Quantitative proteomics and biomarker discovery in human cancer

Proteomics: Unraveling the Cross Talk Between Innate Immunity and Disease Pathophysiology, Diagnostics, and Treatment Options

Inflammation is crucial in diseases, and proteins play a key role in the interplay between innate immunity and pathology. This review explores how proteomics helps understanding this relationship, focusing on diagnosis and treatment. We explore the dynamic innate response and the significance of proteomic techniques in deciphering the complex network of proteins involved in prevalent diseases, including infections, cancer, autoimmune and neurodegenerative disorders. Proteomics identifies key proteins in host-pathogen interactions, shedding light on infection mechanisms and inflammation. These discoveries hold promise for diagnostic tools, therapies, and vaccines. In cancer research, proteomics reveals innate signatures associated with tumor development, immune evasion, and therapeutic response. Additionally, proteomic analysis has unveiled autoantigens and dysregulation of the innate immune system in autoimmunity, offering opportunities for early diagnosis, disease monitoring, and new therapeutic targets. Moreover, proteomic analysis has identified altered protein expression patterns in neurodegenerative diseases like Alzheimer's and Parkinson's, providing insights into potential therapeutic strategies. Proteomics of the innate immune system provides a comprehensive understanding of disease mechanisms, identifies biomarkers, and enables effective interventions in various diseases. Despite still in its early stages, this approach holds great promise to revolutionize innate immunity research and significantly improve patient outcomes across a wide range of diseases.

Oncogenic Proteomics Approaches for Translational Research and HIV-Associated Malignancy Mechanisms

Recent advances in the field of proteomics have allowed extensive insights into the molecular regulations of the cell proteome. Specifically, this allows researchers to dissect a multitude of signaling arrays while targeting for the discovery of novel protein signatures. These approaches based on data mining are becoming increasingly powerful for identifying both potential disease mechanisms as well as indicators for disease progression and overall survival predictive and prognostic molecular markers for cancer. Furthermore, mass spectrometry (MS) integrations satisfy the ongoing demand for in-depth biomarker validation. For the purpose of this review, we will highlight the current developments based on MS sensitivity, to place quantitative proteomics into clinical settings and provide a perspective to integrate proteomics data for future applications in cancer precision medicine. We will also discuss malignancies associated with oncogenic viruses such as Acquire Immunodeficiency Syndrome (AIDS) and suggest novel mechanisms behind this phenomenon. Human Immunodeficiency Virus type-1 (HIV-1) proteins are known to be oncogenic per se, to induce oxidative and endoplasmic reticulum stresses, and to be released from the infected or expressing cells. HIV-1 proteins can act alone or in collaboration with other known oncoproteins, which cause the bulk of malignancies in people living with HIV-1 on ART.

A Standardized Protocol for Assuring the Validity of Proteomics Results from Liquid Chromatography-High-Resolution Mass Spectrometry

Significant advances in the technological development of mass spectrometry in the field of proteomics and the generation of extremely large amounts of data require a very critical approach to assure the validity of results. Commonly used procedures involved liquid chromatography followed by high-resolution mass spectrometry measurements. Proteomics analysis is used in many fields including the investigation of the metabolism of biologically active substances in organisms. Thus, there is a need to care about the validity of the obtained results. In this work, we proposed a standardized protocol for proteomic analysis using liquid chromatography-high-resolution mass spectrometry, which covers all of these analytical steps to ensure the validity of the results. For this purpose, we explored the requirements of the ISO/IEC 17025:2017 standard as a reference document for quality control in biochemistry research-based mass spectrometry.

Quantitative Proteomics Analysis for the Identification of Differential Protein Expression in Calf Muscles between Young and Old SD Rats Using Mass Spectrometry

Aging is associated with loss of muscle mass and strength that leads to a condition termed sarcopenia. Impaired conditions, morbidity, and malnutrition are the factors of devaluation of muscle fibers in aged animals. Satellite cells play an important role in maintaining muscle homeostasis during tissue regeneration and repair. Proteomic profiling on the skeletal muscle tissues of different age group rats helps to determine the differentially expressed (DE) proteins, which may eventually lead to the development of biomarkers in treating the conditions of sarcopenia. In this study, nanoscale liquid chromatography coupled to tandem mass spectrometry (nano-LC-MS/MS) analysis was implemented in the calf tissues of young and old groups of rats. The mass spectrometry (MS) analysis revealed the presence of 335 differentially expressed proteins between the two different age conditions, among which those based on log-fold change 25 proteins were upregulated and 77 were downregulated. The protein-protein interaction network analysis revealed 18 upregulated proteins with three distinct interconnected networks and 57 downregulated proteins with two networks. Further, gene ontology (GO) enrichment analysis showed the biological process, cellular component, and molecular function of the differential proteins. Pathway enrichment analysis of the DE proteins identified nine significantly enriched pathways with a list of eight significant genes (Cryab, Hspb2, Acat1, Ak1, Adssl1, Anxa5, Gys1, Ogdh, Gc, and Adssl1). Quantification of significant genes by quantitative real-time polymerase chain reaction (qRT-PCR) confirmed the downregulation at the mRNA level. Western blot analysis of their protein expression showed concordant results on two candidate proteins (Ogdh and annexin 5) confirming their differential regulation between the two age groups of rats. Thus, these proteomic approaches on young and aged rats provide insights into the development of protein targets in the treatment of sarcopenia (muscle loss).

Challenges and Opportunities in Clinical Applications of Blood-Based Proteomics in Cancer

Simple Summary

The traditional approach in identifying cancer related protein biomarkers has focused on evaluation of a single peptide/protein in tissue or circulation. At best, this approach has had limited success for clinical applications, since multiple pathological tumor pathways may be involved during initiation or progression of cancer which diminishes the significance of a single candidate protein/peptide. Emerging sensitive proteomic based technologies like liquid chromatography mass spectrometry (LC-MS)-based quantitative proteomics can provide a platform for evaluating serial serum or plasma samples to interrogate secreted products of tumor–host interactions, thereby revealing a more “complete” repertoire of biological variables encompassing heterogeneous tumor biology. However, several challenges need to be met for successful application of serum/plasma based proteomics. These include uniform pre-analyte processing of specimens, sensitive and specific proteomic analytical platforms and adequate attention to study design during discovery phase followed by validation of discovery-level signatures for prognostic, predictive, and diagnostic cancer biomarker applications.

Abstract

Blood is a readily accessible biofluid containing a plethora of important proteins, nucleic acids, and metabolites that can be used as clinical diagnostic tools in diseases, including cancer. Like the on-going efforts for cancer biomarker discovery using the liquid biopsy detection of circulating cell-free and cell-based tumor nucleic acids, the circulatory proteome has been underexplored for clinical cancer biomarker applications. A comprehensive proteome analysis of human serum/plasma with high-quality data and compelling interpretation can potentially provide opportunities for understanding disease mechanisms, although several challenges will have to be met. Serum/plasma proteome biomarkers are present in very low abundance, and there is high complexity involved due to the heterogeneity of cancers, for which there is a compelling need to develop sensitive and specific proteomic technologies and analytical platforms. To date, liquid chromatography mass spectrometry (LC-MS)-based quantitative proteomics has been a dominant analytical workflow to discover new potential cancer biomarkers in serum/plasma. This review will summarize the opportunities of serum proteomics for clinical applications; the challenges in the discovery of novel biomarkers in serum/plasma; and current proteomic strategies in cancer research for the application of serum/plasma proteomics for clinical prognostic, predictive, and diagnostic applications, as well as for monitoring minimal residual disease after treatments. We will highlight some of the recent advances in MS-based proteomics technologies with appropriate sample collection, processing uniformity, study design, and data analysis, focusing on how these integrated workflows can identify novel potential cancer biomarkers for clinical applications.

Proteomic profiling reveals crucial retinal protein alterations in the early phase of an experimental glaucoma model

PURPOSE

Clinical glaucoma is difficult to assess in terms of molecular pathophysiology, prompting studies in experimental models of glaucoma. The purpose of this study was to investigate quantitative changes in retinal protein expression at the onset of experimental glaucoma in rats. Analyzing the proteome provides a suitable tool to decipher the pathophysiological processes in glaucomatous degeneration.

METHODS

Thermic cauterization of episcleral veins was utilized to elevate the intraocular pressure in Sprague Dawley rats. Morphological changes were surveyed on a cellular level with a staining of Brn3a-positive cells. The retinal nerve fiber layer was investigated using optical coherence tomography (OCT, Heidelberg Engineering) and the optic nerve was analyzed by an axonal grading system. Mass spectrometry-featured quantitative proteomics and immunohistochemical staining was used to identify specifically altered proteins in the course of intraocular pressure elevation and initial neurodegeneration. Proteomic data were further analyzed with Ingenuity Pathway Analysis and Cytoscape to analyze further molecular associations.

RESULTS

The intraocular pressure rose significantly (p < 0.001) for the follow-up period of 3 weeks after which animals were sacrificed. Eyes exposed to an elevated intraocular pressure showed an initial decrease of retinal ganglion cells, retinal nerve fiber layer (p < 0.05) and an impairment of the optic nerve (p < 0.01). Mass spectrometry led to the identification and quantification of 931 retinal proteins, whereas 32 were considerably altered. Bioinformatics-assisted clustering revealed that a majority of these proteins are functionally associated with cell differentiation, apoptosis and stress response. The creation of an interactive protein network showed that numerous altered proteins are connected regarding their cellular function. Protein kinase b, mitogen-activated protein kinase 1 and the NF-κB complex seem to be essential molecules in this context.

CONCLUSIONS

In conclusion, these results provide further lines of evidence that substantial molecular changes occur at the onset of the disease, identifying potential key players, which might be useful as biomarkers for diagnostics and development of medical treatment in the future.

Proteomic profiling of mitochondria: what does it tell us about the ageing brain?

Mitochondrial dysfunction is evident in numerous neurodegenerative and age-related disorders. It has also been linked to cellular ageing, however our current understanding of the mitochondrial changes that occur are unclear. Functional studies have made some progress reporting reduced respiration, dynamic structural modifications and loss of membrane potential, though there are conflicts within these findings. Proteomic analyses, together with functional studies, are required in order to profile the mitochondrial changes that occur with age and can contribute to unravelling the complexity of the ageing phenotype. The emergence of improved protein separation techniques, combined with mass spectrometry analyses has allowed the identification of age and cell-type specific mitochondrial changes in energy metabolism, antioxidants, fusion and fission machinery, chaperones, membrane proteins and biosynthesis pathways. Here, we identify and review recent data from the analyses of mitochondria from rodent brains. It is expected that knowledge gained from understanding age-related mitochondrial changes of the brain should lead to improved biomarkers of normal ageing and also age-related disease progression.

freeQuant: A Mass Spectrometry Label-Free Quantification Software Tool for Complex Proteome Analysis

Study of complex proteome brings forward higher request for the quantification method using mass spectrometry technology. In this paper, we present a mass spectrometry label-free quantification tool for complex proteomes, called freeQuant, which integrated quantification with functional analysis effectively. freeQuant consists of two well-integrated modules: label-free quantification and functional analysis with biomedical knowledge. freeQuant supports label-free quantitative analysis which makes full use of tandem mass spectrometry (MS/MS) spectral count, protein sequence length, shared peptides, and ion intensity. It adopts spectral count for quantitative analysis and builds a new method for shared peptides to accurately evaluate abundance of isoforms. For proteins with low abundance, MS/MS total ion count coupled with spectral count is included to ensure accurate protein quantification. Furthermore, freeQuant supports the large-scale functional annotations for complex proteomes. Mitochondrial proteomes from the mouse heart, the mouse liver, and the human heart were used to evaluate the usability and performance of freeQuant. The evaluation showed that the quantitative algorithms implemented in freeQuant can improve accuracy of quantification with better dynamic range.

Novel Serum Biomarkers to Differentiate Cholangiocarcinoma from Benign Biliary Tract Diseases Using a Proteomic Approach

Background and Aim. Cholangiocarcinoma (CCA) is the most frequent biliary malignancy, which poses high mortality rate due to lack of early detection. Hence, most CCA cases are present at the advanced to late stages with local or distant metastasis at the time of diagnosis. Currently available tumor markers including CA19-9 and CEA are inefficient and of limited usage due to low sensitivity and specificity. Here, we attempt to identify serum tumor markers for CCA that can effectively distinguish CCA from benign biliary tract diseases (BBTDs). Methods. Serum samples from 19 CCA patients and 17 BBTDs were separated by SDS-PAGE followed with LC-MS/MS and were subjected to statistical analysis and cross-validation to identify proteins whose abundance was significantly elevated or suppressed in CCA samples compared to BBTDs. Results. In addition to identifying several proteins previously known to be differentially expressed in CCA and BBTDs, we also discovered a number of molecules that were previously not associated with CCA. These included FAM19A5, MAGED4B, KIAA0321, RBAK, and UPF3B. Conclusions. Novel serum biomarkers to distinguish CCA from BBTDs were identified using a proteomic approach. Further validation of these proteins has the potential to provide a biomarker for differentiating CCA from BBTDs.

Proteomics perspectives in rotator cuff research: a systematic review of gene expression and protein composition in human tendinopathy

BACKGROUND

Rotator cuff tendinopathy including tears is a cause of significant morbidity. The molecular pathogenesis of the disorder is largely unknown. This review aimed to present an overview of the literature on gene expression and protein composition in human rotator cuff tendinopathy and other tendinopathies, and to evaluate perspectives of proteomics--the comprehensive study of protein composition--in tendon research.

MATERIALS AND METHODS

We conducted a systematic search of the literature published between 1 January 1990 and 18 December 2012 in PubMed, Embase, and Web of Science. We included studies on objectively quantified differential gene expression and/or protein composition in human rotator cuff tendinopathy and other tendinopathies as compared to control tissue.

RESULTS

We identified 2199 studies, of which 54 were included; 25 studies focussed on rotator cuff or biceps tendinopathy. Most of the included studies quantified prespecified mRNA molecules and proteins using polymerase chain reactions and immunoassays, respectively. There was a tendency towards an increase of collagen I (11 of 15 studies) and III (13 of 14), metalloproteinase (MMP)-1 (6 of 12), -9 (7 of 7), -13 (4 of 7), tissue inhibitor of metalloproteinase (TIMP)-1 (4 of 7), and vascular endothelial growth factor (4 of 7), and a decrease in MMP-3 (10 of 12). Fourteen proteomics studies of tendon tissues/cells failed inclusion, mostly because they were conducted in animals or in vitro.

CONCLUSIONS

Based on methods, which only allowed simultaneous quantification of a limited number of prespecified mRNA molecules or proteins, several proteins appeared to be differentially expressed/represented in rotator cuff tendinopathy and other tendinopathies. No proteomics studies fulfilled our inclusion criteria, although proteomics technologies may be a way to identify protein profiles (including non-prespecified proteins) that characterise specific tendon disorders or stages of tendinopathy. Thus, our results suggested an untapped potential for proteomics in tendon research.

Mass spectrometry-based methods for identifying oxidized proteins in disease: advances and challenges

Many inflammatory diseases have an oxidative aetiology, which leads to oxidative damage to biomolecules, including proteins. It is now increasingly recognized that oxidative post-translational modifications (oxPTMs) of proteins affect cell signalling and behaviour, and can contribute to pathology. Moreover, oxidized proteins have potential as biomarkers for inflammatory diseases. Although many assays for generic protein oxidation and breakdown products of protein oxidation are available, only advanced tandem mass spectrometry approaches have the power to localize specific oxPTMs in identified proteins. While much work has been carried out using untargeted or discovery mass spectrometry approaches, identification of oxPTMs in disease has benefitted from the development of sophisticated targeted or semi-targeted scanning routines, combined with chemical labeling and enrichment approaches. Nevertheless, many potential pitfalls exist which can result in incorrect identifications. This review explains the limitations, advantages and challenges of all of these approaches to detecting oxidatively modified proteins, and provides an update on recent literature in which they have been used to detect and quantify protein oxidation in disease.

Over-expressed Testis-specific Protein Y-encoded 1 as a novel biomarker for male hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a male-predominant cancer. Previous studies have focused on the sex-related disparity in HCC, but the underlying mechanism remains unclear. Here, we aimed to discover characteristic biomarkers for male HCC. Clinical samples were subjected to iTRAQ labeling followed by 2DLC-ESI-MS/MS analysis. Seventy-three differential proteins containing 16 up-regulated and 57 down-regulated proteins were screened out in the male HCC group compared to that in female HCC group. Testis-specific Protein Y-encoded 1(TSPY1) is characteristically present in male HCC and was chosen for further investigation. The data from the functional effects of TSPY1 indicated that over-expression of TSPY1 could potentiate HCC cell proliferation, increase soft agar colonization, induce higher cell invasive ability and correlate with the metastatic potential of the HCC cell lines. In addition, TSPY1 and androgen receptor (AR) were co-expressed simultaneously in HCC cell lines as well as in HCC tissue. TSPY1 up- or down-regulation could lead to a high or low level expression of AR. These results implied that TSPY1 may be included in the regulation of AR expression involved in male HCC and it may act as a novel biomarker for male HCC.

Global in vivo terminal amino acid labeling for exploring differential expressed proteins induced by dialyzed serum cultivation

An accurate and high throughput isobaric MS2 quantification strategy based on metabolic labeling and trypsin digestion.

The application of monoclonal antibodies in cancer diagnosis

Cancer becomes the second leading cause of death in the world. An effective strategy for early diagnosis of the disease is key to reduce the mortality and morbidity. Development of effective monoclonal antibody (mAb)-based assays or diagnostic imaging techniques for detection of antigens and small molecules that are released from cancerous cells will enhance modern diagnostic medicine of cancer significantly. Although mAb technology is still under development, recent advances in preparation of recombinant antigen and antibody engineering techniques have dramatically enhanced the applications of this technology in cancer diagnosis. Compared with other methods, mAb-based assays may provide spatial, temporal, accurate and quantitative measurement for diagnosis of the disease. This review summarizes the progress of the mAb-based assays in the field of molecular diagnosis of cancer.

Plasma proteome analysis reveals overlapping, yet distinct mechanisms of immune activation in chronic HCV and HIV infections

BACKGROUND

HIV infection contributes to accelerated rates of progression of liver fibrosis during hepatitis C virus (HCV) infection, and HCV liver disease contributes to mortality during HIV infection. Although mechanisms underlying these interactions are not well known, soluble and cellular markers of immune activation associate with disease progression during both infections.

METHODS

We identified proteins varying in expression across the plasma proteomes of subjects with untreated HIV infection, untreated HCV infection with low aspartate transaminase/platelet ratio index, untreated HCV infection with high aspartate transaminase/platelet ratio index, HIV-HCV coinfection, and controls. We examined correlations between dysregulated proteins and markers of immune activation to uncover biomarkers specific to disease states.

RESULTS

We observed the anticipated higher frequencies of HLA-DRCD38CD4 and CD8 T cells, higher serum soluble CD14 levels, and higher serum interleukin-6 levels for HCV- and HIV-infected groups compared with controls. Plasma proteome analysis identified 2297 peptides mapping to 227 proteins, and quantitative analysis of peptide intensity identified significant changes in 85 proteins across the 5 groups. Abundance for 7 of these proteins was validated by enzyme-linked immunosorbent assay. Forty-three of these proteins correlated with markers of immune activation, including at least 2 proteins that may directly drive T-cell activation. As a functional validation, we tested the enzymatic pathway product (lysophosphatidic acid, LPA) of one such protein, ecotonucleotide pyrophosphatase/phosphodiesterase-2, for ability to activate T cells in vitro. LPA activated T cells to express CD38 and HLA-DR.

CONCLUSIONS

These data indicate that elevated levels of ecotonucleotide pyrophosphatase/phosphodiesterase-2 and LPA during advanced HCV disease may play a role in exacerbating immune activation during HCV-HIV coinfection.

Chemistry-based functional proteomics for drug target deconvolution

Drug target deconvolution, a process that identifies targets to small molecules in complex biological samples, which underlie the biological responses that are observed when a drug is administered, plays an important role in current drug discovery. Despite the fact that genomics and proteomics have provided a flood of information that contributes to the progress of drug target identification and validation, the current approach to drug target deconvolution still poses dilemmas. Chemistry-based functional proteomics, a multidisciplinary strategy, has become the preferred method of choice to deconvolute drug target pools, based on direct interactions between small molecules and their protein targets. This approach has already identified a broad panel of previously undefined enzymes with potential as drug targets and defined targets that can rationalize side effects and toxicity for new drug candidates and existing therapeutics. Herein, the authors discuss both activity-based protein profiling and compound-centric chemical proteomics approaches used in chemistry-based functional proteomics and their applications for the identification and characterization of small molecular targets.

One decade of salivary proteomics: current approaches and outstanding challenges

Efforts have been made in the last decade towards the complete characterization of saliva proteome using gel-based and gel-free approaches. The combination of these strategies resulted in the increment of the dynamic range of saliva proteome, which yield in the identification of more than 3,000 different protein species. Comparative protein profiling using isotope labeling and label free approaches has been used for the identification of novel biomarkers for oral and related diseases. Although progresses have been made in saliva proteome characterization, the comparative profiling in different pathophysiological conditions is still at the beginning if compared to other bodily fluids. The potential biomarkers identified so far lack specificity once common differentially expressed proteins were detected in the saliva of patients with distinct diseases. In addition, recent research works focused on saliva peptidome profiling already allowed a better understanding of peptides' physiological role in oral cavity. This review provides an overview of the major achievements in saliva proteomics giving emphasis to methodological concerns related with saliva collection, treatment and analysis, as well as the main advantages and pitfalls underlying salivary proteomic strategies and potential clinical outcomes.

Tumor-derived secretory clusterin induces epithelial-mesenchymal transition and facilitates hepatocellular carcinoma metastasis

Hepatocellular carcinoma (HCC) is the third most common cause of cancer mortality. Metastasis is the major concern that causes death in HCC. The goal of this study was to identify tumor-derived proteins in serum during HCC metastasis using an orthotopic xenograft tumor model and explore the role of key protein in HCC metastasis. Serum samples collected from HCCLM3-R metastatic HCC tumor model at specific stages of metastasis (1 wk, 3 wks and 6 wks) were subjected to iTRAQ labeling followed by 2DLC-ESI-MS/MS analysis. Twenty tumor-derived proteins were identified through human specific peptides. Secretory clusterin (sCLU), which was significantly upregulated during cancer progression and metastasis, was chosen for further study. The expression of sCLU was significantly higher in metastatic HCC cell lines and samples from metastatic HCC patients. ShRNA-mediated down-regulation of sCLU resulted in a reduced migratory capacity in HCC cell lines, as well as a reduction in pulmonary metastasis in vivo. Overexpression of sCLU in HepG2 cell line showed increased cell migratory ability. Further study found that sCLU contributed to HCC migration and epithelial-mesenchymal transition (EMT) in vitro, and metastasis in vivo. In addition, sCLU also plays an important role in the regulation of TGF-β1-smad3 signaling. These findings suggest that sCLU may promote HCC metastasis via the induction of EMT process and may be a candidate target for HCC therapy.

Human biomarker discovery and predictive models for disease progression for idiopathic pneumonia syndrome following allogeneic stem cell transplantation

Allogeneic hematopoietic stem cell transplantation (SCT) is the only curative therapy for many malignant and nonmalignant conditions. Idiopathic pneumonia syndrome (IPS) is a frequently fatal complication that limits successful outcomes. Preclinical models suggest that IPS represents an immune mediated attack on the lung involving elements of both the adaptive and the innate immune system. However, the etiology of IPS in humans is less well understood. To explore the disease pathway and uncover potential biomarkers of disease, we performed two separate label-free, proteomics experiments defining the plasma protein profiles of allogeneic SCT patients with IPS. Samples obtained from SCT recipients without complications served as controls. The initial discovery study, intended to explore the disease pathway in humans, identified a set of 81 IPS-associated proteins. These data revealed similarities between the known IPS pathways in mice and the condition in humans, in particular in the acute phase response. In addition, pattern recognition pathways were judged to be significant as a function of development of IPS, and from this pathway we chose the lipopolysaccaharide-binding protein (LBP) protein as a candidate molecular diagnostic for IPS, and verified its increase as a function of disease using an ELISA assay. In a separately designed study, we identified protein-based classifiers that could predict, at day 0 of SCT, patients who: 1) progress to IPS and 2) respond to cytokine neutralization therapy. Using cross-validation strategies, we built highly predictive classifier models of both disease progression and therapeutic response. In sum, data generated in this report confirm previous clinical and experimental findings, provide new insights into the pathophysiology of IPS, identify potential molecular classifiers of the condition, and uncover a set of markers potentially of interest for patient stratification as a basis for individualized therapy.

Novel urinary protein biomarkers predicting the development of microalbuminuria and renal function decline in type 1 diabetes

OBJECTIVE

To define a panel of novel protein biomarkers of renal disease.

RESEARCH DESIGN AND METHODS

Adults with type 1 diabetes in the Coronary Artery Calcification in Type 1 Diabetes study who were initially free of renal complications (n = 465) were followed for development of micro- or macroalbuminuria (MA) and early renal function decline (ERFD, annual decline in estimated glomerular filtration rate of ≥3.3%). The label-free proteomic discovery phase was conducted in 13 patients who progressed to MA by the 6-year visit and 11 control subjects, and four proteins (Tamm-Horsfall glycoprotein, α-1 acid glycoprotein, clusterin, and progranulin) identified in the discovery phase were measured by enzyme-linked immunosorbent assay in 74 subjects: group A, normal renal function (n = 35); group B, ERFD without MA (n = 15); group C, MA without ERFD (n = 16); and group D, both ERFD and MA (n = 8).

RESULTS

In the label-free analysis, a model of progression to MA was built using 252 peptides, yielding an area under the curve (AUC) of 84.7 ± 5.3%. In the validation study, ordinal logistic regression was used to predict development of ERFD, MA, or both. A panel including Tamm-Horsfall glycoprotein (odds ratio 2.9, 95% CI 1.3-6.2, P = 0.008), progranulin (1.9, 0.8-4.5, P = 0.16), clusterin (0.6, 0.3-1.1, P = 0.09), and α-1 acid glycoprotein (1.6, 0.7-3.7, P = 0.27) improved the AUC from 0.841 to 0.889.

CONCLUSIONS

A panel of four novel protein biomarkers predicted early renal damage in type 1 diabetes. These findings require further validation in other populations for prediction of renal complications and treatment monitoring.

The proteome of normal pancreatic juice

OBJECTIVES

The aims of this study were to characterize the proteome of normal pancreatic juice, to analyze the effect of secretin on the normal proteome, and to compare these results with published data from patients with pancreatic cancer.

METHODS

Paired pancreatic fluid specimens (before and after intravenous secretin stimulation) were obtained during endoscopic pancreatography from 3 patients without significant pancreatic pathology. Proteins were identified and quantified by mass spectrometry-based protein quantification technology. The human RefSeq (NCBI) database was used to compare the data in samples from patients without pancreatic disease with published data from 3 patients with pancreatic cancer.

RESULTS

A total of 285 proteins were identified in normal pancreatic juice. Ninety had sufficient amino acid sequences identified to characterize the protein with a high level of confidence. All 90 proteins were present before and after secretin administration but with altered relative concentrations, usually by 1 to 2 folds, after stimulation. Comparison with 170 published pancreatic cancer proteins yielded an overlap of only 42 proteins.

CONCLUSIONS

Normal pancreatic juice contains multiple proteins related to many biological processes. Secretin alters the concentration but not the spectrum of these proteins. The pancreatic juice proteome of patients without pancreatic disease and that of patients with pancreatic cancer differ markedly.

Reactome pathway analysis to enrich biological discovery in proteomics data sets

Reactome (http://www.reactome.org) is an open-source, expert-authored, peer-reviewed, manually curated database of reactions, pathways and biological processes. We provide an intuitive web-based user interface to pathway knowledge and a suite of data analysis tools. The Pathway Browser is a Systems Biology Graphical Notation-like visualization system that supports manual navigation of pathways by zooming, scrolling and event highlighting, and that exploits PSI Common Query Interface web services to overlay pathways with molecular interaction data from the Reactome Functional Interaction Network and interaction databases such as IntAct, ChEMBL and BioGRID. Pathway and expression analysis tools employ web services to provide ID mapping, pathway assignment and over-representation analysis of user-supplied data sets. By applying Ensembl Compara to curated human proteins and reactions, Reactome generates pathway inferences for 20 other species. The Species Comparison tool provides a summary of results for each of these species as a table showing numbers of orthologous proteins found by pathway from which users can navigate to inferred details for specific proteins and reactions. Reactome's diverse pathway knowledge and suite of data analysis tools provide a platform for data mining, modeling and analysis of large-scale proteomics data sets. This Tutorial is part of the International Proteomics Tutorial Programme (IPTP 8).

Identification of transaldolase as a novel serum biomarker for hepatocellular carcinoma metastasis using xenografted mouse model and clinic samples

Hepatocellular carcinoma (HCC) is one of serious disorders with the highest morbidities and mortalities worldwide. Metastasis is the major concern that causes death in HCC. The goal of this study was to screen and identify potential serum proteins indicating HCC metastasis. Serum samples collected from control and HCCLM3-R metastatic HCC tumor model at specific stages of metastasis (1 wk, 3 wks and 6 wks) were subjected to iTRAQ labeling followed by 2DLC-ESI-MS/MS analysis. A total of 554 proteins were identified and 80 proteins were differential expressed at least between one adjacent time points. Among them, expression level of transaldolase (TALDO) was validated in mouse and human serum. The level of TALDO protein was found to be higher in metastatic mice serum compared to that of non-metastatic mice. Human specific TALDO was then identified in mouse serum through human specific peptides. Immunohistochemical and western blot analysis showed that the expression of TALDO in human HCC tissues and HCC cell lines was associated with its metastatic behavior. Subsequent screening of TALDO expression in 72 clinical serum samples (comprising 36 non-metastatic HCC and 36 metastatic HCC samples) revealed higher TALDO level in the serum of metastatic HCC patients. A receiver operating characteristic (ROC) curve estimated a maximal sensitivity of 77.8% and 86.1% specificity for TALDO in detection of HCC metastasis. The present results demonstrated that the nude mouse xenograft model is an efficient system for performing metastasis-related biomarker discovery. TALDO may be useful biomarkers for the detection of HCC metastasis.

Identification of PRDX4 and P4HA2 as metastasis-associated proteins in oral cavity squamous cell carcinoma by comparative tissue proteomics of microdissected specimens using iTRAQ technology

Cervical lymph node metastasis represents the major prognosticator for oral cavity squamous cell carcinoma (OSCC). Here, we used an iTRAQ-based quantitative proteomic approach to identify proteins that are differentially expressed between microdissected primary and metastatic OSCC tumors. The selected candidates were examined in tissue sections via immunohistochemistry, and their roles in OSCC cell function investigated using RNA interference. Seventy-four differentially expressed proteins in nodal metastases, including PRDX4 and P4HA2, were identified. Immunohistochemical analysis revealed significantly higher levels of PRDX4 and P4HA2 in tumor cells than adjacent non-tumor epithelia (P < 0.0001 and P < 0.0001, respectively), and even higher expression in the 31 metastatic tumors of lymph nodes, compared to the corresponding primary tumors (P = 0.060 and P = 0.002, respectively). Overexpression of PRDX4 and P4HA2 was significantly associated with positive pN status (P = 0.048 and P = 0.021, respectively). PRDX4 overexpression was a significant prognostic factor for disease-specific survival in both univariate and multivariate analyses (P = 0.034 and P = 0.032, respectively). Additionally, cell migration and invasiveness were attenuated in OEC-M1 cells upon in vitro knockdown of PRDX4 and P4HA2 with specific interfering RNA. Novel metastasis-related prognostic markers for OSCC could be identified by our approach.

Proteomics in bone research

Osteoporosis is prevalent among the elderly and is a major cause of bone fracture in this population. Bone integrity is maintained by the dynamic processes of bone resorption and bone formation (bone remodeling). Osteoporosis results when there is an imbalance of the two counteracting processes. Bone mineral density, measured by dual-energy x-ray absorptiometry has been the primary method to assess fracture risk for decades. Recent studies demonstrated that measurement of bone turnover markers allows for a dynamic assessment of bone remodeling, while imaging techniques, such as dual-energy x-ray absorptiometry, do not. The application of proteomics has permitted discoveries of new, sensitive, bone turnover markers, which provide unique information for clinical diagnosis and treatment of patients with bone diseases. This review summarizes the recent findings of proteomic studies on bone diseases, properties of mesenchymal stem cells with high expansion rates and osteoblast and osteoclast differentiation, with emphasis on the role of quantitative proteomics in the study of signaling dynamics, biomarkers and discovery of therapeutic targets.

Plasma membrane proteomics and its application in clinical cancer biomarker discovery

Plasma membrane proteins that are exposed on the cell surface have important biological functions, such as signaling into and out of the cells, ion transport, and cell-cell and cell-matrix interactions. The expression level of many of the plasma membrane proteins involved in these key functions is altered on cancer cells, and these proteins may also be subject to post-translational modification, such as altered phosphorylation and glycosylation. Additional protein alterations on cancer cells confer metastatic capacities, and some of these cell surface proteins have already been successfully targeted by protein drugs, such as human antibodies, that have enhanced survival of several groups of cancer patients. The combination of novel analytical approaches and subcellular fractionation procedures has made it possible to study the plasma membrane proteome in more detail, which will elucidate cancer biology, particularly metastasis, and guide future development of novel drug targets. The technical advances in plasma membrane proteomics and the consequent biological revelations will be discussed herein. Many of the advances have been made using cancer cell lines, but because the main goal of this research is to improve individualized treatment and increase cancer patient survival, further development is crucial to direct analysis of clinically relevant patient samples. These efforts include optimized specimen handling and preparation as well as improved proteomics platforms. Identification of potentially useful proteomics-based biomarkers must be validated in larger, well defined retrospective and prospective clinical studies, and these combined efforts should result in identification of biomarkers that will greatly improve early detection, prognosis, and prediction of treatment response.

Dual-color proteomic profiling of complex samples with a microarray of 810 cancer-related antibodies

Antibody microarrays have the potential to enable comprehensive proteomic analysis of small amounts of sample material. Here, protocols are presented for the production, quality assessment, and reproducible application of antibody microarrays in a two-color mode with an array of 1,800 features, representing 810 antibodies that were directed at 741 cancer-related proteins. In addition to measures of array quality, we implemented indicators for the accuracy and significance of dual-color detection. Dual-color measurements outperform a single-color approach concerning assay reproducibility and discriminative power. In the analysis of serum samples, depletion of high-abundance proteins did not improve technical assay quality. On the contrary, depletion introduced a strong bias in protein representation. In an initial study, we demonstrated the applicability of the protocols to proteins derived from urine samples. We identified differences between urine samples from pancreatic cancer patients and healthy subjects and between sexes. This study demonstrates that biomedically relevant data can be produced. As demonstrated by the thorough quality analysis, the dual-color antibody array approach proved to be competitive with other proteomic techniques and comparable in performance to transcriptional microarray analyses.

The bottleneck in the cancer biomarker pipeline and protein quantification through mass spectrometry-based approaches: current strategies for candidate verification

BACKGROUND

Although robust discovery-phase platforms have resulted in the generation of large numbers of candidate cancer biomarkers, a comparable system for subsequent quantitative assessment and verification of all candidates is lacking. Established immunoassays and available antibodies permit analysis of small subsets of candidates; however, the lack of commercially available reagents, coupled with high costs and lengthy production and purification times, have rendered the large majority of candidates untestable.

CONTENT

Mass spectrometry (MS), and in particular multiple reaction monitoring (MRM)-MS, has emerged as an alternative technology to immunoassays for quantification of target proteins. Novel biomarkers are expected to be present in serum in the low (microg/L-ng/L) range, but analysis of complex serum or plasma digests by MS has yielded milligram per liter limits of detection at best. The coupling of prior sample purification strategies such as enrichment of target analytes, depletion of high-abundance proteins, and prefractionation, has enabled reliable penetration into the low microgram per liter range. This review highlights prospects for candidate verification through MS-based methods. We first outline the biomarker discovery pipeline and its existing bottleneck; we then discuss various MRM-based strategies for targeted protein quantification, the applicability of such methods for candidate verification, and points of concern.

SUMMARY

Although it is unlikely that MS-based protein quantification will replace immunoassays in the near future, with the expected improvements in limits of detection and specificity in instrumentation, MRM-based approaches show great promise for alleviating the existing bottleneck to discovery.