samples, peptides of three different families showed indeed considerably different stabilities. Generally, peptides were faster degraded in serum than in plasma, but surprisingly all peptides were more stable in fresh blood and the order of degradation rates among the peptides varied among the six different incubation experiments. This indicates, that proteolytic degradation of peptide-based therapeutics may often be misleading stimulating efforts to stabilize peptides at degradation sites relevant only in vitro, i.e., for serum or plasma stability assays, but of lower importance in vivo.

Proteomics for prediction of disease progression and response to therapy in diabetic kidney disease

The past decade has resulted in multiple new findings of potential proteomic biomarkers of diabetic kidney disease (DKD). Many of these biomarkers reflect an important role in the (patho)physiology and biological processes of DKD. Situations in which proteomics could be applied in clinical practice include the identification of individuals at risk of progressive kidney disease and those who would respond well to treatment, in order to tailor therapy for those at highest risk. However, while many proteomic biomarkers have been discovered, and even found to be predictive, most lack rigorous external validation in sufficiently powered studies with renal endpoints. Moreover, studies assessing short-term changes in the proteome for therapy-monitoring purposes are lacking. Collaborations between academia and industry and enhanced interactions with regulatory agencies are needed to design new, sufficiently powered studies to implement proteomics in clinical practice.

A Pathway Proteomic Profile of Ischemic Stroke Survivors Reveals Innate Immune Dysfunction in Association with Mild Symptoms of Depression - A Pilot Study

Depression after stroke is a common occurrence, raising questions as to whether depression could be a long-term biological and immunological sequela of stroke. Early explanations for post-stroke depression (PSD) focused on the neuropsychological/psychosocial effects of stroke on mobility and quality of life. However, recent investigations have revealed imbalances of inflammatory cytokine levels in association with PSD, though to date, there is only one published proteomic pathway analysis testing this hypothesis. Thus, we examined the serum proteome of stroke patients (n = 44, mean age = 63.62 years) and correlated these with the Montgomery–Åsberg Depression Rating Scale (MADRS) scores at 3 months post-stroke. Overall, the patients presented with mild depression symptoms on the MADRS, M = 6.40 (SD = 7.42). A discovery approach utilizing label-free relative quantification was employed utilizing an LC-ESI–MS/MS coupled to a LTQ-Orbitrap Elite (Thermo-Scientific). Identified peptides were analyzed using the gene set enrichment approach on several different genomic databases that all indicated significant downregulation of the complement and coagulation systems with increasing MADRS scores. Complement and coagulation systems are traditionally thought to play a key role in the innate immune system and are established precursors to the adaptive immune system through pro-inflammatory cytokine signaling. Both systems are known to be globally affected after ischemic or hemorrhagic stroke. Thus, our results suggest that lowered complement expression in the periphery in conjunction with depressive symptoms post-stroke may be a biomarker for incomplete recovery of brain metabolic needs, homeostasis, and inflammation following ischemic stroke damage. Further proteomic investigations are now required to construct the temporal profile, leading from acute lesion damage to manifestation of depressive symptoms. Overall, the findings provide support for the involvement of inflammatory and immune mechanisms in PSD symptoms and further demonstrate the value and feasibility of the proteomic approach in stroke research.

Transformative Impact of Proteomics on Cardiovascular Health and Disease: A Scientific Statement From the American Heart Association

The year 2014 marked the 20th anniversary of the coining of the term proteomics. The purpose of this scientific statement is to summarize advances over this period that have catalyzed our capacity to address the experimental, translational, and clinical implications of proteomics as applied to cardiovascular health and disease and to evaluate the current status of the field. Key successes that have energized the field are delineated; opportunities for proteomics to drive basic science research, facilitate clinical translation, and establish diagnostic and therapeutic healthcare algorithms are discussed; and challenges that remain to be solved before proteomic technologies can be readily translated from scientific discoveries to meaningful advances in cardiovascular care are addressed. Proteomics is the result of disruptive technologies, namely, mass spectrometry and database searching, which drove protein analysis from 1 protein at a time to protein mixture analyses that enable large-scale analysis of proteins and facilitate paradigm shifts in biological concepts that address important clinical questions. Over the past 20 years, the field of proteomics has matured, yet it is still developing rapidly. The scope of this statement will extend beyond the reaches of a typical review article and offer guidance on the use of next-generation proteomics for future scientific discovery in the basic research laboratory and clinical settings.