Low Abundance Plasma Proteins Research Articles

0192: A proteomic score improves risk stratification in stable chronic heart failure patients

Risk stratification of patients with stable chronic heart failure (CHF) is critical to better identify those who may benefit the most from invasive strategies such as heart transplantation. To improve cardiovascular (CV) death prediction in CHF, we performed a proteomic analysis using high throughput surface enhanced laser desorption ionization – time of fight – mass spectrometry (SELDI-TOF-MS). Plasma samples were pre-treated to access the deep proteome. The proteomic analysis was first performed in a case (CV death within 3 years) /control (survivors at 3 years) study including 198 patients with a left ventricular ejection fraction (LVEF) <45%. A proteomic score was developed in this derivation population using the support vector machine (SVM) method. The score was then validated in an independent cohort of 309 consecutive patients (CV death at 3 years) with CHF. Altogether, 203 ion m/z peaks were detected. Among them, 42 peaks were significantly differentially expressed between cases and controls after Bonferroni correction (P value at 0.00025). Then, the SVM method was applied to develop a proteomic score. In the derivation population, the score level was higher in cases as compared to controls: 0.7 vs. 0.25 (P=5.10 -29 ). The ROC curve showed an AUC of 0.87 to predict CV mortality. In the validation population, the score level was still higher in patients who experienced a CV death as compared to survivors: 0.53 vs. 0.39 (P=0.0002). The ROC curve showed an AUC of 0.68. After adjustment on confounders (NYHA class, LVEF, BNP, creatinine, Peak VO 2 ), the score was still significantly associated with CV death (HR=15.1, P=0.007) and it allowed a significant improvement of CHF patient reclassification. The net reclassification index (NRI) and the integrated discrimination improvement (IDI) reach both significant p values. Proteomic analysis of low abundance plasma proteins is highly promising to improve CV death risk prediction in CHF.

Practical immunoaffinity-enrichment LC-MS for measuring protein kinetics of low-abundance proteins.

For a more complete understanding of pharmacodynamic, metabolic, and pathophysiologic effects, protein kinetics, such as production rate and fractional catabolic rate, can offer substantially more information than protein concentration alone. Kinetic experiments with stable isotope tracers typically require laborious sample preparation and are most often used for studying abundant proteins. Here we describe a practical methodology for measuring isotope enrichment into low-abundance proteins that uses an automated procedure and immunoaffinity enrichment (IA) with LC-MS. Low-abundance plasma proteins cholesteryl ester transfer protein (CETP) and proprotein convertase subtilisin/kexin type 9 (PCSK9) were studied as examples. Human participants (n = 39) were infused with [(2)H(3)]leucine, and blood samples were collected at multiple time points. Sample preparation and analysis were automated and multiplexed to increase throughput. Proteins were concentrated from plasma by use of IA and digested with trypsin to yield proteotypic peptides that were analyzed by microflow chromatography-mass spectrometry to measure isotope enrichment. The IA procedure was optimized to provide the greatest signal intensity. Use of a gel-free method increased throughput while increasing the signal. The intra- and interassay CVs were <15% at all isotope enrichment levels studied. More than 1400 samples were analyzed in <3 weeks without the need for instrument stoppages or user interventions. The use of automated gel-free methods to multiplex the measurement of isotope enrichment was applied to the low-abundance proteins CETP and PCSK9.

A Label-free Selected Reaction Monitoring Workflow Identifies a Subset of Pregnancy Specific Glycoproteins as Potential Predictive Markers of Early-onset Pre-eclampsia

Pre-eclampsia (PE) is a serious complication of pregnancy with potentially life threatening consequences for both mother and baby. Presently there is no test with the required performance to predict which healthy first-time mothers will go on to develop PE. The high specificity, sensitivity, and multiplexed nature of selected reaction monitoring holds great potential as a tool for the verification and validation of putative candidate biomarkersfor disease states. Realization of this potential involves establishing a high throughput, cost effective, reproducible sample preparation workflow. We have developed a semi-automated HPLC-based sample preparation workflow before a label-free selected reaction monitoring approach. This workflow has been applied to the search for novel predictive biomarkers for PE. To discover novel candidate biomarkers for PE, we used isobaric tagging to identify several potential biomarker proteins in plasma obtained at 15 weeks gestation from nulliparous women who later developed PE compared with pregnant women who remained healthy. Such a study generates a number of "candidate" biomarkers that require further testing in larger patient cohorts. As proof-of-principle, two of these proteins were taken forward for verification in a 100 women (58 PE, 42 controls) using label-free SRM. We obtained reproducible protein quantitation across the 100 samples and demonstrated significant changes in protein levels, even with as little as 20% change in protein concentration. The SRM data correlated with a commercial ELISA, suggesting that this is a robust workflow suitable for rapid, affordable, label-free verification of which candidate biomarkers should be taken forward for thorough investigation. A subset of pregnancy-specific glycoproteins (PSGs) had value as novel predictive markers for PE.

Analysis of the Plasma Proteome in COPD: Novel Low Abundance Proteins Reflect the Severity of Lung Remodeling

The search for COPD biomarkers has largely employed a targeted approach that focuses on plasma proteins involved in the systemic inflammatory response and in lung injury and repair. This proof of concept study was designed to test the idea that an open, unbiased, in-depth proteomics approach could identify novel, low abundance plasma proteins i.e., ng/mL concentration, which could serve as potential biomarkers. Differentially expressed proteins were identified in a discovery group with severe COPD (FEV1 <45% predicted; n = 10). Subjects with normal lung function matched for age, sex, ethnicity and smoking history served as controls (n = 10). Pooled plasma from each group was exhaustively immunodepleted of abundant proteins, d separated by 1-D gel electrophoresis and extensively fractionated prior to LC-tandem mass spectroscopy (GeLC-MS). Thirty one differentially expressed proteins were identified in the discovery group including markers of lung defense against oxidant stress, alveolar macrophage activation, and lung tissue injury and repair. Four of the 31 proteins (i.e., GRP78, soluble CD163, IL1AP and MSPT9) were measured in a separate verification group of 80 subjects with varying COPD severity by immunoassay. All 4 were significantly altered in COPD and 2 (GRP78 and soluble CD163) correlated with both FEV1 and the extent of emphysema. In-depth, plasma proteomic analysis identified a group of novel, differentially expressed, low abundance proteins that reflect known pathogenic mechanisms and the severity of lung remodeling in COPD. These proteins may also prove useful as COPD biomarkers.

Identification of Fatigue Biomarkers in Treated and Treatment-Naive HIV Patients

Objective assessment in human immunodeficiency virus (HIV)-related fatigue has been elusive because the biological mechanisms are not well characterized. We tried to identify low-abundance plasma proteins that correlate with self-reported fatigue intensity in people living with HIV. We used plasma samples from 32 patients with HIV with varying degrees of fatigue who were either treated with nucleoside reverse transcriptase inhibitors or treatment naïve. The plasma samples were enriched for low-abundance proteins and trypsinized. The peptides were analyzed using shotgun proteomics. Five targets correlated with severity of fatigue: apolipoprotein A-1 (ApoA1), apolipoprotein B (ApoB), histine-rich glycoprotein, alpha-1 B glycoprotein, and orosomucoid 2. These targets were selected based on total abundance and spectral count differences, and ApoA1 and ApoB were analyzed via Western blots to verify the mass spectrometry results. ApoA1 levels were higher in untreated patients, while ApoB results suggested a possible positive trend in treated patients. Further analysis is needed to identify additional low-abundance proteins and confirm already-identified proteins as potential fatigue biomarkers.

An Insight into the Changes in Human Plasma Proteome on Adaptation to Hypobaric Hypoxia

Adaptation to hypobaric hypoxia is required by animals and human in several physiological and pathological situations. Hypobaric hypoxia is a pathophysiological condition triggering redox status disturbances of cell organization leading, via oxidative stress, to proteins, lipids, and DNA damage. Identifying the molecular variables playing key roles in this process would be of paramount importance to shed light on the mechanisms known to counteract the negative effects of oxygen lack. To obtain a molecular signature, changes in the plasma proteome were studied by using proteomic approach. To enrich the low-abundance proteins in human plasma, two highly abundant proteins, albumin and IgG, were first removed. By comparing the plasma proteins of high altitude natives with those of a normal control group, several proteins with a significant alteration were found. The up-regulated proteins were identified as vitamin D-binding protein, hemopexin, alpha-1–antitrypsin, haptoglobin β-chain, apolipoprotein A1, transthyretin and hemoglobin beta chain. The down-regulated proteins were transferrin, complement C3, serum amyloid, complement component 4A and plasma retinol binding protein. Among these proteins, the alterations of transthyretin and transferrin were further confirmed by ELISA and Western blotting analysis. Since all the up- and down- regulated proteins identified above are well-known inflammation inhibitors and play a positive anti-inflammatory role, these results show that there is some adaptive mechanism that sustains the inflammation balance in high altitude natives exposed to hypobaric hypoxia.

Application of Selected Reaction Monitoring for Multiplex Quantification of Clinically Validated Biomarkers in Formalin-Fixed, Paraffin-Embedded Tumor Tissue

One of the critical gaps in the clinical diagnostic space is the lack of quantitative proteomic methods for use on formalin-fixed, paraffin-embedded (FFPE) tissue. Herein, we describe the development of a quantitative, multiplexed, mass spectrometry-based selected reaction monitoring (SRM) assay for four therapeutically important targets: epidermal growth factor receptor, human EGF receptor (HER)-2, HER3, and insulin-like growth factor-1 receptor. These assays were developed using the Liquid Tissue-SRM technology platform, in which FFPE tumor tissues were microdissected, completely solubilized, and then subjected to multiplexed quantitation by SRM mass spectrometry. The assays were preclinically validated by comparing Liquid Tissue-SRM quantitation of FFPE cell lines with enzyme-linked immunosorbent assay/electrochemiluminescence quantitation of fresh cells (R(2) > 0.95). Clinical performance was assessed on two cohorts of breast cancer tissue: one cohort of 10 samples with a wide range of HER2 expression and a second cohort of 19 HER2 IHC 3+ tissues. These clinical data demonstrate the feasibility of quantitative, multiplexed clinical analysis of proteomic markers in FFPE tissue. Our findings represent a significant advancement in cancer tissue analysis because multiplexed, quantitative analysis of protein targets in FFPE tumor tissue can be tailored to specific oncological indications to provide the following: i) complementary support for anatomical pathological diagnoses, ii) patient stratification to optimize treatment outcomes and identify drug resistance, and iii) support for the clinical development of novel therapies.

Low abundance plasma proteins in labour

Every year, millions of births worldwide are complicated by prematurity or difficult post-term deliveries, resulting in a high incidence of perinatal mortality and morbidity. Our poor understanding of human parturition is a key reason for our inability to improve the management of preterm and post-term birth. In this study, we used proteomic techniques to look into protein changes in placental blood plasma obtained from women before or after spontaneous or induced labour, with vaginal or caesarean section deliveries. Our aim was to understand the basic mechanisms of human parturition regardless of whether the signals that trigger labour are of maternal and/or fetal origin. We found proteins from 33 genes with significantly altered expression profiles in relation to mode of labour and delivery. Most changes in labour occurred in proteins associated with 'immune and defence responses'. Although the signal transduction and regulation of these pathways varied among modes of delivery, hepatocyte nuclear factor 1 homeobox A emerged as a shared protein in the mechanism of labour. Moreover, several apolipoproteins such as apolipoprotein A-IV and APOE were found to change with labour, and these changes were also confirmed in maternal plasma. This study has identified significant protein changes in placental intervillous plasma with labour and has revealed several pathways related to human parturition.

Unbiased plasma proteomics for novel diagnostic biomarkers in cardiovascular disease: identification of quiescin Q6 as a candidate biomarker of acutely decompensated heart failure

Biochemical marker testing has improved the evaluation and management of patients with cardiovascular diseases over the past decade. Natriuretic peptides (NPs), used in clinical practice to assess cardiac dysfunction, exhibit many limitations, however. We used an unbiased proteomics approach for the discovery of novel diagnostic plasma biomarkers of heart failure (HF). A proteomics pipeline adapted for very low-abundant plasma proteins was applied to clinical samples from patients admitted with acute decompensated HF (ADHF). Quiescin Q6 (QSOX1), a protein involved in the formation of disulfide bridges, emerged as the best performing marker for ADHF (with an area under the receiver operator characteristic curve of 0.86, 95% confidence interval: 0.79-0.92), and novel isoforms of NPs were also identified. Diagnostic performance of QSOX1 for ADHF was confirmed in 267 prospectively collected subjects of whom 76 had ADHF. Combining QSOX1 to B-type NP (BNP) significantly improved diagnostic accuracy for ADHF by particularly improving specificity. Using thoracic aortic constriction in rats, QSOX1 was specifically induced within both left atria and ventricles at the time of HF onset. The novel biomarker QSOX1 accurately identifies ADHF, particularly when combined with BNP. Through both clinical and experimental studies we provide lines of evidence for a link between ADHF and cardiovascular production of QSOX1.

18O-Labeled Proteome Reference as Global Internal Standards for Targeted Quantification by Selected Reaction Monitoring-Mass Spectrometry

Selected reaction monitoring (SRM)-MS is an emerging technology for high throughput targeted protein quantification and verification in biomarker discovery studies; however, the cost associated with the application of stable isotope-labeled synthetic peptides as internal standards can be prohibitive for screening a large number of candidate proteins as often required in the preverification phase of discovery studies. Herein we present a proof of concept study using an (18)O-labeled proteome reference as global internal standards (GIS) for SRM-based relative quantification. The (18)O-labeled proteome reference (or GIS) can be readily prepared and contains a heavy isotope ((18)O)-labeled internal standard for every possible tryptic peptide. Our results showed that the percentage of heavy isotope ((18)O) incorporation applying an improved protocol was >99.5% for most peptides investigated. The accuracy, reproducibility, and linear dynamic range of quantification were further assessed based on known ratios of standard proteins spiked into the labeled mouse plasma reference. Reliable quantification was observed with high reproducibility (i.e. coefficient of variance <10%) for analyte concentrations that were set at 100-fold higher or lower than those of the GIS based on the light ((16)O)/heavy ((18)O) peak area ratios. The utility of (18)O-labeled GIS was further illustrated by accurate relative quantification of 45 major human plasma proteins. Moreover, quantification of the concentrations of C-reactive protein and prostate-specific antigen was illustrated by coupling the GIS with standard additions of purified protein standards. Collectively, our results demonstrated that the use of (18)O-labeled proteome reference as GIS provides a convenient, low cost, and effective strategy for relative quantification of a large number of candidate proteins in biological or clinical samples using SRM.

Low abundance protein enrichment for discovery of plasma protein biomarkers for early detection of breast cancer.

77 Background: Protein biomarkers for breast cancer are desired for early diagnosis, disease prognosis and drug response monitoring. Biomarkers in bodily fluids, such as plasma, allow for non-invasive monitoring and have additional value compared to tissue-based markers. Plasma-based biomarker discovery faces a challenge in that the wide dynamic range of protein concentrations prevents the detection of lower abundance proteins. In this study, we have investigated the use of a novel protein enrichment strategy combined with isobaric label-based LC-MS/MS as well as two experimental designs for the identification of biomarkers of early stage breast cancer. Methods: Plasma from 12 patients with benign breast lesions and 12 with stage I breast cancer were processed using ProteoMiner enrichment followed by on-bead digestion. Two types of standards were investigated: a pooled standard, consisting of equal portions from the 24 plasma digests and a universal standard. The samples were digested, labeled and analyzed using by HPLC-Chip/Q-TOF analysis. Proteins were identified and quantified using Spectrum Mill software. Results: Use of ProteoMiner beads resulted in extraction of sufficient protein for at least 10 technical replicates and cut down preparation time by 80%, as compared to MARS-based immunodepletion. A total of 414 plasma proteins were identified, 89% of which are low abundance plasma proteins and 14 of which were differentially expressed. Expression values normalized using the pooled vs. universal standards were significantly correlated. Conclusions: This study demonstrated use of the ProteoMiner technology for enrichment of low abundance proteins from plasma. Fourteen plasma-based biomarkers of stage I breast cancer were identified with statistical significance. A number of these proteins (e.g., protocadherin FAT2, flightless-1 homolog) have been linked to breast cancer relevant processes, such as cell migration, adhesion, estrogen receptor signaling and proliferation.

Monitoring a Nuclear Factor-κB Signature of Drug Resistance in Multiple Myeloma

The emergence of acquired drug resistance results from multiple compensatory mechanisms acting to prevent cell death. Simultaneous monitoring of proteins involved in drug resistance is a major challenge for both elucidation of the underlying biology and development of candidate biomarkers for assessment of personalized cancer therapy. Here, we have utilized an integrated analytical platform based on SDS-PAGE protein fractionation prior to liquid chromatography coupled to multiple reaction monitoring mass spectrometry, a versatile and powerful tool for targeted quantification of proteins in complex matrices, to evaluate a well-characterized model system of melphalan resistance in multiple myeloma (MM). Quantitative assays were developed to measure protein expression related to signaling events and biological processes relevant to melphalan resistance in multiple myeloma, specifically: nuclear factor-κB subunits, members of the Bcl-2 family of apoptosis-regulating proteins, and Fanconi Anemia DNA repair components. SDS-PAGE protein fractionation prior to liquid chromatography coupled to multiple reaction monitoring methods were developed for quantification of these selected target proteins in amounts of material compatible with direct translation to clinical specimens (i.e. less than 50,000 cells). As proof of principle, both relative and absolute quantification were performed on cell line models of MM to compare protein expression before and after drug treatment in naïve cells and in drug resistant cells; these liquid chromatography-multiple reaction monitoring results are compared with existing literature and Western blots. The initial stage of a systems biology platform for examining drug resistance in MM has been implemented in cell line models and has been translated to MM cells isolated from a patient. The ultimate application of this platform could assist in clinical decision-making for individualized patient treatment. Although these specific assays have been developed to monitor MM, these techniques are expected to have broad applicability in cancer and other types of disease.

Abstract 5116: Low abundance protein enrichment by ProteoMiner coupled to iTRAQ-labeled LC-MS/MS for plasma-based quantitative proteomics

Abstract Background: Protein biomarkers for breast cancer are desired for early diagnosis, disease prognosis and drug response monitoring. Biomarkers in bodily fluids, such as plasma, allow for non-invasive monitoring and thus have additional value compared to tissue-based markers. Plasma-based biomarker discovery faces a challenge in that the wide dynamic range of protein concentrations prevents the detection of lower abundance proteins. Additionally, large sample sizes are needed for sufficient statistical power. In this setting, experimental design and normalization are important considerations. In this study, we have investigated the use of a novel protein enrichment strategy combined with isobaric label-based LC-MS/MS as well as two experimental designs for the identification of biomarkers of early stage breast cancer. Methods: Plasma from 12 patients with benign breast lesions and 12 with stage I breast cancer were processed using ProteoMiner enrichment followed by on-bead digestion. Two types of standards were investigated: a pooled standard, consisting of equal portions of the 24 plasma digests and a universal standard, consisting of 12 independent benign, stage I, stage II, and stage III breast cancer plasma samples. These designs have opposing strengths and weaknesses: pooled standards minimize variation but fix the sample size; universal standards allow for addition of new samples but introduce additional variation. The study required 4 iTRAQ-8plex sets which were subjected to 2-D LC separation followed by HPLC-Chip/Q-TOF analysis. Proteins were identified and quantified using Spectrum Mill software. Algorithms were developed for normalization, missing data imputation, protein grouping and identification of differential expression. Results: Use of ProteoMiner beads resulted in extraction of sufficient protein for at least 10 technical replicates and cut down preparation time by 80%, as compared to MARS-based immunodepletion. A total of 416 plasma proteins were identified, 96% of which are low abundance plasma proteins and 14 of which were differentially expressed. Expression values normalized using the pooled vs. universal standards were significantly correlated; however the use of the universal standard design yields a larger variation in expression values. Conclusion: This study demonstrated use of the ProteoMiner technology for enrichment of low abundance proteins from plasma. Fourteen plasma-based biomarkers of stage I breast cancer were identified with statistical significance. A number of these proteins (e.g. protocadherin FAT2, flightless-1 homolog) have been linked to breast cancer relevant processes, such as cell migration, adhesion, estrogen receptor signaling and proliferation. Data indicates that the universal standard is an adequate replacement for pooled standards with the caveat that higher variance should be expected. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 5116. doi:10.1158/1538-7445.AM2011-5116

Abstract 5076: Multi-protein tissue and blood plasma protein marker patterns of endometrioid endometrial and squamous cervical cancers

Abstract Endometrial cancer is the second spread cancer of women in Western Europe and Nothern America. There is no screening developed for early detection of endometrial cancer, its major types and precursor lesions. We used proteomics-based methods including two-dimensional gel electrophoresis of tissue and blood plasma proteins, analyses of gels by SameSpot (Nonlinear) software and MALDI-TOF MS-assisted identification of proteins. Measurement of DNA ploidy was used for the selection of genomic subtypes of endometrial cancer. Expression of identified proteins was evaluated in endometrial cancers, atypical and simple hyperplasia and normal endometrium using immunohistochemistry. Tumor tissue biopsies of endometrial cancer, normal endometrium, squamous cervical cancer, and squamous cervical epithelium as well as low-abundant blood plasma proteins of the same patients were used for two-dimensional gel electrophoresis. We also analyzed published data on chromosomal changes in early and prognostically unfavorable endometrial cancer and corresponded proteins identified by us to the corresponding coding genes. One hundred and thirty differentially expressed tissue proteins were identified as being related to malignant transformation towards endometrial and cervical cancers. Among them is a group of proteins that specifically differentiate genomically stable and unstable endometrial cancers. Many similarities between the protein expression were found for genomically unstable endometrial cancer and squamous cervical cancer which in most cases are genomically unstable. Moreover, inclusion of squamous cervical cancer cases made it possible to select proteins that are specific for endometrial cancer and proteins which characterize non-malignant tissues. Using available data on chromosomal changes in endometrial cancer we have selected proteins that are markers of prognostically unfavourable endometrial cancer and that change their expression already in atypical hyperplasia of the endometrium. By analysis of low-abundant blood plasma proteins we have identified 18 marker proteins that differentiate endometrial cancer from cervical cancer. In conclusion, proteins differentially expressed in tissue of endometrial cancer include patterns that are typical for genomically stable and unstable subtypes and changes in their expression are detectable already in atypical hyperplasia of the endometrium. Endometrial and cervical cancers are characterized by differential blood plasma protein expression patterns. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 5076. doi:10.1158/1538-7445.AM2011-5076

Increased Selectivity, Analytical Precision, and Throughput in Targeted Proteomics

Proteomics is gradually complementing large shotgun qualitative studies with hypothesis-driven quantitative experiments. Targeted analyses performed on triple quadrupole instruments in selected reaction monitoring mode are characterized by a high degree of selectivity and low limit of detection; however, the concurrent analysis of multiple analytes occurs at the expense of sensitivity because of reduced dwell time and/or selectivity due to limitation to a few transitions. A new data acquisition paradigm is presented in which selected reaction monitoring is performed in two ways to simultaneously quantify and confirm the identity of the targeted peptides. A first set of primary transitions is continuously monitored during a predetermined elution time window to precisely quantify each peptide. In addition, a set of six to eight transitions is acquired in a data-dependent event, triggered when all the primary transitions exceed a preset threshold. These additional transitions are used to generate composite tandem mass spectra to formally confirm the identity of the targeted peptides. This technique was applied to analyze the tryptic digest of a yeast lysate to demonstrate the performance of the technique. We showed a limit of detection down to tens of attomoles injected and a throughput exceeding 6000 transitions in one 60-min experiment. The technique was integrated into a linear work flow, including experimental design, data acquisition, and data evaluation, enabling large scale proteomic studies.

Strategy for purification and mass spectrometry identification of SELDI peaks corresponding to low-abundance plasma and serum proteins

Analysis by SELDI-TOF-MS of low abundance proteins makes it possible to select peaks as candidate biomarkers. Our aim was to define a purification strategy to optimise identification by MS of peaks detected by SELDI-TOF-MS from plasma or serum, regardless of any treatment by a combinatorial peptide ligand library (CPLL). We describe 2 principal steps in purification. First, choosing the appropriate sample containing the selected peak requires setting up a databank that records all the m/z peaks detected from samples in different conditions. Second, the specific purification process must be chosen: separation was achieved with either chromatographic columns or liquid-phase isoelectric focusing, both combined when appropriate with reverse-phase chromatography. After purification, peaks were separated by gel electrophoresis and the candidate proteins were analyzed by nano-liquid-chromatography-MS/MS. We chose 4m/z peaks (9400, 13,571, 13,800 and 15,557) selected for their differential expression between two conditions, as examples to explain the different strategies of purification, and we successfully identified 3 of them. Despite some limitations, our strategy to purify and identify peaks selected from SELDI-TOF-MS analysis was effective.

On the Development of Plasma Protein Biomarkers

The development of plasma biomarkers has proven to be more challenging than initially anticipated. Many studies have reported lists of candidate proteins rather than validated candidate markers with an assigned performance to a specific clinical objective. Biomarker research necessitates a clear rational framework with requirements on a multitude of levels. On the technological front, the platform needs to be effective to detect low abundant plasma proteins and be able to measure them in a high throughput manner over a large amount of samples reproducibly. At a conceptual level, the choice of the technological platform and available samples should be part of an overall clinical study design that depends on a joint effort between basic and clinical research. Solutions to these needs are likely to facilitate more feasible studies. Targeted proteomic workflows based on SRM mass spectrometry show the potential of fast verification of biomarker candidates in plasma and thereby closing the gap between discovery and validation in the biomarker development pipeline. Biological samples need to be carefully chosen based on well-established guidelines either for candidate discovery in the form of disease models with optimal fidelity to human disease or for candidate evaluation as well-designed and annotated clinical cohort groups. Most importantly, they should be representative of the target population and directly address the investigated clinical question. A conceptual structure of a biomarker study can be provided in the form of several sequential phases, each having clear objectives and predefined goals. Furthermore, guidelines for reporting the outcome of biomarker studies are critical to adequately assess the quality of the research, interpretation and generalization of the results. By being attentive to and applying these considerations, biomarker research should become more efficient and lead to directly translatable biomarker candidates into clinical evaluation.

Selectivity of monolithic supports under overloading conditions and their use for separation of human plasma and isolation of low abundance proteins

Human serum albumin (HSA) and immunoglobulin G (IgG) represent over 75% of all proteins present in human plasma. These two proteins frequently interfere with detection, determination and purification of low abundance proteins that can be potential biomarkers and biomarker candidates for various diseases. Some low abundance plasma proteins such as clotting factors and inhibitors are also important therapeutic agents. In this paper, the characterization of ion-exchange monolithic supports under overloading conditions was performed by use of sample displacement chromatography (SDC). If these supports were used for separation of human plasma, the composition of bound and eluted proteins in both anion- and cation-exchange mode is dependent on column loading. Under overloading conditions, the weakly bound proteins such as HSA in anion-exchange and IgG in cation-exchange mode are displaced by stronger binding proteins, and this phenomenon was not dependent on column size. Consequently, small monolithic columns with a column volume of 100 and 200 μL are ideal supports for high-throughput screening in order to develop new methods for separation of complex mixtures, and for sample preparation in proteomic technology.

Combinatorial peptide ligand library plasma treatment: Advantages for accessing low-abundance proteins

Depletion of major blood proteins is one of the most promising approaches to accessing low-abundance biomarkers. This study compared the use of combinatorial peptide ligand library (CPLL) and albumin and immunoglobulins (IgGs) depletion technology for accessing these low-abundance proteins in plasma using 2-DE in an acidic restricted pH range (4-7). Compared with native plasma, both techniques enlarge the visibility of other proteins than albumin and IgG, but there were marked differences in their composition. An increase of the number of spots was detected compared with native plasma (157 spots) with 427 and 557 spots, respectively, detected with albumin and IgG depletion, and CPLL treatment. We selected 70 spots to be identified by MALDI-TOF related to their absence in the 2-D gels from native or albumin and IgG-depleted plasma. The 42 spots identified corresponded to 24 different proteins, with more than half of the proteins which did not belong to the major plasma proteins. CPLL treatment allowed the accessibility to proteolytic fragments obtained from major plasma proteins. We found a large superiority of the CPLL approach over the albumin and IgG depletion process. These findings show the utility of depleting major blood proteins to be able to access low-abundance proteins and the potential of CPLL to select and identify candidate biomarkers in clinical studies.

Deep plasma proteomic analysis of patients with left ventricular remodeling after a first myocardial infarction

Depletion of major blood proteins is one of the most promising approaches to accessing low abundance biomarkers for proteomics studies. The use of combinatorial peptide ligand library (CPLL) for accessing these low abundance proteins in plasma from patients with a myocardial infarction (MI) was tested to identify candidate protein biomarkers of left ventricular remodeling (LVR). Serial blood samples of MI patients followed for one year (at inclusion, 1 month, 3 months, and 1 year) were treated with CPLL and analyzed by SELDI-TOF-MS. The use of CPLL increased resolution, with loss of most abundant plasma proteins, reproducibly and improved the intensity of low-abundance proteins. Longitudinal information allowed us to reduce by 55% the final number of peaks identified as significantly modulated throughout the 1-year follow-up after MI. Interestingly, 19 of the 26 peaks finally selected were detected only in samples treated from CPLL. The 2777 m/z peak, found in less elevated level in high remodeling patients, was identified as being DAHKSEVAHR FKDLGEENFKALVL, the N-terminal peptide (24-48 aa) generated from albumin by pepsin cleavage. This finding shows the potential of CPLL in accessing low-abundance proteins to select and identify candidate biomarkers in patients with LVR.