Protein Biomarker Discovery Studies on Urinary sEV Fractions Separated with UF-SEC for the First Diagnosis and Detection of Recurrence in Bladder Cancer Patients.

Urinary extracellular vesicles (EVs) are an attractive source of bladder cancer biomarkers. Here, a protein biomarker discovery study was performed on the protein content of small urinary EVs (sEVs) to identify possible biomarkers for the primary diagnosis and recurrence of non-muscle-invasive bladder cancer (NMIBC). The sEVs were isolated by ultrafiltration (UF) in combination with size-exclusion chromatography (SEC). The first part of the study compared healthy individuals with NMIBC patients with a primary diagnosis. The second part compared tumor-free patients with patients with a recurrent NMIBC diagnosis. The separated sEVs were in the size range of 40 to 200 nm. Based on manually curated high quality mass spectrometry (MS) data, the statistical analysis revealed 69 proteins that were differentially expressed in these sEV fractions of patients with a first bladder cancer tumor vs. an age- and gender-matched healthy control group. When the discriminating power between healthy individuals and first diagnosis patients is taken into account, the biomarkers with the most potential are MASP2, C3, A2M, CHMP2A and NHE-RF1. Additionally, two proteins (HBB and HBA1) were differentially expressed between bladder cancer patients with a recurrent diagnosis vs. tumor-free samples of bladder cancer patients, but their biological relevance is very limited.

Macrophages Release Extracellular Vesicles of Different Properties and Composition Following Exposure to Nanoparticles.

Extracellular vesicles are membrane-bound carriers with complex cargoes, which play a major role in intercellular communication, for instance, in the context of the immune response. Macrophages are known to release extracellular vesicles in response to different stimuli, and changes in their size, number, and composition may provide important insights into the responses induced. Macrophages are also known to be highly efficient in clearing nanoparticles, when in contact with them, and in triggering the immune system. However, little is known about how the nature and composition of the vesicles released by these cells may vary upon nanoparticle exposure. In order to study this, in this work, alveolar-like macrophages were exposed to a panel of nanoparticles with varying surface and composition, including amino-modified and carboxylated polystyrene and plain silica. We previously showed that these nanoparticles induced very different responses in these cells. Here, experimental conditions were carefully tuned in order to separate the extracellular vesicles released by the macrophages several hours after exposure to sub-toxic concentrations of the same nanoparticles. After separation, different methods, including high-sensitivity flow cytometry, TEM imaging, Western blotting, and nanoparticle tracking analysis, were combined in order to characterize the extracellular vesicles. Finally, proteomics was used to determine their composition and how it varied upon exposure to the different nanoparticles. Our results show that depending on the nanoparticles' properties. The macrophages produced extracellular vesicles of varying number, size, and protein composition. This indicates that macrophages release specific signals in response to nanoparticles and overall suggests that extracellular vesicles can reflect subtle responses to nanoparticles and nanoparticle impact on intercellular communication.

PPE38-Secretion-Dependent Proteins of M. tuberculosis Alter NF-kB Signalling and Inflammatory Responses in Macrophages.

It was previously shown that secretion of PE-PGRS and PPE-MPTR proteins is abolished in clinical M. tuberculosis isolates with a deletion in the ppe38-71 operon, which is associated with increased virulence. Here we investigate the proteins dependent on PPE38 for their secretion and their role in the innate immune response using temporal proteomics and protein turnover analysis in a macrophage infection model. A decreased pro-inflammatory response was observed in macrophages infected with PPE38-deficient M. tuberculosis CDC1551 as compared to wild type bacteria. We could show that dampening of the pro-inflammatory response is associated with activation of a RelB/p50 pathway, while the canonical inflammatory pathway is active during infection with wild type M. tuberculosis CDC1551. These results indicate a molecular mechanism by which M. tuberculosis PE/PPE proteins controlled by PPE38 have an effect on modulating macrophage responses through NF-kB signalling.

Urinary extracellular vesicles: A position paper by the Urine Task Force of the International Society for Extracellular Vesicles.

Urine is commonly used for clinical diagnosis and biomedical research. The discovery of extracellular vesicles (EV) in urine opened a new fast-growing scientific field. In the last decade urinary extracellular vesicles (uEVs) were shown to mirror molecular processes as well as physiological and pathological conditions in kidney, urothelial and prostate tissue. Therefore, several methods to isolate and characterize uEVs have been developed. However, methodological aspects of EV separation and analysis, including normalization of results, need further optimization and standardization to foster scientific advances in uEV research and a subsequent successful translation into clinical practice. This position paper is written by the Urine Task Force of the Rigor and Standardization Subcommittee of ISEV consisting of nephrologists, urologists, cardiologists and biologists with active experience in uEV research. Our aim is to present the state of the art and identify challenges and gaps in current uEV-based analyses for clinical applications. Finally, recommendations for improved rigor, reproducibility and interoperability in uEV research are provided in order to facilitate advances in the field.

Urinary Protein Biomarker Panel for the Diagnosis of Antibody-Mediated Rejection in Kidney Transplant Recipients.

INTRODUCTION: Antibody-mediated rejection (ABMR) impacts kidney allograft outcome. The diagnosis is made based on findings from invasive kidney transplant biopsy specimens. The aim of this study was to identify a noninvasive urinary protein biomarker for ABMR after kidney transplantation. METHODS: We performed a multicenter case-control study to identify a urinary biomarker for ABMR (training cohort, n = 249) and an independent, prospective multicenter cohort study for validation (n = 391). We used concomitant biopsies to classify the samples according to the Banff classification. After untargeted protein identification and quantification, we used a support vector machine to train the model in the training cohort. The primary endpoint was the diagnostic accuracy of the urinary biomarker for ABMR in the validation cohort. RESULTS: We identified a set of 10 urinary proteins that accurately discriminated patients with (n = 60) and without (n = 189) ABMR in the training cohort with an area under the curve (AUC) of 0.98 (95% confidence interval [CI], 0.96-1.00). The diagnostic accuracy was maintained in the validation cohort (AUC, 0.88; 95% CI, 0.8-0.93) for discriminating the presence (n = 43) from the absence (n = 348) of ABMR. The negative predictive value of the 10-protein marker set for exclusion of ABMR was 0.99, and the positive predictive value was 0.33. The diagnostic accuracy was independent of the reason for performing the biopsy, time after transplantation, and better than the accuracy of gross proteinuria (AUC, 0.76). CONCLUSIONS: We identified and validated a urinary protein biomarker set that can be used to exclude ABMR.

Implementation of MALDI Mass Spectrometry Imaging in Cancer Proteomics Research: Applications and Challenges.

Studying the proteome-the entire set of proteins in cells, tissues, organs and body fluids-is of great relevance in cancer research, as differential forms of proteins are expressed in response to specific intrinsic and extrinsic signals. Discovering protein signatures/pathways responsible for cancer transformation may lead to a better understanding of tumor biology and to a more effective diagnosis, prognosis, recurrence and response to therapy. Moreover, proteins can act as a biomarker or potential drug targets. Hence, it is of major importance to implement proteomic, particularly mass spectrometric, approaches in cancer research, to provide new crucial insights into tumor biology. Recently, mass spectrometry imaging (MSI) approaches were implemented in cancer research, to provide individual molecular characteristics of each individual tumor while retaining molecular spatial distribution, essential in the context of personalized disease management and medicine.

MALDI Mass Spectrometry Imaging Linked with Top-Down Proteomics as a Tool to Study the Non-Small-Cell Lung Cancer Tumor Microenvironment.

Advanced non-small-cell lung cancer (NSCLC) is generally linked with a poor prognosis and is one of the leading causes of cancer-related deaths worldwide. Since only a minority of the patients respond well to chemotherapy and/or targeted therapies, immunotherapy might be a valid alternative in the lung cancer treatment field, as immunotherapy attempts to strengthen the body's own immune response to recognize and eliminate malignant tumor cells. However, positive response patterns to immunotherapy remain unclear. In this study, we demonstrate how immune-related factors could be visualized from single NSCLC tissue sections (Biobank@UZA) while retaining their spatial information by using matrix assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI), in order to unravel the molecular profile of NSCLC patients. In this way, different regions in lung cancerous tissues could be discriminated based on the molecular composition. In addition, we linked visualization (MALDI MSI) and identification (based on liquid chromatography higher resolution mass spectrometry) of the molecules of interest for the correct biological interpretation of the observed molecular differences within the area in which these molecules are detected. This is of major importance to fully understand the underlying molecular profile of the NSCLC tumor microenvironment.

Bladder Cancer Diagnosis and Follow-Up: The Current Status and Possible Role of Extracellular Vesicles.

Diagnostic methods currently used for bladder cancer are cystoscopy and urine cytology. Cystoscopy is an invasive tool and has low sensitivity for carcinoma in situ. Urine cytology is non-invasive, is a low-cost method, and has a high specificity but low sensitivity for low-grade urothelial tumors. Despite the search for urinary biomarkers for the early and non-invasive detection of bladder cancer, no biomarkers are used at the present in daily clinical practice. Extracellular vesicles (EVs) have been recently studied as a promising source of biomarkers because of their role in intercellular communication and tumor progression. In this review, we give an overview of Food and Drug Administration (FDA)-approved urine tests to detect bladder cancer and why their use is not widespread in clinical practice. We also include non-FDA approved urinary biomarkers in this review. We describe the role of EVs in bladder cancer and their possible role as biomarkers for the diagnosis and follow-up of bladder cancer patients. We review recently discovered EV-derived biomarkers for the diagnosis of bladder cancer.

The challenges of peptidomics in complementing proteomics in a clinical context.

Naturally occurring peptides, including growth factors, hormones, and neurotransmitters, represent an important class of biomolecules and have crucial roles in human physiology. The study of these peptides in clinical samples is therefore as relevant as ever. Compared to more routine proteomics applications in clinical research, peptidomics research questions are more challenging and have special requirements with regard to sample handling, experimental design, and bioinformatics. In this review, we describe the issues that confront peptidomics in a clinical context. After these hurdles are (partially) overcome, peptidomics will be ready for a successful translation into medical practice.

Exosomal miRNA Analysis in Non-small Cell Lung Cancer (NSCLC) Patients' Plasma Through qPCR: A Feasible Liquid Biopsy Tool.

The discovery of alterations in the EGFR and ALK genes, amongst others, in NSCLC has driven the development of targeted-drug therapy using selective tyrosine kinase inhibitors (TKIs). To optimize the use of these TKIs, the discovery of new biomarkers for early detection and disease progression is mandatory. These plasma-isolated exosomes can be used as a non-invasive and repeatable way for the detection and follow-up of these biomarkers. One ml of plasma from 12 NSCLC patients, with different mutations and treatments (and 6 healthy donors as controls), were used as exosome sources. After RNAse treatment, in order to degrade circulating miRNAs, the exosomes were isolated with a commercial kit and resuspended in specific buffers for further analysis. The exosomes were characterized by western blotting for ALIX and TSG101 and by transmission electron microscopy (TEM) analysis, the standard techniques to obtain biochemical and dimensional data of these nanovesicles. Total RNA extraction was performed with a high yield commercial kit. Due to the limited miRNA-content in exosomes, we decided to perform retro-transcription PCR using an individual assay for each selected miRNA. A panel of miRNAs (30b, 30c, 103, 122, 195, 203, 221, 222), all correlated with NSCLC disease, were analyzed taking advantage of the remarkable sensitivity and specificity of Real-Time PCR analysis; mir-1228-3p was used as endogenous control and data were processed according to the formula 2(-) (ΔΔct) (13). Control values were used as baseline and results are shown in logarithmic scale.

Proteomics in cancer research: Are we ready for clinical practice?

Although genomics has delivered major advances in cancer prognostics, treatment and diagnostics, it still only provides a static image of the situation. To study more dynamic molecular entities, proteomics has been introduced into the cancer research field more than a decade ago. Currently, however, the impact of clinical proteomics on patient management and clinical decision-making is low and the implementations of scientific results in the clinic appear to be scarce. The search for cancer-related biomarkers with proteomics however, has major potential to improve risk assessment, early detection, diagnosis, prognosis, treatment selection and monitoring. In this review, we provide an overview of the transition of oncoproteomics towards translational oncology. We describe which lessons are learned from currently approved protein biomarkers and previous proteomic studies, what the pitfalls and challenges are in clinical proteomics applications, and how proteomic research can be successfully translated into medical practice.

Determination of variation parameters as a crucial step in designing TMT-based clinical proteomics experiments.

In quantitative shotgun proteomic analyses by liquid chromatography and mass spectrometry, a rigid study design is necessary in order to obtain statistically relevant results. Hypothesis testing, sample size calculation and power estimation are fundamental concepts that require consideration upon designing an experiment. For this reason, the reproducibility and variability of the proteomic platform needs to be assessed. In this study, we evaluate the technical (sample preparation), labeling (isobaric labels), and total (biological + technical + labeling + experimental) variability and reproducibility of a workflow that employs a shotgun LC-MS/MS approach in combination with TMT peptide labeling for the quantification of peripheral blood mononuclear cell (PBMC) proteome. We illustrate that the variability induced by TMT labeling is small when compared to the technical variation. The latter is also responsible for a substantial part of the total variation. Prior knowledge about the experimental variability allows for a correct design, a prerequisite for the detection of biologically significant disease-specific differential proteins in clinical proteomics experiments.

Liquid biopsies in lung cancer: the new ambrosia of researchers.

In the last decades the approach to cancer patient management has been deeply revolutionized. We are moving from a "one-fits-all" strategy to the "personalized medicine" based on the molecular characterization of the tumor. In this new era it is becoming more and more clear that the monitoring of the disease is fundamental for the success of the treatment, thus there is the need of new biomarker discovery. More precisely in the last years the scientific community has started to use the term "liquid biopsy". A liquid biopsy is a liquid biomarker that can be easily isolated from many body fluids (blood, saliva, urine, ascites, pleural effusion, etc.) and, as well as a tissue biopsy, a representative of the tissue from which it is spread. In this review we will focus our attention on circulating tumor cells, circulating tumor DNA, exosomes and secretomes with the aim to underlie their usefulness and potential application in a clinical setting for lung cancer patient management.

Colorectal cancer biomarker discovery and validation using LC-MS/MS-based proteomics in blood: truth or dare?

Globally, colorectal cancer (CRC) is the third most common malignant neoplasm. However, highly sensitive, specific, noninvasive tests that allow CRC diagnosis at an early stage are still needed. As circulatory blood reflects the physiological status of an individual and/or the disease status for several disorders, efforts have been undertaken to identify candidate diagnostic CRC markers in plasma and serum. In this review, the challenges, bottlenecks and promising properties of mass spectrometry (MS)-based proteomics in blood are discussed. More specifically, important aspects in clinical design, sample retrieval, sample preparation, and MS analysis are presented. The recent developments in targeted MS approaches in plasma or serum are highlighted as well.

Proteomic analysis of formalin-fixed paraffin-embedded colorectal cancer tissue using tandem mass tag protein labeling.

In clinical research, repositories of biological samples form a rich source of clinical material for biomarker studies. Banked material, however, is often not stored in optimal conditions regarding the technology used for biomarker research. A case in point is formalin-fixed paraffin-embedded (FFPE) tissue that could be used to obtain large cohorts of samples over a short period of time, as these tissues are routinely prepared for pathological analysis. However, in the context of mass spectrometry based peptide-centric proteomics, protein extraction and identification can be hampered by formalin-induced crosslinking. Furthermore, the molecular formalin crosslinks might be entangled differently across various samples, making it more difficult to reproducibly extract the same proteins from different samples. In this study, we establish the crosslink variability using Tandem Mass Tag (TMT) protein labeling followed by digestion, separation, identification and quantification of proteins extracted from FFPE colorectal cancer and paired healthy tissues. Moreover, by applying de novo interpretation of tandem mass spectra and subsequent analysis by Peaks PTM, unspecified modifications could be elucidated, leading to increased protein and proteome coverage. This approach might be useful for future FFPE proteomics studies.

Interindividual variation in the proteome of human peripheral blood mononuclear cells.

Peripheral blood mononuclear cells (PBMCs) are main actors in inflammatory processes and linked to many diseases, including rheumatoid arthritis, atherosclerosis, asthma, HIV and cancer. Moreover, they seem an interesting 'surrogate tissue' that can be used in biomarker discovery. In order to get a good experimental design for quantitative expression studies, the knowledge of the interindividual variation is an essential part. Therefore, PBMCs were isolated from 24 healthy volunteers (15 males, 9 females, ages 63-86) with no clinical signs of inflammation. The extracted proteins were separated using the two dimensional difference in gel electrophoresis technology (2D-DIGE), and the gel images were processed with the DeCyder 2D software. Protein spots present in at least 22 out of 24 healthy volunteers were selected for further statistical analysis. Determination of the coefficient of variation (CV) of the normalized spot volume values of these proteins, reveals that the total variation of the PBMC proteome varies between 12,99% to 148,45%, with a mean value of 28%. A supplemental look at the causes of technical variation showed that the isolation of PBMCs from whole blood is the factor which influences the experimental variance the most. This isolation should be handled with extra care and an additional washing step would be beneficial. Knowing the extent of variation, we show that at least 10 independent samples per group are needed to obtain statistical powerful data. This study demonstrates the importance of considering variance of a human population for a good experimental design for future protein profiling or biomarker studies.

The isotopic distribution conundrum.

Although access to high-resolution mass spectrometry (MS), especially in the field of biomolecular MS, is becoming readily available due to recent advances in MS technology, the accompanied information on isotopic distribution in high-resolution spectra is not used at its full potential, mainly because of lack of knowledge and/or awareness. In this review, we give an insight into the practical problems related to calculating the isotopic distribution for large biomolecules, and present an overview of methods for the calculation of the isotopic distribution. We discuss the key events that triggered the development of various algorithms and explain the rationale of how and why the various isotopic-distribution calculations were performed. The review is focused around the developmental stages as briefly outlined below, starting with the first observation of an isotopic distribution. The observations of Beynon in the field of organic MS that chlorine appeared in a mass spectrum as two variants with odds 3:1 lie at the basis of the first wave of algorithms for the calculation of the isotopic distribution, based on the atomic composition of a molecule. From here on, we explain why more complex biomolecules such as peptides exhibit a highly complex isotope pattern when assayed by MS, and we discuss how combinatorial difficulties complicate the calculation of the isotopic distribution on computers. For this purpose, we highlight three methods, which were introduced in the 1980s. These are the stepwise procedure introduced by Kubinyi, the polynomial expansion from Brownawell and Fillippo, and the multinomial expansion from Yergey. The next development was instigated by Rockwood, who suggested to decompose the isotopic distribution in terms of their nucleon count instead of the exact mass. In this respect, we could claim that the term "aggregated" isotopic distribution is more appropriate. Due to the simplification of the isotopic distribution to its aggregated counterpart, Rockwood was able to use the convolution for the calculation of the "aggregated" isotopic distribution. Convolution methods are computationally efficient and economic in their memory usage. We spend a section on the work introduced by Rockwood during the 1990s. Due to recent breakthroughs in mass spectrometric technology and the widespread high-resolution instruments (e.g., FTICR-MS, FTOrbitrap-MS, and TOF-MS) that provide high-resolution, isotope-resolved, accurate mass data, there is an emerging need for algorithms that can calculate isotopic distributions for large biomolecules. The number of recent publications on this topic does witness this trend. The new methods are mostly based on complex mathematical developments such as, for example, cellular automata (Meija and Caruso [2004]. J Am Soc Mass Spectrom, 15(5):654-658), dynamic programming (Snider [2007]. J Am Soc Mass Spectrom, 18:1511-1515), and hierarchical models (Li et al. [2008] J Am Soc Mass Spectrom, 19:1867-1874). We also comment on the ideas to use Punnet squares and Pascal's triangle to introduce the concept of the isotopic distribution for educational and didactic purposes.

Unraveling tobacco BY-2 protein complexes with BN PAGE/LC-MS/MS and clustering methods.

To understand physiological processes, insight into protein complexes is very important. Through a combination of blue native gel electrophoresis and LC-MS/MS, we were able to isolate protein complexes and identify their potential subunits from Nicotiana tabacum cv. Bright Yellow-2. For this purpose, a bioanalytical approach was used that works without a priori knowledge of the interacting proteins. Different clustering methods (e.g., k-means and hierarchical clustering) and a biclustering approach were evaluated according to their ability to group proteins by their migration profile and to correlate the proteins to a specific complex. The biclustering approach was identified as a very powerful tool for the exploration of protein complexes of whole cell lysates since it allows for the promiscuous nature of proteins. Furthermore, it searches for associations between proteins that co-occur frequently throughout the BN gel, which increases the confidence of the putative associations between co-migrating proteins. The statistical significance and biological relevance of the profile clusters were verified using functional gene ontology annotation. The proof of concept for identifying protein complexes by our BN PAGE/LC-MS/MS approach is provided through the analysis of known protein complexes. Both well characterized long-lived protein complexes as well as potential temporary sequential multi-enzyme complexes were characterized.

PACAP and PDF signaling in the regulation of mammalian and insect circadian rhythms.

Endogenous circadian clocks are inherent to all living organisms. They are needed to guarantee successful life since they regulate very important biological processes such as behavior and reproduction. Secretin-like G-protein coupled receptors are very important factors in the signal transduction pathways of circadian clocks. In this review, we will focus on the role of two secretin-like signaling pathways that play an important role in the regulation of the mammalian and the insect clock, respectively: the pituitary adenylate cyclase-activating polypeptide (PACAP) and pigment dispersing factor (PDF) signaling pathways. Both pathways are most likely related although their function in the biological clock differs.

FMRFamide related peptide ligands activate the Caenorhabditis elegans orphan GPCR Y59H11AL.1.

G-protein coupled receptors (GPCRs) are ancient molecules that can sense environmental and physiological signals. Currently, the majority of the predicted Caenorhabditis elegans GPCRs are orphan. Here, we describe the characterization of such an orphan C. elegans GPCR, which is categorized in the tachykinin-like group of receptors. Since the C. elegans genome predicts only one tachykinin-like peptide (SFDRMGGTEFGLM), which could not activate the receptor, we hypothesized that one or some of the numerous FMRFamide related peptides (FaRPs) could be the cognate ligands for this receptor. This hypothesis was based on the suggestion that RFamides may be ancestral neuropeptides, from which a lot of the amidated neuropeptides, including tachykinins, derived. Indeed, we found that the orphan receptor encoded by the Y59H11AL.1 gene is activated by several C. elegans neuropeptides, including SPMERSAMVRFamide. These peptides activate the receptor in a concentration-dependent way.