Application of SWATH Mass Spectrometry and Machine Learning in the Diagnosis of Inflammatory Bowel Disease Based on the Stool Proteome

Inflammatory bowel disease (IBD) flare-ups exhibit symptoms that are similar to other diseases and conditions, making diagnosis and treatment complicated. Currently, the gold standard for diagnosing and monitoring IBD is colonoscopy and biopsy, which are invasive and uncomfortable procedures, and the fecal calprotectin test, which is not sufficiently accurate. Therefore, it is necessary to develop an alternative method. In this study, our aim was to provide proof of concept for the application of Sequential Window Acquisition of All Theoretical Mass Spectra-Mass spectrometry (SWATH-MS) and machine learning to develop a non-invasive and accurate predictive model using the stool proteome to distinguish between active IBD patients and symptomatic non-IBD patients. Proteome profiles of 123 samples were obtained and data processing procedures were optimized to select an appropriate pipeline. The differentially abundant analysis identified 48 proteins. Utilizing correlation-based feature selection (Cfs), 7 proteins were selected for proceeding steps. To identify the most appropriate predictive machine learning model, five of the most popular methods, including support vector machines (SVMs), random forests, logistic regression, naive Bayes, and k-nearest neighbors (KNN), were assessed. The generated model was validated by implementing the algorithm on 45 prospective unseen datasets; the results showed a sensitivity of 96% and a specificity of 76%, indicating its performance. In conclusion, this study illustrates the effectiveness of utilizing the stool proteome obtained through SWATH-MS in accurately diagnosing active IBD via a machine learning model.

Mass spectrometry as a lens into molecular human nutrition and health

Mass spectrometry (MS) has developed over the last decades into the most informative and versatile analytical technology in molecular and structural biology (). The platform enables discovery, identification, and characterisation of non-volatile biomolecules, such as proteins, peptides, DNA, RNA, nutrients, metabolites, and lipids at both speed and scale and can elucidate their interactions and effects. The versatility, robustness, and throughput have rendered MS a major research and development platform in molecular human health and biomedical science. More recently, MS has also been established as the central tool for 'Molecular Nutrition', enabling comprehensive and rapid identification and characterisation of macro- and micronutrients, bioactives, and other food compounds. 'Molecular Nutrition' thereby helps understand bioaccessibility, bioavailability, and bioefficacy of macro- and micronutrients and related health effects. Hence, MS provides a lens through which the fate of nutrients can be monitored along digestion via absorption to metabolism. This in turn provides the bioanalytical foundation for 'Personalised Nutrition' or 'Precision Nutrition' in which design and development of diets and nutritional products is tailored towards consumer and patient groups sharing similar genetic and environmental predisposition, health/disease conditions and lifestyles, and/or objectives of performance and wellbeing. The next level of integrated nutrition science is now being built as 'Systems Nutrition' where public and personal health data are correlated with life condition and lifestyle factors, to establish directional relationships between nutrition, lifestyle, environment, and health, eventually translating into science-based public and personal heath recommendations and actions. This account provides a condensed summary of the contributions of MS to a precise, quantitative, and comprehensive nutrition and health science and sketches an outlook on its future role in this fascinating and relevant field.

Orthogonal proteomics methods warrant the development of Duchenne muscular dystrophy biomarkers

BACKGROUND

Molecular components in blood, such as proteins, are used as biomarkers to detect or predict disease states, guide clinical interventions and aid in the development of therapies. While multiplexing proteomics methods promote discovery of such biomarkers, their translation to clinical use is difficult due to the lack of substantial evidence regarding their reliability as quantifiable indicators of disease state or outcome. To overcome this challenge, a novel orthogonal strategy was developed and used to assess the reliability of biomarkers and analytically corroborate already identified serum biomarkers for Duchenne muscular dystrophy (DMD). DMD is a monogenic incurable disease characterized by progressive muscle damage that currently lacks reliable and specific disease monitoring tools.

METHODS

Two technological platforms are used to detect and quantify the biomarkers in 72 longitudinally collected serum samples from DMD patients at 3 to 5 timepoints. Quantification of the biomarkers is achieved by detection of the same biomarker fragment either through interaction with validated antibodies in immuno-assays or through quantification of peptides by Parallel Reaction Monitoring Mass Spectrometry assay (PRM-MS).

RESULTS

Five, out of ten biomarkers previously identified by affinity-based proteomics methods, were confirmed to be associated with DMD using the mass spectrometry-based method. Two biomarkers, carbonic anhydrase III and lactate dehydrogenase B, were quantified with two independent methods, sandwich immunoassays and PRM-MS, with Pearson correlations of 0.92 and 0.946 respectively. The median concentrations of CA3 and LDHB in DMD patients was elevated in comparison to those in healthy individuals by 35- and 3-fold, respectively. Levels of CA3 vary between 10.26 and 0.36 ng/ml in DMD patients whereas those of LDHB vary between 15.1 and 0.8 ng/ml.

CONCLUSIONS

These results demonstrate that orthogonal assays can be used to assess the analytical reliability of biomarker quantification assays, providing a means to facilitate the translation of biomarkers to clinical practice. This strategy also warrants the development of the most relevant biomarkers, markers that can be reliably quantified with different proteomics methods.

Prediction, Discovery, and Characterization of Plant- and Food-Derived Health-Beneficial Bioactive Peptides

Nature may have the answer to many of our questions about human, animal, and environmental health. Natural bioactives, especially when harvested from sustainable plant and food sources, provide a plethora of molecular solutions to nutritionally actionable, chronic conditions. The spectrum of these conditions, such as metabolic, immune, and gastrointestinal disorders, has changed with prolonged human life span, which should be matched with an appropriately extended health span, which would in turn favour more sustainable health care: "adding years to life and adding life to years". To date, bioactive peptides have been undervalued and underexploited as food ingredients and drugs. The future of translational science on bioactive peptides-and natural bioactives in general-is being built on (a) systems-level rather than reductionist strategies for understanding their interdependent, and at times synergistic, functions; and (b) the leverage of artificial intelligence for prediction and discovery, thereby significantly reducing the time from idea and concept to finished solutions for consumers and patients. This new strategy follows the path from benefit definition via design to prediction and, eventually, validation and production.

Mass Spectrometry-Based Proteomics for Biomarker Discovery

Proteomics plays a pivotal role in systems medicine, in which pharmacoproteomics and toxicoproteomics have been developed to address questions related to efficacy and toxicity of drugs. Mass spectrometry is the core technology for quantitative proteomics, providing the capabilities of identification and quantitation of thousands of proteins. The technology has been applied to biomarker discovery and understanding the mechanisms of drug action. Both stable isotope labeling of proteins or peptides and label-free approaches have been incorporated with multidimensional LC separation and tandem mass spectrometry (LC-MS/MS) to increase the coverage and depth of proteome analysis. A protocol of such an approach exemplified by dimethyl labeling in combination with 2D-LC-MS/MS is described. With further development of novel proteomic tools and increase in sample throughput, the full spectrum of mass spectrometry-based proteomic research will greatly advance systems medicine.

Proteomics applications in biomarker discovery and pathogenesis for abdominal aortic aneurysm

Introduction: Abdominal aortic aneurysm (AAA) is a common, complex, and life-threatening disease. Currently, the pathogenesis of AAA is not well understood. No biomarkers or specific drugs are available for AAA in clinical applications. Proteomics is a powerful tool in biomarker discovery, exploration of pathogenesis, and drug target identification.Areas covered: We review the application of mass spectrometry-based proteome analysis in AAA patients within the last ten years. Differentially expressed proteins associated with AAA were identified in multiple sample sources, including vascular tissue, intraluminal thrombus, tissue secretome, blood, and cells. Some potential disease biomarkers, pathogenic mechanisms, or therapeutic targets for AAA were discovered using proteome analysis. The challenges and prospects of proteomics applied to AAA are also discussed.Expert opinion: Since most of the previous proteomic studies used relatively small sample sizes, some promising biomarkers need to be validated in multicenter cohorts to accelerate their clinical application. With the rapid development of mass spectrometry technology, modification-specific proteomics and multi-omics research in the future will enhance our understanding of the pathogenesis of AAA and promote biomarker discovery and drug development for clinical translation.

Clinical Perspective on Proteomic and Glycomic Biomarkers for Diagnosis, Prognosis, and Prediction of Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is known as a highly aggressive malignant disease. Prognosis for patients is notoriously poor, despite improvements in surgical techniques and new (neo)adjuvant chemotherapy regimens. Early detection of PDAC may increase the overall survival. It is furthermore foreseen that precision medicine will provide improved prognostic stratification and prediction of therapeutic response. In this review, omics-based discovery efforts are presented that aim for novel diagnostic and prognostic biomarkers of PDAC. For this purpose, we systematically evaluated the literature published between 1999 and 2020 with a focus on protein- and protein-glycosylation biomarkers in pancreatic cancer patients. Besides genomic and transcriptomic approaches, mass spectrometry (MS)-based proteomics and glycomics of blood- and tissue-derived samples from PDAC patients have yielded new candidates with biomarker potential. However, for reasons discussed in this review, the validation and clinical translation of these candidate markers has not been successful. Consequently, there has been a change of mindset from initial efforts to identify new unimarkers into the current hypothesis that a combination of biomarkers better suits a diagnostic or prognostic panel. With continuing development of current research methods and available techniques combined with careful study designs, new biomarkers could contribute to improved detection, prognosis, and prediction of pancreatic cancer.

Characterization of the Immunomodulatory Mechanism of a Pleurotus eryngii Protein by Isobaric Tags for Relative and Absolute Quantitation Proteomics

PEP 1b is a novel immunoregulatory protein isolated from Pleurotus eryngii, a popular edible mushroom. In this study, isobaric tags for relative and absolute quantitation (iTRAQ) approach and bioinformatics analysis were used to characterize the PEP-1b-induced proteome alterations in Raw 264.7 macrophage cells, to comprehensively excavate the molecular mechanisms involved in the immunoregulatory effects of PEP 1b. In comparison to the control group, PEP 1b treatment significantly changed the expression of 292 proteins, including 191 upregulated and 101 downregulated proteins. Bioinformatics analysis showed that PEP-1b-regulated proteins were involved in 437 biological process domains, 131 cellular component domains, and 90 molecular function domains. Moreover, PEP 1b played the role of immunomodulator by mainly modulating the Rap1 signaling pathway, Wnt signaling pathway, Ras signaling pathway, and PI3K-Akt signaling pathway. Interestingly, PEP 1b regulated the proteins involved in the immune system, signal transduction, and transport processes, which were related to the immunoregulatory effects of PEP 1b. The western blotting analysis confirmed that the immune-boosting activities of PEP 1b were associated with modulating the expression of Sqstm1, Cox2, Rap1b, and Pyk2. The current research provided a comprehensive understanding of the immunoregulatory effects and molecular mechanisms involved in the PEP 1b supplementation.

THE PRESENT AND FUTURE OF THE MASS SPECTROMETRY-BASED INVESTIGATION OF THE EXOSOME LANDSCAPE

Exosomes are critical intercellular messengers released upon the fusion of multivesicular bodies with the cellular plasma membrane that deliver their cargo in the form of extracellular vesicles. Containing numerous nonrandomly packed functional proteins, lipids, and RNAs, exosomes are vital intercellular messengers that contribute to the physiologic processes of the healthy organism. During the post-genome era, exosome-oriented proteomics have garnered great interest. Since its establishment, mass spectrometry (MS) has been indispensable for the field of proteomics research and has advanced rapidly to interrogate biological samples at a higher resolution and sensitivity. Driven by new methodologies and more advanced instrumentation, MS-based approaches have revolutionized our understanding of protein biology. As the access to online proteomics database platforms has blossomed, experimental data processing occurs with more speed and accuracy. Here, we review recent advances in the technological progress of MS-based proteomics and several new detection strategies for MS-based proteomics research. We also summarize the use of integrated online databases for proteomics research in the era of big data. © 2020 John Wiley & Sons Ltd. Mass Spec Rev.

Venomous Arachnid Diagnostic Assays, Lessons from Past Attempts

Diagnostic tests for arachnid accidents remain unavailable for patients and clinicians. Together with snakes, these accidents are still a global medical concern, and are recognized as neglected tropical issues. Due to arachnid toxins’ fast mechanism of action, quick detection and quantification of venom is required to accelerate treatment decisions, rationalize therapy, and reduce costs and patient risks. This review aims to understand the current limitations for arachnid venom identification and quantification in biological samples. We benchmarked the already existing initiatives regarding test requirements (sample or biomarkers of choice), performances (time, detection limit, sensitivity and specificity) and their validation (on animal models or on samples from envenomed humans). Our analysis outlines unmet needs for improving diagnosis and consequently treatment of arachnid accidents. Hence, based on lessons from past attempts, we propose a road map for raising best practice guidelines, leading to recommendations for future progress in the development of arachnid diagnostic assays.

Changes in the urinary extracellular vesicle proteome are associated with nephronophthisis-related ciliopathies

Nephronophthisis is one of the leading genetic causes of end-stage renal disease in childhood. Early diagnostics and prognostics for nephronophthisis are currently limited. We aimed to identify non-invasive protein biomarkers for nephronophthisis in urinary extracellular vesicles. Extracellular vesicles were isolated from urine of 12 patients with a nephronophthisis-related ciliopathy and 12 age- and gender-matched controls, followed by in-depth label-free LC-MS/MS proteomics analysis of gel fractionated extracellular vesicle proteins. Supervised cluster analysis of proteomic profiles separated patients from controls. We identified 156 differentially expressed proteins with fold change ≥4 in patients compared to controls (P < .05). Importantly, expression levels of discriminating proteins were correlated with chronic kidney disease stage, suggesting possible applications for urinary extracellular vesicle biomarkers in prognostics for nephronophthisis. Enrichment analysis of gene ontology terms revealed GO terms including signaling, actin cytoskeleton and endocytosis among the downregulated proteins in patients, whereas terms related to response to wounding and extracellular matrix organization were enriched among upregulated proteins. Our findings represent the first step towards a non-invasive diagnostic test for nephronophthisis. Further research is needed to determine specificity of the candidate biomarkers. In conclusion, proteomic profiles of urinary extracellular vesicles differentiate nephronophthisis-related ciliopathy patients from healthy controls. SIGNIFICANCE: Nephronophthisis is an important cause of end-stage renal disease in children and is associated with an average diagnostic delay of 3.5 years. This is the first study investigating candidate biomarkers for nephronophthisis using global proteomics analysis of urinary extracellular vesicles in patients with nephronophthisis compared to control individuals. We show that measuring protein markers in urinary extracellular vesicles is a promising approach for non-invasive early diagnostics of nephronophthisis.

Evaluation and Application of Dimethylated Amino Acids as Isobaric Tags for Quantitative Proteomics of the TGF-β/Smad3 Signaling Pathway

Isobaric labeling has become a widespread tool for quantitative proteomic studies. Here, we report the development and evaluation of several dimethylated amino acids as novel isobaric tags for quantitative proteomics. Four-plex dimethylated alanine (DiAla), valine (DiVal), and leucine (DiLeu) have been synthesized, sharing common features of peptide tagging and reporter ion production. DiAla and DiLeu are shown to achieve complete labeling. These two tags' impacts on peptide fragmentation and quantitation are further evaluated using HEK293 cell lysate. DiAla labeling generates more abundant backbone fragmentation whereas DiLeu labeling produces more intense reporter ions. Nonetheless, both tags enable accurate quantitative analysis of HEK293 cell proteomes. DiAla and DiLeu tags are then applied to study the TGF-β/Smad3 pathway with four differentially treated mouse vascular smooth muscle (MOVAS) cells. Our MS data reveal proteome-wide changes of AdSmad3 as compared to the GFP control, consistent with previous findings of causing smooth muscle cell (SMC) dedifferentiation.1 Additionally, the other two novel mutations on the hub protein Smad3, Y226A, and D408H, show compromised TGF-β/Smad3-dependent gene transcription and reversed phenotypic switch. These results are further corroborated with Western blotting and demonstrate that the novel DiAla and DiLeu isobaric tagging reagents provide useful tools for multiplex quantitative proteomics.

Peptide-mediated 'miniprep' isolation of extracellular vesicles is suitable for high-throughput proteomics

Extracellular vesicles (EVs) are cell-secreted membrane vesicles enclosed by a lipid bilayer derived from endosomes or from the plasma membrane. Since EVs are released into body fluids, and their cargo includes tissue-specific and disease-related molecules, they represent a rich source for disease biomarkers. However, standard ultracentrifugation methods for EV isolation are laborious, time-consuming, and require high inputs. Ghosh and co-workers recently described an isolation method utilizing Heat Shock Protein (HSP)-binding peptide Vn96 to aggregate HSP-decorated EVs, which can be performed at small 'miniprep' scale. Based on microscopic, immunoblot, and RNA sequencing analyses this method compared well with ultracentrifugation-mediated EV isolation, but a detailed proteomic comparison was lacking. Therefore, we compared both methods using label-free proteomics of replicate EV isolations from HT-29 cell-conditioned medium. Despite a 30-fold different scale (ultracentrifugation: 60 ml/Vn96-mediated aggregation: 2 ml) both methods yielded comparable numbers of identified proteins (3115/3085), with similar reproducibility of identification (72.5%/75.5%) and spectral count-based quantification (average CV: 31%/27%). EV fractions obtained with either method contained established EV markers and proteins linked to vesicle-related gene ontologies. Thus, Vn96 peptide-mediated aggregation is an advantageous, simple and rapid approach for EV isolation from small biological samples, enabling high-throughput analysis in a biomarker discovery setting.

Protein expression changes induced in a malignant melanoma cell line by the curcumin analogue compound D6

Background

We have previously demonstrated that the hydroxylated biphenyl compound D6 (3E,3′E)-4,4′-(5,5′,6,6′-tetramethoxy-[1,1′-biphenyl]-3,3′-diyl)bis(but-3-en-2-one), a structural analogue of curcumin, exerts a strong antitumor activity on melanoma cells both in vitro and in vivo. Although the mechanism of action of D6 is yet to be clarified, this compound is thought to inhibit cancer cell growth by arresting the cell cycle in G2/M phase, and to induce apoptosis through the mitochondrial intrinsic pathway. To investigate the changes in protein expression induced by exposure of melanoma cells to D6, a differential proteomic study was carried out on D6-treated and untreated primary melanoma LB24Dagi cells.

Methods

Proteins were fractionated by SDS-PAGE and subjected to in gel digestion. The peptide mixtures were analyzed by liquid chromatography coupled with tandem mass spectrometry. Proteins were identified and quantified using database search and spectral counting. Proteomic data were finally uploaded into the Ingenuity Pathway Analysis software to find significantly modulated networks and pathways.

Results

Analysis of the differentially expressed protein profiles revealed the activation of a strong cellular stress response, with overexpression of several HSPs and stimulation of ubiquitin-proteasome pathways. These were accompanied by a decrease of protein synthesis, evidenced by downregulation of proteins involved in mRNA processing and translation. These findings are consistent with our previous results on gene expression profiling in melanoma cells treated with D6.

Conclusions

Our findings confirm that the curcumin analogue D6 triggers a strong stress response in melanoma cells, turning down majority of cell functions and finally driving cells to apoptosis.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-016-2362-6) contains supplementary material, which is available to authorized users.

Clinical proteomics-driven precision medicine for targeted cancer therapy: current overview and future perspectives

Cancer is a common disease that is a leading cause of death worldwide. Currently, early detection and novel therapeutic strategies are urgently needed for more effective management of cancer. Importantly, protein profiling using clinical proteomic strategies, with spectacular sensitivity and precision, offer excellent promise for the identification of potential biomarkers that would direct the development of targeted therapeutic anticancer drugs for precision medicine. In particular, clinical sample sources, including tumor tissues and body fluids (blood, feces, urine and saliva), have been widely investigated using modern high-throughput mass spectrometry-based proteomic approaches combined with bioinformatic analysis, to pursue the possibilities of precision medicine for targeted cancer therapy. Discussed in this review are the current advantages and limitations of clinical proteomics, the available strategies of clinical proteomics for the management of precision medicine, as well as the challenges and future perspectives of clinical proteomics-driven precision medicine for targeted cancer therapy.

Power Normalization for Mass Spectrometry Data Analysis and Analytical Method Assessment

Biomarker profiling using mass spectrometry plays an essential role in biological studies and is highly dependent on the data analysis for sample classification. In this study, we introduced power nomination of the mass spectra as a method for systematically altering the weights of peaks at different intensity levels. In combination with the use of support vector machine method (SVM), the impact on the sample classification has been characterized using data in four studies previously reported, including the distinctions of anomeric configurations of sugars, types of bacteria, stages of melanoma, and the types of breast cancer. Comprehensive analysis of the data with normalization at different power normalization index (PNI) was developed and analysis tools, including error-PNI plots, reference profiles, and error source profiles, were used to assess the potential of the analytical methods as well as to find the proper approaches to classify the samples.

Novel diagnostic cerebrospinal fluid biomarkers for pathologic subtypes of frontotemporal dementia identified by proteomics

Introduction

Reliable cerebrospinal fluid (CSF) biomarkers enabling identification of frontotemporal dementia (FTD) and its pathologic subtypes are lacking.

Methods

Unbiased high-resolution mass spectrometry–based proteomics was applied on CSF of FTD patients with TAR DNA-binding protein 43 (TDP-43, FTD-TDP, n = 12) or tau pathology (FTD-tau, n = 8), and individuals with subjective memory complaints (SMC, n = 10). Validation was performed by applying enzyme-linked immunosorbent assay (ELISA) or enzymatic assays, when available, in a larger cohort (FTLD-TDP, n = 21, FTLD-tau, n = 10, SMC, n = 23) and in Alzheimer's disease (n = 20), dementia with Lewy bodies (DLB, n = 20), and vascular dementia (VaD, n = 18).

Results

Of 1914 identified CSF proteins, 56 proteins were differentially regulated (fold change >1.2, P < .05) between the different patient groups: either between the two pathologic subtypes (10 proteins), or between at least one of these FTD subtypes and SMC (47 proteins). We confirmed the differential expression of YKL-40 by ELISA in a partly independent cohort. Furthermore, enzyme activity of catalase was decreased in FTD subtypes compared with SMC. Further validation in a larger cohort showed that the level of YKL-40 was twofold increased in both FTD pathologic subtypes compared with SMC and that the levels in FTLD-tau were higher compared to Alzheimer's dementia (AD), DLB, and VaD patients. Clinical validation furthermore showed that the catalase enzyme activity was decreased in the FTD subtypes compared to SMC, AD and DLB.

Discussion

We identified promising CSF biomarkers for both FTD differential diagnosis and pathologic subtyping. YKL-40 and catalase enzyme activity should be validated further in similar pathology defined patient cohorts for their use for FTD diagnosis or treatment development.

Mass spectrometry-based proteomics: from cancer biology to protein biomarkers, drug targets, and clinical applications

Proteomics is optimally suited to bridge the gap between genomic information on the one hand and biologic functions and disease phenotypes at the other, since it studies the expression and/or post-translational modification (especially phosphorylation) of proteins--the major cellular players bringing about cellular functions--at a global level in biologic specimens. Mass spectrometry technology and (bio)informatic tools have matured to the extent that they can provide high-throughput, comprehensive, and quantitative protein inventories of cells, tissues, and biofluids in clinical samples at low level. In this article, we focus on next-generation proteomics employing nanoliquid chromatography coupled to high-resolution tandem mass spectrometry for in-depth (phospho)protein profiling of tumor tissues and (proximal) biofluids, with a focus on studies employing clinical material. In addition, we highlight emerging proteogenomic approaches for the identification of tumor-specific protein variants, and targeted multiplex mass spectrometry strategies for large-scale biomarker validation. Below we provide a discussion of recent progress, some research highlights, and challenges that remain for clinical translation of proteomic discoveries.

Cancer biomarker detection: recent achievements and challenges

We provide an overview covering the existing challenges and latest developments in achieving high selectivity and sensitivity cancer-biomarker detection.

Distribution volumes of macromolecules in human ovarian and endometrial cancers--effects of extracellular matrix structure

Elements of the extracellular matrix (ECM), notably collagen and glucosaminoglycans, will restrict part of the space available for soluble macromolecules simply because the molecules cannot occupy the same space. This phenomenon may influence macromolecular drug uptake. To study the influence of steric and charge effects of the ECM on the distribution volumes of macromolecules in human healthy and malignant gynecologic tissues we used as probes 15 abundant plasma proteins quantified by high-resolution mass spectrometry. The available distribution volume (VA) of albumin was increased in ovarian carcinoma compared with healthy ovarian tissue. Furthermore, VA of plasma proteins between 40 and 190 kDa decreased with size for endometrial carcinoma and healthy ovarian tissue, but was independent of molecular weight for the ovarian carcinomas. An effect of charge on distribution volume was only found in healthy ovaries, which had lower hydration and high collagen content, indicating that a condensed interstitium increases the influence of negative charges. A number of earlier suggested biomarker candidates were detected in increased amounts in malignant tissue, e.g., stathmin and spindlin-1, showing that interstitial fluid, even when unfractionated, can be a valuable source for tissue-specific proteins. We demonstrate that the distribution of abundant plasma proteins in the interstitium can be elucidated by mass spectrometry methods and depends markedly on hydration and ECM structure. Our data can be used in modeling of drug uptake, and give indications on ECM components to be targeted to increase the uptake of macromolecular substances.

Immunodiagnostics and immunosensor design (IUPAC Technical Report)

This work compiles information on the principles of diagnostic immunochemical methods and the recent advances in this field. It presents an overview of modern techniques for the production of diagnostic antibodies, their modification with the aim of improving their diagnostic potency, the different types of immunochemical detection systems, and the increasing diagnostic applications for human health that include specific disease markers, individualized diagnosis of cancer subtypes, therapeutic and addictive drugs, food residues, and environmental contaminants. A special focus lies in novel developments of immunosensor techniques, promising approaches to miniaturized detection units and the associated microfluidic systems. The trends towards high-throughput systems, multiplexed analysis, and miniaturization of the diagnostic tools are discussed. It is also made evident that progress in the last few years has largely relied on novel chemical approaches.

Methylcrotonyl-CoA Carboxylase Regulates Triacylglycerol Accumulation in the Model Diatom Phaeodactylum tricornutum

The model marine diatom Phaeodactylum tricornutum can accumulate high levels of triacylglycerols (TAGs) under nitrogen depletion and has attracted increasing attention as a potential system for biofuel production. However, the molecular mechanisms involved in TAG accumulation in diatoms are largely unknown. Here, we employed a label-free quantitative proteomics approach to estimate differences in protein abundance before and after TAG accumulation. We identified a total of 1193 proteins, 258 of which were significantly altered during TAG accumulation. Data analysis revealed major changes in proteins involved in branched-chain amino acid (BCAA) catabolic processes, glycolysis, and lipid metabolic processes. Subsequent quantitative RT-PCR and protein gel blot analysis confirmed that four genes associated with BCAA degradation were significantly upregulated at both the mRNA and protein levels during TAG accumulation. The most significantly upregulated gene, encoding the β-subunit of methylcrotonyl-CoA carboxylase (MCC2), was selected for further functional studies. Inhibition of MCC2 expression by RNA interference disturbed the flux of carbon (mainly in the form of leucine) toward BCAA degradation, resulting in decreased TAG accumulation. MCC2 inhibition also gave rise to incomplete utilization of nitrogen, thus lowering biomass during the stationary growth phase. These findings help elucidate the molecular and metabolic mechanisms leading to increased lipid production in diatoms.

Clinical proteomic biomarkers: relevant issues on study design & technical considerations in biomarker development

Biomarker research is continuously expanding in the field of clinical proteomics. A combination of different proteomic-based methodologies can be applied depending on the specific clinical context of use. Moreover, current advancements in proteomic analytical platforms are leading to an expansion of biomarker candidates that can be identified. Specifically, mass spectrometric techniques could provide highly valuable tools for biomarker research. Ideally, these advances could provide with biomarkers that are clinically applicable for disease diagnosis and/ or prognosis. Unfortunately, in general the biomarker candidates fail to be implemented in clinical decision making. To improve on this current situation, a well-defined study design has to be established driven by a clear clinical need, while several checkpoints between the different phases of discovery, verification and validation have to be passed in order to increase the probability of establishing valid biomarkers. In this review, we summarize the technical proteomic platforms that are available along the different stages in the biomarker discovery pipeline, exemplified by clinical applications in the field of bladder cancer biomarker research.

Proteomics, genomics and transcriptomics: their emerging roles in the discovery and validation of colorectal cancer biomarkers

Colorectal cancer (CRC) is the second most common cancer in females and the third in males. Since CRC is often diagnosed at an advanced stage when prognosis is poor, identification of biomarkers for early diagnosis is urgently required. Recent advances in proteomics, genomics and transcriptomics have facilitated high-throughput profiling of data generated from CRC-related genes and proteins, providing a window of information for biomarker discovery and validation. However, transfer of candidate biomarkers from bench to bedside remains a dilemma. In this review, we will discuss emerging proteomic technologies and highlight various sample types utilized for proteomics-based identification of CRC biomarkers. Moreover, recent breakthroughs in genomics and transcriptomics for the identification of CRC biomarkers, with particular emphasis on the merits of emerging methylomic and miRNAomic strategies, will be discussed. Integration of proteomics, genomics and transcriptomics will facilitate the discovery and validation of CRC biomarkers leading to the emergence of personalized medicine.

Quantitative mass spectrometry for colorectal cancer proteomics

This review documents the uses of quantitative MS applied to colorectal cancer (CRC) proteomics for biomarker discovery and molecular pathway profiling. Investigators are adopting various labeling and label-free MS approaches to quantitate differential protein levels in cells, tumors, and plasma/serum. We comprehensively review recent uses of this technology to examine mouse models of CRC, CRC cell lines, their secretomes and subcellular fractions, CRC tumors, CRC patient plasma/serum, and stool samples. For biomarker discovery these approaches are uncovering proteins with potential diagnostic and prognostic utility, while in vitro cell culture experiments are characterizing proteomic and phosphoproteomic responses to disrupted signaling pathways due to mutations or to inhibition of drugable enzymes.

Colorectal cancer candidate biomarkers identified by tissue secretome proteome profiling

Colorectal cancer (CRC) is a major health problem. Biomarkers associated with molecular changes in cancer cells can aid early detection, diagnosis, prognosis, therapy selection, and disease monitoring. Tumor tissue secretomes are a rich source of candidate biomarkers. To identify CRC protein biomarkers, secretomes of four pairs of human CRC tissue and patient-matched normal colon tissue samples, and secretomes of five CRC cell lines were analyzed by GeLC-MS/MS. Subsequent data analysis was based on label-free spectral counting, Ingenuity Pathway Analysis, Secretome/SignalP, STRING and Cytoscape, resulting in 2703 protein identifications in the tissue secretomes, of which 409 proteins were significantly more present in CRC samples than in controls. Biomarker selection of 76 candidates was based on consistent and abundant over-representation in cancer- compared to control-secretomes, and presumed neoplastic origin. Overlap analysis with previously obtained datasets revealed 21 biomarkers suited for early detection of CRC. Immunohistochemistry confirmed overexpression in CRC of one candidate marker (MCM5). In conclusion, a human reference dataset of 76 candidate biomarkers was identified for which we illustrate that combination with existing pre-clinical datasets allows pre-selection of biomarkers for blood- or stool-based assays to support clinical management of CRC. Further dedicated validation studies are required to demonstrate their clinical applicability.

BIOLOGICAL SIGNIFICANCE

Tissue secretome proteomes are a rich source of candidate biomarkers. Several secretome proteome datasets have been obtained from pre-clinical in vitro and in vivo colorectal cancer (CRC) model systems, yielding promising CRC biomarkers obtained under well-defined experimentally controlled conditions. However, which of these biomarker proteins are actually secreted by human CRC samples was not known. To our knowledge, this is the first study that directly compares secretome proteomes from clinically relevant human CRC tissues to patient-matched normal colon tissues. We identified 76 human CRC protein biomarkers that may facilitate blood-based or stool-based assay development to support clinical management of CRC. Overlap analysis with datasets from well-defined pre-clinical studies helps to determine what clinical application suits these human CRC biomarkers best, i.e. early detection, diagnosis, prognosis, therapy selection, and/or disease monitoring of CRC. This is demonstrated for a CRC mouse model dataset, revealing 21 human CRC biomarkers suited for early detection of CRC.

Exosomal ITGA3 interferes with non-cancerous prostate cell functions and is increased in urine exosomes of metastatic prostate cancer patients

Background

Cancer cells are able to change the protein expression and behavior of non-cancerous surrounding cells. Exosomes, secreted by prostate cancer (PCa) cells, may have a functional role in cancer metastasis and present a promising source for protein biomarkers. The aim of the present study was to identify which proteins in exosomes can influence non-cancerous cells, and to determine whether we can use urine exosomal proteins to identify high-risk PCa patients.

Method

Exosomes were isolated by ultracentrifugation. Migration and invasion were studied by the transwell (invasion) assay. Proteomics was performed by LC-MS/MS and identified proteins were validated by Western blotting. Cellular uptake of fluorescent labeled PKH67-exosomes was measured by FACS.

Results

Based on comparative protein profiling by mass spectrometry-based proteomics of LNCaP- and PC3-exosomes, we selected ITGA3 and ITGB1, involved in migration/invasion, for further analyses. Inhibition of exosomal ITGA3 reduced the migration and invasion of non-cancerous prostate epithelial cells (prEC) almost completely. Cellular uptake of exosomes by prEC was higher with PC3-exosomes compared to LNCaP exosomes. Finally, ITGA3 and ITGB1 were more abundant in urine exosomes of metastatic patients (p<0.05), compared to benign prostate hyperplasia or PCa.

Conclusion

These data indicate exosomal ITGA3 and ITGB1 may play a role in manipulating non-cancerous surrounding cells and that measurement of ITGA3 and ITGB1 in urine exosomes has the potential to identify patients with metastatic PCa in a non-invasive manner.

Mass spectrometric protein maps for biomarker discovery and clinical research

Among the wide range of proteomic technologies, targeted mass spectrometry (MS) has shown great potential for biomarker studies. To extend the degree of multiplexing achieved by selected reaction monitoring (SRM), we recently developed SWATH MS. SWATH MS is a variant of the emerging class of data-independent acquisition (DIA) methods and essentially converts the molecules in a physical sample into perpetually re-usable digital maps. The thus generated SWATH maps are then mined using a targeted data extraction strategy, allowing us to profile disease-related proteomes at a high degree of reproducibility. The successful application of both SRM and SWATH MS requires the a priori generation of reference spectral maps that provide coordinates for quantification. Herein, we demonstrate that the application of the mass spectrometric reference maps and the acquisition of personalized SWATH maps hold a particular promise for accelerating the current process of biomarker discovery.

Surface proteomic analysis of osteosarcoma identifies EPHA2 as receptor for targeted drug delivery

BACKGROUND

Osteosarcoma (OS) is the most common bone tumour in children and adolescents. Despite aggressive therapy regimens, treatment outcomes are unsatisfactory. Targeted delivery of drugs can provide higher effective doses at the site of the tumour, ultimately improving the efficacy of existing therapy. Identification of suitable receptors for drug targeting is an essential step in the design of targeted therapy for OS.

METHODS

We conducted a comparative analysis of the surface proteome of human OS cells and osteoblasts using cell surface biotinylation combined with nano-liquid chromatography - tandem mass spectrometry-based proteomics to identify surface proteins specifically upregulated on OS cells. This approach generated an extensive data set from which we selected a candidate to study for its suitability as receptor for targeted treatment delivery to OS. First, surface expression of the ephrin type-A receptor 2 (EPHA2) receptor was confirmed using FACS analysis. Ephrin type-A receptor 2 expression in human tumour tissue was tested using immunohistochemistry. Receptor targeting and internalisation studies were conducted to assess intracellular uptake of targeted modalities via EPHA2. Finally, tissue micro arrays containing cores of human OS tissue were stained using immunohistochemistry and EPHA2 staining was correlated to clinical outcome measures.

RESULTS

Using mass spectrometry, a total of 2841 proteins were identified of which 156 were surface proteins significantly upregulated on OS cells compared with human primary osteoblasts. Ephrin type-A receptor 2 was highly upregulated and the most abundant surface protein on OS cells. In addition, EPHA2 was expressed in a vast majority of human OS samples. Ephrin type-A receptor 2 effectively mediates internalisation of targeted adenoviral vectors into OS cells. Patients with EPHA2-positive tumours showed a trend toward inferior overall survival.

CONCLUSION

The results presented here suggest that the EPHA2 receptor can be considered an attractive candidate receptor for targeted delivery of therapeutics to OS.

Breast cancer classification by proteomic technologies: current state of knowledge

Breast cancer is traditionally considered as a heterogeneous disease. Molecular profiling of breast cancer by gene expression studies has provided us an important tool to discriminate a number of subtypes. These breast cancer subtypes have been shown to be associated with clinical outcome and treatment response. In order to elucidate the functional consequences of altered gene expressions related to each breast cancer subtype, proteomic technologies can provide further insight by identifying quantitative differences at the protein level. In recent years, proteomic technologies have matured to an extent that they can provide proteome-wide expressions in different clinical materials. This technology can be applied for the identification of proteins or protein profiles to further refine breast cancer subtypes or for discovery of novel protein biomarkers pointing towards metastatic potential or therapy resistance in a specific subtype. In this review, we summarize the current state of knowledge of proteomic research on molecular breast cancer classification and discuss important aspects of the potential usefulness of proteomics for discovery of breast cancer-associated protein biomarkers in the clinic.

Identification of Enolase 1 and Thrombospondin-1 as serum biomarkers in HBV hepatic fibrosis by proteomics

Hepatic fibrosis is an inevitable process in the progression of chronic HBV infection to hepatic cirrhosis, but its detailed mechanism is still unknown. Clinic serum biomarkers of HBV hepatic cirrhosis were scanned by proteomic methods. We used two-dimensional electrophoresis (2-DE) and Matrix-Assisted Laser Desorption/Ionization Time of Flight Mass Spectrometry (MALDI-TOF-MS) to separate and identify the proteins which were differentially expressed in the serum of patients with hepatic fibrosis compared to HBV carriers. We identified 27 differentially expressed proteins, of which 19 proteins were up-regulated and 8 proteins were down-regulated in the serum of patients with hepatic fibrosis compared to HBV carriers. The expression level of enolase-1 (α-enolase) was decreased while the level of thrombospondin-1 (TSP-1) increased in the serum of patients with hepatic fibrosis by western blot. Enolase-1 and TSP-1 may be useful as biomarkers for the clinic diagnosis of hepatic fibrosis, but further study is necessary.

Comparability of differential proteomics data generated from paired archival fresh-frozen and formalin-fixed samples by GeLC-MS/MS and spectral counting

In this study, a Veterinary Department repository composed by paired formalin-fixed paraffin-embedded (FFPE) and fresh-frozen (FrFr) sets of the same tissues, routinely archived in the typical conditions of a clinical setting, was exploited to perform a comparative evaluation of the results generated by GeLC-MS/MS (1-DE followed by in-gel digestion and LC-MS/MS) and spectral counting with the two types of archival samples. Therefore, two parallel differential proteomic studies were performed using 3 canine mammary carcinomas and 3 normal controls in a paired fashion (6 FrFr and 6 FFPE in total). As a result, the FrFr and FFPE differential proteomic datasets exhibited fair consistency in differential expression trends, according to protein molecular function, cellular localization, networks, and pathways. However, FFPE samples were globally slightly less informative, especially concerning the high-MW subproteome. As a further investigation, new insights into the molecular aspects of protein fixation and retrieval were obtained. In conclusion, archival FFPE samples can be reliably used for differential proteomics studies employing a spectral counting GeLC-MS/MS approach, although some typical biases need to be taken into account, and FrFr specimens (when available) should still be considered as the gold standard for clinical proteomics.