Targeted mass spectrometry approaches for protein biomarker verification

Retinol-binding protein 4 as a promising serum biomarker for the diagnosis and prognosis of hepatocellular Carcinoma

BACKGROUND

The prognosis of hepatocellular carcinoma (HCC) is universally poor. Early diagnosis plays a pivotal role in determining the outcome of HCC.

METHODS

We employed a comparative proteomics approach to identify potential biomarkers and validated the application of retinol-binding protein 4 (RBP4) as a biomarker for HCC. RBP4 protein expression was examined in liver tissues from 80 HCC patients through immunohistochemical analysis. Serum RBP4 concentrations were measured by ELISA in a cohort comprising 290 HCC patients, matched 202 chronic hepatitis B patients and 269 healthy controls. Survival data were collected from HCC patients. The diagnostic and prognostic values of RBP4 were evaluated using receiver operating curve (ROC) analysis.

RESULTS

The validation results demonstrated a significant reduction in RBP4 levels in both liver tissues and serum samples from HCC patients. ROC analysis of the diagnostic value of RBP4 revealed an AUC of 0.879 (95 % CI: 0.854∼0.903) for HCC. When combined with AFP, the AUC increased to 0.919, with a sensitivity of 87.9 % and specificity of 80 %. Survival analysis revealed significantly reduced overall survival time in individuals with low-expression of RBP4 compared to those with high-expression. The joint prognostic model exhibited an AUC of 0.926 (95 % CI: 0.888∼0.964), which was significantly higher than that of AFP alone (AUC=0.809; P <0.0001).

CONCLUSIONS

RBP4 shows a great potential as a biomarker with appreciable diagnostic value, complementing the AFP in HCC diagnosis. Additionally, it holds promise as a prognostic biomarker that, when integrated into a combined prognostic model, could greatly improve HCC prognosis efficiency.

MRMPro: a web-based tool to improve the speed of manual calibration for multiple reaction monitoring data analysis by mass spectrometry

BACKGROUND

As a gold-standard quantitative technique based on mass spectrometry, multiple reaction monitoring (MRM) has been widely used in proteomics and metabolomics. In the analysis of MRM data, as no peak picking algorithm can achieve perfect accuracy, manual inspection is necessary to correct the errors. In large cohort analysis scenarios, the time required for manual inspection is often considerable. Apart from the commercial software that comes with mass spectrometers, the open-source and free software Skyline is the most popular software for quantitative omics. However, this software is not optimized for manual inspection of hundreds of samples, the interactive experience also needs to be improved.

RESULTS

Here we introduce MRMPro, a web-based MRM data analysis platform for efficient manual inspection. MRMPro supports data analysis of MRM and schedule MRM data acquired by mass spectrometers of mainstream vendors. With the goal of improving the speed of manual inspection, we implemented a collaborative review system based on cloud architecture, allowing multiple users to review through browsers. To reduce bandwidth usage and improve data retrieval speed, we proposed a MRM data compression algorithm, which reduced data volume by more than 60% and 80% respectively compared to vendor and mzML format. To improve the efficiency of manual inspection, we proposed a retention time drift estimation algorithm based on similarity of chromatograms. The estimated retention time drifts were then used for peak alignment and automatic EIC grouping. Compared with Skyline, MRMPro has higher quantification accuracy and better manual inspection support.

CONCLUSIONS

In this study, we proposed MRMPro to improve the usability of manual calibration for MRM data analysis. MRMPro is free for non-commercial use. Researchers can access MRMPro through http://mrmpro.csibio.com/ . All major mass spectrometry formats (wiff, raw, mzML, etc.) can be analyzed on the platform. The final identification results can be exported to a common.xlsx format for subsequent analysis.

Next-generation proteomics technologies in Alzheimer's disease: from clinical research to routine diagnostics

INTRODUCTION

Clinical proteomics studies of Alzheimer's disease (AD) research aim to identify biomarkers useful for clinical research, diagnostics, and improve our understanding of the pathological processes involved in the disease. The rapidly increasing performance of proteomics technologies is likely to have great impact on AD research.

AREAS COVERED

We review recent proteomics approaches that have advanced the field of clinical AD research. Specifically, we discuss the application of targeted mass spectrometry (MS), labeling-based and label-free MS-based as well as affinity-based proteomics to AD biomarker development, underpinning their importance with the latest impactful clinical studies. We evaluate how proteomics technologies have been adapted to meet current challenges. Finally, we discuss the limitations and potential of proteomics techniques and whether their scope might extend beyond current research-based applications.

EXPERT OPINION

To date, proteomics technologies in the AD field have been largely limited to AD biomarker discovery. The recent development of the first successful disease-modifying treatments of AD will further increase the need for blood biomarkers for early, accurate diagnosis, and CSF biomarkers that reflect specific pathological processes. Proteomics has the potential to meet these requirements and to progress into clinical routine practice, provided that current limitations are overcome.

Simultaneous Quantification of Apolipoprotein C-III O-Glycoforms by Protein-MRM

Apolipoprotein C-III (APOC-III) regulates triglyceride levels, associated with a risk of cardiovascular disease. One gene generates several proteoforms, each with a different molecular mass and a unique function. Unlike peptide multiple reaction monitoring (MRM), protein-MRM without digestion is required to analyze clinically relevant individual proteoforms. We developed a protein-MRM method without digestion to individually quantify APOC-III proteoforms in human serum. We optimized the protein-MRM method following 60% acetonitrile extraction with C18 filtration. Bovine serum and myoglobin served as supporting cushions and the internal standard during sample preparation, respectively. Furthermore, we evaluated the LOD, lower limit of quantification, linearity, accuracy, and precision. Good correlation compared with turbidimetric immunoassay (TIA) and peptide-MRM was observed using 30 clinical sera. Individual APOC-III O-glycoforms were identified by top-down proteomics and simultaneously quantified using the protein-MRM method. The sum abundance of APOC-III proteoforms was significantly correlated with TIA and peptide-MRM. Our protein-MRM method provides an affordable and rapid quantification of potential disease-specific proteoforms. Precise quantification of each proteoform allows investigators to identify novel biological roles potentially related to cardiovascular disease or novel biomarkers. We expect our protein-oriented method to be more clinically useful than antibody-based immunoassays and peptide-oriented MRM analysis, especially for quantification of a biomarker proteoform with certain post-translational modifications.

Mass spectrometry based biomarkers for early detection of HCC using a glycoproteomic approach

Hepatocellular carcinoma (HCC) is the fourth most common cause of cancer-related mortality worldwide and 80%-90% of HCC develops in patients that have underlying cirrhosis. Better methods of surveillance are needed to increase early detection of HCC and the proportion of patients that can be offered curative therapies. Recent work in novel mass spec-based methods for glycomic and glycopeptide analysis for discovery and confirmation of markers for early detection of HCC versus cirrhosis is reviewed in this chapter. Results from recent work in these fields by several groups and the progress made in developing markers of early HCC which can outperform the current serum-based markers are described and discussed. Also, recent developments in isoform analysis of glycans and glycopeptides and in various mass spec fragmentation methods will be described and discussed.

A comprehensive review on molecular mechanism of defective dry-cured ham with excessive pastiness, adhesiveness, and bitterness by proteomics insights

Excessive bitterness, pastiness, and adhesiveness are the main organoleptic and textural defects of dry-cured ham, which often cause a lot of financial losses to manufacturers and seriously damage the quality of the product. These sensory and textural defects are related to the protein degradation of dry-cured ham. Proteomics shows great potential to improve our understanding of the molecular mechanism of sensory and textural defects and identify biomarkers for monitoring their quality traits. This review presents some of the major achievements and considerations in organoleptic and textural defects of dry-cured ham by proteomics analysis in the recent decades and gives an overview about how to correct sensory and textural defects of dry-cured ham. Proteomics reveals that muscle proteins derived from myofibril and cytoskeleton and involved in metabolic enzymes and oxygen transport have been identified as potential biomarkers in defective dry-cured ham. Relatively high residual activities of cathepsin B and L are responsible for the excessive degradation of these protein biomarkers in defective dry-cured ham. Ultrasound-assisted mild thermal or high-pressure treatment shows a good correction for the organoleptic and textural defects of dry-cured ham by changing microstructure and conformation of muscle proteins by accelerating degradation of proteins and polypeptides into free amino acids.

Mass Spectrometry Techniques: Principles and Practices for Quantitative Proteomics

In the current omics-age of research, major developments have been made in technologies that attempt to survey the entire repertoire of genes, transcripts, proteins, and metabolites present within a cell. While genomics has led to a dramatic increase in our understanding of such things as disease morphology and how organisms respond to medications, it is critical to obtain information at the proteome level since proteins carry out most of the functions within the cell. The primary tool for obtaining proteome-wide information on proteins within the cell is mass spectrometry (MS). While it has historically been associated with the protein identification, developments over the past couple of decades have made MS a robust technology for protein quantitation as well. Identifying quantitative changes in proteomes is complicated by its dynamic nature and the inability of any technique to guarantee complete coverage of every protein within a proteome sample. Fortunately, the combined development of sample preparation and MS methods have made it capable of quantitatively comparing many thousands of proteins obtained from cells and organisms.

Biofilm formation and extracellular microvesicles-The way of foodborne pathogens toward resistance

Almost all known foodborne pathogens are able to form biofilms as one of the strategies for survival under harsh living conditions, to ward off the inhibition and the disinfection during food production, transport and storage, as well as during cleaning and sanitation of corresponding facilities. Biofilms are communities where microbial cells live under constant intracellular interaction and communication. Members of the biofilm community are embedded into extracellular matrix that contains polysaccharides, DNA, lipids, proteins, and small molecules that protect microorganisms and enable their intercellular communication under stress conditions. Membrane vesicles (MVs) are produced by both Gram positive and Gram negative bacteria. These lipid membrane-enveloped nanoparticles play an important role in biofilm genesis and in communication between different biofilm members. Furthermore, MVs are involved in other important steps of bacterial life like cell wall modeling, cellular division, and intercellular communication. They also carry toxins and virulence factors, as well as nucleic acids and different metabolites, and play a key role in host infections. After entering host cells, MVs can start many pathologic processes and cause serious harm and cell death. Prevention and inhibition of both biofilm formation and shedding of MVs by foodborne pathogens has a very important role in food production, storage, and food safety in general. Better knowledge of biofilm formation and maintaining, as well as the role of microbial vesicles in this process and in the process of host cells' infection is essential for food safety and prevention of both food spoilage and host infection.

Quantitative Proteomics Comparison of Total Expressed Proteomes of Anisakis simplex Sensu Stricto, A. pegreffii, and Their Hybrid Genotype

The total proteomes of Anisakis simplex s.s., A. pegreffii and their hybrid genotype have been compared by quantitative proteomics (iTRAQ approach), which considers the level of expressed proteins. Comparison was made by means of two independent experiments considering four biological replicates of A. simplex and two each for A. pegreffii and hybrid between both species. A total of 1811 and 1976 proteins have been respectively identified in the experiments using public databases. One hundred ninety-six proteins were found significantly differentially expressed, and their relationships with the nematodes' biological replicates were estimated by a multidimensional statistical approach. Results of pairwise Log2 ratio comparisons among them were statistically treated and supported in order to convert them into discrete character states. Principal component analysis (PCA) confirms the validity of the method. This comparison selected thirty seven proteins as discriminant taxonomic biomarkers among A. simplex, A. pegreffii and their hybrid genotype; 19 of these biomarkers, encoded by ten loci, are specific allergens of Anisakis (Ani s7, Ani s8, Ani s12, and Ani s14) and other (Ancylostoma secreted) is a common nematodes venom allergen. The rest of the markers comprise four unknown or non-characterized proteins; five different proteins (leucine) related to innate immunity, four proteolytic proteins (metalloendopeptidases), a lipase, a mitochondrial translocase protein, a neurotransmitter, a thyroxine transporter, and a structural collagen protein. The proposed methodology (proteomics and statistical) solidly characterize a set of proteins that are susceptible to take advantage of the new targeted proteomics.

Proteome Multimarker Panel With Multiple Reaction Monitoring-Mass Spectrometry for Early Detection of Hepatocellular Carcinoma

There is an urgent need for new biomarkers that address the shortcomings of current screening methods which fail to detect a large proportion of cases with hepatocellular carcinoma (HCC) at early stage. To develop a robust, multiple-biomarker panel based on multiple reaction monitoring-mass spectrometry with high performance in detecting early-stage HCC within at-risk populations. In the discovery set, 150 samples were analyzed to identify candidate biomarkers. The resulting list of candidates was tested in the training set (713 samples) to establish a multimarker panel, which was evaluated in the validation set (305 samples). We identified 385 serum HCC biomarker candidates in the discovery set and developed a multimarker panel consisting of 28 peptides that best differentiated HCC from controls. The area under the receiver operating characteristic curve of multimarker panel was significantly higher than alpha-fetoprotein (AFP) in the training (0.976 vs. 0.804; P < 0.001) and validation (0.898 vs. 0.778; P < 0.001) sets. In the validation set, this multimarker panel, compared with AFP, showed significantly greater sensitivity (81.1% vs. 26.8%; P < 0.001) and lower specificity (84.8% vs. 98.8%; P < 0.001) in detecting HCC cases. Combining AFP with the multimarker panel did not significantly improve the area under the receiver operating characteristic curve compared with the panel alone in the training (0.981 vs. 0.976; P = 0.37) and validation set (0.906 vs. 0.898; P = 0.75). Conclusion: The multiple reaction monitoring-mass spectrometry multimarker panel consisting of 28 peptides discriminates HCC cases from at-risk controls with high performance and may have potential for clinical application in HCC surveillance.

Oncoproteomic and gene expression analyses identify prognostic biomarkers for second primary malignancy in patients with head and neck squamous cell carcinoma

Patients with head and neck squamous cell carcinoma are at increased risk of developing a second primary malignancy, which is associated with poor prognosis and early death. To help improve clinical outcome, we aimed to identify biomarkers for second primary malignancy risk prediction using the routinely obtained formalin-fixed paraffin-embedded tissues of the index head and neck cancer. Liquid chromatography-tandem mass spectrometry was initially performed for candidate biomarker discovery in 16 pairs of primary cancer tissues and their matched normal mucosal epithelia from head and neck squamous cell carcinoma patients with or without second primary malignancy. The 32 candidate proteins differentially expressed between head and neck cancers with and without second primary malignancy were identified. Among these, 30 selected candidates and seven more from literature review were further studied using NanoString nCounter gene expression assay in an independent cohort of 49 head and neck cancer patients. Focusing on the p16-negative cases, we showed that a multivariate logistic regression model comprising the expression levels of ITPR3, KMT2D, EMILIN1, and the patient's age can accurately predict second primary malignancy occurrence with 88% sensitivity and 75% specificity. Furthermore, using Cox proportional hazards regression analysis and survival analysis, high expression levels of ITPR3 and DSG3 were found to be significantly associated with shorter time to second primary malignancy development (log-rank test P = 0.017). In summary, we identified a set of genes whose expressions may serve as the prognostic biomarkers for second primary malignancy occurrence in head and neck squamous cell carcinomas. In combination with the histopathologic examination of index tumor, these biomarkers can be used to guide the optimum frequency of second primary malignancy surveillance, which may lead to early diagnosis and better survival outcome.

Mass spectrometry: A platform for biomarker discovery and validation for Alzheimer's and Parkinson's diseases

Accurate, reliable, and objective biomarkers for Alzheimer's disease (AD), Parkinson's disease (PD), and related age-associated neurodegenerative disorders are urgently needed to assist in both diagnosis, particularly at early stages, and monitoring of disease progression. Technological advancements in protein detection platforms over the last few decades have resulted in a plethora of reported molecular biomarker candidates for both AD and PD; however, very few of these candidates are developed beyond the discovery phase of the biomarker development pipeline, a reflection of the current bottleneck within the field. In this review, the expanded use of selected reaction monitoring (SRM) targeted mass spectrometry will be discussed in detail as a platform for systematic verification of large panels of protein biomarker candidates prior to costly validation testing. We also advocate for the coupling of discovery-based proteomics with modern targeted MS-based approaches (e.g., SRM) within a single study in future workflows to expedite biomarker development and validation for AD and PD. It is our hope that improving the efficiency within the biomarker development process by use of an SRM pipeline may ultimately hasten the development of biomarkers that both decrease misdiagnosis of AD and PD and ultimately lead to detection at early stages of disease and objective assessment of disease progression. This article is part of the special issue "Proteomics".

Quantitative measurement of selected protein biomarkers of endothelial dysfunction in plasma by micro-liquid chromatography-tandem mass spectrometry based on stable isotope dilution method

The aim of this study was to develop and validate the novel microLC/MS-MRM method for the simultaneous quantification of six proteins: angiopoietin 2 (Angpt-2), soluble form of fms-like tyrosine kinase 1 (sFLT-1), plasminogen activator inhibitor 1 (PAI-1), tissue plasminogen activator (t-PA), endocan (ESM-1), soluble form of E-selectin (sE-sel), and one peptide: adrenomedullin (ADM) in mouse plasma. Two approaches were compared: a stable isotope dilution (SID) method- used as a reference and a modified SID (mSID) procedure. In SID strategy the calibration curves were used, whereas in mSID the ratio between the chromatogram peak area of endogenous tryptic peptides at unknown concentration to chromatogram peak area of exogenous, stable isotope-labelled internal standards (SISs) added to the sample at known concentration was calculated. The microLC/MS-MRM method in the SID approach was linear from 0.250 pmol/mL to 250 pmol/mL for Angpt-2; 5 pmol/mL to 5000 pmol/mL for sFLT-1; 2.5 pmol/mL to 5000 pmol/mL for PAI-1; 0.375 pmol/mL to 250 pmol/mL for t-PA; 0.375 pmol/mL to 187.5 pmol/mL for ESM-1; 2.5 pmol/mL to 5000 pmol/mL for sE-sel and 0.375 pmol/mL to 250 pmol/mL for ADM. LPS-induced changes in plasma assessed based on SID and mSID approaches gave comparable quantitative results and featured LPS-induced dysregulation of endothelial permeability (Angpt-2, sFLT-1), glycocalyx injury (SDC-1) accompanied by a pro-thrombotic response (PAI-1). In addition, we applied microLC/MS-MRM method with mSID strategy to analyze human plasma samples from patients with chronic myeloid leukemia (CML) and obstructive sleep apnoea (OSA) and demonstrated usefulness of the method to characterize endothelial function in humans. In conclusion, the microLC/MS-MRM method with mSID strategy applied for simultaneous quantification of protein biomarkers of endothelial function in plasma represents a novel targeted proteomic platform for the comprehensive evaluation of endothelial function in mice and humans.

Contribution of the plasma and lymph Degradome and Peptidome to the MHC Ligandome

Every biological fluid, blood, interstitial fluid and lymph, urine, saliva, lacrimal fluid, nipple aspirate, and spinal fluid, contains a peptidome-degradome derived from the cellular secretome along with byproducts of the metabolic/catabolic activities of each parenchymal organ. Clement et al. (J Proteomics 78:172-187, 2013), Clement et al. (J Biol Chem 291:5576-5595, 2016), Clement et al. (PLoS One 5:e9863, 2010), Clement et al. (Trends Immunol 32:6-11, 2011), Clement et al. (Front Immunol 4:424, 2013), Geho et al. (Curr Opin Chem Biol 10, 50-55, 2006), Interewicz et al. (Lymphology 37:65‑72, 2004), Leak et al. (Proteomics 4:753‑765, 2004), Popova et al. (PLoS One 9:e110873, 2014), Zhou et al. (Electrophoresis 25:1289‑1298, 2004), D'Alessandro et al. (Shock 42:509‑517, 2014), Dzieciatkowska et al. (Shock 42:485‑498, 2014), Dzieciatkowska et al. (Shock 35:331‑338, 2011), Jordan et al. (J Surg Res 143:130‑135, 2007), Peltz et al. (Surgery 146:347‑357, 2009), Zurawel et al. (Clin Proteomics 8:1, 2011), Ling et al. (Clin Proteomics 6:175‑193, 2010), Sturm et al. (Nat Commun 4:1616, 2013). Over the last decade, qualitative and quantitative analysis of the biological fluids peptidome and degradome have provided a dynamic measurement of tissue homeostasis as well as the tissue response to pathological damage. Proteomic profiling has mapped several of the proteases and resulting degradation by-products derived from cell cycle progression, organ/tissue remodeling and cellular growth, physiological apoptosis, hemostasis, and angiogenesis. Currently, a growing interest lies in the degradome observed during pathological conditions such as cancer, autoimmune diseases, and immune responses to pathogens as a way to exploit biological fluids as liquid biopsies for biomarker discovery Dzieciatkowska et al. (Shock 42:485-498, 2014), Dzieciatkowska et al. (Shock 35:331-338, 2011), Ling et al. (Clin Proteomics 6:175-193, 2010), Ugalde et al. (Methods Mol Biol 622:3-29, 2010), Quesada et al. (Nucleic Acids Res 37:D239‑243, 2009), Cal et al. (Front Biosci 12, 4661-4669, 2007), Shen et al. (PLoS One 5:e13133, 2010a), Antwi et al. (Mol Immunol 46:2931-2937, 2009a), Antwi et al. (J Proteome Res 8:4722‑4731, 2009b), Bedin et al. (J Cell Physiol 231, 915‑925, 2016), Bery et al. (Clin Proteomics 11:13, 2014), Bhalla et al. (Sci Rep 7:1511, 2017), Fan et al. (Diagn Pathol 7:45, 2012a), Fang et al. (Shock 34:291‑298, 2010), Fiedler et al. (Clin Cancer Res 15:3812‑3819, 2009), Fredolini et al. (AAPS J 12:504‑518, 2010), Greening et al. (Enzymes 42:27‑64, 2017), He et al. (PLoS One 8:e63724, 2013), Huang et al. (Int J Gynecol Cancer 28:355‑362, 2018), Hashiguchi et al. (Med Hypotheses 73:760‑763, 2009), Liotta and Petricoin (J Clin Invest 116:26‑30, 2006), Petricoin et al. (Nat Rev Cancer 6:961‑967, 2006), Shen et al. (J Proteome Res 9:2339‑2346, 2010a), Shen et al. (J Proteome Res 5:3154‑3160, 2006), Smith (Clin Proteomics 11:23, 2014), Wang et al. (Oncotarget 8:59376‑59386, 2017), Yang et al. (Clin Exp Med 12:79‑87, 2012a), Yang et al. (J Clin Lab Anal 26:148‑154, 2012b), Yang et al. (Anat Rec (Hoboken) 293:2027‑2033, 2010), Zapico-Muniz et al. (Pancreas 39:1293‑1298, 2010), Villanueva et al. (Mol Cell Proteomics 5:1840‑1852, 2006), Robbins et al. (J Clin Oncol 23:4835‑4837, 2005), Klupczynska et al. (Int J Mol Sci 17:410, 2016). In this review, we focus on the current knowledge of the degradome/peptidome observed in two main biological fluids (plasma and lymph) during physiological and pathological conditions and its importance for immune surveillance.

Recent advances in mass spectrometry-based glycoproteomics

Protein glycosylation plays fundamental roles in many biological processes as one of the most common, and the most complex, posttranslational modification. Alterations in glycosylation profile are now known to be associated with many diseases. As a result, the discovery and detailed characterization of glycoprotein disease biomarkers is a primary interest of biomedical research. Advances in mass spectrometry (MS)-based glycoproteomics and glycomics are increasingly enabling qualitative and quantitative approaches for site-specific structural analysis of protein glycosylation. While the complexity presented by glycan heterogeneity and the wide dynamic range of clinically relevant samples like plasma, serum, cerebrospinal fluid, and tissue make comprehensive analyses of the glycoproteome a challenging task, the ongoing efforts into the development of glycoprotein enrichment, enzymatic digestion, and separation strategies combined with novel quantitative MS methodologies have greatly improved analytical sensitivity, specificity, and throughput. This review summarizes current MS-based glycoproteomics approaches and highlights recent advances in its application to cancer biomarker and neurodegenerative disease research.

Quantification of cardiac troponin I in human plasma by immunoaffinity enrichment and targeted mass spectrometry

Quantification of cardiac troponin I (cTnI), a protein biomarker used for diagnosing myocardial infarction, has been achieved in native patient plasma based on an immunoaffinity enrichment strategy and isotope dilution (ID) liquid chromatography-tandem mass spectrometry (LC-MS/MS) method. The key steps in the workflow involved isolating cTnI from plasma using anti-cTnI antibody coupled to magnetic nanoparticles, followed by an enzymatic digestion with trypsin. Three tryptic peptides from cTnI were monitored and used for quantification by ID-LC-MS/MS via multiple reaction monitoring (MRM). Measurements were performed using a matrix-matched calibration system. NIST SRM 2921 Human Cardiac Troponin Complex acted as the calibrant and a full-length isotopically labeled protein analog of cTnI was used as an internal standard. The method was successfully demonstrated on five patient plasma samples, with cTnI concentrations measuring between 4.86 μg/L and 11.3 μg/L (signifying moderate myocardial infarctions). LC-MS/MS measurement precision was validated by three unique peptides from cTnI and two MRM transitions per peptide. Relative standard deviation (CV) from the five plasma samples was determined to be ≤14.3%. This study has demonstrated that quantification of cTnI in native plasma from myocardial infarction patients can be achieved based on an ID-LC-MS/MS method. The development of an ID-LC-MS/MS method for cTnI in plasma is a first step for future certification of matrix-based reference materials, which may be used to help harmonize discordant cTnI clinical assays. Graphical abstract A schematic of the workflow for measuring cardiac troponin I (cTnI), a low-abundant protein biomarker used for diagnosing myocardial infarction, in human plasma by isotope-dilution LC-MS/MS analysis.

Mass spectrometry to complement standardization of house dust mite and other complex allergenic extracts

In the United States, the Center for Biologics Evaluation and Research of the US Food and Drug Administration regulates biologics used for diagnosis and treatment of allergic diseases. The Code of Federal Regulations 21CFR680.3(e) states that when measured, the potency of an allergenic extract is assessed according to its allergenic activity. As of 2016, 19 allergenic extracts are standardized for potency in the United States. While these standardized extracts constitute a minority of those available, they treat the most prevalent allergies (e.g. grass and ragweed pollens, dust mites, and cat) and those that induce life-threatening anaphylaxis (e.g. Hymenoptera venom). Standardization for potency enhances safety and efficacy of immunotherapy by minimizing the risks of variations in allergen dosing when switching from one lot of manufactured extract to another, and by providing an objective measure of stability of each lot of allergenic extract over time. Allergenic extracts that have multiple immunodominant allergenic proteins are standardized with little or no information about compositional differences among extracts. Here, we propose application of mass spectrometry towards measurement of compositional differences among extracts that may affect the efficacy and safety of allergen immunotherapy. In addition, we discuss of house dust mite allergen extracts as a prototypical complex extract that may be standardized by mass spectrometry.

Development, validation and application of a micro-liquid chromatography-tandem mass spectrometry based method for simultaneous quantification of selected protein biomarkers of endothelial dysfunction in murine plasma

The objective of this study was to develop and validate the method based on micro-liquid chromatography-tandem mass spectrometry (microLC/MS-MRM) for simultaneous determination of adiponectin (ADN), von Willebrand factor (vWF), soluble form of vascular cell adhesion molecule 1 (sVCAM-1), soluble form of intercellular adhesion molecule 1 (sICAM-1) and syndecan-1 (SDC-1) in mouse plasma. The calibration range was established from 2.5pmol/mL to 5000pmol/mL for ADN; 5pmol/mL to 5000pmol/mL for vWF; 0.375pmol/mL to 250pmol/mL for sVCAM-1 and sICAM-1; and 0.25pmol/mL to 250pmol/mL for SDC-1. The method was applied to measure the plasma concentration of selected proteins in mice fed high-fat diet (HFD), and revealed the pro-thrombotic status by increased concentration of vWF (1.31±0.17 nmol/mL (Control) vs 1.98±0.09 nmol/mL (HFD), p <0.05) and the dysregulation of adipose tissue metabolism by decreased concentration of ADN (0.62±0.08 nmol/mL (Control) vs 0.37±0.06 nmol/mL (HFD), p <0.05). In conclusion, the microLC/MS-MRM-based method allows for reliable measurements of selected protein biomarkers of endothelial dysfunction in mouse plasma.

Serum fibronectin distinguishes the early stages of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death, necessitating the discovery of serum markers for its early detection. In this study, a total of 180 serum samples from liver cirrhosis (LC), hepatocellular carcinoma (HCC) patients and paired samples of HCC patients who recovered (Recovery) were analyzed by multiple reaction monitoring-mass spectrometry (MRM-MS) to verify biomarkers. The three-fold crossvalidation was repeated 100 times in the training and test sets to evaluate statistical significance of 124 candidate proteins. This step resulted in 2 proteins that had an area under the receiver operating curve (AUROC) values ≥0.800 in the training (n = 90) and test sets (n = 90). Specifically, fibronectin (FN1, WCGTTQNYDADQK), distinguished HCC from LC patients, with an AUROC value of 0.926 by logistic regression. A FN1 protein was selected for validation in an independent sample (n = 60) using enzyme-linked immunosorbent assay (ELISA). The combination of alpha-fetoprotein (AFP) and FN1 improved the diagnostic performance and differentiated HCC patients with normal AFP levels. Our study has examined candidate markers for the benign disease state and malignancy and has followed up on the consequent recovery. Thus, improvement in the early detection of HCC by a 2-marker panel (AFP + FN1) might benefit HCC patients.

Omics analysis of human bone to identify genes and molecular networks regulating skeletal remodeling in health and disease

The skeleton is a metabolically active organ throughout life where specific bone cell activity and paracrine/endocrine factors regulate its morphogenesis and remodeling. In recent years, an increasing number of reports have used multi-omics technologies to characterize subsets of bone biological molecular networks. The skeleton is affected by primary and secondary disease, lifestyle and many drugs. Therefore, to obtain relevant and reliable data from well characterized patient and control cohorts are vital. Here we provide a brief overview of omics studies performed on human bone, of which our own studies performed on trans-iliacal bone biopsies from postmenopausal women with osteoporosis (OP) and healthy controls are among the first and largest. Most other studies have been performed on smaller groups of patients, undergoing hip replacement for osteoarthritis (OA) or fracture, and without healthy controls. The major findings emerging from the combined studies are: 1. Unstressed and stressed bone show profoundly different gene expression reflecting differences in bone turnover and remodeling and 2. Omics analyses comparing healthy/OP and control/OA cohorts reveal characteristic changes in transcriptomics, epigenomics (DNA methylation), proteomics and metabolomics. These studies, together with genome-wide association studies, in vitro observations and transgenic animal models have identified a number of genes and gene products that act via Wnt and other signaling systems and are highly associated to bone density and fracture. Future challenge is to understand the functional interactions between bone-related molecular networks and their significance in OP and OA pathogenesis, and also how the genomic architecture is affected in health and disease.

Targeted Proteomics for Multiplexed Verification of Markers of Colorectal Tumorigenesis

Targeted proteomic methods can accelerate the verification of multiple tumor marker candidates in large series of patient samples. We utilized the targeted approach known as selected/multiple reaction monitoring (S/MRM) to verify potential protein markers of colorectal adenoma identified by our group in previous transcriptomic and quantitative shotgun proteomic studies of a large cohort of precancerous colorectal lesions. We developed SRM assays to reproducibly detect and quantify 25 (62.5%) of the 40 selected proteins in an independent series of precancerous and cancerous tissue samples (19 adenoma/normal mucosa pairs; 17 adenocarcinoma/normal mucosa pairs). Twenty-three proteins were significantly up-regulated (n = 17) or downregulated (n = 6) in adenomas and/or adenocarcinomas, as compared with normal mucosa (linear fold changes ≥ ±1.3, adjusted p value <0.05). Most changes were observed in both tumor types (up-regulation of ANP32A, ANXA3, SORD, LDHA, LCN2, NCL, S100A11, SERPINB5, CDV3, OLFM4, and REG4; downregulation of ARF6 and PGM5), and a five-protein biomarker signature distinguished neoplastic tissue from normal mucosa with a maximum area under the receiver operating curve greater than 0.83. Other changes were specific for adenomas (PPA1 and PPA2 up-regulation; KCTD12 downregulation) or adenocarcinoma (ANP32B, G6PD, RCN1, and SET up-regulation; downregulated AKR1B1, APEX1, and PPA1). Some changes significantly correlated with a few patient- or tumor-related phenotypes. Twenty-two (96%) of the 23 proteins have a potential to be released from the tumors into the bloodstream, and their detectability in plasma has been previously reported. The proteins identified in this study expand the pool of biomarker candidates that can be used to develop a standardized precolonoscopy blood test for the early detection of colorectal tumors.

Elemental Mass Spectrometry for Absolute Intact Protein Quantification without Protein-Specific Standards: Application to Snake Venomics

Absolute protein quantification methods based on molecular mass spectrometry usually require stable isotope-labeled analogous standards for each target protein or peptide under study, which in turn must be certified using natural standards. In this work, we report a direct and accurate methodology based on capLC-ICP-QQQ and online isotope dilution analysis for the absolute and sensitive quantification of intact proteins. The combination of the postcolumn addition of ³⁴S and a generic S-containing internal standard spiked to the sample provides full compound independent detector response and thus protein quantification without the need for specific standards. Quantitative recoveries, using a chromatographic core-shell C4 column for the various protein species assayed were obtained (96-100%). Thus, the proposed strategy enables the accurate quantification of proteins even if no specific standards are available for them. In addition, to the best of our knowledge, we obtained the lowest detection limits reported in the quantitative analysis of intact proteins by direct measurement of sulfur with ICPMS (358 fmol) and protein (ranging from 7 to 15 fmol depending on the assayed protein). The quantitative results for individual and simple mixtures of model proteins were statistically indistinguishable from the manufacturer's values. Finally, the suitability of the strategy for real sample analysis (including quantitative protein recovery from the column) was illustrated for the individual absolute quantification of the proteins and whole protein content in a venom sample. Parallel capLC-ESI-QTOF analysis was employed to identify the proteins, a prerequisite to translate the mass of quantified S for each chromatographic peak into individual protein mass.

COPD Exacerbation Biomarkers Validated Using Multiple Reaction Monitoring Mass Spectrometry

BACKGROUND

Acute exacerbations of chronic obstructive pulmonary disease (AECOPD) result in considerable morbidity and mortality. However, there are no objective biomarkers to diagnose AECOPD.

METHODS

We used multiple reaction monitoring mass spectrometry to quantify 129 distinct proteins in plasma samples from patients with COPD. This analytical approach was first performed in a biomarker cohort of patients hospitalized with AECOPD (Cohort A, n = 72). Proteins differentially expressed between AECOPD and convalescent states were chosen using a false discovery rate <0.01 and fold change >1.2. Protein selection and classifier building were performed using an elastic net logistic regression model. The performance of the biomarker panel was then tested in two independent AECOPD cohorts (Cohort B, n = 37, and Cohort C, n = 109) using leave-pair-out cross-validation methods.

RESULTS

Five proteins were identified distinguishing AECOPD and convalescent states in Cohort A. Biomarker scores derived from this model were significantly higher during AECOPD than in the convalescent state in the discovery cohort (p<0.001). The receiver operating characteristic cross-validation area under the curve (CV-AUC) statistic was 0.73 in Cohort A, while in the replication cohorts the CV-AUC was 0.77 for Cohort B and 0.79 for Cohort C.

CONCLUSIONS

A panel of five biomarkers shows promise in distinguishing AECOPD from convalescence and may provide the basis for a clinical blood test to diagnose AECOPD. Further validation in larger cohorts is necessary for future clinical translation.

Peptide Biosynthesis with Stable Isotope Labeling from a Cell-free Expression System for Targeted Proteomics with Absolute Quantification

Because of its specificity and sensitivity, targeted proteomics using mass spectrometry for multiple reaction monitoring is a powerful tool to detect and quantify pre-selected peptides from a complex background and facilitates the absolute quantification of peptides using isotope-labeled forms as internal standards. How to generate isotope-labeled peptides remains an urgent challenge for accurately quantitative targeted proteomics on a large scale. Herein, we propose that isotope-labeled peptides fused with a quantitative tag could be synthesized through an expression system in vitro, and the homemade peptides could be enriched by magnetic beads with tag-affinity and globally quantified based on the corresponding multiple reaction monitoring signals provided by the fused tag. An Escherichia coli cell-free protein expression system, protein synthesis using recombinant elements, was adopted for the synthesis of isotope-labeled peptides fused with Strep-tag. Through a series of optimizations, we enabled efficient expression of the labeled peptides such that, after Strep-Tactin affinity enrichment, the peptide yield was acceptable in scale for quantification, and the peptides could be completely digested by trypsin to release the Strep-tag for quantification. Moreover, these recombinant peptides could be employed in the same way as synthetic peptides for multiple reaction monitoring applications and are likely more economical and useful in a laboratory for the scale of targeted proteomics. As an application, we synthesized four isotope-labeled glutathione S-transferase (GST) peptides and added them to mouse sera pre-treated with GST affinity resin as internal standards. A quantitative assay of the synthesized GST peptides confirmed the absolute GST quantification in mouse sera to be measurable and reproducible.

Targeted proteomics: Current status and future perspectives for quantification of food allergens

Allergen levels in fresh and processed foods can vary dynamically. As different sources of foods can cause different types of allergic reactions, the food industry and regulatory bodies urgently require reliable detection and absolute quantitation methods for allergen detection in complex food products to effectively safeguard the food-allergic population. Recent advances of targeted proteomic technologies namely multiple-reaction monitoring (MRM) mass spectrometry (MS) coupled with isotope-labeled internal standard, also known as AQUA peptides offers absolute quantitation of food allergens even at 10ppb level in a multiplex fashion. However, development of successful AQUA-MRM assay relies on a number of pre and post MS criteria. In this review, we briefly describe how allergen levels could potentially change in plant and animal based foods, necessitating the development of a high throughput multiplexed allergen quantification methodology for successful AQUA-MRM assay. We also propose some future strategies that could provide better management of food allergy.

BIOLOGICAL SIGNIFICANCE

Given the rapid increases of food allergenicity, it has become imperative to know absolute allergen levels in foods. This essential information could be the most effective means of protecting humans suffering from allergies. In this review, we emphasize the significance of the absolute quantitation of food allergens using AQUA-MRM approach and discuss the likely critical steps for successful assay development.

Identification of novel serum peptides biomarkers for female breast cancer patients in Western China

This study aimed to identify novel serum peptides biomarkers for female breast cancer (BC) patients. We analyzed the serum proteomic profiling of 247 serum samples from 96 BC patients, 48 additional paired pre- and postoperative BC patients, 39 fibroadenoma patients as benign disease controls, and 64 healthy controls, using magnetic-bead-based separation followed by MALDI-TOF MS. ClinProTools software identified 78 m/z peaks that differed among all analyzed groups, ten peaks were significantly different (P < 0.0001), with Peaks 1-6 upregulated and Peaks 7-10 downregulated in BC. Moreover, three peaks of ten (Peak 1, m/z: 2660.11; Peak 2, m/z: 1061.09; Peak 10, m/z: 1041.25) showed a tendency to return to healthy control values after surgery. And these three peptide biomarkers were identified as FGA605-629, ITIH4 347-356, and APOA2 43-52. Methods used in this study could generate serum peptidome profiles of BC, and provide a new approach to identify potential biomarkers for diagnosis as well as prognosis of this malignancy.

Current application of proteomics in biomarker discovery for inflammatory bowel disease

Recently, the field of proteomics has rapidly expanded in its application towards clinical research with objectives ranging from elucidating disease pathogenesis to discovering clinical biomarkers. As proteins govern and/or reflect underlying cellular processes, the study of proteomics provides an attractive avenue for research as it allows for the rapid identification of protein profiles in a biological sample. Inflammatory bowel disease (IBD) encompasses several heterogeneous and chronic conditions of the gastrointestinal tract. Proteomic technology provides a powerful means of addressing major challenges in IBD today, especially for identifying biomarkers to improve its diagnosis and management. This review will examine the current state of IBD proteomics research and its use in biomarker research. Furthermore, we also discuss the challenges of translating proteomic research into clinically relevant tools. The potential application of this growing field is enormous and is likely to provide significant insights towards improving our future understanding and management of IBD.

Serum protein profiles of patients with lung cancer of different histological types

AIMS

To compare serum protein expression profiles between lung cancer patients and healthy individuals, and to examine whether there are differences in serum protein expression profiles among patients with lung cancers of different histological types and whether the characteristic expression of serum proteins may assist in differential diagnosis of various subtypes of lung cancers.

METHODS

Blood samples were collected from 123 lung cancer patients before commencement of treatment who attended Shanxi Cancer Hospital, China, between 2008 and 2013. Blood samples from 60 healthy individuals were also collected in the same period. Serum protein expression profiles were analyzed using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry. The differences in the serum protein spectrums of lung cancer patients with different histological subtypes were analyzed by one-way Analysis of Variance and receiver operating characteristic curves.

RESULTS

A cluster of 48 protein mass-to-change ratio (M/Z) peaks was differentially expressed between sera of lung cancer patients and healthy individuals. The M/Z 1205, 4673, 1429 and 4279 peaks were differentially expressed among patients with lung squamous cell carcinomas, adenocarcinomas and small-cell lung carcinomas.

CONCLUSION

These results reinforce the notion that profiling of serum proteins may be of diagnostic value in lung cancer, and suggest that the differences in serum protein profiles may be useful in differential diagnosis of lung cancers of varying histological subtypes.

Facilitating the Validation of Novel Protein Biomarkers for Dementia: An Optimal Workflow for the Development of Sandwich Immunoassays

Different neurodegenerative disorders, such as Alzheimer’s disease (AD) and frontotemporal dementia (FTD), lead to dementia syndromes. Dementia will pose a huge impact on society and thus it is essential to develop novel tools that are able to detect the earliest, most sensitive, discriminative, and dynamic biomarkers for each of the disorders. To date, the most common assays used in large-scale protein biomarker analysis are enzyme-linked immunosorbent assays (ELISA), such as the sandwich immunoassays, which are sensitive, practical, and easily implemented. However, due to the novelty of many candidate biomarkers identified during proteomics screening, such assays or the antibodies that specifically recognize the desired marker are often not available. The development and optimization of a new ELISA should be carried out with considerable caution since a poor planning can be costly, ineffective, time consuming, and it may lead to a misinterpretation of the findings. Previous guidelines described either the overall biomarker development in more general terms (i.e., the process from biomarker discovery to validation) or the specific steps of performing an ELISA procedure. However, a workflow describing and guiding the main issues in the development of a novel ELISA is missing. Here, we describe a specific and detailed workflow to develop and validate new ELISA for a successful and reliable validation of novel dementia biomarkers. The proposed workflow highlights the main issues in the development of an ELISA and covers several critical aspects, including production, screening, and selection of specific antibodies until optimal fine-tuning of the assay. Although these recommendations are designed to analyze novel biomarkers for dementia in cerebrospinal fluid, they are generally applicable for the development of immunoassays for biomarkers in other human body fluids or tissues. This workflow is designed to maximize the quality of the developed ELISA using a time- and cost-efficient strategy. This will facilitate the validation of the dementia biomarker candidates ultimately allowing accurate diagnostic conclusions.

Targeted Proteomics to Assess the Response to Anti-Angiogenic Treatment in Human Glioblastoma (GBM)

Glioblastoma (GBM) is a highly aggressive primary brain tumor with dismal outcome for affected patients. Because of the significant neo-angiogenesis exhibited by GBMs, anti-angiogenic therapies have been intensively evaluated during the past years. Recent clinical studies were however disappointing, although a subpopulation of patients may benefit from such treatment. We have previously shown that anti-angiogenic targeting in GBM increases hypoxia and leads to a metabolic adaptation toward glycolysis, suggesting that combination treatments also targeting the glycolytic phenotype may be effective in GBM patients. The aim of this study was to identify marker proteins that are altered by treatment and may serve as a short term readout of anti-angiogenic therapy. Ultimately such proteins could be tested as markers of efficacy able to identify patient subpopulations responsive to the treatment. We applied a proteomics approach based on selected reaction monitoring (SRM) to precisely quantify targeted protein candidates, selected from pathways related to metabolism, apoptosis and angiogenesis. The workflow was developed in the context of patient-derived intracranial GBM xenografts developed in rodents and ensured the specific identification of human tumor versus rodent stroma-derived proteins. Quality control experiments were applied to assess sample heterogeneity and reproducibility of SRM assays at different levels. The data demonstrate that tumor specific proteins can be precisely quantified within complex biological samples, reliably identifying small concentration differences induced by the treatment. In line with previous work, we identified decreased levels of TCA cycle enzymes, including isocitrate dehydrogenase, whereas malectin, calnexin, and lactate dehydrogenase A were augmented after treatment. We propose the most responsive proteins of our subset as potential novel biomarkers to assess treatment response after anti-angiogenic therapy that warrant future analysis in clinical GBM samples.

Proteomics analysis of bodily fluids in pancreatic cancer

Proteomics study of pancreatic cancer using bodily fluids emphasizes biomarker discovery and clinical application, presenting unique prospect and challenges. Depending on the physiological nature of the bodily fluid and its proximity to pancreatic cancer, the proteomes of bodily fluids, such as pancreatic juice, pancreatic cyst fluid, blood, bile, and urine, can be substantially different in terms of protein constitution and the dynamic range of protein concentration. Thus, a comprehensive discovery and specific detection of cancer-associated proteins within these varied fluids is a complex task, requiring rigorous experiment design and a concerted approach. While major challenges still remain, fluid proteomics studies in pancreatic cancer to date have provided a wealth of information in revealing proteome alterations associated with pancreatic cancer in various bodily fluids.

Application of a discovery to targeted LC-MS proteomics approach to identify deregulated proteins associated with idiosyncratic liver toxicity in a rat model of LPS/diclofenac co-administration

Increasing experimental and clinical evidence suggest a contribution of non-drug related risk factors (e.g., underlying disease, bacterial/viral infection) to idiosyncratic drug reactions (IDR). Our previous work showed that co-treatment with bacterial endotoxin (LPS) and therapeutic doses of diclofenac (Dcl), an analgesic associated with drug idiosyncrasy in patients, induced severe hepatotoxicity in rats. Here, we used an integrated discovery to targeted LC-MS proteomics approach to identify mechanistically relevant liver and plasma proteins modulated by LPS/Dcl treatment, potentially applicable as early markers for IDRs. Based on pre-screening results and their role in liver toxicity, 47 liver and 15 plasma proteins were selected for targeted LC-MS analysis. LPS alone significantly changed the levels of 19 and 3 of these proteins, respectively. T-kininogen-1, previously suggested as a marker of drug-induced liver injury, was markedly elevated in plasma after repeated Dcl treatment in the absence of hepatotoxicity, possibly indicating clinically silent stress. Dcl both alone and in combination with LPS, caused up-regulation of the ATP synthase subunits (ATP5J, ATPA, and ATPB), suggesting that Dcl may sensitize cells against additional stress factors, such as LPS through generation of mitochondrial stress. Additionally, depletion of plasma fibrinogen was observed in the co-treatment group, consistent with an increased hepatic fibrin deposition and suspected contribution of the hemostatic system to IDRs. In contrast, several proteins previously suggested as liver biomarkers, such as clusterin, did not correlate with liver injury in this model. Taken together, these analyses revealed proteomic changes in a rat model of LPS/Dcl co-administration that could offer mechanistic insight and may serve as biomarkers or safety alert for a drug's potential to cause IDRs.

Animal board invited review: advances in proteomics for animal and food sciences

Animal production and health (APH) is an important sector in the world economy, representing a large proportion of the budget of all member states in the European Union and in other continents. APH is a highly competitive sector with a strong emphasis on innovation and, albeit with country to country variations, on scientific research. Proteomics (the study of all proteins present in a given tissue or fluid - i.e. the proteome) has an enormous potential when applied to APH. Nevertheless, for a variety of reasons and in contrast to disciplines such as plant sciences or human biomedicine, such potential is only now being tapped. To counter such limited usage, 6 years ago we created a consortium dedicated to the applications of Proteomics to APH, specifically in the form of a Cooperation in Science and Technology (COST) Action, termed FA1002--Proteomics in Farm Animals: www.cost-faproteomics.org. In 4 years, the consortium quickly enlarged to a total of 31 countries in Europe, as well as Israel, Argentina, Australia and New Zealand. This article has a triple purpose. First, we aim to provide clear examples on the applications and benefits of the use of proteomics in all aspects related to APH. Second, we provide insights and possibilities on the new trends and objectives for APH proteomics applications and technologies for the years to come. Finally, we provide an overview and balance of the major activities and accomplishments of the COST Action on Farm Animal Proteomics. These include activities such as the organization of seminars, workshops and major scientific conferences, organization of summer schools, financing Short-Term Scientific Missions (STSMs) and the generation of scientific literature. Overall, the Action has attained all of the proposed objectives and has made considerable difference by putting proteomics on the global map for animal and veterinary researchers in general and by contributing significantly to reduce the East-West and North-South gaps existing in the European farm animal research. Future activities of significance in the field of scientific research, involving members of the action, as well as others, will likely be established in the future.

Sample treatment methods involving combinatorial peptide ligand libraries for improved proteomes analyses

If used in an optimized manner, the technology of combinatorial peptide solid-phase libraries can easily improve the analytical determinations of proteomes by several factors. The discovery of novel species and of early stage biomarkers becomes thus reachable with a simple sample treatment. This report describes the most important point to consider (overloading and full recovery) along with a minimum scientific background and gives then detailed recipes to laboratory technicians. Orientations for optional routes are also given according to the objective of the experimental investigations. This covers different approaches to capture proteins of very low abundance. Total protein harvestings to prevent partial losses are also described such as single exhaustive desorption and fractionated elutions for more detailed analyses. Documented results are also reported demonstrating the capability of the technology well beyond what is the common assumption.

Tumor antigens as proteogenomic biomarkers in invasive ductal carcinomas

Background

The majority of genetic biomarkers for human cancers are defined by statistical screening of high-throughput genomics data. While a large number of genetic biomarkers have been proposed for diagnostic and prognostic applications, only a small number have been applied in the clinic. Similarly, the use of proteomics methods for the discovery of cancer biomarkers is increasing. The emerging field of proteogenomics seeks to enrich the value of genomics and proteomics approaches by studying the intersection of genomics and proteomics data. This task is challenging due to the complex nature of transcriptional and translation regulatory mechanisms and the disparities between genomic and proteomic data from the same samples. In this study, we have examined tumor antigens as potential biomarkers for breast cancer using genomics and proteomics data from previously reported laser capture microdissected ER+ tumor samples.

Results

We applied proteogenomic analyses to study the genetic aberrations of 32 tumor antigens determined in the proteomic data. We found that tumor antigens that are aberrantly expressed at the genetic level and expressed at the protein level, are likely involved in perturbing pathways directly linked to the hallmarks of cancer. The results found by proteogenomic analysis of the 32 tumor antigens studied here, capture largely the same pathway irregularities as those elucidated from large-scale screening of genomics analyses, where several thousands of genes are often found to be perturbed.

Conclusion

Tumor antigens are a group of proteins recognized by the cells of the immune system. Specifically, they are recognized in tumor cells where they are present in larger than usual amounts, or are physiochemically altered to a degree at which they no longer resemble native human proteins. This proteogenomic analysis of 32 tumor antigens suggests that tumor antigens have the potential to be highly specific biomarkers for different cancers.

Advances in Proteomic Technologies and Its Contribution to the Field of Cancer

Systematic studies of the cancer genome have generated a wealth of knowledge in recent years. These studies have uncovered a number of new cancer genes not previously known to be causal targets in cancer. Genetic markers can be used to determine predisposition to tumor development, but molecularly targeted treatment strategies are not widely available for most cancers. Precision care plans still must be developed by understanding and implementing basic science research into clinical treatment. Proteomics is continuing to make major strides in the discovery of fundamental biological processes as well as more recent transition into an assay platform capable of measuring hundreds of proteins in any biological system. As such, proteomics can translate basic science discoveries into the clinical practice of precision medicine. The proteomic field has progressed at a fast rate over the past five years in technology, breadth and depth of applications in all areas of the bioscience. Some of the previously experimental technical approaches are considered the gold standard today, and the community is now trying to come to terms with the volume and complexity of the data generated. Here I describe contribution of proteomics in general and biological mass spectrometry in particular to cancer research, as well as related major technical and conceptual developments in the field.

PeptideManager: a peptide selection tool for targeted proteomic studies involving mixed samples from different species

The search for clinically useful protein biomarkers using advanced mass spectrometry approaches represents a major focus in cancer research. However, the direct analysis of human samples may be challenging due to limited availability, the absence of appropriate control samples, or the large background variability observed in patient material. As an alternative approach, human tumors orthotopically implanted into a different species (xenografts) are clinically relevant models that have proven their utility in pre-clinical research. Patient derived xenografts for glioblastoma have been extensively characterized in our laboratory and have been shown to retain the characteristics of the parental tumor at the phenotypic and genetic level. Such models were also found to adequately mimic the behavior and treatment response of human tumors. The reproducibility of such xenograft models, the possibility to identify their host background and perform tumor-host interaction studies, are major advantages over the direct analysis of human samples. At the proteome level, the analysis of xenograft samples is challenged by the presence of proteins from two different species which, depending on tumor size, type or location, often appear at variable ratios. Any proteomics approach aimed at quantifying proteins within such samples must consider the identification of species specific peptides in order to avoid biases introduced by the host proteome. Here, we present an in-house methodology and tool developed to select peptides used as surrogates for protein candidates from a defined proteome (e.g., human) in a host proteome background (e.g., mouse, rat) suited for a mass spectrometry analysis. The tools presented here are applicable to any species specific proteome, provided a protein database is available. By linking the information from both proteomes, PeptideManager significantly facilitates and expedites the selection of peptides used as surrogates to analyze proteins of interest.

Next generation of food allergen quantification using mass spectrometric systems

Food allergies are increasing worldwide and becoming a public health concern. Food legislation requires detailed declarations of potential allergens in food products and therefore an increased capability to analyze for the presence of food allergens. Currently, antibody-based methods are mainly utilized to quantify allergens; however, these methods have several disadvantages. Recently, mass spectrometry (MS) techniques have been developed and applied to food allergen analysis. At present, 46 allergens from 11 different food sources have been characterized using different MS approaches and some specific signature peptides have been published. However, quantification of allergens using MS is not routinely employed. This review compares the different aspects of food allergen quantification using advanced MS techniques including multiple reaction monitoring. The latter provides low limits of quantification for multiple allergens in simple or complex food matrices, while being robust and reproducible. This review provides an overview of current approaches to analyze food allergens, with specific focus on MS systems and applications.

Absolute quantitation of Met using mass spectrometry for clinical application: assay precision, stability, and correlation with MET gene amplification in FFPE tumor tissue

Background

Overexpression of Met tyrosine kinase receptor is associated with poor prognosis. Overexpression, and particularly MET amplification, are predictive of response to Met-specific therapy in preclinical models. Immunohistochemistry (IHC) of formalin-fixed paraffin-embedded (FFPE) tissues is currently used to select for ‘high Met’ expressing tumors for Met inhibitor trials. IHC suffers from antibody non-specificity, lack of quantitative resolution, and, when quantifying multiple proteins, inefficient use of scarce tissue.

Methods

After describing the development of the Liquid-Tissue-Selected Reaction Monitoring-mass spectrometry (LT-SRM-MS) Met assay, we evaluated the expression level of Met in 130 FFPE gastroesophageal cancer (GEC) tissues. We assessed the correlation of SRM Met expression to IHC and mean MET gene copy number (GCN)/nucleus or MET/CEP7 ratio by fluorescence in situ hybridization (FISH).

Results

Proteomic mapping of recombinant Met identified ⁴¹⁸TEFTTALQR⁴²⁶ as the optimal SRM peptide. Limits of detection (LOD) and quantitation (LOQ) for this peptide were 150 and 200 amol/µg tumor protein, respectively. The assay demonstrated excellent precision and temporal stability of measurements in serial sections analyzed one year apart. Expression levels of 130 GEC tissues ranged (<150 amol/µg to 4669.5 amol/µg. High correlation was observed between SRM Met expression and both MET GCN and MET/CEP7 ratio as determined by FISH (n = 30; R² = 0.898). IHC did not correlate well with SRM (n = 44; R² = 0.537) nor FISH GCN (n = 31; R² = 0.509). A Met SRM level of ≥1500 amol/µg was 100% sensitive (95% CI 0.69–1) and 100% specific (95% CI 0.92–1) for MET amplification.

Conclusions

The Met SRM assay measured the absolute Met levels in clinical tissues with high precision. Compared to IHC, SRM provided a quantitative and linear measurement of Met expression, reliably distinguishing between non-amplified and amplified MET tumors. These results demonstrate a novel clinical tool for efficient tumor expression profiling, potentially leading to better informed therapeutic decisions for patients with GEC.

Novel serum protein biomarker panel revealed by mass spectrometry and its prognostic value in breast cancer

Introduction

Serum profiling using proteomic techniques has great potential to detect biomarkers that might improve diagnosis and predict outcome for breast cancer patients (BC). This study used surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry (MS) to identify differentially expressed proteins in sera from BC and healthy volunteers (HV), with the goal of developing a new prognostic biomarker panel.

Methods

Training set serum samples from 99 BC and 51 HV subjects were applied to four adsorptive chip surfaces (anion-exchange, cation-exchange, hydrophobic, and metal affinity) and analyzed by time-of-flight MS. For validation, 100 independent BC serum samples and 70 HV samples were analyzed similarly. Cluster analysis of protein spectra was performed to identify protein patterns related to BC and HV groups. Univariate and multivariate statistical analyses were used to develop a protein panel to distinguish breast cancer sera from healthy sera, and its prognostic potential was evaluated.

Results

From 51 protein peaks that were significantly up- or downregulated in BC patients by univariate analysis, binary logistic regression yielded five protein peaks that together classified BC and HV with a receiver operating characteristic (ROC) area-under-the-curve value of 0.961. Validation on an independent patient cohort confirmed the five-protein parameter (ROC value 0.939). The five-protein parameter showed positive association with large tumor size (P = 0.018) and lymph node involvement (P = 0.016). By matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MS, immunoprecipitation and western blotting the proteins were identified as a fragment of apolipoprotein H (ApoH), ApoCI, complement C3a, transthyretin, and ApoAI. Kaplan-Meier analysis on 181 subjects after median follow-up of >5 years demonstrated that the panel significantly predicted disease-free survival (P = 0.005), its efficacy apparently greater in women with estrogen receptor (ER)-negative tumors (n = 50, P = 0.003) compared to ER-positive (n = 131, P = 0.161), although the influence of ER status needs to be confirmed after longer follow-up.

Conclusions

Protein mass profiling by MS has revealed five serum proteins which, in combination, can distinguish between serum from women with breast cancer and healthy control subjects with high sensitivity and specificity. The five-protein panel significantly predicts recurrence-free survival in women with ER-negative tumors and may have value in the management of these patients.

Combining bioinformatics and MS-based proteomics: clinical implications

Clinical proteomics research aims at i) discovery of protein biomarkers for screening, diagnosis and prognosis of disease, ii) discovery of protein therapeutic targets for improvement of disease prevention, treatment and follow-up, and iii) development of mass spectrometry (MS)-based assays that could be implemented in clinical chemistry, microbiology or hematology laboratories. MS has been increasingly applied in clinical proteomics studies for the identification and quantification of proteins. Bioinformatics plays a key role in the exploitation of MS data in several aspects such as the generation and curation of protein sequence databases, the development of appropriate software for MS data treatment and integration with other omics data and the establishment of adequate standard files for data sharing. In this article, we discuss the main MS approaches and bioinformatics solutions that are currently applied to accomplish the objectives of clinical proteomic research.

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

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

Proteomic identification of potential prognostic biomarkers in resectable pancreatic ductal adenocarcinoma

Pancreatic cancer is a devastating disease with a mortality rate almost identical with its incidence. In this context, the investigation of the pancreatic cancer proteome has gained considerable attention because profiles of proteins may be able to identify disease states and progression more accurately. Therefore, our objective was to investigate the changes in the proteome of patients suffering from pancreatic ductal adenocarcinoma (PDAC) by a comprehensive quantitative approach. Comparative proteomic profiling by label-free LC-MS/MS analysis of nine matched pairs of tumor and nontumor pancreas samples was used to identify differences in protein levels characteristic for PDAC. In this analysis, 488 proteins were quantified by at least two peptides of which 99 proteins displayed altered levels in PDAC (p < 0.01, fold change >1.3). Screening of data revealed a number of molecules that had already been related to PDAC such as galectin-1 (LEG1), major vault protein, adenylyl cyclase-associated protein 1 (CAP1), but also a potential new prognostic biomarker prolargin (PRELP). The Kaplan-Meier survival analysis revealed a significant correlation of protein abundance of PRELP with postoperative survival of patients with PDAC. For selected proteins the findings were verified by targeted proteomics (SRM), validated by immunohistochemistry and Western blotting and their value as candidate biomarkers is discussed.