Mass spectrometry-based proteomics of endoscopically collected pancreatic fluid in chronic pancreatitis research

MS-based investigation of pancreatic fluid enables the high-throughput identification of proteins present in the pancreatic secretome. Pancreatic fluid is a complex admixture of digestive, inflammatory, and other proteins secreted by the pancreas into the duodenum, and thus is amenable to MS-based proteomic analysis. Recent advances in endoscopic techniques, in particular the endoscopic pancreatic function test (ePFT), have improved the collection methodology of pancreatic fluid for proteomic analysis. Here, we provide an overview of MS-based proteomic techniques as applied to the study of pancreatic fluid. We address sample collection, protein extraction, MS sample preparation and analysis, and bioinformatic approaches, and summarize current MS-based investigations of pancreatic fluid. We then examine the limitations and the future potential of such technologies in the investigation of pancreatic disease. We conclude that pancreatic fluid represents a rich reservoir of potential biomarkers and that the study of the molecular mechanisms of chronic pancreatitis may benefit substantially from MS-based proteomics.     

Searching for potential biomarkers of cisplatin resistance in human ovarian cancer using a label-free LC/MS-based protein quantification method

Platinum-based chemotherapy, such as cisplatin, is the primary treatment for ovarian cancer. However, drug resistance has become a major impediment to the successful treatment of ovarian cancer. To date, the molecular mechanisms of resistance to platinum-based chemotherapy remain unclear. In this study, we applied an LC/MS-based protein quantification method to examine the global protein expression of two pairs of ovarian cancer cell lines, A2780/A2780-CP (cisplatin-sensitive/cisplatin-resistant) and 2008/2008-C13*5.25 (cisplatin-sensitive/cisplatin-resistant). We identified and quantified over 2000 proteins from these cell lines and 760 proteins showed significant expression changes with a false discovery rate of less than 5% between paired groups. Based on the results we obtained, we suggest several potential pathways that may be involved in cisplatin resistance in human ovarian cancer. This study provides not only a new proteomic platform for large-scale quantitative protein analysis, but also important information for discovery of potential biomarkers of cisplatin resistance in ovarian cancer. Furthermore, these results may be clinically relevant for diagnostics, prognostics, and therapeutic improvement for ovarian cancer treatment.     

Functional protease profiling for diagnosis of malignant disease

Clinical proteomic profiling by mass spectrometry (MS) aims at uncovering specific alterations within mass profiles of clinical specimens that are of diagnostic value for the detection and classification of various diseases including cancer. However, despite substantial progress in the field, the clinical proteomic profiling approaches have not matured into routine diagnostic applications so far. Their limitations are mainly related to high-abundance proteins and their complex processing by a multitude of endogenous proteases thus making rigorous standardization difficult. MS is biased towards the detection of low-molecular-weight peptides. Specifically, in serum specimens, the particular fragments of proteolytically degraded proteins are amenable to MS analysis. Proteases are known to be involved in tumour progression and tumour-specific proteases are released into the blood stream presumably as a result of invasive progression and metastasis. Thus, the determination of protease activity in clinical specimens from patients with malignant disease can offer diagnostic and also therapeutic options. The identification of specific substrates for tumour proteases in complex biological samples is challenging, but proteomic screens for proteases/substrate interactions are currently experiencing impressive progress. Such proteomic screens include peptide-based libraries, differential isotope labelling in combination with MS, quantitative degradomic analysis of proteolytically generated neo-N-termini, monitoring the degradation of exogenous reporter peptides with MS, and activity-based protein profiling. In the present article, we summarize and discuss the current status of proteomic techniques to identify tumour-specific protease-substrate interactions for functional protease profiling. Thereby, we focus on the potential diagnostic use of the respective approaches.     

Ensembles of protein termini and specific proteolytic signatures as candidate biomarkers of disease

Early accurate diagnosis and personalized treatment are essential in order to treat complex or fatal diseases such as cancer and autoimmune, cardiovascular and neurodegenerative diseases. To realize this vision, new diagnostic and prognostic biomarkers are urgently required. MS-based proteomics is the most promising approach for protein biomarker identification, but suffers in clinical translation of biomarker candidates that show only quantitative differences from normal tissue. Indeed, success in translating proteomic data to biomarkers in the clinic has been disappointing. Here, we propose that protein termini provide a new opportunity for biomarker discovery due to qualitative differences in intact and new protein termini between diseased and normal tissues. Altered proteolysis occurs in most pathologies. Disease- and process-specific protein modifications, including proteolytic processing and subsequent modification of the terminal amino acids, frequently lead to altered protein activity that plays key roles in the disease process. Thus, mapping of ensembles of characteristic protein termini provides a proteolytic signature of high information content that shows both quantitative and most importantly qualitative differences in different diseases and stage of disease. These unique protein biomarkers have the added benefit of being mechanistically informative by revealing the activity state of the bioactive protein. Moreover, proteome-wide isolation of protein termini leads to generalized sample simplification, thereby enabling up to three orders of magnitude lower LODs compared to traditional shotgun proteomic approaches. We introduce the potential of protein termini for biomarker discovery, briefly review methods enabling large-scale studies of protein termini, and discuss how these may be integrated into a termini-oriented biomarker discovery pipeline from discovery to clinical application.     

Chaperoning heat shock proteins: Proteomic analysis and relevance for normal and dystrophin-deficient muscle

Molecular chaperones play a key role in normal muscle function and during physiological adaptations to extensive exercise and numerous forms of cellular stress. The various classes of HSPs and related chaperones are also involved in the molecular pathogenesis of a large number of neuromuscular diseases. Several MS-based proteomic studies have recently shown that the expression levels of molecular chaperones are severely altered in dystrophin-deficient muscles. Dystrophin isoform Dp427 (where Dp427 is dystrophin protein of 427 kDa) is a large membrane cytoskeletal protein and its deficiency is the primary underlying cause of Duchenne muscular dystrophy. Current efforts have focused on the establishment of a comprehensive biomarker signature of dystrophinopathy in order to improve diagnostic methods, establish reliable prognostic factors and identify novel therapeutic targets. Following an introduction into the biology of HSPs and their general role in skeletal muscle, this review outlines the proteomic profiling of molecular chaperones in dystrophinopathy. The focus is especially on the molecular fate of HSPs cardiovascular HSP (HSPB7), αBC (HSPB5), HSP70 (HSPA) and HSP90 (HSPC) in dystrophin-deficient muscles and their involvement in progressive muscular dystrophy. Furthermore, the potential usage of distinct chaperones as disease markers of secondary pathobiochemical changes for the evaluation of novel treatment options is discussed.     

Prostate cancer serum biomarker discovery through proteomic analysis of alpha‐2 macroglobulin protein complexes

Alpha‐2 macroglobulin (A2M) functions as a universal protease inhibitor in serum and is capable of binding various cytokines and growth factors. In this study, we investigated if immunoaffinity enrichment and proteomic analysis of A2M protein complexes from human serum could improve detection of biologically relevant and novel candidate protein biomarkers in prostate cancer. Serum samples from six patients with androgen‐independent, metastatic prostate cancer and six control patients without malignancy were analyzed by immunoaffinity enrichment of A2M protein complexes and MS identification of associated proteins. Known A2M substrates were reproducibly identified from patient serum in both cohorts, as well as proteins previously undetected in human serum. One example is heat shock protein 90 alpha (HSP90α), which was identified only in the serum of cancer patients in this study. Using an ELISA, the presence of HSP90α in human serum was validated on expanded test cohorts and found to exist in higher median serum concentrations in prostate cancer (n = 18) relative to control (n = 13) patients (median concentrations 50.7 versus 27.6 ng/mL, respectively, p = 0.001). Our results demonstrate the technical feasibility of this approach and support the analysis of A2M protein complexes for proteomic‐based serum biomarker discovery.     

Phosphoproteomics for the discovery of kinases as cancer biomarkers and drug targets

Early detection and targeted therapy represent a novel regimen of cancer management. The understanding of receptor tyrosine kinases in tumorigenesis at the molecular level has led to the first generation of kinase inhibitors for anticancer therapy that targets a specific kinase or pathway. While the therapeutic advantage is obvious, targeted therapy often relapses and results in drug resistance for advanced cancers. To achieve feasible early detection and better efficacy of therapeutics targeting multiple pathways, significantly more biomarkers and drug targets are in demand, especially for individualized therapy. Recent advances in phosphoprotein enrichment and MS technologies for quantitative phosphoproteome analysis provide great opportunities in the identification and validation of kinases as drug targets. The MS-based phosphoproteomic technologies would be useful tools as well for the identification of phosphosignatures unique to a specific type or subtype of cancer and drug responsive biomarkers. This review summarizes the major kinases acting as cancer biomarkers and drug targets, the advances of MS-based phosphoproteomic technologies, and some potential values and challenges of this emerging phosphoproteomics-based biomarker and drug target discovery field. Strategies for global, targeted, and quantitative phosphoproteomics are discussed, and some recent interesting applications are also evaluated.     

Proteomics in human cancer research

Proteomics is now widely employed in the study of cancer. Many laboratories are applying the rapidly emerging technologies to elucidate the underlying mechanisms associated with cancer development, progression, and severity in addition to developing drugs and identifying patients who will benefit most from molecular targeted compounds. Various proteomic approaches are now available for protein separation and identification, and for characterization of the function and structure of candidate proteins. In spite of significant challenges that still exist, proteomics has rapidly expanded to include the discovery of novel biomarkers for early detection, diagnosis and prognostication (clinical application), and for the identification of novel drug targets (pharmaceutical application). To achieve these goals, several innovative technologies including 2-D-difference gel electrophoresis, SELDI, multidimensional protein identification technology, isotope-coded affinity tag, solid-state and suspension protein array technologies, X-ray crystallography, NMR spectroscopy, and computational methods such as comparative and de novo structure prediction and molecular dynamics simulation have evolved, and are being used in different combinations. This review provides an overview of the field of proteomics and discusses the key proteomic technologies available to researchers. It also describes some of the important challenges and highlights the current pharmaceutical and clinical applications of proteomics in human cancer research.     

Understanding the pathogenesis of endometriosis through proteomics: Recent advances and future prospects

Endometriosis is a complex gynecological disease, characterized by the presence and growth of endometrial tissue outside the uterus, resulting in pelvic pain and infertility. It occurs in 10% of women in their reproductive age. The viable endometrial cells enter the peritoneal cavity by retrograde menstruation, implant, and cause lesions ectopically; depending on their ability to survive, attach, grow, and invade. These “normal” endometrial cells turn “endometriotic” apparently because of inherent abnormalities present in them. Information on these molecular abnormalities is now being sought through proteomic approaches. Recent proteome-based comparisons between the eutopic endometrium from normal women and patients with endometriosis have revealed several proteins (many of which are shown to have a role in several cancers), of which a few have been validated as potential players in the etiology of endometriosis. After an initial in-flow of information from these proteome studies of eutopic endometrium, focus now needs to be expanded to the changes in the various protein PTMs and their upstream effectors present in these tissues. Early diagnosis of endometriosis through noninvasive means is the need of the hour as well—which would require the use of the presently existing immunoassays, along with the advancing MS-based proteomics. In this review, we aim to discuss these future thrust areas of human endometriosis proteomics and also present the proteomic advances made so far in understanding the molecular basis of endometriosis.     

Degradomics in Biomarker Discovery

The upregulation of protease expression and proteolytic activity is implicated in numerous pathological conditions such as neurodegeneration, cancer, cardiovascular and autoimmune diseases, and bone degeneration. During disease progression, various proteases form characteristic patterns of cleaved proteins and peptides, which can affect disease severity and course of progression. It has been shown that qualitative and quantitative monitoring of cleaved protease substrates can provide relevant prognostic, diagnostic, and therapeutic information. As proteolytic fragments and peptides generated in the affected tissue are commonly translocated to blood, urine, and other proximal fluids, their possible application as biomarkers is the subject of ongoing research. The field of degradomics has been established to enable the global identification of proteolytic events on the organism level, utilizing proteomic approaches and sample preparation techniques that facilitate the detection of proteolytic processing of protease substrates in complex biological samples. In this review, some of the latest developments in degradomic methodologies used for the identification and validation of biologically relevant proteolytic events and their application in the search for clinically relevant biomarker candidates are presented. The current state of degradomics in clinics is discussed and the future perspectives of the field are outlined.     

Proteomic approaches to the study of malignant lymphoma: Analyses on patient samples

We describe the application of proteomic techniques for protein profiling and biomarker discovery in malignant lymphoma. Hematologic malignancies are primarily characterized by their clinical, morphological, immunophenotypical, and molecular-genetic features. However, when based on these parameters, apparently identical lymphomas may show distinct clinical courses, suggesting underlying biological heterogeneity. Recent proteomic analyses have identified differences in protein expression both with regard to subclassification of the malignant lymphoma entities, as well as in correlation with clinical outcome. In this review, studies on quantification of differential protein expression in and between malignant lymphoma entities are included. Studies are included that are based on patient samples, that is, serum/plasma or cytological specimens, as well as intact tumor tissues, together with studies that focus on tumor cells alone, or in conjunction with the tumor microenvironment. For biomarker discovery in malignant lymphoma, these approaches are used to uncover the underlying biological mechanisms and identify proteins with potential diagnostic and prognostic utility, either as predictive biomarkers or as novel future treatment targets.     

Application of proteomics in the study of rodent models of cancer

The molecular and cellular mechanisms underlying the multistage processes of cancer progression and metastasis are complex and strictly depend on the interplay between tumor cells and surrounding tissues. Identification of protein aberrations in cancer pathophysiology requires a physiologically relevant experimental model. The mouse offers such a model to identify protein changes associated with tumor initiation and progression, metastasis development, tumor/microenvironment interplay, and treatment responses. Furthermore, the mouse model offers the ability to collect samples at any stage in tumor development from highly matched disease cases and controls with identical environmental and genetic backgrounds, thus providing an excellent method for biomarker discovery. Xenograft and genetically engineered mouse models have been widely used to identify proteomic patterns in tumor tissues and plasma samples associated with different stages of human cancer, including early cancer detection and development of metastasis. Here, we review proteomic strategies to identify proteins involved in key cancer processes within such animal models as well as biomarkers for diagnosis, prognosis, and monitoring of cancer progression and treatment response. Central to such studies is the ability to ensure at an early stage that the identified proteins are of clinical relevance by examining relevant specimens from larger cohorts of cancer patients.     

Proteomic profiling of 13 paired ductal infiltrating breast carcinomas and non-tumoral adjacent counterparts

According to recent statistics, breast cancer remains one of the leading causes of death among women in Western countries. Breast cancer is a complex and heterogeneous disease, presently classified into several subtypes according to their cellular origin. Among breast cancer histotypes, infiltrating ductal carcinoma represents the most common and potentially aggressive form. Despite the current progress achieved in early cancer detection and treatment, including the new generation of molecular therapies, there is still need for identification of multiparametric biomarkers capable of discriminating between cancer subtypes and predicting cancer progression for personalized therapies. One established step in this direction is the proteomic strategy, expected to provide enough information on breast cancer profiling. To this aim, in the present study we analyzed 13 breast cancer tissues and their matched non-tumoral tissues by 2-DE. Collectively, we identified 51 protein spots, corresponding to 34 differentially expressed proteins, which may represent promising candidate biomarkers for molecular-based diagnosis of breast cancer and for pattern discovery. The relevance of these proteins as factors contributing to breast carcinogenesis is discussed.     

Revisiting the Warburg effect in cancer cells with proteomics. The emergence of new approaches to diagnosis, prognosis and therapy

Most cancer cells exhibit elevated levels of glycolysis and this metabolic pathway seems to be related to a greater glucose uptake. This phenomenon, known as the Warburg effect, is considered one of the most fundamental metabolic alterations during malignant transformation. Originally, Warburg hypothesised that the aerobic glycolysis of cancer cells could be just an aspect of a more complex metabolic adaptation. However, this intriguing discovery was partially misinterpreted and disregarded over time. In recent years, the peculiarities of cancer cell metabolism have been re-evaluated in light of new metabolic data that seem to confirm and to widen the original concept of the Warburg effect. In fact, biochemical, molecular, and, above all, proteomic studies on the multifaceted roles of glycolytic enzymes in cancer cells in general, and in cancer stem cells in particular, seem to suggest more complex functional adaptations. These adaptations result in significantly altered protein expression patterns, and they have fundamental implications for diagnosis, prognosis and therapy. Revisiting the Warburg effect in cancer cells with a proteomic approach could deepen our knowledge of cancer cell metabolism and of cancer cell biology in general. Moreover, by identifying useful diagnostic, prognostic and therapeutic targets, it could significantly impact clinical practice.     

Vascular proteomics

The characterization of patients with acute coronary syndromes (ACS) at the molecular and cellular levels provides a novel vision for understanding the pathological and clinical expression of the disease. Recent advances in proteomic technologies permit the evaluation of systematic changes in protein expression in many biological systems and have been extensively applied to cardiovascular diseases (CVD). The cardiovascular system is in permanent intimate contact with blood, making blood-based biomarker discovery a particularly worthwhile approach. Thus, proteomics can potentially yield novel biomarkers reflecting CVD, establish earlier detection strategies, and monitor response to therapy. Here we review the different proteomic strategies used in the study of atherosclerosis and the novel proteins differentially expressed and secreted by atherosclerotic lesions which constitute novel potential biomarkers (HSP-27, Cathepsin D). Special attention is paid to MS-Imaging of atheroma plaque and the generation, for the first time, of 2-D images of lipids, showing the distribution of these molecules in the different areas of the atherosclerotic lesions. In addition new potential biomarkers have been identified in plasma (amyloid A1α, transtherytin), circulating cells (protein profile in monocytes from ACS patients) and individual cells constituents of atheroma plaques (endothelial, VSMC, macrophages) which provide novel insights into vascular pathophysiology.     

Proteomic-based approach for biomarkers discovery in early detection of invasive urothelial carcinoma

Identification of reliable non-invasive markers for the detection of invasive phenotype of urothelial carcinoma is needed. This study characterizes and compares protein expression profiles of adjacent non-neoplastic urothelium and invasive urothelial carcinoma to identify biomarkers for early detection of de novo bladder cancer. Differences in protein expression between adjacent non-neoplastic and high-grade, stage T4, grade 3 invasive urothelial carcinoma tissues were investigated using 2-DE, MALDI-TOF-MS, and data processing. Ingenuity Pathway Analysis (IPA) was applied to examine the biological mechanisms represented by the altered proteins. The 2-DE of the adjacent non-neoplastic urothelium and invasive urothelial carcinoma showed reproducibly similar proteomic mapping for each group distinguishing adjacent non-neoplastic urothelium from invasive urothelial carcinoma. Twenty-one proteins were altered in expression and one of these proteins, Choroideremia-like protein (CHML) was significantly overexpressed (p<0.005) and therefore was analyzed further using IHC and Western blot. Urothelial carcinoma presented an elevated expression of CHML but not adjacent non-neoplastic or normal bladder tissues. IPA revealed the involvement of CHML in cell morphology, cellular assembly, and organization. Further investigation is warranted to elucidate the biological significance of CHML and to validate its role as a biomarker for early detection of invasive urothelial carcinoma de novo.     

Mapping orphan proteases by proteomics: Meprin metalloproteases deciphered as potential therapeutic targets

The protease web is a synonym for highly regulated molecular networks comprising enzymes, substrates, inhibitors, and other regulatory proteins. Latest high-throughput methods provided huge data sets, revealing an amazing complexity of proteolytic systems important for health and disease. Based on our previous studies, we discuss major problems and questions that have to be solved to gain precise insight into the regulation of the protease web and its impact on pathophysiological conditions. The goal is a combination of different proteomic approaches that help to investigate specific protease function at a glance. Exemplarily, the characterization of the metalloproteases meprin α and meprin β by proteomic identification of cleavage sites and terminal amine isotopic labeling of substrates demonstrates the power of MS-based techniques. Meprins are rather orphan proteases and could not be assigned to precise biological functions until recently. Proteomics helped to identify meprin α and meprin β being important for collagen assembly and deposition in skin, which makes them potential therapeutic targets in fibrotic conditions. Additionally, identification of the cleavage site specificity provides the basis for the development of activity-based probes and small compound inhibitors, important for the regulation of meprin activity and subsequent treatment of associated diseases.