Detection of aggressive prostate cancer associated glycoproteins in urine using glycoproteomics and mass spectrometry

Recent progress in mass spectrometry-based urinary proteomics

Serum or plasma is frequently utilized in biomedical research; however, its application is impeded by the requirement for invasive sample collection. The non-invasive nature of urine collection makes it an attractive alternative for disease characterization and biomarker discovery. Mass spectrometry-based protein profiling of urine has led to the discovery of several disease-associated biomarkers. Proteomic analysis of urine has not only been applied to disorders of the kidney and urinary bladder but also to conditions affecting distant organs because proteins excreted in the urine originate from multiple organs. This review provides a progress update on urinary proteomics carried out over the past decade. Studies summarized in this review have expanded the catalog of proteins detected in the urine in a variety of clinical conditions. The wide range of applications of urine analysis-from characterizing diseases to discovering predictive, diagnostic and prognostic markers-continues to drive investigations of the urinary proteome.

Differentially expressed glycoproteins in pre- and post-digital rectal examination urine samples for detecting aggressive prostate cancer

Urinary glycoproteins associated with aggressive prostate cancer (AG-PCa) were previously reported using post-digital rectal examination (DRE) urine specimens. To explore the potential of using pre-DRE urine specimens for detecting AG-PCa, we compared glycoproteins between pre- and post-DRE urine specimens, verified the previously identified post-DRE AG-PCa-associated urinary glycoproteins in pre-DRE urine specimens, and explored potential new glycoproteins for AG-PCa detection in pre-DRE urine specimens. Quantitative glycoproteomic data were acquired for 154 pre-DRE urine specimens from 41 patients with no cancer at biopsy, 48 patients with non-AG-PCa (Gleason score = 6), and 65 patients with AG-PCa (Gleason score 7 or above). Compared to glycopeptides from the post-DRE urine data, humoral immunity-related proteins were enriched in pre-DRE urine samples, whereas cell mediated immune response proteins were enriched in post-DRE urine samples. Analyses of AG-PCa-associated glycoproteins from pre-DRE urine revealed that the three urinary glycoproteins, prostate-specific antigen (PSA), prostatic acid phosphatase (ACPP), and CD97 antigen (CD97) that were previously identified in post-DRE urine samples, were also observed as AG-PCa associated glycoproteins in pre-DRE urine. In addition, we identified three new glycoproteins, fibrillin 1 (FBN1), vitronectin (VTN), and hemicentin 2 (HMCN2), to be potentially associated with AG-PCa in pre-DRE urine specimens. In summary, glycoprotein profiles differ between pre- and post-DRE urine specimens. The identified AG-PCa-associated glycoproteins may be further evaluated in large cohort of pre-DRE urine specimens for detecting clinically significant PCa.

Proteomics reveals MRPL4 as a high-risk factor and a potential diagnostic biomarker for prostate cancer

Through digital rectal examinations (DRE) and routine prostate-specific antigen (PSA) screening, early prostate cancer (PC) treatment has become possible. However, PC is a complex and heterogeneous disease. In vivo, cancer cells can invade adjacent tissues and metastasize to other tissues resulting in hard cures. Therefore, the key to improving PC patients' survival time is preventing cancer cells' metastasis. We used mass spectrometry to profile primary PC in patients with versus without metastatic PC. We named these two groups of PC patients as high-risk primary PC (n = 11) and low-risk primary PC (n = 7), respectively. At the same time, patients with benign prostatic hyperplasia (BPH, n = 6) were used as controls to explore the possible factors driving PC metastasis. Based on comprehensive mass spectrometry analysis and biological validation, we found significant upregulation of MRPL4 expression in high-risk primary PC relative to low-risk primary PC and BPH. Further, through research of the extensive clinical cohort data in the database, we discovered that MRPL4 could be a high-risk factor for PC and serve as a potential diagnostic biomarker. The MRPL4 might be used as an auxiliary indicator for clinical status/stage of primary PC to predict patient survival time.

Quantitative clinical glycomics strategies: A guide for selecting the best analysis approach

Glycans introduce complexity to the proteins to which they are attached. These modifications vary during the progression of many diseases; thus, they serve as potential biomarkers for disease diagnosis and prognosis. The immense structural diversity of glycans makes glycosylation analysis and quantitation difficult. Fortunately, recent advances in analytical techniques provide the opportunity to quantify even low-abundant glycopeptides and glycans derived from complex biological mixtures, allowing for the identification of glycosylation differences between healthy samples and those derived from disease states. Understanding the strengths and weaknesses of different quantitative glycomics analysis methods is important for selecting the best strategy to analyze glycosylation changes in any given set of clinical samples. To provide guidance towards selecting the proper approach, we discuss four widely used quantitative glycomics analysis platforms, including fluorescence-based analysis of released N-linked glycans and three different varieties of MS-based analysis: liquid chromatography (LC)-mass spectrometry (MS) analysis of glycopeptides, matrix-assisted laser desorption ionization-time of flight MS, and LC-ESI-MS analysis of released N-linked glycans. These methods' strengths and weaknesses are compared, particularly associated with the figures of merit that are important for clinical biomarker studies, including: the initial sample requirements, the methods' throughput, sample preparation time, the number of species identified, the methods' utility for isomer separation and structural characterization, method-related challenges associated with quantitation, repeatability, the expertise required, and the cost for each analysis. This review, therefore, provides unique guidance to researchers who endeavor to undertake a clinical glycomics analysis by offering insights on the available analysis technologies.

Urinary marker panels for aggressive prostate cancer detection

Majority of patients with indolent prostate cancer (PCa) can be managed with active surveillance. Therefore, finding biomarkers for classifying patients between indolent and aggressive PCa is essential. In this study, we investigated urinary marker panels composed of urinary glycopeptides and/or urinary prostate-specific antigen (PSA) for their clinical utility in distinguishing non-aggressive (Grade Group 1) from aggressive (Grade Group ≥ 2) PCa. Urinary glycopeptides acquired via data-independent acquisition mass spectrometry (DIA-MS) were quantitatively analyzed, where prostatic acid phosphatase (ACPP), clusterin (CLU), alpha-1-acid glycoprotein 1 (ORM1), and CD antigen 97 (CD97) were selected to be evaluated in various combinations with and without urinary PSA. Targeted parallel reaction monitoring (PRM) assays of the glycopeptides from urinary ACPP and CLU were investigated along with urinary PSA for the ability of aggressive PCa detection. The multi-urinary marker panels, combined via logistic regression, were statistically evaluated using bootstrap resampling and validated by an independent cohort. Majority of the multi-urinary marker panels (e.g., a panel consisted of ACPP, CLU, and Urinary PSA) achieved area under the curve (AUC) ranged from 0.70 to 0.85. Thus, multi-marker panels investigated in this study showed clinically meaningful results on aggressive PCa detection to separate Grade Group 1 from Grade Group 2 and above warranting further evaluation in clinical setting in future.

Mass Spectrometry-Based Glycoproteomics and Prostate Cancer

Aberrant glycosylation has long been known to be associated with cancer, since it is involved in key mechanisms such as tumour onset, development and progression. This review will focus on protein glycosylation studies in cells, tissue, urine and serum in the context of prostate cancer. A dedicated section will cover the glycoforms of prostate specific antigen, the molecule that, despite some important limitations, is routinely tested for helping prostate cancer diagnosis. Our aim is to provide readers with an overview of mass spectrometry-based glycoproteomics of prostate cancer. From this perspective, the first part of this review will illustrate the main strategies for glycopeptide enrichment and mass spectrometric analysis. The molecular information obtained by glycoproteomic analysis performed by mass spectrometry has led to new insights into the mechanism linking aberrant glycosylation to cancer cell proliferation, migration and immunoescape.

Clinically Viable Assay for Monitoring Uromodulin Glycosylation

Uromodulin, also known as the Tamm-Horsfall protein or THP, is the most abundant protein excreted in human urine. It is associated with the progression of kidney diseases; therefore, changes in the glycosylation profile of this protein could serve as a potential biomarker for kidney health. The typical glycomics analysis approaches used to quantify uromodulin glycosylation involve time-consuming and tedious glycoprotein isolation and labeling steps, which limit their utility in clinical glycomics assays, where sample throughput is important. Herein, we introduce a radically simplified sample preparation workflow, with direct ESI-MS analysis, enabling the quantification of N-linked glycans that originate from uromodulin. The method omits any glycan labeling steps but includes steps to reduce the salt content of the samples, thereby minimizing ion suppression. The method is effective for quantifying subtle glycosylation differences of uromodulin samples derived from different biological states. As a proof of concept, glycosylation from samples that differ by pregnancy status were shown to be differentiable.

The Complexity and Dynamics of the Tissue Glycoproteome Associated With Prostate Cancer Progression

The complexity and dynamics of the immensely heterogeneous glycoproteome of the prostate cancer (PCa) tumor microenvironment remain incompletely mapped, a knowledge gap that impedes our molecular-level understanding of the disease. To this end, we have used sensitive glycomics and glycoproteomics to map the protein-, cell-, and tumor grade-specific N- and O-glycosylation in surgically removed PCa tissues spanning five histological grades (n = 10/grade) and tissues from patients with benign prostatic hyperplasia (n = 5). Quantitative glycomics revealed PCa grade-specific alterations of the oligomannosidic-, paucimannosidic-, and branched sialylated complex-type N-glycans, and dynamic remodeling of the sialylated core 1- and core 2-type O-glycome. Deep quantitative glycoproteomics identified ∼7400 unique N-glycopeptides from 500 N-glycoproteins and ∼500 unique O-glycopeptides from nearly 200 O-glycoproteins. With reference to a recent Tissue and Blood Atlas, our data indicate that paucimannosidic glycans of the PCa tissues arise mainly from immune cell-derived glycoproteins. Furthermore, the grade-specific PCa glycosylation arises primarily from dynamics in the cellular makeup of the PCa tumor microenvironment across grades involving increased oligomannosylation of prostate-derived glycoproteins and decreased bisecting GlcNAcylation of N-glycans carried by the extracellular matrix proteins. Furthermore, elevated expression of several oligosaccharyltransferase subunits and enhanced N-glycoprotein site occupancy were observed associated with PCa progression. Finally, correlations between the protein-specific glycosylation and PCa progression were observed including increased site-specific core 2-type O-glycosylation of collagen VI. In conclusion, integrated glycomics and glycoproteomics have enabled new insight into the complexity and dynamics of the tissue glycoproteome associated with PCa progression generating an important resource to explore the underpinning disease mechanisms.

The Mitochondrial Proteome of Tumor Cells: A SnapShot on Methodological Approaches and New Biomarkers

Simple Summary

Mitochondria are central hubs of cellular signaling, energy metabolism, and redox balance. The plasticity of these cellular organelles is an essential requisite for the cells to cope with different stimuli and stress conditions. Cancer cells are characterized by changes in energy metabolism, mitochondrial signaling, and dynamics. These changes are driven by alterations in the mitochondrial proteome. For this reason, in the last years a focus of basic and cancer research has been the implementation and optimization of technologies to investigate changes in the mitochondrial proteome during cancer initiation and progression. This review presents an overview of the most used technologies to investigate the mitochondrial proteome and recent evidence on changes in the expression levels and delocalization of certain proteins in and out the mitochondria for shaping the functional properties of tumor cells.

Abstract

Mitochondria are highly dynamic and regulated organelles implicated in a variety of important functions in the cell, including energy production, fatty acid metabolism, iron homeostasis, programmed cell death, and cell signaling. Changes in mitochondrial metabolism, signaling and dynamics are hallmarks of cancer. Understanding whether these modifications are associated with alterations of the mitochondrial proteome is particularly relevant from a translational point of view because it may contribute to better understanding the molecular bases of cancer development and progression and may provide new potential prognostic and diagnostic biomarkers as well as novel molecular targets for anti-cancer treatment. Making an inventory of the mitochondrial proteins has been particularly challenging given that there is no unique consensus targeting sequence that directs protein import into mitochondria, some proteins are present at very low levels, while other proteins are expressed only in some cell types, in a particular developmental stage or under specific stress conditions. This review aims at providing the state-of-the-art on methodologies used to characterize the mitochondrial proteome in tumors and highlighting the biological relevance of changes in expression and delocalization of proteins in and out the mitochondria in cancer biology.

Urinary glycoproteins associated with aggressive prostate cancer

Background: There is an urgent need for the detection of aggressive prostate cancer. Glycoproteins play essential roles in cancer development, while urine is a noninvasive and easily obtainable biological fluid that contains secretory glycoproteins from the urogenital system. Therefore, here we aimed to identify urinary glycoproteins that are capable of differentiating aggressive from non-aggressive prostate cancer.

Methods: Quantitative mass spectrometry data of glycopeptides from a discovery cohort comprised of 74 aggressive (Gleason score ≥8) and 68 non-aggressive (Gleason score = 6) prostate cancer urine specimens were acquired via a data independent acquisition approach. The glycopeptides showing distinct expression profiles in aggressive relative to non-aggressive prostate cancer were further evaluated for their performance in distinguishing the two groups either individually or in combination with others using repeated 5-fold cross validation with logistic regression to build predictive models. Predictive models showing good performance from the discovery cohort were further evaluated using a validation cohort.

Results: Among the 20 candidate glycoproteins, urinary ACPP outperformed the other candidates. Urinary ACPP can also serve as an adjunct to serum PSA to further improve the discrimination power for aggressive prostate cancer (AUC= 0.82, 95% confidence interval 0.75 to 0.89). A three-signature panel including urinary ACPP, urinary CLU, and serum PSA displayed the ability to distinguish aggressive prostate cancer from non-aggressive prostate cancer with an AUC of 0.86 (95% confidence interval 0.8 to 0.92). Another three-signature panel containing urinary ACPP, urinary LOX, and serum PSA also demonstrated its ability in recognizing aggressive prostate cancer (AUC=0.82, 95% confidence interval 0.75 to 0.9). Moreover, consistent performance was observed from each panel when evaluated using a validation cohort.

Conclusion: We have identified glycopeptides of urinary glycoproteins associated with aggressive prostate cancer using a quantitative mass spectrometry-based glycoproteomic approach and demonstrated their potential to serve as noninvasive urinary glycoprotein biomarkers worthy of further validation by a multi-center study.

A risk prediction model of DNA methylation improves prognosis evaluation and indicates gene targets in prostate cancer

Aim: Prostate cancer (PCa) is the most common malignancy found in males worldwide. Although it is mostly indolent, PCa still poses a serious threat to long-term health. Materials & methods: The Cancer Genome Atlas data were randomly divided into training and validation groups. Least absolute shrinkage and selection operator regression on DNA methylation data in the training group was conducted to build the model, which was validated in the validation group. Weighted correlation network analysis was conducted on RNA-seq data to identify the therapy target. Functional validation (western blot, quantitative real-time PCR, cell transfection, Cell Counting Kit-8 assay, colony formation assay, wound healing assay and transwell invasion assay) for the target was conducted. Results: The model is an independent predictor of prognosis. The knockdown of FOXD1 inhibits cell proliferation, migration and invasion of PCa. Conclusion: The risk of patients could be evaluated by the model, which revealed that FOXD1 might promote poor prognosis.

Sensitive discrimination of glycoproteins and cell differentiation with an array sensing platform exploiting pyrene-derived amphiphile/surfactant assemblies

An array sensing platform exploiting phenyl boronic acid-functionalized pyrene amphiphile/surfactant assemblies is constructed for glycoprotein discrimination, achieving a discrimination sensitivity of 50 nM. Gastric cancer cell lines of various differentiation grades are successfully discriminated, demonstrating its great potential in sensitive differentiation of glycoprotein-related samples in biomedical diagnosis.

Tissue Proteome Signatures Associated with Five Grades of Prostate Cancer and Benign Prostatic Hyperplasia

The histology-based Gleason score (GS) of prostate cancer (PCa) tissue biopsy is the most accurate predictor of disease aggressiveness and an important measure to guide treatment strategies and patient management. The variability associated with PCa tumor sampling and the subjective determination of the GS are challenges that limit accurate diagnostication and prognostication. Thus, novel molecular signatures are needed to distinguish between indolent and aggressive forms of PCa for better patient management and outcomes. Herein, label-free LC-MS/MS proteomics is used to profile the proteome of 50 PCa tissues spanning five grade groups (n = 10 per group) relative to tissues from individuals with benign prostatic hyperplasia (BPH). Over 2000 proteins are identified albeit at different levels between and within the patient groups, revealing biological processes associated with specific grades. A panel of 11 prostate-derived proteins including IGKV3D-20, RNASET2, TACC2, ANXA7, LMOD1, PRCP, GYG1, NDUFV1, H1FX, APOBEC3C, and CTSZ display the potential to stratify patients from low and high PCa grade groups. Parallel reaction monitoring of the same sample cohort validate the differential expression of LMOD1, GYG1, IGKV3D-20, and RNASET2. The four proteins associated with low and high PCa grades reported here warrant further exploration as candidate biomarkers for PCa aggressiveness.

Mapping human N-linked glycoproteins and glycosylation sites using mass spectrometry

N-linked glycoprotein is a highly interesting class of proteins for clinical and biological research. Over the last decade, large-scale profiling of N-linked glycoproteins and glycosylation sites from biological and clinical samples has been achieved through mass spectrometry-based glycoproteomic approaches. In this paper, we reviewed the human glycoproteomic profiles that have been reported in more than 80 individual studies, and mainly focused on the N-glycoproteins and glycosylation sites identified through their deglycosylated forms of glycosite-containing peptides. According to our analyses, more than 30,000 glycosite-containing peptides and 7,000 human glycoproteins have been identified from five different body fluids, twelve human tissues (or related cell lines), and four special cell types. As the glycoproteomic data is still missing for many organs and tissues, a systematical glycoproteomic analysis of various human tissues and body fluids using a uniform platform is still needed for an integrated map of human N-glycoproteomes.

Human Periprostatic Adipose Tissue: Secretome from Patients With Prostate Cancer or Benign Prostate Hyperplasia

BACKGROUND/AIM

Periprostatic adipose tissue (PPAT) directs tumour behaviour. Microenvironment secretome provides information related to its biology. This study was performed to identify secreted proteins by PPAT, from both prostate cancer and benign prostate hyperplasia (BPH) patients.

PATIENTS AND METHODS

Liquid chromatography-mass spectrometry-based proteomic analysis was performed in PPAT-conditioned media (CM) from patients with prostate cancer (CMs-T) (stage T3: CM-T3, stage T2: CM-T2) or benign disease (CM-BPH).

RESULTS

The highest number and diversity of proteins was identified in CM-T3. Locomotion was the biological process mainly associated to CMs-T and reproduction to CM-T3. Immune responses were enriched in CMs-T. Extracellular matrix and structural proteins were associated to CMs-T. CM-T3 was enriched in proteins with catalytic activity and CM-T2 in proteins with defense/immunity activity. Metabolism and energy pathways were enriched in CM-T3 and those with immune system functions in CMs-T. Transport proteins were enriched in CM-T2 and CM-BPH.

CONCLUSION

Proteins and pathways reported in this study could be useful to distinguish stages of disease and may become targets for novel therapies.

Clinically Relevant Post-Translational Modification Analyses-Maturing Workflows and Bioinformatics Tools

Post-translational modifications (PTMs) can occur soon after translation or at any stage in the lifecycle of a given protein, and they may help regulate protein folding, stability, cellular localisation, activity, or the interactions proteins have with other proteins or biomolecular species. PTMs are crucial to our functional understanding of biology, and new quantitative mass spectrometry (MS) and bioinformatics workflows are maturing both in labelled multiplexed and label-free techniques, offering increasing coverage and new opportunities to study human health and disease. Techniques such as Data Independent Acquisition (DIA) are emerging as promising approaches due to their re-mining capability. Many bioinformatics tools have been developed to support the analysis of PTMs by mass spectrometry, from prediction and identifying PTM site assignment, open searches enabling better mining of unassigned mass spectra-many of which likely harbour PTMs-through to understanding PTM associations and interactions. The remaining challenge lies in extracting functional information from clinically relevant PTM studies. This review focuses on canvassing the options and progress of PTM analysis for large quantitative studies, from choosing the platform, through to data analysis, with an emphasis on clinically relevant samples such as plasma and other body fluids, and well-established tools and options for data interpretation.

Comprehensive Glycoproteomic Analysis of Chinese Hamster Ovary Cells

The Chinese hamster ovary (CHO) cell line is a major expression system for the production of therapeutic proteins, the majority of which are glycoproteins, such as antibodies and erythropoietin (EPO). The characterization glycosylation profile of therapeutic proteins produced from engineered CHO cells and therapeutic functions, as well as side effects, are critical to understand the important roles of glycosylation. In this study, a large scale glycoproteomic workflow was established and applied to CHO-K1 cells expressing EPO. The workflow includes enrichment of intact glycopeptides from CHO-K1 cell lysate and medium using hydrophilic enrichment, fractionation of the obtained intact glycopeptides (IGPs) by basic reversed phase liquid chromatography (bRPLC), analyzing the glycopeptides using LC-MS/MS, and annotating the results by GPQuest 2.0. A total of 10 338 N-linked glycosite-containing IGPs were identified, representing 1162 unique glycosites in 530 glycoproteins, including 71 unique atypical N-linked IGPs on 18 atypical N-glycosylation sequons with an overrepresentation of the N-X-C motifs. Moreover, we compared the glycoproteins from CHO cell lysate with those from medium using the in-depth N-linked glycoproteome data. The obtained large scale glycoproteomic data from intact N-linked glycopeptides in this study is complementary to the genomic, proteomic, and N-linked glycomic data previously reported for CHO cells. Our method has the potential to monitor the production of recombinant therapeutic glycoproteins.

Glycomics of prostate cancer: updates

Introduction: Prostate cancer (PCa) is a life-threatening disease affecting millions of men. The current best PCa biomarker (level of prostate-specific antigen in serum) lacks specificity for PCa diagnostics and this is why novel PCa biomarkers in addition to the conventional ones based on biomolecules such as DNA, RNA and proteins need to be identified. Areas covered: This review details the potential of glycans-based biomarkers to become diagnostic, prognostic, predictive and therapeutic PCa biomarkers with a brief description of the innovative approaches applied to glycan analysis to date. Finally, the review covers the possibility to use exosomes as a rich source of glycans for future innovative and advanced diagnostics of PCa. The review covers updates in the field since 2016. Expert commentary: The summary provided in this review paper suggests that glycan-based biomarkers can offer high-assay accuracy not only for diagnostic purposes but also for monitoring/surveillance of the PCa disease.

Current Technologies for Complex Glycoproteomics and Their Applications to Biology/Disease-Driven Glycoproteomics

Glycoproteomics is an important recent advance in the field of glycoscience. In glycomics, glycan structures are comprehensively analyzed after glycans are released from glycoproteins. However, a major limitation of glycomics is the lack of insight into glycoprotein functions. The Biology/Disease-driven Human Proteome Project has a particular focus on biological and medical applications. Glycoproteomics technologies aimed at obtaining a comprehensive understanding of intact glycoproteins, i.e., the kind of glycan structures that are attached to particular amino acids and proteins, have been developed. This Review focuses on the recent progress of the technologies and their applications. First, the methods for large-scale identification of both N- and O-glycosylated proteins are summarized. Next, the progress of analytical methods for intact glycopeptides is outlined. MS/MS-based methods were developed for improving the sensitivity and speed of the mass spectrometer, in parallel with the software for complex spectrum assignment. In addition, a unique approach to identify intact glycopeptides using MS1-based accurate masses is introduced. Finally, as an advance of glycomics, two approaches to provide the spatial distribution of glycans in cells are described, i.e., MS imaging and lectin microarray. These methods allow rapid glycomic profiling of different types of biological samples and thus facilitate glycoproteomics.

A sequential separation strategy for facile isolation and comprehensive analysis of human urine N-glycoproteome

Urine is an attractive and non-invasive alternative source to tissue, blood or other biofluids for biomarker screening in clinical research. In normal human adult urine, 48% of the total urinary protein is in the sediment, 49% is soluble and the remaining 3% is contained in urinary extracellular vesicles (EVs). The soluble proteins and EV proteins in urine have attracted particular attention in recent years as cancer diagnostics. Furthermore, considering the important role of N-glycoproteins in practically all physiological processes, including regulating receptor-ligand binding, cell-cell interactions, inflammatory response and tumour progression, N-glycoproteome in human urine is an invaluable target for monitoring the physiological status and pathological changes of the kidney and urinary tract. Given the different origins of the soluble proteins and EV proteins in the urine, different N-glycoproteome patterns exist. Therefore, isolating the soluble N-glycoproteins and EV N-glycoproteins for separate analysis will provide a more specific and comprehensive view and provide a deeper understanding of human urinary N-glycoproteome. In this work, we developed a sequential separation method that isolates urinary soluble proteins and EV proteins via stepwise ultrafiltration based on their obvious size difference. A facile and reproducible protein isolation was achieved using this strategy. Subsequent N-glycoproteome enrichment and identification revealed distinct patterns in the two sub-proteomes of urine with more than 60% differential N-glycopeptides. A more comprehensive picture of the urinary N-glycoproteome with close to 1800 identified N-glycopeptides was obtained by this new analysis strategy, therefore making it advantageous for urinary biomarker screening. Graphical abstract A sequential separation method that isolates urinary soluble proteins and EV proteins via stepwise ultrafiltration was developed in this work. Subsequent N-glycopeptides enrichment and mass spectrometry analysis reveals distinct N-glycoproteome patterns in the two sub-proteomes of urine and a deep mapping of close to 1800 N-glycopeptides.

Promise and Implementation of Proteomic Prostate Cancer Biomarkers

Prostate cancer is one of the most commonly diagnosed malignancy and the fifth leading cause of cancer mortality in men. Despite the broad use of prostate-specific antigen test that resulted in an increase in number of diagnosed cases, disease management needs to be improved. Proteomic biomarkers alone and or in combination with clinical and pathological risk calculators are expected to improve on decreasing the unnecessary biopsies, stratify low risk patients, and predict response to treatment. To this end, significant efforts have been undertaken to identify novel biomarkers that can accurately discriminate between indolent and aggressive cancer forms and indicate those men at high risk for developing prostate cancer that require immediate treatment. In the era of “big data” and “personalized medicine” proteomics-based biomarkers hold great promise to provide clinically applicable tools, as proteins regulate all biological functions, and integrate genomic information with the environmental impact. In this review article, we aim to provide a critical assessment of the current proteomics-based biomarkers for prostate cancer and their actual clinical applicability. For that purpose, a systematic review of the literature published within the last 10 years was performed using the Web of Science Database. We specifically discuss the potential and prospects of use for diagnostic, prognostic and predictive proteomics-based biomarkers, including both body fluid- and tissue-based markers.

Integrative proteomics in prostate cancer uncovers robustness against genomic and transcriptomic aberrations during disease progression

To understand functional consequences of genetic and transcriptional aberrations in prostate cancer, the proteomic changes during disease formation and progression need to be revealed. Here we report high-throughput mass spectrometry on clinical tissue samples of benign prostatic hyperplasia (BPH), untreated primary prostate cancer (PC) and castration resistant prostate cancer (CRPC). Each sample group shows a distinct protein profile. By integrative analysis we show that, especially in CRPC, gene copy number, DNA methylation, and RNA expression levels do not reliably predict proteomic changes. Instead, we uncover previously unrecognized molecular and pathway events, for example, several miRNA target correlations present at protein but not at mRNA level. Notably, we identify two metabolic shifts in the citric acid cycle (TCA cycle) during prostate cancer development and progression. Our proteogenomic analysis uncovers robustness against genomic and transcriptomic aberrations during prostate cancer progression, and significantly extends understanding of prostate cancer disease mechanisms.

Understanding of molecular events in cancer requires proteome-level characterisation. Here, proteome profiling of patient samples representing primary and progressed prostate cancer enables the authors to identify pathway alterations that are not reflected at the genomic and transcriptomic levels.

Mass Spectrometry Approaches to Glycomic and Glycoproteomic Analyses

Glycomic and glycoproteomic analyses involve the characterization of oligosaccharides (glycans) conjugated to proteins. Glycans are produced through a complicated nontemplate driven process involving the competition of enzymes that extend the nascent chain. The large diversity of structures, the variations in polarity of the individual saccharide residues, and the poor ionization efficiencies of glycans all conspire to make the analysis arguably much more difficult than any other biopolymer. Furthermore, the large number of glycoforms associated with a specific protein site makes it more difficult to characterize than any post-translational modification. Nonetheless, there have been significant progress, and advanced separation and mass spectrometry methods have been at its center and the main reason for the progress. While glycomic and glycoproteomic analyses are still typically available only through highly specialized laboratories, new software and workflow is making it more accessible. This review focuses on the role of mass spectrometry and separation methods in advancing glycomic and glycoproteomic analyses. It describes the current state of the field and progress toward making it more available to the larger scientific community.

Molecular correlates in urine for the obesity and prostatic inflammation of BPH/LUTS patients

PURPOSE

Benign prostatic hyperplasia (BPH) is strongly associated with obesity and prostatic tissue inflammation, but the molecular underpinning of this relationship is not known. Here, we examined the association between urine levels of chemokines/adipokines with histological markers of prostate inflammation, obesity, and lower urinary tract symptoms LUTS in BPH patients.

METHODS

Frozen urine specimens from 207 BPH/LUTS patients enrolled in Nashville Men's Health Study were sent for blinded analysis of 11 analytes, namely sIL-1RA, CXC chemokines (CXCL-1, CXCL-8, CXCL-10), CC chemokines (CCL2, CCL3, CCL5), PDGF-BB, interleukins IL-6, IL-17, and sCD40L using Luminex™ xMAP® technology. After adjusting for age and medication use, the urine levels of analytes were correlated with the scales of obesity, prostate inflammation grade, extent, and markers of lymphocytic infiltration (CD3 and CD20) using linear regression.

RESULTS

sIL-1RA levels were significantly raised with higher BMI, waist circumference and waist-hip ratio in BPH patients after correction for multiple testing (P = 0.02). Men with greater overall extent of inflammatory infiltrates and maximal CD3 infiltration were marginally associated with CXCL-10 (P = 0.054) and CCL5 (P = 0.054), respectively. CCL3 in 15 patients with moderate to severe grade inflammation was marginally associated with maximal CD20 infiltration (P = 0.09), whereas CCL3 was undetectable in men with mild prostate tissue inflammation. There was marginal association of sCD40L with AUA-SI scores (P = 0.07).

CONCLUSIONS

Strong association of sIL-1RA in urine with greater body size supports it as a major molecular correlate of obesity in the urine of BPH patients. Increased urine levels of CXCL-10, CCL5, and CCL3 were marginally associated with the scores for prostate tissue inflammation and lymphocytic infiltration. Overall, elevated urinary chemokines support that BPH is a metabolic disorder and suggest a molecular link between BPH/LUTS and prostatic inflammation.

Prostate cancer proteomics: clinically useful protein biomarkers and future perspectives

INTRODUCTION

Although prostate cancer constitutes one of the most important, death-related diseases in the male population, there is still a need for identification of sensitive biomarkers that could precociously detect the disease and differentiate aggressive from indolent cancers, in order to decrease overtreatment. Proteomics research has improved understanding on mechanisms underlying tumorigenesis, cancer cells migration and invasion potential, and castration resistance. This review has focused on proteomic studies of prostate cancer published in the recent years, with a special emphasis on determination of biomarkers for cancer progression and diagnosis. Areas covered: Shotgun and targeted-proteomic studies of prostate cancer in different matrices are reviewed, i.e., prostate tissue, prostate cell lines, blood (serum and plasma), urine, seminal plasma, and exosomes. The most important biomarkers for cancer diagnosis and aggressiveness characterization are highlighted. Expert commentary: In general, results demonstrate alteration in cell cycle control, DNA repair, proteasomal degradation, and metabolic activity. However, these studies suffer from low reproducibility due to heterogeneity of the cancer itself, as well as to techniques utilized for protein identification/quantification. Downstream confirmatory studies in separate cohorts are warranted in order to demonstrate accuracy of these results.

High-throughput analysis of N-glycans using AutoTip via glycoprotein immobilization

Analysis of a large number of samples requires an efficient, rapid and reproducible method. Automation is an ideal approach for high-throughput sample preparation. Multi-plexing sample preparation via a 96-well plate format becomes popular in recent years; however, those methods lack specificity and require several cleanup steps via chromatography purification. To overcome these drawbacks, a chemoenzymatic method has been developed utilizing protein conjugation on solid-phase. Previously, sample preparation was successfully performed in a snap-cap spin-column (SCSC) format. However, sample preparation using SCSC is time-consuming and lacks reproducibility. In this work, we integrated the chemoenzymatic technique in a pipette tip (AutoTip) that was operated by an automated liquid handler. We established a multi-step protocol involving protein immobilization, sialic acid modification, and N-glycan release. We first optimized our automated protocol using bovine fetuin as a standard glycoprotein, and then assessed the reproducibility of the AutoTip using isobaric tags for relative N-linked glycan quantification. We then applied this methodology to profile N-glycans from 58 prostate cancer patient urine samples, revealing increased sialyation on urinary N-glycans derived from prostate cancer patients. Our results indicated AutoTip has applications for high-throughput sample preparation for studying the N-linked glycans.