Unravelling in vitro variables of major importance for the outcome of mass spectrometry-based serum proteomics

Selected reaction monitoring for colorectal cancer diagnosis using a set of five serum peptides identified by BLOTCHIP®-MS analysis

BACKGROUND

Colorectal cancer (CRC) is one of the most predominant types of cancer, and it is the fourth most common cause of cancer-related death and it is important to diagnose CRC in early stage to decrease the mortality by CRC. In our previous study, we identified a combination of five peptides as a biomarker candidate to diagnose CRC by BLOTCHIP^®-MS analysis using a set of healthy control subjects and CRC patients (stage II-IV). The aim of the present study was to validate the serum biomarker peptides reported in our previous study using a second cohort and to establish their potential usefulness in CRC diagnosis.

METHODS

A total of 56 patients with CRC (n = 14 each of stages I-IV), 60 healthy controls, and 60 patients with colonic adenoma were included in this study. The five peptides were extracted and analyzed by selected reaction monitoring using ProtoKey^® Colorectal Cancer Risk Test Kit (Protosera, Inc., Amagasaki, Japan).

RESULTS

The results clearly showed that the four CRC groups, stages I-IV, could be sufficiently discriminated from the control group and colonic polyp group. This five-peptide set could identify CRC at each stage compared to the control population in this validation cohort, including those with early-stage disease. The AUC values for each stage of CRC compared to the control population were 0.779, 0.946, 0.852, and 0.973 for stages I, II, III, and IV, respectively.

CONCLUSIONS

In this case-control validation study, we confirmed high diagnostic performance for CRC using five peptides that were identified in our previous study as serum biomarker candidates for the detection of CRC.

Random and independent sampling of endogenous tryptic peptides from normal human EDTA plasma by liquid chromatography micro electrospray ionization and tandem mass spectrometry

Background

Normal human EDTA plasma samples were collected on ice, processed ice cold, and stored in a freezer at – 80 °C prior to experiments. Plasma test samples from the – 80 °C freezer were thawed on ice or intentionally warmed to room temperature.

Methods

Protein content was measured by CBBR binding and the release of alcohol soluble amines by the Cd ninhydrin assay. Plasma peptides released over time were collected over C18 for random and independent sampling by liquid chromatography micro electrospray ionization and tandem mass spectrometry (LC–ESI–MS/MS) and correlated with X!TANDEM.

Results

Fully tryptic peptides by X!TANDEM returned a similar set of proteins, but was more computationally efficient, than “no enzyme” correlations. Plasma samples maintained on ice, or ice with a cocktail of protease inhibitors, showed lower background amounts of plasma peptides compared to samples incubated at room temperature. Regression analysis indicated that warming plasma to room temperature, versus ice cold, resulted in a ~ twofold increase in the frequency of peptide identification over hours–days of incubation at room temperature. The type I error rate of the protein identification from the X!TANDEM algorithm combined was estimated to be low compared to a null model of computer generated random MS/MS spectra.

Conclusion

The peptides of human plasma were identified and quantified with low error rates by random and independent sampling that revealed 1000s of peptides from hundreds of human plasma proteins from endogenous tryptic peptides.

Electronic supplementary material

The online version of this article (10.1186/s12014-017-9176-7) contains supplementary material, which is available to authorized users.

The proteins cleaved by endogenous tryptic proteases in normal EDTA plasma by C18 collection of peptides for liquid chromatography micro electrospray ionization and tandem mass spectrometry

The tryptic peptides from ice cold versus room temperature plasma were identified by C18 liquid chromatography and micro electrospray ionization tandem mass spectrometry (LC–ESI–MS/MS). Samples collected on ice showed low levels of endogenous tryptic peptides compared to the same samples incubated at room temperature. Plasma on ice contained peptides from albumin, complement, and apolipoproteins and others that were observed by the X!TANDEM and SEQUEST algorithms. In contrast to ice cold samples, after incubation at room temperature, greater numbers of tryptic peptides from well characterized plasma proteins, and from cellular proteins were observed. A total of 583,927 precursor ions and MS/MS spectra were correlated to 94,669 best fit peptides that reduced to 22,287 correlations to the best accession within a gene symbol and to 7174 correlations to at least 510 gene symbols with ≥ 5 independent MS/MS correlations (peptide counts) that showed FDR q-values ranging from E−9 (i.e. FDR = 0.000000001) to E−227. A set of 528 gene symbols identified by X!TANDEM and SEQUEST including C4B showed ≥ fivefold variation between ice cold versus room temperature incubation. STRING analysis of the protein gene symbols observed from endogenous peptides in normal plasma revealed an extensive protein-interaction network of cellular factors associated with cell signalling and regulation, the formation of membrane bound organelles, cellular exosomes and exocytosis network proteins. Taken together the results indicated that a pool of cellular proteins, or protein complexes, in plasma are apparently not stable and degrade soon after incubation at room temperature.

Freeze-dried plasma proteins are stable at room temperature for at least 1 year

Thirty human EDTA plasma samples from male and female subjects ranging in age from 24 to 74 years were collected on ice, processed ice cold and stored frozen at -80 °C, in liquid nitrogen (LN2), or freeze dried and stored at room temperature in a desiccator (FDRT) or freeze dried and stored at -20 °C for 1 year (FD-20). In a separate experiment, EDTA plasma samples were collected onto ice, processed ice cold and maintained on ice ± protease inhibitors versus incubated at room temperature for up to 96 h. Random and independent sampling by liquid chromatography and tandem mass spectrometry (LC-ESI-MS/MS), as correlated by the MASCOT, OMSSA, X!TANDEM and SEQUEST algorithms, showed that tryptic peptides from complement component 4B (C4B) were rapidly released in plasma at room temperature. Random sampling by LC-ESI-MS/MS showed that peptides from C4B were undetectable on ice, but peptides were cleaved from the mature C4B protein including NGFKSHALQLNNR within as little as 1 h at room temperature. The frequency and intensity of precursors within ± 3 m/z of the C4B peptide NGFKSHALQLNNR was confirmed by automated targeted analysis where the precursors from MS/MS spectra that correlated to the target sequence were analyzed in SQL/R. The C4B preproprotein was processed at the N terminus to release the mature chain that was cleaved on the carboxyl side of the isoprene C2 domain within a polar C terminal sequence of the mature C4B protein, to reveal the thioester reaction site, consistent with LC-ESI-MS/MS and Western blot. Random sampling showed that proteolytic peptides from complement component C4B were rarely observed with long term storage at - 80 °C in a freezer or in liquid nitrogen (LN2), freeze drying with storage at - 20 °C (FD-20 °C) or freeze drying and storage at room temperature (FDRT). Plasma samples maintained at room temperature (RT) showed at least 10-fold to 100-fold greater frequency of peptide correlation to C4B and measured peptide intensity compared to samples on ice for up to 72 h or stored at - 80 °C, LN2, FDRT or FD-20 °C for up to a year.

Characterization of the Low-Molecular-Weight Human Plasma Peptidome

The human plasma proteome represents an important secreted sub-proteome. Proteomic analysis of blood plasma with mass spectrometry is a challenging task. The high complexity and wide dynamic range of proteins as well as the presence of several proteins at very high concentrations complicate the profiling of the human plasma proteome. The peptidome (or low-molecular-weight fraction, LMF) of the human plasma proteome is an invaluable source of biological information, especially in the context of identifying plasma-based markers of disease. Peptides are generated by active synthesis and proteolytic processing, often yielding proteolytic fragments that mediate a variety of physiological and pathological functions. As such, degradomic studies, investigating cleavage products via peptidomics and top-down proteomics in particular, have warranted significant research interest. However, due to their molecular weight, abundance, and solubility, issues with identifying specific cleavage sites and coverage of peptide fragments remain challenging. Peptidomics is currently focused toward comprehensively studying peptides cleaved from precursor proteins by endogenous proteases. This protocol outlines a standardized rapid and reproducible procedure for peptidomic profiling of human plasma using centrifugal ultrafiltration and mass spectrometry. Ultrafiltration is a convective process that uses anisotropic semipermeable membranes to separate macromolecular species on the basis of size. We have optimized centrifugal ultrafiltration (cellulose triacetate membrane) for plasma fractionation with respect to buffer and solvent composition, centrifugal force, duration, and temperature to facilitate recovery >95% and enrichment of the human plasma peptidome. This method serves as a comprehensive and facile process to enrich and identify a key, underrepresented sub-proteome of human blood plasma.

Plasma degradome affected by variable storage of human blood

Background

The successful application of—omics technologies in the discovery of novel biomarkers and targets of therapeutic interventions is facilitated by large collections of well curated clinical samples stored in bio banks. Mining the plasma proteome holds promise to improve our understanding of disease mechanisms and may represent a source of biomarkers. However, a major confounding factor for defining disease-specific proteomic signatures in plasma is the variation in handling and processing of clinical samples leading to protein degradation. To address this, we defined a plasma proteolytic signature (degradome) reflecting pre-analytical variability in blood samples that remained at ambient temperature for different time periods after collection and prior to processing.

Methods

We obtained EDTA blood samples from five healthy volunteers (n = 5), and blood tubes remained at ambient temperature for 30 min, 8, 24 and 48 h prior to centrifugation and isolation of plasma. Naturally occurred peptides derived from plasma samples were compared by label-free quantitative LC–MS/MS. To profile protein degradation, we analysed pooled plasma samples at T = 30 min and 48 h using PROTOMAP analysis. The proteolytic pattern of selected protein candidates was further validated by immunoblotting.

Results

A total of 820 plasma proteins were surveyed by PROTOMAP, and for 4 % of these, marked degradation was observed. We show distinct proteolysis patterns for talin-1, coagulation factor XI, complement protein C1r, C3, C4 and thrombospondin, and several proteins including S100A8, A9, annexin A1, profiling-1 and platelet glycoprotein V are enriched after 48 h blood storage at ambient temperature. In particular, thrombospondin protein levels increased after 8 h and proteolytic fragments appeared after 24 h storage time.

Conclusions

The overall impact of blood storage at ambient temperature for variable times on the plasma proteome and degradome is relatively minor, but in some cases can cause a potential bias in identifying and assigning relevant proteomic markers. The observed effects on the plasma proteome and degradome are predominantly triggered by limited leucocyte and platelet cell activation due to blood handling and storage. The baseline plasma degradome signature presented here can help filtering candidate protein markers relevant for clinical biomarker studies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12014-016-9126-9) contains supplementary material, which is available to authorized users.

Blood-borne biomarkers and bioindicators for linking exposure to health effects in environmental health science

Environmental health science aims to link environmental pollution sources to adverse health outcomes to develop effective exposure intervention strategies that reduce long-term disease risks. Over the past few decades, the public health community recognized that health risk is driven by interaction between the human genome and external environment. Now that the human genetic code has been sequenced, establishing this "G × E" (gene-environment) interaction requires a similar effort to decode the human exposome, which is the accumulation of an individual's environmental exposures and metabolic responses throughout the person's lifetime. The exposome is composed of endogenous and exogenous chemicals, many of which are measurable as biomarkers in blood, breath, and urine. Exposure to pollutants is assessed by analyzing biofluids for the pollutant itself or its metabolic products. New methods are being developed to use a subset of biomarkers, termed bioindicators, to demonstrate biological changes indicative of future adverse health effects. Typically, environmental biomarkers are assessed using noninvasive (excreted) media, such as breath and urine. Blood is often avoided for biomonitoring due to practical reasons such as medical personnel, infectious waste, or clinical setting, despite the fact that blood represents the central compartment that interacts with every living cell and is the most relevant biofluid for certain applications and analyses. The aims of this study were to (1) review the current use of blood samples in environmental health research, (2) briefly contrast blood with other biological media, and (3) propose additional applications for blood analysis in human exposure research.

Mass spectrometry-based serum and plasma peptidome profiling for prediction of treatment outcome in patients with solid malignancies

INTRODUCTION

Treatment selection tools are needed to enhance the efficacy of targeted treatment in patients with solid malignancies. Providing a readout of aberrant signaling pathways and proteolytic events, mass spectrometry-based (MS-based) peptidomics enables identification of predictive biomarkers, whereas the serum or plasma peptidome may provide easily accessible signatures associated with response to treatment. In this systematic review, we evaluate MS-based peptide profiling in blood for prompt clinical implementation.

METHODS

PubMed and Embase were searched for studies using a syntax based on the following hierarchy: (a) blood-based matrix-assisted or surface-enhanced laser desorption/ionization time-of-flight MS peptide profiling (b) in patients with solid malignancies (c) prior to initiation of any treatment modality, (d) with availability of outcome data.

RESULTS

Thirty-eight studies were eligible for review; the majority were performed in patients with non-small cell lung cancer (NSCLC). Median classification prediction accuracy was 80% (range: 66%-93%) in 11 models from 14 studies reporting an MS-based classification model. A pooled analysis of 9 NSCLC studies revealed clinically significant median progression-free survival in patients classified as "poor outcome" and "good outcome" of 2.0 ± 1.06 months and 4.6 ± 1.60 months, respectively; median overall survival was also clinically significant at 4.01 ± 1.60 months and 10.52 ± 3.49 months, respectively.

CONCLUSION

Pretreatment MS-based serum and plasma peptidomics have shown promising results for prediction of treatment outcome in patients with solid tumors. Limited sample sizes and absence of signature validation in many studies have prohibited clinical implementation thus far. Our pooled analysis and recent results from the PROSE study indicate that this profiling approach enables treatment selection, but additional prospective studies are warranted.

Comparative serum proteomic analysis of serum diagnosis proteins of colorectal cancer based on magnetic bead separation and maldi-tof mass spectrometry

BACKGROUND

At present, the diagnosis of colorectal cancer (CRC) requires a colorectal biopsy which is an invasive procedure. We undertook this pilot study to develop an alternative method and potential new biomarkers for diagnosis, and validated a set of well-integrated tools called ClinProt to investigate the serum peptidome in CRC patients.

METHODS

Fasting blood samples from 67 patients diagnosed with CRC by histological diagnosis, 55 patients diagnosed with colorectal adenoma by biopsy, and 65 healthy volunteers were collected. Division was into a model construction group and an external validation group randomly. The present work focused on serum proteomic analysis of model construction group by ClinProt Kit combined with mass spectrometry. This approach allowed construction of a peptide pattern able to differentiate the studied populations. An external validation group was used to verify the diagnostic capability of the peptidome pattern blindly. An immunoassay method was used to determine serum CEA of CRC and controls.

RESULTS

The results showed 59 differential peptide peaks in CRC, colorectal adenoma and health volunteers. A genetic algorithm was used to set up the classification models. Four of the identified peaks at m/z 797, 810, 4078 and 5343 were used to construct peptidome patterns, achieving an accuracy of 100% (> CEA, P < 0. 05). Furthermore, the peptidome patterns could differentiate the validation group with high accuracy close to 100%.

CONCLUSIONS

Our results showed that proteomic analysis of serum with MALDI-TOF MS is a fast and reproducible approach, which may provide a novel approach to screening for CRC.

Identification alpha-2-HS-glycoprotein precursor and tubulin beta chain as serology diagnosis biomarker of colorectal cancer

BACKGROUND

Colorectal cancer (CRC) remains a major worldwide cause of cancer-related morbidity and mortality largely due to the insidious onset of the disease. The current clinical procedures utilized for disease diagnosis are invasive, unpleasant, and inconvenient. Hence, the need for simple blood tests that could be used for the early detection is crucial for its ultimate control and prevention.

METHODS

The present work is a case-control study focused on proteomic analysis of serum of healthy volunteers and CRC patients by the ClinProt profiling technology based on mass spectrometry. This approach allowed to identifying a pattern of proteins/peptides able to differentiate the studied populations. Moreover, some of peptides differentially expressed in the serum of patients as compared to healthy volunteers were identified by LTQ Orbitrap XL.

RESULTS

A Quick Classifier Algorithm was used to construct the peptidome patterns (m/z 1208, 1467, 1505, 1618, 1656 and 4215) for the identification of CRC from healthy volunteers with accuracy close to 100% (>CEA, P < 0.05). Peaks at m/z 1505 and 1618 were identified as alpha-2-HS-glycoprotein precursor and tubulin beta chain, respectively.

CONCLUSIONS

Alpha-2-HS-glycoprotein precursor and tubulin beta chain could be involved in the pathogenesis of CRC and perform as potential serology diagnosis biomarker.

VIRTUAL SLIDES

The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/4796578761089186.

Optimization and evaluation of magnetic bead separation combined with matrix-assisted laser desorption/ionization time-of-flight mass spectroscopy (MALDI-TOF MS) for proteins profiling of peritoneal dialysis effluent

Peritoneal dialysis effluent (PDE) potentially carries an archive of peptides relevant to pathological processes in abdominal and surrounding tissues. Magnetic beads and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry is one such approach that offers a unique tool for profiling of peptides, but this approach has not been used in the PDE analysis. In this study, we developed a strategy for screening PDE proteins <15 kDa and applied this technique to identify potential biomarkers for peritonitis. We examined four kinds of magnetic beads, including a carbon series (C3, C8), weak cation exchange (WCX) and immobilized metal-affinity chromatography (IMAC-Cu) beads. Samples processed with IMAC-Cu magnetic beads consistently showed more MS signals across all beads within the measured mass range. Moreover, there was no difference in the number and morphology of MS signals between concentrated and unconcentrated samples. The PDE peptidome pattern, based on a panel of 15 peaks, accurately recognized peritonitis PD patients from peritonitis-free patients with sensitivity of 90.5% and specificity of 94.7% respectively. Therefore, IMAC-Cu magnetic beads and unconcentrated samples can be used as a fast and cost-effective approach for sample preparation prior to more in-depth discovery of predictive biomarkers of disease in patients on dialysis.

Identification of evidence-based biospecimen quality-control tools: a report of the International Society for Biological and Environmental Repositories (ISBER) Biospecimen Science Working Group

Control of biospecimen quality that is linked to processing is one of the goals of biospecimen science. Consensus is lacking, however, regarding optimal sample quality-control (QC) tools (ie, markers and assays). The aim of this review was to identify QC tools, both for fluid and solid-tissue samples, based on a comprehensive and critical literature review. The most readily applicable tools are those with a known threshold for the preanalytical variation and a known reference range for the QC analyte. Only a few meaningful markers were identified that meet these criteria, such as CD40L for assessing serum exposure at high temperatures and VEGF for assessing serum freeze-thawing. To fully assess biospecimen quality, multiple QC markers are needed. Here we present the most promising biospecimen QC tools that were identified.

Serum peptidome patterns of colorectal cancer based on magnetic bead separation and MALDI-TOF mass spectrometry analysis

Background. Colorectal cancer (CRC) is one of the most common cancers in the world, identification of biomarkers for early detection of CRC represents a relevant target. The present study aims to determine serum peptidome patterns for CRC diagnosis. Methods. The present work focused on serum proteomic analysis of 32 health volunteers and 38 CRC by ClinProt Kit combined with mass spectrometry. This approach allowed the construction of a peptide patterns able to differentiate the studied populations. An independent group of serum (including 33 health volunteers, 34 CRC, 16 colorectal adenoma, 36 esophageal carcinoma, and 31 gastric carcinoma samples) was used to verify the diagnostic and differential diagnostic capability of the peptidome patterns blindly. An immunoassay method was used to determine serum CEA of CRC and controls. Results. A quick classifier algorithm was used to construct the peptidome patterns for identification of CRC from controls. Two of the identified peaks at m/z 741 and 7772 were used to construct peptidome patterns, achieving an accuracy close to 100% (>CEA, P < 0.05). Furthermore, the peptidome patterns could differentiate validation group with high accuracy. Conclusions. These results suggest that the ClinProt Kit combined with mass spectrometry yields significantly higher accuracy for the diagnosis and differential diagnosis of CRC.

Development of multiplexed bead-based immunoassays for the detection of early stage ovarian cancer using a combination of serum biomarkers

CA125 as a biomarker of ovarian cancer is ineffective for the general population. The aim of this study was to evaluate multiplexed bead-based immunoassay of multiple ovarian cancer-associated biomarkers such as transthyretin and apolipoprotein A1, together with CA125, to improve the identification and evaluation of prognosis of ovarian cancer. We measured the serum levels of CA125, transthyretin, and apolipoprotein A1 from the serum of 61 healthy individuals, 84 patients with benign ovarian disease, and 118 patients with ovarian cancer using a multiplex liquid assay system, Luminex 100. The results were then analyzed according to healthy and/or benign versus ovarian cancer subjects. When CA125 was combined with the other biomarkers, the overall sensitivity and specificity were significantly improved in the ROC curve, which showed 95% and 97% sensitivity and specificity, respectively. At 95% specificity for all stages the sensitivity increased to 95.5% compared to 67% for CA125 alone. For stage I+II, the sensitivity increased from 30% for CA125 alone to 93.9%. For stage III+IV, the corresponding values were 96.5% and 91.6%, respectively. Also, the three biomarkers were sufficient for maximum separation between noncancer (healthy plus benign group) and stage I+II or all stages (I-IV) of disease. The new combination of transthyretin, and apolipoprotein A1 with CA125 improved both the sensitivity and the specificity of ovarian cancer diagnosis compared with those of individual biomarkers. These findings suggest the benefit of the combination of these markers for the diagnosis of ovarian cancer.

Serum peptidome patterns for early screening of esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is one of the most common cancers in the world. Early diagnosis is critical for guiding the therapeutic management of ESCC. The present study aims to determine serum peptidome patterns for diagnosing ESCC. To identify novel peptidome patterns for diagnosing ESCC, sera from 31 healthy volunteers and 32 ESCC patients were subjected to a comparative proteomic analysis using a ClinProt™ Kit combined with mass spectrometry (MS). This approach enables the determination of peptidome patterns that can differentiate between ESCC sera and sera from healthy volunteers. For further validation, the diagnostic and differential diagnostic capabilities of the peptidome patterns were verified blindly by using an independent group of sera, consisting of sera from 31 ESCC patients, 33 healthy volunteers, 38 colorectal patients, and 36 gastric cancer patients. A Quick Classifier Algorithm was used to construct the peptidome patterns for the identification of ESCC from the control samples. Five of the identified peaks at mass to charge ratios 759, 786, 1,866, 3,316, and 6,634 were used to construct the peptidome patterns with almost 100% accuracy. Furthermore, the peptidome patterns could also differentiate the validation group with high accuracy. These results suggest that the ClinProt™ Kit combined with MS achieves significantly high accuracy for ESCC diagnosis and differential diagnosis.

Multiplexed bead-based immunoassay of four serum biomarkers for diagnosis of ovarian cancer

The purpose of the present study was to evaluate multiplex liquid assay-based measurement of multiple ovarian cancer-associated biomarkers such as hemoglobin, haptoglobin and apolipoprotein E, together with CA125, which has been widely used in the diagnosis of ovarian cancer, in order to provide a higher diagnostic power. We measured the serum levels of CA125, hemoglobin, haptoglobin and apolipoprotein E from the serum of 76 healthy individuals and 69 ovarian cancer patients using a multiplex liquid assay system, Luminex 100. The results were analyzed according to normal versus ovarian cancer, tumor stages and tumor histology. In addition, to validate the use of these biomarkers for the diagnosis of ovarian cancer, the sensitivity and specificity of each biomarker was analyzed by its receiver operating characteristics (ROC) curve. The serum levels of all four biomarkers in ovarian cancer patients were significantly higher than those of healthy individuals. When CA125 was combined with the biomarkers, the overall sensitivity and specificity were significantly improved in the ROC curve, which showed 95 and 75% sensitivity and specificity, respectively. At 95% specificity for all stages the sensitivity increased to 75% compared to 41% for CA125 alone. For stage I+II increased the sensitivity to 68% from 36% for CA125 alone. For stage III+IV the corresponding values were 100 and 95%, respectively. Taken together, the new combination of hemoglobin, haptoglobin and apolipoprotein E with CA125 significantly improved both the sensitivity and the specificity of ovarian cancer diagnosis compared with those of individual biomarkers. These findings suggest the benefit of the combination of these markers for the diagnosis of ovarian cancer.

Serum peptidome patterns of breast cancer based on magnetic bead separation and mass spectrometry analysis

Background

Breast cancer is one of the most common cancers in the world, and the identification of biomarkers for the early detection of breast cancer is a relevant target. The present study aims to determine serum peptidome patterns for screening of breast cancer.

Methods

The present work focused on the serum proteomic analysis of 36 healthy volunteers and 37 breast cancer patients using a ClinProt Kit combined with mass spectrometry (MS). This approach allows the determination of peptidome patterns that are able to differentiate the studied populations. An independent group of sera (36 healthy volunteers and 37 breast cancer patients) was used to verify the diagnostic capabilities of the peptidome patterns blindly. An immunoassay method was used to determine the serum mucin 1 (CA15-3) of validation group samples.

Results

Support Vector Machine (SVM) Algorithm was used to construct the peptidome patterns for the identification of breast cancer from the healthy volunteers. Three of the identified peaks at m/z 698, 720 and 1866 were used to construct the peptidome patterns with 91.78% accuracy. Furthermore, the peptidome patterns could differentiate the validation group achieving a sensitivity of 91.89% (34/37) and a specitivity of 91.67% (33/36) (> CA 15–3, P < 0.05).

Conclusions

These results suggest that the ClinProt Kit combined with MS shows great potentiality for the diagnosis of breast cancer.

Virtual slides

The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1501556838687844

MS/MS library facilitated MRM quantification of native peptides prepared by denaturing ultrafiltration

Naturally occurring native peptides provide important information about physiological states of an organism and its changes in disease conditions but protocols and methods for assessing their abundance are not well-developed. In this paper, we describe a simple procedure for the quantification of non-tryptic peptides in body fluids. The workflow includes an enrichment step followed by two-dimensional fractionation of native peptides and MS/MS data management facilitating the design and validation of LC- MRM MS assays. The added value of the workflow is demonstrated in the development of a triplex LC-MRM MS assay used for quantification of peptides potentially associated with the progression of liver disease to hepatocellular carcinoma.

Global stability of plasma proteomes for mass spectrometry-based analyses

Peptide-based mass spectrometry approaches, such as multiple reaction monitoring, provide a powerful means to measure candidate protein biomarkers in plasma. A potential confounding problem is the effect of preanalytical variables, which may affect the integrity of proteins and peptides. Although some blood proteins undergo rapid physiological proteolysis ex vivo, the stability of most plasma proteins to preanalytical variables remains largely unexplored. We applied liquid chromatography-tandem mass spectrometry shotgun proteomics and multiple reaction monitoring analyses to characterize the stability of proteins at the peptide level in plasma. We systematically evaluated the effects of delay in plasma preparation at different temperatures, multiple freeze-thaw cycles and erythocyte hemolysis on peptide and protein inventories in prospectively collected human plasma. Time course studies indicated few significant changes in peptide and protein identifications, semitryptic peptides and methionine-oxidized peptides in plasma from blood collected in EDTA plasma tubes and stored for up to a week at 4 °C or room temperature prior to plasma isolation. Similarly, few significant changes were observed in similar analyses of plasma subjected to up to 25 freeze-thaw cycles. Hemolyzed samples produced no significant differences beyond the presence of hemoglobin proteins. Finally, paired comparisons of plasma and serum samples prepared from the same patients also yielded few significant differences, except for the depletion of fibrinogen in serum. Blood proteins thus are broadly stable to preanalytical variables when analyzed at the peptide level. Collection protocols to generate plasma for multiple reaction monitoring-based analyses may have different requirements than for other analyses directed at intact proteins.

From “Clinical Proteomics” to “Clinical Chemistry Proteomics”: considerations using quantitative mass-spectrometry as a model approach

Clinical Proteomics biomarker discovery programs lead to the selection of putative new biomarkers of human pathologies. Following an initial discovery phase, validation of these candidates in larger populations is a major task that recently started relying upon the use of mass spectrometry approaches, especially in cases where classical immune-detection methods were lacking. Thanks to highly sensitive spectrometers, adapted measurement methods like selective reaction monitoring (SRM) and various pre-fractionation methods, the quantitative detection of protein/peptide biomarkers in low concentrations is now feasible from complex biological fluids. This possibility leads to the use of similar methodologies in clinical biology laboratories, within a new proteomic field that we shall name “Clinical Chemistry Proteomics” (CCP). Such evolution of Clinical Proteomics adds important constraints with regards to the in vitro diagnostic (IVD) application. As measured values of analytes will be used to diagnose, follow-up and adapt patient treatment on a routine basis; medical utility, robustness, reference materials and clinical feasibility are among the new issues of CCP to consider.

Detection and measurement of carbohydrate deficient transferrin in serum using immuno-capture mass spectrometry: diagnostic applications for annual ryegrass toxicity and corynetoxin exposure

The neurological livestock disease annual ryegrass toxicity (ARGT) is caused by the ingestion of the naturally occurring glycolipid toxins - the corynetoxins. Corynetoxins also threaten human health as potential contaminants of the food supply. Presently, there are no routine diagnostic tests for corynetoxins-exposure in humans or livestock. Chronic ingestion of corynetoxins has been modeled in rats exposed to dietary tunicamycins for 12 months and carbohydrate deficient transferrin (CDT) has been previously identified as a candidate disease biomarker. Here, the technique of immuno-capture mass spectrometry (icMS) was used to evaluate serum levels of CDT, discriminating between control and tunicamycins-exposed rats with 85% accuracy. The icMS approach is based on the combination of specific transferrin enrichment with functionalized magnetic beads and automated matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). With no other clinically-relevant diagnostic tests available icMS could be readily adapted for high-throughput clinical assessment of corynetoxins-exposure in humans or livestock.

Mass spectrometry of peptides and proteins from human blood

It is difficult to convey the accelerating rate and growing importance of mass spectrometry applications to human blood proteins and peptides. Mass spectrometry can rapidly detect and identify the ionizable peptides from the proteins in a simple mixture and reveal many of their post-translational modifications. However, blood is a complex mixture that may contain many proteins first expressed in cells and tissues. The complete analysis of blood proteins is a daunting task that will rely on a wide range of disciplines from physics, chemistry, biochemistry, genetics, electromagnetic instrumentation, mathematics and computation. Therefore the comprehensive discovery and analysis of blood proteins will rank among the great technical challenges and require the cumulative sum of many of mankind's scientific achievements together. A variety of methods have been used to fractionate, analyze and identify proteins from blood, each yielding a small piece of the whole and throwing the great size of the task into sharp relief. The approaches attempted to date clearly indicate that enumerating the proteins and peptides of blood can be accomplished. There is no doubt that the mass spectrometry of blood will be crucial to the discovery and analysis of proteins, enzyme activities, and post-translational processes that underlay the mechanisms of disease. At present both discovery and quantification of proteins from blood are commonly reaching sensitivities of ∼1 ng/mL.

A well-characterised peak identification list of MALDI MS profile peaks for human blood serum

MALDI MS profiling, using easily available body fluids such as blood serum, has attracted considerable interest for its potential in clinical applications. Despite the numerous reports on MALDI MS profiling of human serum, there is only scarce information on the identity of the species making up these profiles, particularly in the mass range of larger peptides. Here, we provide a list of more than 90 entries of MALDI MS profile peak identities up to 10 kDa obtained from human blood serum. Various modifications such as phosphorylation were detected among the peptide identifications. The overlap with the few other MALDI MS peak lists published so far was found to be limited and hence our list significantly extends the number of identified peaks commonly found in MALDI MS profiling of human blood serum.

Low-molecular weight plasma proteome analysis using centrifugal ultrafiltration

The low-molecular weight fraction (LMF) of the human plasma proteome is an invaluable source of biological information, especially in the context of identifying plasma-based biomarkers of disease. This protocol outlines a standardized procedure for the rapid/reproducible LMF profiling of human plasma samples using centrifugal ultrafiltration fractionation, followed by 1D-SDS-PAGE separation and nano-LC-MS/MS. Ultrafiltration is a convective process that uses anisotropic semipermeable membranes to separate macromolecular species on the basis of size. We have optimized centrifugal ultrafiltration for plasma fractionation with respect to buffer and solvent composition, centrifugal force, duration and temperature to facilitate >95% recovery, and enrichment of low-M (r) components from human plasma. Using this protocol, >260 unique peptides can be identified from a single plasma profiling experiment using 100 μL of plasma (Greening and Simpson, J Proteomics 73:637-648, 2010). The efficacy of this method is demonstrated by the identification, for the first time, of several plasma proteins (e.g., protein KIAA0649 (Q9Y4D3), rheumatoid factor D5, serine protease inhibitor A3, and transmembrane adapter protein PAG) previously not reported in extant high-confidence Human Proteome Organization Plasma Proteome Project datasets.

Proteomic serum biomarkers and their potential application in cancer screening programs

Early diagnosis of cancer is of pivotal importance to reduce disease-related mortality. There is great need for non-invasive screening methods, yet current screening protocols have limited sensitivity and specificity. The use of serum biomarkers to discriminate cancer patients from healthy persons might be a tool to improve screening programs. Mass spectrometry based proteomics is widely applied as a technology for mapping and identifying peptides and proteins in body fluids. One commonly used approach in proteomics is peptide and protein profiling. Here, we present an overview of profiling methods that have the potential for implementation in a clinical setting and in national screening programs.

Specific Investigation of Sample Handling Effects on Protease Activities and Absolute Serum Concentrations of Various Putative Peptidome Cancer Biomarkers

Introduction

In the search for novel cancer biomarkers, various proteolytically derived peptides have been proposed to exhibit cancer or cancer-type specificity. As these peptides are presumably also generated after sample collection by tumor-specific proteases, extensive investigation of the involved proteolytic processes is crucial for further research.

Materials and Methods

Using two previously developed and fully validated liquid-chromatography coupled to tandem-mass spectrometry assays, absolute quantification of, in total, 13 proteolytically derived peptides in human serum was accomplished. The analytes included eight peptides derived from inter-α-trypsin inhibitor heavy chain-4 (ITIH₄-30, ITIH₄-29, ITIH₄-28, ITIH₄-27, ITIH₄-26, ITIH₄-25, ITIH₄-22, and ITIH₄-21), bradykinin, des-Arg⁹-bradykinin, Hyp³-bradykinin, and fragments from fibrinogen-α-chain (Fib-α _[605–629]) and complement component 4a (C4a _{[1337–1350]}). Samples were obtained from different healthy individuals and prepared with variable tube types, clotting times, and temperatures. Furthermore, stabilities in the serum fraction were assessed and compared to stabilities in serum from breast cancer patients.

Results and Discussion

The quantitative analyses showed either increasing or decreasing serum concentrations during blood coagulation, while comparable effects were observed in serum separated from the blood clot. Furthermore, comparisons of inter- and intra-individual variations suggested better reflection of an individual’s protease activity after prolonged ex vivo incubation. This was illustrated for the putative breast cancer marker ITIH₄-22, revealing better differentiation after incubation of serum at ambient temperature for 24 h.

Conclusion

The presented study provides suggestions for more specific and optimized sample preparation, as well as extended knowledge necessary to further explore the opportunities of these proteolytic peptides as cancer biomarkers.

Potential biomarkers for esophageal carcinoma detected by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

BACKGROUND

Currently, no satisfactory biomarkers are available to screen for esophageal squamous cell carcinoma (ESCC). The goal of this study was to find biomarkers and establish a serum protein fingerprint model for early diagnosis of ESCC using the ClinProt protocol of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS).

METHODS

Serum samples were collected from 62 patients with ESCC, nine patients with esophageal adenocarcinoma (EA) and 38 healthy individuals. Proteomic spectra of mass to charge ratio (m/z) were generated following the application of plasma to weak cationic-exchanger magnetic beads (WCX-MB). The spectral data were analyzed using a support vector machine, and potential biomarkers were chosen for system training and used to construct diagnostic models.

RESULTS

Three differential patterns were established using MALDI-TOF MS. Pattern 1, consisting of 11 protein peaks, separated ESCC patients from the healthy individuals with a sensitivity of 90.0% and a specificity of 88.4%. Pattern 2, consisting of eight protein peaks, separated ESCC in stage I and stage II from stage III and stage IV with a sensitivity of 92.9% and a specificity of 82.3%. Pattern 3, consisting of seven protein peaks, separated ESCC from EA with a sensitivity of 91.3% and a specificity of 80.0%.

CONCLUSIONS

These results suggested that MALDI-TOF MS combined with MB separation yields significantly higher sensitivity and specificity for the detection of serum protein in patients with ESCC.

High-throughput and targeted in-depth mass spectrometry-based approaches for biofluid profiling and biomarker discovery

Proteomics aims to create a link between genomic information, biological function and disease through global studies of protein expression, modification and protein-protein interactions. Recent advances in key proteomics tools, such as mass spectrometry (MS) and (bio)informatics, provide tremendous opportunities for biomarker-related clinical applications. In this review, we focus on two complementary MS-based approaches with high potential for the discovery of biomarker patterns and low-abundant candidate biomarkers in biofluids: high-throughput matrix-assisted laser desorption/ionization time-of-flight mass spectroscopy-based methods for peptidome profiling and label-free liquid chromatography-based methods coupled to MS for in-depth profiling of biofluids with a focus on subproteomes, including the low-molecular-weight proteome, carrier-bound proteome and N-linked glycoproteome. The two approaches differ in their aims, throughput and sensitivity. We discuss recent progress and challenges in the analysis of plasma/serum and proximal fluids using these strategies and highlight the potential of liquid chromatography-MS-based proteomics of cancer cell and tumor secretomes for the discovery of candidate blood-based biomarkers. Strategies for candidate validation are also described.

Protein mass spectra data analysis for clinical biomarker discovery: a global review

The identification of new diagnostic or prognostic biomarkers is one of the main aims of clinical cancer research. In recent years there has been a growing interest in using high throughput technologies for the detection of such biomarkers. In particular, mass spectrometry appears as an exciting tool with great potential. However, to extract any benefit from the massive potential of clinical proteomic studies, appropriate methods, improvement and validation are required. To better understand the key statistical points involved with such studies, this review presents the main data analysis steps of protein mass spectra data analysis, from the pre-processing of the data to the identification and validation of biomarkers.

Current technological challenges in biomarker discovery and validation

In this review we will give an overview of the issues related to biomarker discovery studies with a focus on liquid chromatography-mass spectrometry (LC-MS) methods. Biomarker discovery is based on a close collaboration between clinicians, analytical scientists and chemometritians/statisticians. It is critical to define the final purpose of a biomarker or biomarker pattern at the onset of the study and to select case and control samples accordingly. This is followed by designing the experiment, starting with the sampling strategy, sample collection, storage and separation protocols, choice and validation of the quantitative profiling platform followed by data processing, statistical analysis and validation workflows. Biomarker candidates that result after statistical validation should be submitted for further validation and, ideally, be connected to the disease mechanism after their identification. Since most discovery studies work with a relatively small number of samples, it is necessary to assess the specificity and sensitivity of a given biomarker-based assay in a larger set of independent samples, preferably analyzed at another clinical center. Targeted analytical methods of higher throughput than the original discovery method are needed at this point and LC-tandem mass spectrometry is gaining acceptance in this field. Throughout this review, we will focus on possible sources of variance and how they can be assessed and reduced in order to avoid false positives and to reduce the number of false negatives in biomarker discovery research.

Mass spectrometry based proteomics profiling as diagnostic tool in oncology: current status and future perspective

Proteomics analysis has been heralded as a novel tool for identifying new and specific biomarkers that may improve diagnosis and monitoring of various disease states. Recent years have brought a number of proteomics profiling technologies. Although proteomics profiling has resulted in the detection of disease-associated differences and modification of proteins, current proteomics technologies display certain limitations that are hampering the introduction of these new technologies into clinical laboratory diagnostics and routine applications. In this review, we summarize current advances in mass spectrometry based biomarker discovery. The promises and challenges of this new technology are discussed with particular emphasis on diagnostic perspectives of mass-spectrometry based proteomics profiling for malignant diseases.

The stability of the circulating human proteome to variations in sample collection and handling procedures measured with an aptamer-based proteomics array

Blood-based protein biomarkers hold great promise to advance medicine with applications that detect and diagnose diseases and aid in their treatment. We are developing such applications with our proteomics technology that combines high-content with low limits of detection. Biomarker discovery relies heavily on archived blood sample collections. Blood is dynamic and changes with different sampling procedures potentially confounding biomarker studies. In order to better understand the effects of sampling procedures on the circulating proteome, we studied three sample collection variables commonly encountered in archived sample sets. These variables included (1) three different sample tube types, PPT plasma, SST serum, and Red Top serum, (2) the time from venipuncture to centrifugation, and (3) the time from centrifugation to freezing. We profiled 498 proteins for each of 240 samples and compared the results by ANOVA. The results found no significant variation in the measurements for most proteins (approximately 99%) when the two sample processing times tested were 2h or less, regardless of sample tube type. Even at the longest timepoints, 20 h, approximately 82% of the proteins, on average for the three collection tube types, showed no significant change. These results are encouraging for proteomic biomarker discovery.

Industrialized MS-based proteomics in the search for circulating biomarkers

Proteomics is the study of the expression, structure and function of proteins under a range of cellular conditions. A rapidly evolving component of this field is clinical proteomics, which focuses on proteins involved in human disease and how they are affected by therapeutic intervention. MS is the main analytical technology for identifying and quantifying proteins whose expression is modulated across the normal to disease continuum. Applying this technology to clinical samples, however, is particularly challenging due to high biological variability in the population, a variety of disease stages, nonuniform response to therapy, multiple concomitant treatments and special requirements for handling samples from clinical trials. Given these challenges, an ‘industrialized’ approach is best suited to clinical biomarker development, with its standard operating procedures, process control and ‘chain of custody’. This review will focus, therefore, on MS-based industrialized proteomics for the discovery and verification of circulating candidate clinical protein biomarkers.

Optimal preparation methods for automated matrix-assisted laser desorption/ionization time-of-flight mass spectrometry profiling of low molecular weight proteins and peptides

Mass spectrometry (MS) profiling of the proteome and peptidome for disease-associated patterns is a new concept in clinical diagnostics. The technique, however, is highly sensitive to external sources of variation leading to potentially unacceptable numbers of false positive and false negative results. Before MS profiling can be confidently implemented in a medical setting, standard experimental methods must be developed that minimize technical variance. Past studies of variance have focused largely on pre-analytical variation (i.e., sample collection, handling, etc.). Here, we examined how factors at the analytical stage including the matrix and solid-phase extraction influence MS profiling. Firstly, a standard peptide/protein sample was measured automatically by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MS across five consecutive days using two different preparation methods, dried droplet and sample/matrix, of four types of matrix: alpha-cyano-4-hydroxycinnamic acid (HCCA), sinapinic acid (SA), 2,5-dihydroxybenzoic acid (DHB) and 2,5-dihydroxyacetophenone (DHAP). The results indicated that the matrix preparation greatly influenced a number of key parameters of the spectra including repeatability (within-day variability), reproducibility (inter-day variability), resolution, signal strength, background intensity and detectability. Secondly, an investigation into the variance associated with C8 magnetic bead extraction of the standard sample prior to automated MS profiling demonstrated that the process did not adversely affect these same parameters. In fact, the spectra were generally more robust following extraction. Thirdly, the best performing matrix preparations were evaluated using C8 magnetic bead extracted human plasma. We conclude that the DHAP prepared according to the dried-droplet method is the most appropriate matrix to use when performing automated MS profiling.

Pre-analytical factors in clinical proteomics investigations: impact of ex vivo protein modifications for multiple sclerosis biomarker discovery

Serum proteome investigations have raised an incredible interest in the research of novel molecular biomarker, nevertheless few of the proposed evidences have been translated to the clinical practice. One of the limiting factors has been the lack of generally accepted guidelines for clinical proteomics studies and the lack of a robust analytical and pre-analytical ground for the proposed classification models. Pre-analytical issues may results in a deep impact for biomarker discovery campaign. In this study we present a systematic evaluation of sample storage and sampling conditions for clinical proteomics investigations. We have developed and validated a linear MALDI-TOF-MS protein profiling method to explore the low protein molecular weight region (5-20 kDa) of serum samples. Data normalization and processing was performed using optimise peak detection routine (LIMPIC) able to describe each group under investigation. Data were acquired either from healthy volunteers and from multiple sclerosis patients in order to highlight ex vivo protein profile alteration related to different physio-pathological conditions. Our data showed critical conditions for serum protein profiles depending on storage times and temperatures: 23 degrees C, 4 degrees C, -20 degrees C and -80 degrees C. We demonstrated that upon a -20 degrees C short term storage, characteristic degradation profiles are associated with different clinical groups. Protein signals were further identified after preparative HPLC separation by peptide sequencing on a nanoLC-Q-TOF TANDEM mass spectrometer. Apolipoprotein A-IV and complement C3 protein fragments, transthyretin and the oxidized isoforms in different apolipoprotein species represent the major molecular features of such a degradation pattern.

Using the protein chip interface with quadrupole time-of-flight mass spectrometry to directly identify peaks in SELDI profiles--initial evaluation using low molecular weight serum peaks

Mass spectrometric profiling, particularly in the form of SELDI, has been used in many studies, particularly in attempts to generate diagnostic serum profiles. Several studies have generated promising results but one of the limitations is the inability to identify easily potential discriminatory peaks. This may enable specific assays to be developed and increased biological insight. We describe the first systematic technical evaluation of the ProteinChip interface coupled to a tandem mass spectrometer which allows direct sequencing of peptides <6000 Da, and describe the direct sequence identification of 21 peaks commonly observed in serum samples. Additionally we describe for the first time the use of on-chip acetylation to assist in the validation of sequence identification.

Progressive degradation of serum samples limits proteomic biomarker discovery

Preanalytical variables play a key role in discovery of biomarkers. Although the effect of several preanalytical variables on the mass spectral profiles has been studied extensively, little is known about long-term storage of serum samples. This is important because samples used in case-control or epidemiological studies are usually stored for a long time before analysis. Here we evaluated long-term storage effects on mass spectral peak patterns of serum peptides extracted using weak cation exchange magnetic beads. For this, 20 serum samples stored at -80 degrees C were divided equally into two groups based on their storage time. We found that intensities of 26 mass spectral peaks significantly varied between these two groups. Intensities of these peaks significantly correlated with storage time. Genetic algorithm-based models generated using these 26 peaks could classify 63 additional samples into these two groups with 100% and 96% accuracy, respectively. We also show that storing samples for 10 months at -80 and -20 degrees C results in the appearance/disappearance or intensity variation of peaks, some of which were previously reported as disease biomarkers.

Evaluation of the variation in sample preparation for comparative proteomics using stable isotope labeling by amino acids in cell culture

In comparative proteomic studies, it is important to know the variability associated with sample preparation. In this study, we report the strategy of using SILAC (stable isotope labeling by amino acids in cell culture) to evaluate the effect of the variation in sample preparation for quantitative proteomics. Variability can be measured when equal amounts of light and heavy SILAC samples undergo the same sample preparation procedures in parallel, and the two samples are mixed for relative protein quantitation by mass spectrometry. The high quantitative accuracy of SILAC allows for characterization of small variations. First, the reproducibility of immunoprecipitation (IP) and in-gel digestion was evaluated, and the impact of replicate number on quantitative accuracy was characterized. Second, we evaluated the overall variation in a comparative workflow involving three sequential sample preparation steps: IP, SDS-PAGE fractionation, and in-gel digestion. The evaluation of individual sample preparation steps was very valuable for experimental design: the optimal number of replicates for each step could be readily determined and the overall variation of the workflow could be predicted from the variation of the individual steps involved. By using informed experimental design, we demonstrated that the error associated with multiple steps of sample preparation in a comparative experiment can be limited to a reasonably low level.

Proteomic avenues for clinical diagnosis: where are they leading?

New technologies make possible increasingly comprehensive and quantitative assessment of the suite of proteins and peptides and all their modified forms (the proteomes) present in biological samples. These proteomic technologies should facilitate the discovery of new and more efficient protein and peptide biomarkers. However, the discovery rate of new, clinically useful diagnostic markers appears not to have been influenced by the technological advances over the last 5 years. In reality, the opposite, that is, a decreasing trend in the number of new protein biomarkers approved for clinical use, has been observed. The possible reasons for this paradox and the remedies that are going to make the next generation of proteomic biomarker projects more likely to contribute to medical diagnostics are discussed in this editorial.

Optimizing sample handling for urinary proteomics

Interrogation of the urinary proteome for clinically useful biomarkers of disease will require normalization of methods for protein extraction and sample handling. Variations in collection methods and other procedures may introduce significant discrepancies in qualitative and quantitative measurements. Here we demonstrate that the method of protein extraction, length of handling at room temperature, and repetitive freeze-thaw cycles do not seem to alter the urinary proteome at either the protein or peptide level in a manner that degrades information obtainable by mass spectrometry.