Effects of preanalytical variables on peptide and protein measurements in human serum and plasma: implications for clinical proteomics

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.

Biomarker Reproducibility Challenge: A Review of Non-Nucleotide Biomarker Discovery Protocols from Body Fluids in Breast Cancer Diagnosis

Breast cancer has now become the most commonly diagnosed cancer, accounting for one in eight cancer diagnoses worldwide. Non-invasive diagnostic biomarkers and associated tests are superlative candidates to complement or improve current approaches for screening, early diagnosis, or prognosis of breast cancer. Biomarkers detected from body fluids such as blood (serum/plasma), urine, saliva, nipple aspiration fluid, and tears can detect breast cancer at its early stages in a minimally invasive way. The advancements in high-throughput molecular profiling (omics) technologies have opened an unprecedented opportunity for unbiased biomarker detection. However, the irreproducibility of biomarkers and discrepancies of reported markers have remained a major roadblock to clinical implementation, demanding the investigation of contributing factors and the development of standardised biomarker discovery pipelines. A typical biomarker discovery workflow includes pre-analytical, analytical, and post-analytical phases, from sample collection to model development. Variations introduced during these steps impact the data quality and the reproducibility of the findings. Here, we present a comprehensive review of methodological variations in biomarker discovery studies in breast cancer, with a focus on non-nucleotide biomarkers (i.e., proteins, lipids, and metabolites), highlighting the pre-analytical to post-analytical variables, which may affect the accurate identification of biomarkers from body fluids.

Challenges and Opportunities in Clinical Diagnostic Routine of Envenomation Using Blood Plasma Proteomics

Specific and sensitive tools for the diagnosis and monitoring of accidents by venomous animals are urgently needed. Several diagnostic and monitoring assays have been developed; however, they have not yet reached the clinic. This has resulted in late diagnoses, which represents one of the main causes of progression from mild to severe disease. Human blood is a protein-rich biological fluid that is routinely collected in hospital settings for diagnostic purposes, which can translate research progress from the laboratory to the clinic. Although it is a limited view, blood plasma proteins provide information about the clinical picture of envenomation. Proteome disturbances in response to envenomation by venomous animals have been identified, allowing mass spectrometry (MS)-based plasma proteomics to emerge as a tool in a range of clinical diagnostics and disease management that can be applied to cases of venomous animal envenomation. Here, we provide a review of the state of the art on routine laboratory diagnoses of envenomation by snakes, scorpions, bees, and spiders, as well as a review of the diagnostic methods and the challenges encountered. We present the state of the art on clinical proteomics as the standardization of procedures to be performed within and between research laboratories, favoring a more excellent peptide coverage of candidate proteins for biomarkers. Therefore, the selection of a sample type and method of preparation should be very specific and based on the discovery of biomarkers in specific approaches. However, the sample collection protocol (e.g., collection tube type) and the processing procedure of the sample (e.g., clotting temperature, time allowed for clotting, and anticoagulant used) are equally important to eliminate any bias.

The Known Unknowns: An Overview of the State of Blood-Based Protein Biomarkers of Mild Traumatic Brain Injury

Blood-based protein biomarkers have revolutionized several fields of medicine by enabling molecular level diagnosis, as well as monitoring disease progression and treatment efficacy. Traumatic brain injury (TBI) so far has benefitted only moderately from using protein biomarkers to improve injury outcome. Because of its complexity and dynamic nature, TBI, especially its most prevalent mild form (mild TBI; mTBI), presents unique challenges toward protein biomarker discovery and validation given that blood is frequently obtained and processed outside of the clinical laboratory (e.g., athletic fields, battlefield) under variable conditions. As it stands, the field of mTBI blood biomarkers faces a number of outstanding questions. Do elevated blood levels of currently used biomarkers-ubiquitin carboxy-terminal hydrolase L1, glial fibrillary acidic protein, neurofilament light chain, and tau/p-tau-truly mirror the extent of parenchymal damage? Do these different proteins represent distinct injury mechanisms? Is the blood-brain barrier a "brick wall"? What is the relationship between intra- versus extracranial values? Does prolonged elevation of blood levels reflect de novo release or extended protein half-lives? Does biological sex affect the pathobiological responses after mTBI and thus blood levels of protein biomarkers? At the practical level, it is unknown how pre-analytical variables-sample collection, preparation, handling, and stability-affect the quality and reliability of biomarker data. The ever-increasing sensitivity of assay systems and lack of quality control of samples, combined with the almost complete reliance on antibody-based assay platforms, represent important unsolved issues given that false-negative results can lead to false clinical decision making and adverse outcomes. This article serves as a commentary on the state of mTBI biomarkers and the landscape of significant challenges. We highlight and discusses several biological and methodological "known unknowns" and close with some practical recommendations.

Peptidomics: A Review of Clinical Applications and Methodologies

Improvements in both liquid chromatography (LC) and mass spectrometry (MS) instrumentation have greatly enhanced proteomic and small molecule metabolomic analysis in recent years. Less focus has been on the improved capability to detect and quantify small bioactive peptides, even though the exact sequences of the peptide species produced can have important biological consequences. Endogenous bioactive peptide hormones, for example, are generated by the targeted and regulated cleavage of peptides from their prohormone sequence. This process may include organ specific variants, as proglucagon is converted to glucagon in the pancreas but glucagon-like peptide-1 (GLP-1) in the small intestine, with glucagon raising, whereas GLP-1, as an incretin, lowering blood glucose. Therefore, peptidomics workflows must preserve the structure of the processed peptide products to prevent the misidentification of ambiguous peptide species. The poor in vivo and in vitro stability of peptides in biological matrices is a major factor that needs to be considered when developing methods to study them. The bioinformatic analysis of peptidomics data sets requires the inclusion of specific post-translational modifications, which are critical for the function of many bioactive peptides. This review aims to discuss and contrast the various extraction, analytical, and bioinformatics approaches used for human peptidomics studies in a multitude of matrices.

Ranking Biomarkers of Aging by Citation Profiling and Effort Scoring

Aging affects most living organisms and includes the processes that reduce health and survival. The chronological and the biological age of individuals can differ remarkably, and there is a lack of reliable biomarkers to monitor the consequences of aging. In this review we give an overview of commonly mentioned and frequently used potential aging-related biomarkers. We were interested in biomarkers of aging in general and in biomarkers related to cellular senescence in particular. To answer the question whether a biological feature is relevant as a potential biomarker of aging or senescence in the scientific community we used the PICO strategy known from evidence-based medicine. We introduced two scoring systems, aimed at reflecting biomarker relevance and measurement effort, which can be used to support study designs in both clinical and research settings.

An Exploratory Pilot Study with Plasma Protein Signatures Associated with Response of Patients with Depression to Antidepressant Treatment for 10 Weeks

Major depressive disorder (MDD) is a leading cause of global disability with a chronic and recurrent course. Recognition of biological markers that could predict and monitor response to drug treatment could personalize clinical decision-making, minimize unnecessary drug exposure, and achieve better outcomes. Four longitudinal plasma samples were collected from each of ten patients with MDD treated with antidepressants for 10 weeks. Plasma proteins were analyzed qualitatively and quantitatively with a nanoflow LC−MS/MS technique. Of 1153 proteins identified in the 40 longitudinal plasma samples, 37 proteins were significantly associated with response/time and clustered into six according to time and response by the linear mixed model. Among them, three early-drug response markers (PHOX2B, SH3BGRL3, and YWHAE) detectable within one week were verified by liquid chromatography-multiple reaction monitoring/mass spectrometry (LC-MRM/MS) in the well-controlled 24 patients. In addition, 11 proteins correlated significantly with two or more psychiatric measurement indices. This pilot study might be useful in finding protein marker candidates that can monitor response to antidepressant treatment during follow-up visits within 10 weeks after the baseline visit.

An Integrated Quantitative Proteomics Workflow for Cancer Biomarker Discovery and Validation in Plasma

Blood plasma is one of the most widely used samples for cancer biomarker discovery research as well as clinical investigations for diagnostic and therapeutic purposes. However, the plasma proteome is extremely complex due to its wide dynamic range of protein concentrations and the presence of high-abundance proteins. Here we have described an optimized, integrated quantitative proteomics pipeline combining the label-free and multiplexed-labeling-based (iTRAQ and TMT) plasma proteome profiling methods for biomarker discovery, followed by the targeted approaches for validation of the identified potential marker proteins. In this workflow, the targeted quantitation of proteins is carried out by multiple-reaction monitoring (MRM) and parallel-reaction monitoring (PRM) mass spectrometry. Thus, our approach enables both unbiased screenings of biomarkers and their subsequent selective validation in human plasma. The overall procedure takes only ~2 days to complete, including the time for data acquisition (excluding database searching). This protocol is quick, flexible, and eliminates the need for a separate immunoassay-based validation workflow in blood cancer biomarker investigations. We anticipate that this plasma proteomics workflow will help to accelerate the cancer biomarker discovery program and provide a valuable resource to the cancer research community.

Challenges and Opportunities in Clinical Applications of Blood-Based Proteomics in Cancer

Simple Summary

The traditional approach in identifying cancer related protein biomarkers has focused on evaluation of a single peptide/protein in tissue or circulation. At best, this approach has had limited success for clinical applications, since multiple pathological tumor pathways may be involved during initiation or progression of cancer which diminishes the significance of a single candidate protein/peptide. Emerging sensitive proteomic based technologies like liquid chromatography mass spectrometry (LC-MS)-based quantitative proteomics can provide a platform for evaluating serial serum or plasma samples to interrogate secreted products of tumor–host interactions, thereby revealing a more “complete” repertoire of biological variables encompassing heterogeneous tumor biology. However, several challenges need to be met for successful application of serum/plasma based proteomics. These include uniform pre-analyte processing of specimens, sensitive and specific proteomic analytical platforms and adequate attention to study design during discovery phase followed by validation of discovery-level signatures for prognostic, predictive, and diagnostic cancer biomarker applications.

Abstract

Blood is a readily accessible biofluid containing a plethora of important proteins, nucleic acids, and metabolites that can be used as clinical diagnostic tools in diseases, including cancer. Like the on-going efforts for cancer biomarker discovery using the liquid biopsy detection of circulating cell-free and cell-based tumor nucleic acids, the circulatory proteome has been underexplored for clinical cancer biomarker applications. A comprehensive proteome analysis of human serum/plasma with high-quality data and compelling interpretation can potentially provide opportunities for understanding disease mechanisms, although several challenges will have to be met. Serum/plasma proteome biomarkers are present in very low abundance, and there is high complexity involved due to the heterogeneity of cancers, for which there is a compelling need to develop sensitive and specific proteomic technologies and analytical platforms. To date, liquid chromatography mass spectrometry (LC-MS)-based quantitative proteomics has been a dominant analytical workflow to discover new potential cancer biomarkers in serum/plasma. This review will summarize the opportunities of serum proteomics for clinical applications; the challenges in the discovery of novel biomarkers in serum/plasma; and current proteomic strategies in cancer research for the application of serum/plasma proteomics for clinical prognostic, predictive, and diagnostic applications, as well as for monitoring minimal residual disease after treatments. We will highlight some of the recent advances in MS-based proteomics technologies with appropriate sample collection, processing uniformity, study design, and data analysis, focusing on how these integrated workflows can identify novel potential cancer biomarkers for clinical applications.

Guidelines for the standardized collection of blood-based biomarkers in psychiatry: Steps for laboratory validity - a consensus of the Biomarkers Task Force from the WFSBP

Recently, there has been a major shift in the field of psychiatry towards the exploration of complex relationships between blood-based biomarkers and the pathophysiology of psychiatric and neuropsychiatric disorders. However, issues with study reproducibility, validity and reliability have hindered progress towards the identification of clinically relevant biomarkers for psychiatry. The achievement of laboratory validity is a crucial first step for the posterior development of clinical validity. There is evidence that the variability observed in blood-based research studies may be minimised with the implementation of standardised pre-analytical methods and uniform clinical protocols (i.e., pre-venipuncture). It has been documented that errors made in the pre-analytical phase account for 46-68.2% of laboratory testing errors. Thus, standardising clinical assessment, ethical procedures and pre-analytical phase of clinical research is essential for the reproducibility, validity and reliability of blood marker assessment, and reducing the risk of invalid test results. Various other areas of research have already moved towards guidelines for the standardised collection of blood-based biomarkers. Here we aim to provide a set of guidelines that we believe would improve biomarker research: (1) pre-venipuncture information and documentation, (2) ethics of participant consent and (3) pre-analytical methods. Ultimately, we hope this will assist study planning and will improve data comparison across studies allowing for the discovery of biomarkers in psychiatry with both laboratorial and clinical validity.

Effects of Long-Term Storage at -80 °C on the Human Plasma Metabolome

High-quality biological samples are required for the favorable outcome of research studies, and valid data sets are crucial for successful biomarker identification. Prolonged storage of biospecimens may have an artificial effect on compound levels. In order to investigate the potential effects of long-term storage on the metabolome, human ethylenediaminetetraacetic acid (EDTA) plasma samples stored for up to 16 years were analyzed by gas and liquid chromatography-tandem mass spectrometry-based metabolomics. Only 2% of 231 tested plasma metabolites were altered in the first seven years of storage. However, upon longer storage periods of up to 16 years and more time differences of few years significantly affected up to 26% of the investigated metabolites when analyzed within subject age groups. Ontology classes that were most affected included complex lipids, fatty acids, energy metabolism molecules, and amino acids. In conclusion, the human plasma metabolome is adequately stable to long-term storage at −80 °C for up to seven years but significant changes occur upon longer storage. However, other biospecimens may display different sensitivities to long-term storage. Therefore, in retrospective studies on EDTA plasma samples, analysis is best performed within the first seven years of storage.

A smartphone-assisted pressure-measuring-based diagnosis system for acute myocardial infarction diagnosis

Background

Acute myocardial infarction (AMI), usually caused by atherosclerosis of coronary artery, is the most severe manifestation of coronary artery disease which results in a large amount of death annually. A new diagnosis approach with high accuracy, reliability and low measuring-time-consuming is essential for AMI quick diagnosis.

Purpose

The objective of this study was to develop a new point-of-care testing system with high accuracy and reliability for AMI quick diagnosis.

Patients and methods

50 plasma samples of acute myocardial infarction patients were analyzed by developed Smartphone-Assisted Pressure-Measuring-Based Diagnosis System (SPDS). The concentration of substrate was firstly optimized. The effect of antibody labeling and matrix solution on measuring result were then evaluated. And standard curves for cTnI, CK-MB and Myo were built for clinical sample analysis. The measuring results of 50 clinical samples were finally evaluated by comparing with the measuring result obtained by CLIA.

Results

The concentration of substrate H₂O₂ was firstly optimized as 30% to increase measuring signal. A commercial serum matrix was chosen as the matrix solution to dilute biomarkers for standard curve building to minimize matrix effect on the accuracy of clinical plasma sample measuring. The standard curves for cTnI, CK-MB and Myo were built, with measuring dynamic range of 0–25 ng/mL, 0–33 ng/mL and 0–250 ng/mL, and limit of detection of 0.014 ng/mL, 0.16 ng/mL and 0.85 ng/mL respectively. The measuring results obtained by the developed system of 50 clinical plasma samples for three biomarkers matched well with the results obtained by chemiluminescent immunoassay.

Conclusion

Due to its small device size, high sensitivity and accuracy, SPDS showed a bright potential for point-of-care testing (POCT) applications.

Quantification of protein markers monitoring the pre-analytical effect of blood storage time before plasma isolation using 15 N metabolically labeled recombinant proteins

In the hospital, blood samples are collected to monitor patients' health states, and thus various protein-based clinical methods have been developed. However, some proteins are found to change in abundances during the process of blood collection and storage. In order to account such pre-analytical effects, we performed liquid chromatography multiple reaction monitoring mass spectrometry (LC-MRM-MS) on 15 selected proteins in plasma samples prepared by varying storage time and temperature of whole blood prior to plasma isolation. Two cytosolic proteins, profilin-1 (PFN1) and thymosin beta-4 (TMSB4X), were absolutely quantified using ¹⁵ N-labeled recombinant proteins spiked externally. The other 13 proteins were quantified in a relative way compared with the two reference proteins. Triplicated LC-MRM-MS measurements showed that the median CV of MRM peak areas was 5.7%. The amounts of PFN1 and TMSB4X increased rapidly depending on the storage time between blood collection and plasma preparation. It indicates the leakage of cellular components into the plasma fraction. Relative quantification further revealed that five proteins including PFN1, S10A8, S10A9, S10A11, and TMSB4X showed significant difference (P < 0.05). We further monitored PFN1 and TMSB4X on 40 samples collected for protein diagnostics under a typical clinical study condition. Compared with the plasma samples prepared within a day, the level of both PFN1 and TMSB4X increased in the plasma samples prepared from the blood collected the day before and kept overnight at 4°C (0.51 to 3.11 μg/mL for PFN1 and 0.98 to 5.36 μg/mL for TMSB4X in average). Our result suggests an effort of assuring plasma quality for accurate protein-based diagnosis or biomarker discovery and validation.

Impact of biological matrix on inflammatory protein biomarker quantification based on targeted mass spectrometry

Background: Serum and plasma are widely used matrices in biological and clinical studies. To improve reliability and consistency of markers quantification, the influence of these matrices on proteins was evaluated by targeted mass spectrometry. Results: 65 proteins were quantified in matched blood samples collected in serum, ethylenediaminetetraacetic acid and heparin plasma tubes from 40 healthy and 10 pathological individuals. Only 52% of the proteins were not impacted by any of the biological matrices tested, and the effects on quantification of proteins affected was matrix and protein dependent. Conclusion: Matrix comparisons using mass spectrometry is therefore recommended to assess the relevance of using surrogate matrix, performing biomarker discovery study or evaluating the clinical use of biomarkers in large clinical cohorts.

A feasibility study prior to an international multicentre paediatric study to assess pharmacokinetic/pharmacodynamic sampling and sample preparation procedures, logistics and bioanalysis

Background

Variability in pre-analytical procedures such as blood sampling, sample preparation and transport can substantially influence bioanalytical results and subsequently impair reliability of data gathered during clinical trials. Especially in vulnerable populations, all efforts should be made to facilitate high-quality data extraction excluding unnecessary or repeated intervention.

Methods

The EU-funded LENA project (Labeling of Enalapril from Neonates up to Adolescents) included a feasibility study in its preparatory procedures prior to first-in-child studies. Derived from a regular study visit, it encompassed all procedures, from sampling of two study-specific drugs and four sensitive humoral parameters to bioanalysis, to evaluate the quality of obtained samples and applicability of logistical and bioanalytical procedures. Drug administration to healthy adults was circumvented by pre-spiking the blood collection tubes with a drug solution. Five clinical sites were evaluated.

Results

Clinical teams' preparedness and applicability of required sampling procedures was investigated in 18 volunteers, on-site. 97% of collected pharmacokinetic (PK) samples and 93% of samples for humoral parameters were obtained eligibly. Results met expectations, though one team had to be re-trained and performed a re-run. Planned procedures for sampling, sample preparation, transport and analysis were found to be suitable for being applied within paediatric trials.

Conclusion

The concept of the presented feasibility study that simultaneously assesses PK/PD sampling, sample preparation, logistics and bioanalysis proved to be a promising tool for trial preparation. It revealed improperly installed processes and bottlenecks that required adjustments prior to start of recruitment. It facilitated high-quality conduct from the first moment of paediatric pivotal studies.

Applications of MALDI-TOF mass spectrometry in clinical proteomics

INTRODUCTION

The development of precision medicine requires advanced technologies to address the multifactorial disease stratification and to support personalized treatments. Among omics techniques, proteomics based on Mass Spectrometry (MS) is becoming increasingly relevant in clinical practice allowing a phenotypic characterization of the dynamic functional status of the organism. From this perspective, Matrix Assisted Laser Desorption Ionization Time of Flight (MALDI-TOF) MS is a suitable platform for providing a high-throughput support to clinics. Areas covered: This review aims to provide an updated overview of MALDI-TOF MS applications in clinical proteomics. The most relevant features of this analysis have been discussed, highlighting both pre-analytical and analytical factors that are crucial in proteomics studies. Particular emphasis is placed on biofluids proteomics for biomarkers discovery and on recent progresses in clinical microbiology, drug monitoring, and minimal residual disease (MRD). Expert commentary: Despite some analytical limitations, the latest technological advances together with the easiness of use, the low time and low cost consuming and the high throughput are making MALDI-TOF MS instruments very attractive for the clinical practice. These features offer a significant potential for the routine of the clinical laboratory and ultimately for personalized medicine.

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.

Targeted On-line SPE-LC-MS/MS Assay for the Quantitation of 12 Apolipoproteins from Human Blood

Laborious sample pretreatment of biological samples represents the most limiting factor for the translation of targeted proteomics assays from research to clinical routine. An optimized method for the simultaneous quantitation of 12 major apolipoproteins (apos) combining on-line SPE and fast LC-MS/MS analysis in 6.5 min total run time was developed, reducing the manual sample pretreatment time of 3 μL serum or plasma by 60%. Within-run and between-day imprecisions below 10 and 15% (n = 10) and high recovery rates (94-131%) were obtained applying the high-throughput setup. High-quality porcine trypsin was used, which outperformed cost-effective bovine trypsin regarding digestion efficiency. Comparisons with immunoassays and another LC-MS/MS assay demonstrated good correlation (Pearson's R: 0.81-0.98). Further, requirements on sample quality concerning sampling, processing, and long-term storage up to 1 year were investigated revealing significant influences of the applied sampling material and coagulant on quantitation results. Apo profiles of 1339 subjects of the LIFE-Adult-Study were associated with lifestyle and physiological parameters as well as establish parameters of lipid metabolism (e.g., triglycerides, cholesterol). Besides gender effects, most significant impact was seen regarding lipid-lowering medication. In conclusion, this novel highly standardized, high-throughput targeted proteomics assay utilizes a fast, simultaneous analysis of 12 apos from least sample amounts.

Impact of Prolonged Blood Incubation and Extended Serum Storage at Room Temperature on the Human Serum Metabolome

Metabolomics is a powerful technology with broad applications in life science that, like other -omics approaches, requires high-quality samples to achieve reliable results and ensure reproducibility. Therefore, along with quality assurance, methods to assess sample quality regarding pre-analytical confounders are urgently needed. In this study, we analyzed the response of the human serum metabolome to pre-analytical variations comprising prolonged blood incubation and extended serum storage at room temperature by using gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) -based metabolomics. We found that the prolonged incubation of blood results in a statistically significant 20% increase and 4% decrease of 225 tested serum metabolites. Extended serum storage affected 21% of the analyzed metabolites (14% increased, 7% decreased). Amino acids and nucleobases showed the highest percentage of changed metabolites in both confounding conditions, whereas lipids were remarkably stable. Interestingly, the amounts of taurine and O-phosphoethanolamine, which have both been discussed as biomarkers for various diseases, were 1.8- and 2.9-fold increased after 6 h of blood incubation. Since we found that both are more stable in ethylenediaminetetraacetic acid (EDTA) blood, EDTA plasma should be the preferred metabolomics matrix.

Ensuring sample quality for blood biomarker studies in clinical trials: a multicenter international study for plasma and serum sample preparation

Background

Sample quality is critical for biomarker detection in oncology, and platelet degradation and contamination in plasma have a remarkable impact on the ability to accurately quantify many blood-based biomarkers. Platelet factor 4 (PF4) can be used as an indicator to monitor sample quality. This multicenter study aimed to determine the impact of critical components of the blood sample handling process on platelet degradation/contamination and to establish an optimal method for collecting platelet-poor plasma samples.

Methods

At each of six participating centers, blood samples were drawn from 12-13 healthy volunteers. Serum and plasma samples were prepared from whole blood samples using nine different methods that have been commonly used in ongoing multicenter trials. PF4 levels in the prepared samples were measured by enzyme-linked immunosorbent assay (ELISA). Paired t-tests were used for statistical analysis.

Results

Blood samples were collected from 74 subjects enrolled in six centers. PF4 levels were significantly higher in serum samples than in plasma samples (P<0.001), in plasma samples from blood that sat at room temperature for 5 minutes (P=0.021), in plasma samples prepared at an insufficient centrifugal force (P<0.001), and in plasma samples prepared from blood that sat for longer than 4 hours on ice (P=0.001). For each method, the PF4 levels did not differ significantly among the centers or between Chinese and American subjects. The methods that resulted in normal levels of PF4 involved keeping blood samples on ice for 30 minutes to <4 hours and centrifugation at 2,500-3,000 ×g for 30 min.

Conclusions

This multicenter study evaluated multiple blood sample handling conditions for minimizing platelet degradation during plasma serum preparation and determined an optimal method for preparing platelet-poor plasma. The findings of this study can be applied in future blood biomarker studies.

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.

Degradation and Stabilization of Peptide Hormones in Human Blood Specimens

Plasma hormone peptides, including GLP-1, GIP, Glucagon, and OXM, possess multiple physiological roles and potential therapeutic and diagnostic utility as biomarkers in the research of metabolic disorders. These peptides are subject to proteolytic degradation causing preanalytical variations. Stabilization for accurate quantitation of these active peptides in ex vivo blood specimens is essential for drug and biomarker development. We investigated the protease-driven instability of these peptides in conventional serum, plasma, anticoagulated whole blood, as well as whole blood and plasma stabilized with protease inhibitors. The peptide was monitored by both time-course Matrix-Assisted Laser Desorption Ionization Time-to-Flight Mass Spectrometry (MALDI –TOF MS) and Ab-based assay (ELISA or RIA). MS enabled the identification of proteolytic fragments. In non-stabilized blood samples, the results clearly indicated that dipeptidyl peptidase-IV (DPP-IV) removed the N-terminal two amino acid residues from GLP-1, GIP and OXM(1-37) and not-yet identified peptidase(s) cleave(s) the full-length OXM(1-37) and its fragments. DPP-IV also continued to remove two additional N-terminal residues of processed OXM(3–37) to yield OXM(5–37). Importantly, both DPP-IV and other peptidase(s) activities were inhibited efficiently by the protease inhibitors included in the BD P800* tube. There was preservation of GLP-1, GIP, OXM and glucagon in the P800 plasma samples with half-lives > 96, 96, 72, and 45 hours at room temperature (RT), respectively. In the BD P700* plasma samples, the stabilization of GLP-1 was also achieved with half-life > 96 hours at RT. The stabilization of these variable peptides increased their utility in drug and/or biomarker development. While stability results of GLP-1 obtained with Ab-based assay were consistent with those obtained by MS analysis, the Ab-based results of GIP, Glucagon, and OXM did not reflect the time-dependent degradations revealed by MS analysis. Therefore, we recommended characterizing the degradation of the peptide using the MS-based method when investigating the stability of a specific peptide.

Exploring phlebotomy technique as a pre-analytical factor in proteomic analyses by mass spectrometry

Multiple reaction monitoring mass spectrometry (MRM-MS) is an emerging technology for blood biomarker verification and validation; however, the results may be influenced by pre-analytical factors. This exploratory study was designed to determine if differences in phlebotomy techniques would significantly affect the abundance of plasma proteins in an upcoming biomarker development study. Blood was drawn from 10 healthy participants using four techniques: (1) a 20-gauge IV with vacutainer, (2) a 21-gauge direct vacutainer, (3) an 18-gauge butterfly with vacutainer, and (4) an 18-gauge butterfly with syringe draw. The abundances of a panel of 122 proteins (117 proteins, plus 5 matrix metalloproteinase (MMP) proteins) were targeted by LC/MRM-MS. In addition, complete blood count (CBC) data were also compared across the four techniques. Phlebotomy technique significantly affected 2 of the 11 CBC parameters (red blood cell count, p = 0.010; hemoglobin concentration, p = 0.035) and only 12 of the targeted 117 proteins (p < 0.05). Of the five MMP proteins, only MMP7 was detectable and its concentration was not significantly affected by different techniques. Overall, most proteins in this exploratory study were not significantly influenced by phlebotomy technique; however, a larger study with additional patients will be required for confirmation.

A proteomic approach to obesity and type 2 diabetes

The incidence of obesity and type diabetes 2 has increased dramatically resulting in an increased interest in its biomedical relevance. However, the mechanisms that trigger the development of diabetes type 2 in obese patients remain largely unknown. Scientific, clinical and pharmaceutical communities are dedicating vast resources to unravel this issue by applying different omics tools. During the last decade, the advances in proteomic approaches and the Human Proteome Organization have opened and are opening a new door that may be helpful in the identification of patients at risk and to improve current therapies. Here, we briefly review some of the advances in our understanding of type 2 diabetes that have occurred through the application of proteomics. We also review, in detail, the current improvements in proteomic methodologies and new strategies that could be employed to further advance our understanding of this pathology. By applying these new proteomic advances, novel therapeutic and/or diagnostic protein targets will be discovered in the obesity/Type 2 diabetes area.

Need for gender-specific pre-analytical testing: the dark side of the moon in laboratory testing

Many international organisations encourage studies in a sex-gender perspective. However, research with a gender perspective presents a high degree of complexity, and the inclusion of sex-gender variable in experiments presents many methodological questions, the majority of which are still neglected. Overcoming these issues is fundamental to avoid erroneous results. Here, pre-analytical aspects of the research, such as study design, choice of utilised specimens, sample collection and processing, animal models of diseases, and the observer's role, are discussed. Artefacts in this stage of research could affect the predictive value of all analyses. Furthermore, the standardisation of research subjects according to their lifestyles and, if female, to their life phase and menses or oestrous cycle, is urgent to harmonise research worldwide. A sex-gender-specific attention to pre-analytical aspects could produce a decrease in the time for translation from the bench to bedside. Furthermore, sex-gender-specific pre-clinical pharmacological testing will enable adequate assessment of pharmacokinetic and pharmacodynamic actions of drugs and will enable, where appropriate, an adequate gender-specific clinical development plan. Therefore, sex-gender-specific pre-clinical research will increase the gender equity of care and will produce more evidence-based medicine.

Guidelines for the standardization of preanalytic variables for blood-based biomarker studies in Alzheimer's disease research

The lack of readily available biomarkers is a significant hindrance toward progressing to effective therapeutic and preventative strategies for Alzheimer's disease (AD). Blood-based biomarkers have potential to overcome access and cost barriers and greatly facilitate advanced neuroimaging and cerebrospinal fluid biomarker approaches. Despite the fact that preanalytical processing is the largest source of variability in laboratory testing, there are no currently available standardized preanalytical guidelines. The current international working group provides the initial starting point for such guidelines for standardized operating procedures (SOPs). It is anticipated that these guidelines will be updated as additional research findings become available. The statement provides (1) a synopsis of selected preanalytical methods utilized in many international AD cohort studies, (2) initial draft guidelines/SOPs for preanalytical methods, and (3) a list of required methodological information and protocols to be made available for publications in the field to foster cross-validation across cohorts and laboratories.

Method validation for preparing serum and plasma samples from human blood for downstream proteomic, metabolomic, and circulating nucleic acid-based applications

BACKGROUND

Formal method validation for biospecimen processing in the context of accreditation in laboratories and biobanks is lacking. Serum and plasma processing protocols were validated for fitness-for-purpose in terms of key downstream endpoints, and this article demonstrates methodology for biospecimen processing method validation.

METHODS

Serum and plasma preparation from human blood was optimized for centrifugation conditions with respect to microparticle counts. Optimal protocols were validated for methodology and reproducibility in terms of acceptance criteria based on microparticle counts, DNA and hemoglobin concentration, and metabolomic and proteomic profiles. These parameters were also used to evaluate robustness for centrifugation temperature (4°C versus room temperature [RT]), deceleration (low, medium, high) and blood stability (after a 2-hour delay).

RESULTS

Optimal protocols were 10-min centrifugation for serum and 20-min for plasma at 2000 g, medium brake, RT. Methodology and reproducibility acceptance criteria were met for both protocols except for reproducibility of plasma metabolomics. Overall, neither protocol was robust for centrifugation at 4°C versus RT. RT gave higher microparticles and free DNA yields in serum, and fewer microparticles with less hemolysis in plasma. Overall, both protocols were robust for fast, medium, and low deceleration, with a medium brake considered optimal. Pre-centrifugation stability after a 2-hour delay was seen at both temperatures for hemoglobin concentration and proteomics, but not for microparticle counts.

CONCLUSIONS

We validated serum and plasma collection methods suitable for downstream protein, metabolite, or free nucleic acid-based applications. Temperature and pre-centrifugation delay can influence analytic results, and laboratories and biobanks should systematically record these conditions in the scope of accreditation.

Biotransformation and in vivo stability of protein biotherapeutics: impact on candidate selection and pharmacokinetic profiling

Historically, since the metabolism of administered peptide/protein drugs ("biotherapeutics") has been expected to undergo predictable pathways similar to endogenous proteins, comprehensive biotherapeutic metabolism studies have not been widely reported in the literature. However, since biotherapeutics have rapidly evolved into an impressive array of eclectic modalities, there has been a shift toward understanding the impact of metabolism on biotherapeutic development. For biotherapeutics containing non-native chemical linkers and other moieties besides natural amino acids, metabolism studies are critical as these moieties may impart undesired toxicology. For biotherapeutics that are composed solely of natural amino acids, where end-stage peptide and amino acid catabolites do not generally pose toxicity concerns, the understanding of biotherapeutic biotransformation, defined as in vivo modifications such as peripherally generated intermediate circulating catabolites prior to end-stage degradation or elimination, may impact in vivo stability and potency/clearance. As of yet, there are no harmonized methodologies for understanding biotherapeutic biotransformation and its impact on drug development, nor is there clear guidance from regulatory agencies on how and when these studies should be conducted. This review provides an update on biotherapeutic biotransformation studies and an overview of lessons learned, tools that have been developed, and suggestions of approaches to address issues. Biotherapeutic biotransformation studies, especially for certain modalities, should be implemented at an early stage of development to 1) understand the impact on potency/clearance, 2) select the most stable candidates or direct protein re-engineering efforts, and 3) select the best bioanalytical technique(s) for proper drug quantification and subsequent pharmacokinetic profiling and exposure/response assessment.

Mass spectrometry based biomarker discovery, verification, and validation--quality assurance and control of protein biomarker assays

In its early years, mass spectrometry (MS)-based proteomics focused on the cataloging of proteins found in different species or different tissues. By 2005, proteomics was being used for protein quantitation, typically based on "proteotypic" peptides which act as surrogates for the parent proteins. Biomarker discovery is usually done by non-targeted "shotgun" proteomics, using relative quantitation methods to determine protein expression changes that correlate with disease (output given as "up-or-down regulation" or "fold-increases"). MS-based techniques can also perform "absolute" quantitation which is required for clinical applications (output given as protein concentrations). Here we describe the differences between these methods, factors that affect the precision and accuracy of the results, and some examples of recent studies using MS-based proteomics to verify cancer-related biomarkers.

Cytokines as biomarkers in rheumatoid arthritis

RA is a complex disease that develops as a series of events often referred to as disease continuum. RA would benefit from novel biomarker development for diagnosis where new biomarkers are still needed (even if progresses have been made with the inclusion of ACPA into the ACR/EULAR 2010 diagnostic criteria) and for prognostic notably in at risk of evolution patients with autoantibody-positive arthralgia. Risk biomarkers for rapid evolution or cardiovascular complications are also highly desirable. Monitoring biomarkers would be useful in predicting relapse. Finally, predictive biomarkers for therapy outcome would allow tailoring therapy to the individual. Increasing numbers of cytokines have been involved in RA pathology. Many have the potential as biomarkers in RA especially as their clinical utility is already established in other diseases and could be easily transferable to rheumatology. We will review the current knowledge's relation to cytokine used as biomarker in RA. However, given the complexity and heterogeneous nature of RA, it is unlikely that a single cytokine may provide sufficient discrimination; therefore multiple biomarker signatures may represent more realistic approach for the future of personalised medicine in RA.

Peptidomics analysis of human blood specimens for biomarker discovery

This review addresses the concepts, limitations and perspectives for the application of peptidomics science and technologies to discover putative biomarkers in blood specimens. Peptidomics can be defined as the comprehensive multiplex analysis of endogenous peptides contained within a biological sample under defined conditions to describe the multitude of native peptides in a biological compartment. In addition to the discovery of disease associated biomarkers, an emerging field in peptidomics is the analysis of peptides to describe in vivo effects of protease inhibitors. The development and application of peptidomics technologies represent an arena of biomarker research that has the potential for adding significant clinical value.

Challenges and prospects for biomarker research: a current perspective from the developing world

Majority of deaths due to communicable and non-communicable diseases occur in the low and middle-income nations (LMNs), mainly due to the lack of early diagnoses and timely treatments. In such a scenario, biomarkers serve as an indispensible resource that can be used as indicators of biological processes, specific disease conditions or response to therapeutic interventions. Evaluation, diagnosis and management of diseases in developing world by following/extrapolating the findings obtained on the basis of the research work involving only the populations from the developed countries, could often be highly misleading due to existence of diverse patterns of diseases in developing countries compared to the developed world. Biomarker candidates identified from high-throughput integrated omics technologies have promising potential; however, their actual clinical applications are found to be limited, primarily due to the challenges of disease heterogeneity and pre-analytical variability associated with the biomarker discovery pipeline. Additionally, in the developing world, economic crunches, lack of awareness and education, paucity of biorepositories, enormous diversities in socio-epidemiological background, ethnicity, lifestyle, diet, exposure to various environmental risk factors and infectious agents, and ethical and social issues also cumulatively hinder biomarker discovery ventures. Establishment of standard operating procedures, comprehensive data repositories and exchange of scientific findings are crucial for reducing the variability and fragmentation of data. This review highlights the challenges associated with the discovery, validation and translational phases of biomarker research in LMNs with some of their amenable solutions and future prospects. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge.

Differential expression of serum/plasma proteins in various infectious diseases: specific or nonspecific signatures

Apart from direct detection of the infecting organisms or biomarker of the pathogen itself, surrogate host markers are also useful for sensitive and early diagnosis of pathogenic infections. Early detection of pathogenic infections, discrimination among closely related diseases with overlapping clinical manifestations, and monitoring of disease progression can be achieved by analyzing blood biomarkers. Therefore, over the last decade large numbers of proteomics studies have been conducted to identify differentially expressed human serum/plasma proteins in different infectious diseases with the intent of discovering novel potential diagnostic/prognostic biomarkers. However, in-depth review of the literature indicates that many reported biomarkers are altered in the same way in multiple infectious diseases, regardless of the type of infection. This might be a consequence of generic acute phase reactions, while the uniquely modulated candidates in different pathogenic infections could be indicators of some specific responses. In this review article, we will provide a comprehensive analysis of differentially expressed serum/plasma proteins in various infectious diseases and categorize the protein markers associated with generic or specific responses. The challenges associated with the discovery, validation, and translational phases of serum/plasma biomarker establishment are also discussed.

Quality markers addressing preanalytical variations of blood and plasma processing identified by broad and targeted metabolite profiling

BACKGROUND

Metabolomics is a valuable tool with applications in almost all life science areas. There is an increasing awareness of the essential need for high-quality biospecimens in studies applying omics technologies and biomarker research. Tools to detect effects of both blood and plasma processing are a key for assuring reproducible and credible results. We report on the response of the human plasma metabolome to common preanalytical variations in a comprehensive metabolomics analysis to reveal such high-quality markers.

METHODS

Human EDTA blood was subjected to preanalytical variations while being processed to plasma: microclotting, prolonged processing times at different temperatures, hemolysis, and contamination with buffy layer. In a second experiment, EDTA plasma was incubated at different temperatures for up to 16 h. Samples were subjected to GC-MS and liquid chromatography-tandem mass spectrometry-based metabolite profiling (MxP™ Broad Profiling) complemented by targeted methods, i.e., sphingoids (as part of MxP™ Lipids), MxP™ Catecholamines, and MxP™ Eicosanoids.

RESULTS

Short-term storage of blood, hemolysis, and short-term storage of noncooled plasma resulted in statistically significant increases of 4% to 19% and decreases of 8% to 12% of the metabolites. Microclotting, contamination of plasma with buffy layer, and short-term storage of cooled plasma were of less impact on the metabolome (0% to 11% of metabolites increased, 0% to 8% decreased).

CONCLUSIONS

The response of the human plasma metabolome to preanalytical variation demands implementation of thorough quality assurance and QC measures to obtain reproducible and credible results from metabolomics studies. Metabolites identified as sensitive to preanalytics can be used to control for sample quality.

A novel multiplex-protein array for serum diagnostics of colorectal cancer: impact of pre-analytical storage conditions

INTRODUCTION

Biomarker discovery studies seldom report on pre-analytical effects. We used a novel multiplex protein biochip for colorectal cancer screening to investigate effects of different storage temperatures and repeated freeze-thaw cycles.

METHODS

This biochip, composed of CEA, IL-8, VEGF, M-CSF, S100A11, C3adesArg, CD26, and CRP, was applied to twenty highly standardized preserved serum samples.

RESULTS

Aliquot comparison of long-term storage at -80°C (n=20) versus -170°C (n=20) did not show significant differences for any of the eight markers. In contrast, three freeze-thaw cycles (3 × 20 aliquots) detected changes in the serum level for all markers (p<0.05) but S100A11 and CD26: levels of CEA, IL-8, C3adesArg, and CRP increased, while VEGF and M-CSF levels decreased. However, applying diagnostic thresholds for CEA, IL-8, and CRP revealed that freeze-thaw cycles did not affect diagnostic performance. In contrast, analysis of samples stored at -80°C compared to -170°C failed to detect one out of three detectable malignancies.

CONCLUSION

We conclude that three freeze-thaw cycles modulated serum marker levels significantly, but do not compromise biochip diagnostic performance. For our marker panel, serum preservation at -80°C seems comparable to -170°C; however, storage at -80°C could lead to misdiagnosis. Our findings emphasize the need for standardized sample collection, processing, storage, and reporting.

Pre-analytical and analytical variability in absolute quantitative MRM-based plasma proteomic studies

Quantitative plasma proteomics, through the use of targeted MRM-MS and isotopically labeled standards, is emerging as a popular technique to address biological- and biomedical-centered queries. High precision and accuracy are essential in such measurements, particularly in protein biomarker research where translation to the clinic is sought. Standardized procedures and routine performance evaluation of all stages of the workflow (both pre-analytical and analytical) are therefore imperative to satisfy these requisites and enable high inter-laboratory reproducibility and transferability. In this review, we first discuss the pre-analytical and analytical variables that can affect the precision and accuracy of ‘absolute’ quantitative plasma proteomic measurements. Proposed strategies to limit such variability will then be highlighted and unmet needs for future exploration will be noted. Although there is no way to conduct a truly comprehensive review on this broad, rapidly changing topic, we have highlighted key aspects and included references to review articles on various sub-topics.

Pre-analytical stability of the plasma proteomes based on the storage temperature

Background

This study examined the effect of storage temperature on the protein profile of human plasma. Plasma samples were stored for 13 days at -80°C, -20°C, +4°C and room temperature (20-25°C) prior to proteomic analysis. The proteomic comparisons were based on the differences of mean intensity values of protein spots between fresh plasma samples (named “time zero”) and plasma samples stored at different temperatures. To better understand the thermally induced biochemical changes that may affect plasma proteins during storage we identified proteins with different expressions with respect to the time zero sample.

Results

Using two-dimensional electrophoresis followed by MALDI-TOF MS and /or LC-MS/MS 20 protein spots representing 10 proteins were identified with significant differences in abundance when stored at different temperatures. Our results, in agreement with various authors, indicate that during storage for a short period (13 days) at four different temperatures plasma proteins were more affected by degradation processes at +4°C compared to the other temperatures analysed. However, we founded that numerous protein spots (vitamin D binding protein, alpha-1-antitrypsin, serotransferrin, apoplipoprotein A-I, apolipoprotein E, haptoglobin and complement factor B) decrease in abundance with increasing temperature up to 4°C, but at room temperature their intensity mean values are similar to those of time zero and -80°C. We hypothesize that these proteins are labile at 4°C, but at the same time they are stable at room temperature (20-25°C). Furthermore we have grouped the proteins based on their different sensitivity to the storage temperature. Spots of serum albumin, fibrinogen gamma chain and haptoglobin are more resistant to the higher temperatures tested, as they have undergone changes in abundance only at room temperature; conversely, other spots of serum albumin, fibrinogen beta chain and serotransferrin are more labile as they have undergone changes in abundance at all temperatures except at -80°C.

Conclusions

Although there are many studies concerning protein stability of clinical samples during storage these findings may help to provide a better understanding of the changes of proteins induced by storage temperature.

Current status and advances in quantitative proteomic mass spectrometry

The accurate quantitation of proteins and peptides in complex biological systems is one of the most challenging areas of proteomics. Mass spectrometry-based approaches have forged significant in-roads allowing accurate and sensitive quantitation and the ability to multiplex vastly complex samples through the application of robust bioinformatic tools. These relative and absolute quantitative measures using label-free, tags, or stable isotope labelling have their own strengths and limitations. The continuous development of these methods is vital for increasing reproducibility in the rapidly expanding application of quantitative proteomics in biomarker discovery and validation. This paper provides a critical overview of the primary mass spectrometry-based quantitative approaches and the current status of quantitative proteomics in biomedical research.

Collection and handling of blood specimens for peptidomics

Pre-analytical variables can alter the analysis of blood-derived samples. In particular sample collection and specimen preparation can alter the validity of results obtained by modern multiplex assays (e.g., LC-MS). Low-molecular-weight proteins (peptides) as products of proteolytic cleavage events exhibit a close connection to protease activity. Increased or altered activity of proteases during sample collection, specimen generation, sample storage, and processing is mirrored by alterations in abundance of specific peptides. Awareness of clinical practices in medical laboratories and the current knowledge allow for identification of specific variables that affect the results of a peptidomic study. Knowledge of pre-analytical variables is a prerequisite to understand and control their impact.

The effect of pre-analytical variability on the measurement of MRM-MS-based mid- to high-abundance plasma protein biomarkers and a panel of cytokines

Blood sample processing and handling can have a significant impact on the stability and levels of proteins measured in biomarker studies. Such pre-analytical variability needs to be well understood in the context of the different proteomics platforms available for biomarker discovery and validation. In the present study we evaluated different types of blood collection tubes including the BD P100 tube containing protease inhibitors as well as CTAD tubes, which prevent platelet activation. We studied the effect of different processing protocols as well as delays in tube processing on the levels of 55 mid and high abundance plasma proteins using novel multiple-reaction monitoring-mass spectrometry (MRM-MS) assays as well as 27 low abundance cytokines using a commercially available multiplexed bead-based immunoassay. The use of P100 tubes containing protease inhibitors only conferred proteolytic protection for 4 cytokines and only one MRM-MS-measured peptide. Mid and high abundance proteins measured by MRM are highly stable in plasma left unprocessed for up to six hours although platelet activation can also impact the levels of these proteins. The levels of cytokines were elevated when tubes were centrifuged at cold temperature, while low levels were detected when samples were collected in CTAD tubes. Delays in centrifugation also had an impact on the levels of cytokines measured depending on the type of collection tube used. Our findings can help in the development of guidelines for blood collection and processing for proteomic biomarker studies.

Analysis of factors influencing the generation of unqualified clinical samples and measures to prevent this generation

Background

We investigated the influence of pre-analytical factors on the results of clinical tests and thereby analyzed approaches to improve quality management in clinical laboratories.

Methods

Unqualified clinical samples were selected from all the samples received at our clinical laboratory. The data were collected for 2009 and 2010, i.e., the years before and after the establishment of the laboratory quality management system. The rate and causes of generation of unqualified samples were analyzed, and measures to improve the laboratory practices were studied and implemented.

Results

A total of 1,051 unqualified samples were identified from among the 553,158 samples (the overall incidence rate of unqualified samples was 0.19%). The number of unqualified samples substantially varied according to the nature of the sample, and clinical samples collected for routine blood tests or coagulation tests were the predominant unqualified samples. The main causes of generation of unqualified samples were insufficient sample volumes and improper methods of mixing the samples. The rate of generation of unqualified samples decreased significantly after the implementation of improvement measures (0.26% in 2009 vs. 0.13% in 2010, P<0.001).

Conclusions

The number of unqualified samples decreased significantly after the establishment of the laboratory quality management system, which promoted active communication among and training of the clinical staff to reduce the occurrence of pre-analytical errors. Comprehensive control of pre-analytical factors is an important approach in improving the clinical laboratory practices.

Impact of preanalytic factors on the design and application of integral biomarkers for directing patient therapy

Molecular assays have been routinely applied to improve diagnosis for the last 25 years. Assays that guide therapy have a similar history; however, their evolution has lacked the focus on analytic integrity that is required for the molecularly targeted therapies of today. New molecularly targeted agents require assays of greater precision/quantitation to predict the likelihood of response, i.e., to identify patients whose tumors will respond, while at the same time excluding and protecting those patients whose tumors will not respond or in whom treatment will cause unacceptable toxicity. The handling of tissue has followed a fit-for-purpose approach focused on appropriateness for diagnostic needs, which is less rigorous than the demands of new molecular assays that interrogate DNA, RNA, and proteins in a quantitative, multiplex manner. There is a new appreciation of the importance and fragility of tissue specimens as the source of analytes to direct therapy. By applying a total test paradigm and defining and measuring sources of variability in specimens, we can develop a set of specifications that can be incorporated into the clinical-care environment to ensure that a specimen is appropriate for analysis and will return a true result.

Pre-analytical effects of blood sampling and handling in quantitative immunoassays for rheumatoid arthritis

Variability in pre-analytical blood sampling and handling can significantly impact results obtained in quantitative immunoassays. Understanding the impact of these variables is critical for accurate quantification and validation of biomarker measurements. Particularly, in the design and execution of large clinical trials, even small differences in sample processing and handling can have dramatic effects in analytical reliability, results interpretation, trial management and outcome. The effects of two common blood sampling methods (serum vs. plasma) and two widely-used serum handling methods (on the clot with ambient temperature shipping, "traditional", vs. centrifuged with cold chain shipping, "protocol") on protein and autoantibody concentrations were examined. Matched serum and plasma samples were collected from 32 rheumatoid arthritis (RA) patients representing a wide range of disease activity status. Additionally, a set of matched serum samples with two sample handling methods was collected. One tube was processed per manufacturer's instructions and shipped overnight on cold packs (protocol). The matched tube, without prior centrifugation, was simultaneously shipped overnight at ambient temperatures (traditional). Upon delivery, the traditional tube was centrifuged. All samples were subsequently aliquoted and frozen prior to analysis of protein and autoantibody biomarkers. Median correlation between paired serum and plasma across all autoantibody assays was 0.99 (0.98-1.00) with a median % difference of -3.3 (-7.5 to 6.0). In contrast, observed protein biomarker concentrations were significantly affected by sample types, with median correlation of 0.99 (0.33-1.00) and a median % difference of -10 (-55 to 23). When the two serum collection/handling methods were compared, the median correlation between paired samples for autoantibodies was 0.99 (0.91-1.00) with a median difference of 4%. In contrast, significant increases were observed in protein biomarker concentrations among certain biomarkers in samples processed with the 'traditional' method. Autoantibody quantification appears robust to both sample type (plasma vs. serum) and pre-analytical sample collection/handling methods (protocol vs. traditional). In contrast, for non-antibody protein biomarker concentrations, sample type had a significant impact; plasma samples generally exhibit decreased protein biomarker concentrations relative to serum. Similarly, sample handling significantly impacted the variability of protein biomarker concentrations. When biomarker concentrations are combined algorithmically into a single test score such as a multi-biomarker disease activity test for rheumatoid arthritis (MBDA), changes in protein biomarker concentrations may result in a bias of the score. These results illustrate the importance of characterizing pre-analytical methodology, sample type, sample processing and handling procedures for clinical testing in order to ensure test accuracy.

Comparative 2D DIGE analysis of the depleted serum proteome for biomarker discovery

Serum is unarguably the most used diagnostic fluid. As it circulates throughout the body, leakage peptides/proteins from damaged and dying cells, host-response proteins including inflammatory mediators, and aberrant secretions from tumors and diseased tissues are released into serum, potentially providing a rich source of disease biomarkers. Here, a method for extending access to the serum proteome by removing highly abundant proteins prior to comparative two-dimensional difference gel electrophoresis (2D DIGE) and subsequent protein digestion for identification by mass spectrometry is described.