Development and Validation of Urine-based Peptide Biomarker Panels for Detecting Bladder Cancer in a Multi-center Study

Comprehensive Urinary Proteome Profiling Analysis Identifies Diagnosis and Relapse Surveillance Biomarkers for Bladder Cancer

Bladder cancer (BCa) is the predominant malignancy of the urinary system. Herein, a comprehensive urine proteomic feature was initially established for the noninvasive diagnosis and recurrence monitoring of bladder cancer. 279 cases (63 primary BCa, 87 nontumor controls (NT), 73 relapsed BCa (BCR), and 56 nonrelapsed BCa (BCNR)) were collected to screen urinary protein biomarkers. 4761 and 3668 proteins were qualified and quantified by DDA and sequential window acquisition of all theoretical mass spectra (SWATH-MS) analysis in two discovery sets, respectively. Upregulated proteins were validated by multiple reaction monitoring (MRM) in two independent combined sets. Using the multi-support vector machine-recursive feature elimination (mSVM-RFE) algorithm, a model comprising 13 proteins exhibited good performance between BCa and NT with an AUC of 0.821 (95% CI: 0.675-0.967), 90.9% sensitivity (95% CI: 72.7-100%), and 73.3% specificity (95% CI: 53.3-93.3%) in the diagnosis test set. Meanwhile, an 11-marker classifier significantly distinguished BCR from BCNR with 75.0% sensitivity (95% CI: 50.0-100%), 81.8% specificity (95% CI: 54.5-100%), and an AUC of 0.784 (95% CI: 0.609-0.959) in the test cohort for relapse surveillance. Notably, six proteins (SPR, AK1, CD2AP, ADGRF1, GMPS, and C8A) of 24 markers were newly reported. This paper reveals novel urinary protein biomarkers for BCa and offers new theoretical insights into the pathogenesis of bladder cancer (data identifier PXD044896).

Integration of Urinary Peptidome and Fecal Microbiome to Explore Patient Clustering in Chronic Kidney Disease

Millions of people worldwide currently suffer from chronic kidney disease (CKD), requiring kidney replacement therapy at the end stage. Endeavors to better understand CKD pathophysiology from an omics perspective have revealed major molecular players in several sample sources. Focusing on non-invasive sources, gut microbial communities appear to be disturbed in CKD, while numerous human urinary peptides are also dysregulated. Nevertheless, studies often focus on isolated omics techniques, thus potentially missing the complementary pathophysiological information that multidisciplinary approaches could provide. To this end, human urinary peptidome was analyzed and integrated with clinical and fecal microbiome (16S sequencing) data collected from 110 Non-CKD or CKD individuals (Early, Moderate, or Advanced CKD stage) that were not undergoing dialysis. Participants were visualized in a three-dimensional space using different combinations of clinical and molecular data. The most impactful clinical variables to discriminate patient groups in the reduced dataspace were, among others, serum urea, haemoglobin, total blood protein, urinary albumin, urinary erythrocytes, blood pressure, cholesterol measures, body mass index, Bristol stool score, and smoking; relevant variables were also microbial taxa, including Roseburia, Butyricicoccus, Flavonifractor, Burkholderiales, Holdemania, Synergistaceae, Enterorhabdus, and Senegalimassilia; urinary peptidome fragments were predominantly derived from proteins of collagen origin; among the non-collagen parental proteins were FXYD2, MGP, FGA, APOA1, and CD99. The urinary peptidome appeared to capture substantial variation in the CKD context. Integrating clinical and molecular data contributed to an improved cohort separation compared to clinical data alone, indicating, once again, the added value of this combined information in clinical practice.

Peptidome Profiling of Bubalus bubalis Urine and Assessment of Its Antimicrobial Activity against Mastitis-Causing Pathogens

Urinary proteins have been studied quite exhaustively in the past, however, the small sized peptides have remained neglected for a long time in dairy cattle. These peptides are the products of systemic protein turnover, which are excreted out of the body and hence can serve as an important biomarker for various pathophysiologies. These peptides in other species of bovine have been reported to possess several bioactive properties. To investigate the urinary peptides in buffalo and simultaneously their bioactivities, we generated a peptidome profile from the urine of Murrah Buffaloes (n = 10). Urine samples were processed using <10 kDa MWCO filter and filtrate obtained was used for peptide extraction using Solid Phase Extraction (SPE). The nLC-MS/MS of the aqueous phase from ten animals resulted in the identification of 8165 peptides originating from 6041 parent proteins. We further analyzed these peptide sequences to identify bioactive peptides and classify them into anti-cancerous, anti-hypertensive, anti-microbial, and anti-inflammatory groups with a special emphasis on antimicrobial properties. With this in mind, we simultaneously conducted experiments to evaluate the antimicrobial properties of urinary aqueous extract on three pathogenic bacterial strains: S. aureus, E. coli, and S. agalactiae. The urinary peptides observed in the study are the result of the activity of possibly 76 proteases. The GO of these proteases showed the significant enrichment of the antibacterial peptide production. The total urinary peptide showed antimicrobial activity against the aforementioned pathogenic bacterial strains with no significant inhibitory effects against a buffalo mammary epithelial cell line. Just like our previous study in cows, the present study suggests the prime role of the antimicrobial peptides in the maintenance of the sterility of the urinary tract in buffalo by virtue of their amino acid composition.

Multiple urinary peptides display distinct sex-specific distribution

Previous studies have established the association of sex with gene and protein expression. This study investigated the association of sex with the abundance of endogenous urinary peptides, using capillary electrophoresis-coupled to mass spectrometry (CE-MS) datasets from 2008 healthy individuals and patients with type II diabetes, divided in one discovery and two validation cohorts. Statistical analysis using the Mann-Whitney test, adjusted for multiple testing, revealed 143 sex-associated peptides in the discovery cohort. Of these, 90 peptides were associated with sex in at least one of the validation cohorts and showed agreement in their regulation trends across all cohorts. The 90 sex-associated peptides were fragments of 29 parental proteins. Comparison with previously published transcriptomics data demonstrated that the genes encoding 16 of these parental proteins had sex-biased expression. The 143 sex-associated peptides were combined into a support vector machine-based classifier that could discriminate males from females in two independent sets of healthy individuals and patients with type II diabetes, with an AUC of 89% and 81%, respectively. Collectively, the urinary peptidome contains multiple sex-associated differences, which may enable a better understanding of sex-biased molecular mechanisms and the development of more accurate diagnostic, prognostic, or predictive classifiers for each individual sex.

New Perspectives on the Role of Liquid Biopsy in Bladder Cancer: Applicability to Precision Medicine

Bladder cancer (BC) is one of the most common tumors in the world. Cystoscopy and tissue biopsy are the standard methods in screening and early diagnosis of suspicious bladder lesions. However, they are invasive procedures that may cause pain and infectious complications. Considering the limitations of both procedures, and the recurrence and resistance to BC treatment, it is necessary to develop a new non-invasive methodology for early diagnosis and multiple evaluations in patients under follow-up for bladder cancer. In recent years, liquid biopsy has proven to be a very useful diagnostic tool for the detection of tumor biomarkers. This non-invasive technique makes it possible to analyze single tumor components released into the peripheral circulation and to monitor tumor progression. Numerous biomarkers are being studied and interesting clinical applications for these in BC are being presented, with promising results in early diagnosis, detection of microscopic disease, and prediction of recurrence and response to treatment.

Fetal biomarkers for lower urinary tract obstruction secondary to posterior urethral valves

Today, prenatal diagnosis of congenital urogenital malformations is mostly dependent on anatomical variations found on imaging. However, these findings can mislead us in telling us when to intervene, and about post-natal prognosis. Since many findings are dependent on multiple assessments, delayed diagnosis can occur, leading to less optimal outcomes compared to early intervention. Analyses of fetal urinary biomarkers have been proposed as a method of finding biological changes that are predictive for diagnosis and prognosis in fetuses at risk of kidney disease. We interviewed a group of researchers that have demonstrated that by combining multiple omics traits extracted from fetal urine, the biological variability found in single omics data can be circumvented. By analyzing multiple fetal urine peptides and metabolites at single time point, the prognostic power of postnatal renal outcome in fetuses with lower urinary tract obstruction is significantly increased. In this interview, we inquired about the technical aspects of the tests, challenges, and limitations the research group have come across, and how they envision the future for multi-omics fetal analysis in the clinic.

Peptidomics Strategies to Evaluate Cancer Diagnosis, Prognosis, and Treatment

Peptides have potential bioactive functions, and the peptidomics landscape has been broadly investigated for various diseases, including cancer. In this chapter, we reviewed the past four years of literature available and selected 16 peer-reviewed publications exploring peptidomics in diagnosis, prognosis, and treatment in cancer research. We highlighted their main aims, mass spectrometry-based peptidomics, multi-omics, data-driven and in silico strategies, functional assays, and clinical applications. Moreover, we underscored several levels of difficulties in translating the peptidomics findings to clinical practice, aiming to learn with the accumulated knowledge and guide upcoming studies. Finally, this review reinforces the peptidomics robustness in discovering potential candidates for monitoring the several stages of cancer disease and therapeutic treatment, leveraging the management of cancer patients in the future.

Urinary peptides provide information about the risk of mortality across a spectrum of diseases and scenarios

BACKGROUND

There is evidence of pre-established vulnerability in individuals that increases the risk of their progression to severe disease or death, although the mechanisms causing this are still not fully understood. Previous research has demonstrated that a urinary peptide classifier (COV50) predicts disease progression and death from SARS-CoV-2 at an early stage, indicating that the outcome prediction may be partly due to vulnerabilities that are already present. The aim of this study is to examine the ability of COV50 to predict future non-COVID-19-related mortality, and evaluate whether the pre-established vulnerability can be generic and explained on a molecular level by urinary peptides.

METHODS

Urinary proteomic data from 9193 patients (1719 patients sampled at intensive care unit (ICU) admission and 7474 patients with other diseases (non-ICU)) were extracted from the Human Urinary Proteome Database. The previously developed COV50 classifier, a urinary proteomics biomarker panel consisting of 50 peptides, was applied to all datasets. The association of COV50 scoring with mortality was evaluated.

RESULTS

In the ICU group, an increase in the COV50 score of one unit resulted in a 20% higher relative risk of death [adjusted HR 1.2 (95% CI 1.17-1.24)]. The same increase in COV50 in non-ICU patients resulted in a higher relative risk of 61% [adjusted HR 1.61 (95% CI 1.47-1.76)], consistent with adjusted meta-analytic HR estimate of 1.55 [95% CI 1.39-1.73]. The most notable and significant changes associated with future fatal events were reductions of specific collagen fragments, most of collagen alpha I (I).

CONCLUSION

The COV50 classifier is predictive of death in the absence of SARS-CoV-2 infection, suggesting that it detects pre-existing vulnerability. This prediction is mainly based on collagen fragments, possibly reflecting disturbances in the integrity of the extracellular matrix. These data may serve as a basis for proteomics-guided intervention aiming towards manipulating/ improving collagen turnover, thereby reducing the risk of death.

Liquid biopsy in urothelial carcinoma: Detection techniques and clinical applications

The types of urothelial carcinoma (UC) include urothelial bladder cancer and upper tract urothelial carcinoma. Current diagnostic techniques cannot meet the needs of patients. Liquid biopsy is an accurate method of determining the molecular profile of UC and is a cutting-edge and popular technique that is expected to complement existing detection techniques and benefit patients with UC. Circulating tumor cells, cell-free DNA, cell-free RNA, extracellular vesicles, proteins, and metabolites can be found in the blood, urine, or other bodily fluids and are examined during liquid biopsies. This article focuses on the components of liquid biopsies and their clinical applications in UC. Liquid biopsies have tremendous potential in multiple aspects of precision oncology, from early diagnosis and treatment monitoring to predicting prognoses. They may therefore play an important role in the management of UC and precision medicine.

Mass spectrometry-based proteomics as an emerging tool in clinical laboratories

Mass spectrometry (MS)-based proteomics have been increasingly implemented in various disciplines of laboratory medicine to identify and quantify biomolecules in a variety of biological specimens. MS-based proteomics is continuously expanding and widely applied in biomarker discovery for early detection, prognosis and markers for treatment response prediction and monitoring. Furthermore, making these advanced tests more accessible and affordable will have the greatest healthcare benefit.This review article highlights the new paradigms MS-based clinical proteomics has created in microbiology laboratories, cancer research and diagnosis of metabolic disorders. The technique is preferred over conventional methods in disease detection and therapy monitoring for its combined advantages in multiplexing capacity, remarkable analytical specificity and sensitivity and low turnaround time.Despite the achievements in the development and adoption of a number of MS-based clinical proteomics practices, more are expected to undergo transition from bench to bedside in the near future. The review provides insights from early trials and recent progresses (mainly covering literature from the NCBI database) in the application of proteomics in clinical laboratories.

Recent Advances of Proteomics in Management of Acute Kidney Injury

Acute Kidney Injury (AKI) is currently recognized as a life-threatening disease, leading to an exponential increase in morbidity and mortality worldwide. At present, AKI is characterized by a significant increase in serum creatinine (SCr) levels, typically followed by a sudden drop in glomerulus filtration rate (GFR). Changes in urine output are usually associated with the renal inability to excrete urea and other nitrogenous waste products, causing extracellular volume and electrolyte imbalances. Several molecular mechanisms were proposed to be affiliated with AKI development and progression, ultimately involving renal epithelium tubular cell-cycle arrest, inflammation, mitochondrial dysfunction, the inability to recover and regenerate proximal tubules, and impaired endothelial function. Diagnosis and prognosis using state-of-the-art clinical markers are often late and provide poor outcomes at disease onset. Inappropriate clinical assessment is a strong disease contributor, actively driving progression towards end stage renal disease (ESRD). Proteins, as the main functional and structural unit of the cell, provide the opportunity to monitor the disease on a molecular level. Changes in the proteomic profiles are pivotal for the expression of molecular pathways and disease pathogenesis. Introduction of highly-sensitive and innovative technology enabled the discovery of novel biomarkers for improved risk stratification, better and more cost-effective medical care for the ill patients and advanced personalized medicine. In line with those strategies, this review provides and discusses the latest findings of proteomic-based biomarkers and their prospective clinical application for AKI management.

Proteomics strategies for urothelial bladder cancer diagnosis, prognosis and treatment: Trends for tumor biomarker sources

Urothelial bladder cancer (UBC) is a heterogeneous multifactorial malignancy with a high recurrence rate. Current procedures for UBC diagnosis suffering from the lack of clinical sensitivity and specificity screening tests. Therefore, biomarkers have promising values to predict pathological conditions and can be considered as effective targets for early diagnosis, prognosis and antitumor immunotherapy. Recently, researchers have been interested for tumor proteins as biomarkers for different diseases. At present, proteomics methods have rapidly progressive that has potential identified biomarkers of UBC. Specifically, there has been several studies on the potential application of proteomics for the identification, quantification, and profiling of proteins for UBC in different sources. Based on these studies, using the panel of biomarkers as proteomic patterns may achieve higher sensitivity and specificity than single proteins in the diagnosis of UBC. In the present review, we evaluate recent literature related to the UBC proteome focusing especially on new proteomics techniques. Moreover, we classify UBC tumor biomarkers as diagnostic, prognostic, and therapeutic targets based on their sources (urine, serum/plasm, cell line, and tumor tissue) and we also discuss the advantages and limitations of each source. In this manner, this review article provides a critical assessment presentation of the advances in proteomics for all aspects of UBC diagnosis, prognosis, and treatment based on sources.

Mass Spectrometry-Based Biomarkers to Detect Prostate Cancer: A Multicentric Study Based on Non-Invasive Urine Collection without Prior Digital Rectal Examination

(1) Background: Prostate cancer (PCa) is the most frequently diagnosed cancer in men. Wide application of prostate specific antigen test has historically led to over-treatment, starting from excessive biopsies. Risk calculators based on molecular and clinical variables can be of value to determine the risk of PCa and as such, reduce unnecessary and invasive biopsies. Urinary molecular studies have been mostly focusing on sampling after initial intervention (digital rectal examination and/or prostate massage). (2) Methods: Building on previous proteomics studies, in this manuscript, we aimed at developing a biomarker model for PCa detection based on urine sampling without prior intervention. Capillary electrophoresis coupled to mass spectrometry was applied to acquire proteomics profiles from 970 patients from two different clinical centers. (3) Results: A case-control comparison was performed in a training set of 413 patients and 181 significant peptides were subsequently combined by a support vector machine algorithm. Independent validation was initially performed in 272 negative for PCa and 138 biopsy-confirmed PCa, resulting in an AUC of 0.81, outperforming current standards, while a second validation phase included 147 PCa patients. (4) Conclusions: This multi-dimensional biomarker model holds promise to improve the current diagnosis of PCa, by guiding invasive biopsies.

Multicentric validation of diagnostic tests based on BC-116 and BC-106 urine peptide biomarkers for bladder cancer in two prospective cohorts of patients

BACKGROUND

Non-invasive urine-based biomarkers can potentially improve current diagnostic and monitoring protocols for bladder cancer (BC). Here we assess the performance of earlier published biomarker panels for BC detection (BC-116) and monitoring of recurrence (BC-106) in combination with cytology, in two prospectively collected patient cohorts.

METHODS

Of the 602 patients screened for BC, 551 were found eligible. For the primary setting, 73 patients diagnosed with primary BC (n = 27) and benign urological disorders, including patients with macroscopic haematuria, cystitis and/or nephrolithiasis (n = 46) were included. In total, 478 patients under surveillance were additionally considered (83 BC recurrences; 395 negative for recurrence). Urine samples were analysed with capillary electrophoresis-mass spectrometry. The biomarker score was estimated via support vector machine-based software.

RESULTS

Validation of BC-116 biomarker panel resulted in 89% sensitivity and 67% specificity (AUCBC-116 = 0.82). A diagnostic score based on cytology and BC-116 resulted in good (AUCNom116 = 0.85) but not significantly better performance (P = 0.5672). A diagnostic score including BC-106 and cytology was evaluated (AUCNom106 = 0.82), significantly outperforming both cytology (AUCcyt = 0.72; P = 0.0022) and BC-106 (AUCBC-106 = 0.67; P = 0.0012).

CONCLUSIONS

BC-116 biomarker panel is a useful test for detecting primary BC. BC-106 classifier integrated with cytology showing >95% negative predictive value, might be useful for decreasing the number of cystoscopies during surveillance.

Selective Detection and Characterization of Small Cysteine-Containing Peptides with Cluster-Modified Nanopore Sensing

It was recently demonstrated that one can monitor ligand-induced structure fluctuations of individual thiolate-capped gold nanoclusters using resistive-pulse nanopore sensing. The magnitude of the fluctuations scales with the size of the capping ligand, and it was later shown one can observe ligand exchange in this nanopore setup. We expand on these results by exploring the different types of current fluctuations associated with peptide ligands attaching to tiopronin-capped gold nanoclusters. We show here that the fluctuations can be used to identify the attaching peptide through either the magnitude of the peptide-induced current jumps or the onset of high-frequency current fluctuations. Importantly, the peptide attachment process requires that the peptide contains a cysteine residue. This suggests that nanopore-based monitoring of peptide attachments with thiolate-capped clusters could provide a means for selective detection of cysteine-containing peptides. Finally, we demonstrate the cluster-based protocol with various peptide mixtures to show that one can identify more than one cysteine-containing peptide in a mixture.

Predicting Recurrence of Non-Muscle-Invasive Bladder Cancer: Current Techniques and Future Trends

Bladder cancer (BC) is the 10th most common cancer globally and has a high mortality rate if not detected early and treated promptly. Non-muscle-invasive BC (NMIBC) is a subclassification of BC associated with high rates of recurrence and progression. Current tools for predicting recurrence and progression on NMIBC use scoring systems based on clinical and histopathological markers. These exclude other potentially useful biomarkers which could provide a more accurate personalized risk assessment. Future trends are likely to use artificial intelligence (AI) to enhance the prediction of recurrence in patients with NMIBC and decrease the use of standard clinical protocols such as cystoscopy and cytology. Here, we provide a comprehensive survey of the most recent studies from the last decade (N = 70 studies), focused on the prediction of patient outcomes in NMIBC, particularly recurrence, using biomarkers such as radiomics, histopathology, clinical, and genomics. The value of individual and combined biomarkers is discussed in detail with the goal of identifying future trends that will lead to the personalized management of NMIBC.

The Role of Novel Bladder Cancer Diagnostic and Surveillance Biomarkers-What Should a Urologist Really Know?

The aim of this review is to analyze and describe the current landscape of bladder cancer diagnostic and surveillance biomarkers. We researched the literature from 2016 to November 2021 to find the most promising new molecules and divided them into seven different subgroups based on their function and location in the cell. Although cystoscopy and cytology are still the gold standard for diagnosis and surveillance when it comes to bladder cancer (BCa), their cost is quite a burden for national health systems worldwide. Currently, the research is focused on finding a biomarker that has high negative predictive value (NPV) and can exclude with a certainty the presence of the tumor, considering missing it could be disastrous for the patient. Every subgroup has its own advantages and disadvantages; for example, protein biomarkers cost less than genomic ones, but on the other hand, they seem to be less precise. We tried to simplify this complicated topic as much as possible in order to make it comprehensible to doctors and urologists that are not as familiar with it, as well as encourage them to actively participate in ongoing research.

circRNA CRIM1 regulates the migration and invasion of bladder cancer by targeting miR182/Foxo3a axis

PURPOSE

To explore the molecular mechanism of circRNA CRIM1 in the regulation of bladder cancer by targeting the miR182/Foxo3a axis.

METHODS

50 pairs of cancer tissues and para-cancerous tissues of patients with bladder cancer were collected. RT-PCR method was used to detect the expression of CRIM1 and miR-182. The association between circRNA CRIM1 and clinical data was analyzed. qPCR was used to measure the expression of circRNA CRIM1 and miR-182 in bladder cancer cell UMUC3 and endothelial cell line HUVEC. CRIM1 genes and miR-182 in UMUC3 cell lines were overexpressed and silenced, respectively, to investigate their effects on invasion and migration of bladder cancer, and to detect the changes of miR182/Foxo3a expression. The association between circRNA CRIM1 and miR182/Foxo3a was determined by bioinformatics analysis.

RESULTS

The results showed that there was a significant association between the expression of circRNA CRIM1 and distal migration. The expression of CRIM1 in adjacent tissues was significantly down-regulated and negatively correlated with distal migration. The overexpression of circRNA CRIM1 reduced migration and invasion processes in bladder cancer cells. After circRNA CRIM1 was overexpressed, the miR-182 was significantly down-regulated. The expression levels of Foxo3a mRNA and proteins were up-regulated after miR-182 silencing of bladder cancer cell line UMUC3. miR-182 silencing inhibited invasion and migration of cancer cells to some extent. In bladder cancer cells and tissues, CRIM1 and Foxo3a were significantly down-regulated, miR-182 was significantly up-regulated.

CONCLUSION

circRNA CRIM1 regulated the migration and invasion of bladder cancer by targeting the miR182/Foxo3a axis.

Peptidomics analysis reveals changes in small urinary peptides in patients with interstitial cystitis/bladder pain syndrome

Interstitial cystitis/bladder pain syndrome (IC/BPS) is a chronic and debilitating pain disorder of the bladder and urinary tract with poorly understood etiology. A definitive diagnosis of IC/BPS can be challenging because many symptoms are shared with other urological disorders. An analysis of urine presents an attractive and non-invasive resource for monitoring and diagnosing IC/BPS. The antiproliferative factor (APF) peptide has been previously identified in the urine of IC/BPS patients and is a proposed biomarker for the disorder. Nevertheless, other small urinary peptides have remained uninvestigated in IC/BPS primarily because protein biomarker discovery efforts employ protocols that remove small endogenous peptides. The purpose of this study is to investigate the profile of endogenous peptides in IC/BPS patient urine, with the goal of identifying putative peptide biomarkers. Here, a non-targeted peptidomics analysis of urine samples collected from IC/BPS patients were compared to urine samples from asymptomatic controls. Our results show a general increase in the abundance of urinary peptides in IC/BPS patients, which is consistent with an increase in inflammation and protease activity characteristic of this disorder. In total, 71 peptides generated from 39 different proteins were found to be significantly altered in IC/BPS. Five urinary peptides with high variable importance in projection (VIP) coefficients were found to reliably differentiate IC/BPS from healthy controls by receiver operating characteristic (ROC) analysis. In parallel, we also developed a targeted multiple reaction monitoring method to quantify the relative abundance of the APF peptide from patient urine samples. Although the APF peptide was found in moderately higher abundance in IC/BPS relative to control urine, our results show that the APF peptide was inconsistently present in urine, suggesting that its utility as a sole biomarker of IC/BPS may be limited. Overall, our results revealed new insights into the profile of urinary peptides in IC/BPS that will aid in future biomarker discovery and validation efforts.

Proteomics for Early Detection of Non-Muscle-Invasive Bladder Cancer: Clinically Useful Urine Protein Biomarkers

Bladder cancer is the fourth most common cancer in men, and most cases are non-muscle-invasive. A high recurrence rate is a critical problem in non-muscle-invasive bladder cancer. The availability of few urine tests hinders the effective detection of superficial and small bladder tumors. Cystoscopy is the gold standard for diagnosis; however, it is associated with urinary tract infections, hematuria, and pain. Early detection is imperative, as intervention influences recurrence. Therefore, urinary biomarkers need to be developed to detect these bladder cancers. Recently, several protein candidates in the urine have been identified as biomarkers. In the present narrative review, the current status of the development of urinary protein biomarkers, including FDA-approved biomarkers, is summarized. Additionally, contemporary proteomic technologies, such as antibody-based methods, mass-spectrometry-based methods, and machine-learning-based diagnosis, are reported. Furthermore, new strategies for the rapid and correct profiling of potential biomarkers of bladder cancer in urine are introduced, along with their limitations. The advantages of urinary protein biomarkers and the development of several related technologies are highlighted in this review. Moreover, an in-depth understanding of the scientific background and available protocols in research and clinical applications of the surveillance of non-muscle bladder cancer is provided.

Sensitive Identification of Known and Unknown Protease Activities by Unsupervised Linear Motif Deconvolution

The cleavage-site specificities for many proteases are not well understood, restricting the utility of supervised classification methods. We present an algorithm and web interface to overcome this limitation through the unsupervised detection of overrepresented patterns in protein sequence data, providing insight into the mixture of protease activities contributing to a complex system. Here, we apply the RObust LInear Motif Deconvolution (RoLiM) algorithm to confidently detect substrate cleavage patterns for SARS-CoV-2 MPro protease in the N-terminome data of an infected human cell line. Using mass spectrometry-based peptide data from a case-control comparison of 341 primary urothelial bladder cancer cases and 110 controls, we identified distinct sequence motifs indicative of increased matrix metallopeptidase activity in urine from cancer patients. The evaluation of N-terminal peptides from patient plasma post-chemotherapy detected novel granzyme B/corin activity. RoLiM will enhance the unbiased investigation of peptide sequences to establish the composition of known and uncharacterized protease activities in biological systems. RoLiM is available at http://langelab.org/rolim/.

Validation of diagnostic nomograms based on CE-MS urinary biomarkers to detect clinically significant prostate cancer

PURPOSE

Prostate cancer (PCa) is one of the most common cancers and one of the leading causes of death worldwide. Thus, one major issue in PCa research is to accurately distinguish between indolent and clinically significant (csPCa) to reduce overdiagnosis and overtreatment. In this study, we aim to validate the usefulness of diagnostic nomograms (DN) to detect csPCa, based on previously published urinary biomarkers.

METHODS

Capillary electrophoresis/mass spectrometry was employed to validate a previously published biomarker model based on 19 urinary peptides specific for csPCa. Added value of the 19-biomarker (BM) model was assessed in diagnostic nomograms including prostate-specific antigen (PSA), PSA density and the risk calculator from the European Randomized Study of Screening. For this purpose, urine samples from 147 PCa patients were collected prior to prostate biopsy and before performing digital rectal examination (DRE). The 19-BM score was estimated via a support vector machine-based software based on the pre-defined cutoff criterion of - 0.07. DNs were subsequently developed to assess added value of integrative diagnostics.

RESULTS

Independent validation of the 19-BM resulted in an 87% sensitivity and 65% specificity, with an AUC of 0.81, outperforming PSA (AUC _PSA: 0.64), PSA density (AUC _PSAD: 0.64) and ERSPC-3/4 risk calculator (0.67). Integration of 19-BM with the rest clinical variables into distinct DN, resulted in improved (AUC range: 0.82-0.88) but not significantly better performances over 19-BM alone.

CONCLUSION

19-BM alone or upon integration with clinical variables into DN, might be useful for detecting csPCa by decreasing the number of biopsies.

Molecular Mapping of Urinary Complement Peptides in Kidney Diseases

Defective complement activation has been associated with various types of kidney disease. This led to the hypothesis that specific urine complement fragments may be associated with kidney disease etiologies, and disease progression may be reflected by changes in these complement fragments. We investigated the occurrence of complement fragments in urine, their association with kidney function and disease etiology in 16,027 subjects, using mass spectrometry based peptidomics data from the Human Urinary Proteome/Peptidome Database. Twenty-three different urinary peptides originating from complement proteins C3, C4 and factor B (CFB) could be identified. Most C3-derived peptides showed inverse association with estimated glomerular filtration rate (eGFR), while the majority of peptides derived from CFB demonstrated positive association with eGFR. Several peptides derived from the complement proteins C3, C4 and CFB were found significantly associated with specific kidney disease etiologies. These peptides may depict disease-specific complement activation and could serve as non-invasive biomarkers to support development of complement interventions through assessing complement activity for patients’ stratification and monitoring of drug impact. Further investigation of these complement peptides may provide additional insight into disease pathophysiology and could possibly guide therapeutic decisions, especially when targeting complement factors.

Peptidomics and Capillary Electrophoresis

Peptides play a crucial role in many vitally important functions of living organisms. The goal of peptidomics is the identification of the "peptidome," the whole peptide content of a cell, organ, tissue, body fluid, or organism. In peptidomic or proteomic studies, capillary electrophoresis (CE) is an alternative technique for liquid chromatography. It is a highly efficient and fast separation method requiring extremely low amounts of sample. In peptidomic approaches, CE is commonly combined with mass spectrometric (MS) detection. Most often, CE is coupled with electrospray ionization MS and less frequently with matrix-assisted laser desorption/ionization MS. CE-MS has been employed in numerous studies dealing with determination of peptide biomarkers in different body fluids for various diseases, or in food peptidomic research for the analysis and identification of peptides with special biological activities. In addition to the above topics, sample preparation techniques commonly applied in peptidomics before CE separation and possibilities for peptide identification and quantification by CE-MS or CE-MS/MS methods are discussed in this chapter.

Current applications of capillary electrophoresis-mass spectrometry for the analysis of biologically important analytes in urine (2017 to mid-2021): A review

Capillary electrophoresis coupled online with mass detection is a modern tool for analyzing wide ranges of compounds in complex samples, including urine. Capillary electrophoresis with mass spectrometry allows the separation and identification of various analytes spanning from small ions to high molecular weight protein complexes. Similarly to the much more common liquid chromatography‐mass spectrometry techniques, the capillary electrophoresis separation reduces the complexity of the mixture of analytes entering the mass spectrometer resulting in reduced ion suppression and a more straightforward interpretation of the mass spectrometry data. This review summarizes capillary electrophoresis with mass spectrometry studies published between the years 2017 and 2021, aiming at the determination of various compounds excreted in urine. The properties of the urine, including its diagnostical and analytical features and chemical composition, are also discussed including general protocols for the urine sample preparation. The mechanism of the electrophoretic separation and the instrumentation for capillary electrophoresis with mass spectrometry coupling is also included. This review shows the potential of the capillary electrophoresis with mass spectrometry technique for the analyses of different kinds of analytes in a complex biological matrix. The discussed applications are divided into two main groups (capillary electrophoresis with mass spectrometry for the determination of drugs and drugs of abuse in urine and capillary electrophoresis with mass spectrometry for the studies of urinary metabolome).

Integrative Transcriptomic, Lipidomic, and Metabolomic Analysis Reveals Potential Biomarkers of Basal and Luminal Muscle Invasive Bladder Cancer Subtypes

Muscle invasive bladder cancer (MIBC) is a heterogeneous disease with a high recurrence rate and poor clinical outcomes. Molecular subtype provides a new framework for the study of MIBC heterogeneity. Clinically, MIBC can be classified as basal and luminal subtypes; they display different clinical and pathological characteristics, but the molecular mechanism is still unclear. Lipidomic and metabolomic molecules have recently been considered to play an important role in the genesis and development of tumors, especially as potential biomarkers. Their different expression profiles in basal and luminal subtypes provide clues for the molecular mechanism of basal and luminal subtypes and the discovery of new biomarkers. Herein, we stratified MIBC patients into basal and luminal subtypes using a MIBC classifier based on transcriptome expression profiles. We qualitatively and quantitatively analyzed the lipids and metabolites of basal and luminal MIBC subtypes and identified their differential lipid and metabolite profiles. Our results suggest that free fatty acids (FFAs) and sulfatides (SLs), which are closely associated with immune and stromal cell types, can contribute to the diagnosis of basal and luminal subtypes of MIBC. Moreover, we showed that glycerophosphocholine (GCP)/imidazoles and nucleosides/imidazoles ratios can accurately distinguish the basal and luminal tumors. Overall, by integrating transcriptomic, lipidomic, and metabolomic data, our study reveals specific biomarkers to differentially diagnose basal and luminal MIBC subtypes and may provide a basis for precision therapy of MIBC.

Pathophysiological Implications of Urinary Peptides in Hepatocellular Carcinoma

Simple Summary

In this study, the application of capillary electrophoresis mass spectrometry enabled identification of 31 urinary peptides significantly associated with hepatocellular carcinoma diagnosis and prognosis. Further assessment of these peptides lead to prediction of cellular proteases involved in their development namely Meprin A subunit α and Kallikrein-6. Subsequent identification of the proteases was verified by immunohistochemistry in normal liver, cirrhosis and hepatocellular carcinoma. Histopathological assessment of the proteases revealed numerical gradient staining signifying their involvement in liver fibrosis and hepatocellular carcinoma formation. The discovered urinary peptides offered a potential noninvasive tool for diagnosis and prognosis of hepatocellular carcinoma.

Abstract

Hepatocellular carcinoma (HCC) is known to be associated with protein alterations and extracellular fibrous deposition. We investigated the urinary proteomic profiles of HCC patients in this prospective cross sectional multicentre study. 195 patients were recruited from the UK (Coventry) and Germany (Hannover) between 1 January 2013 and 30 June 2019. Out of these, 57 were HCC patients with a background of liver cirrhosis (LC) and 138 were non-HCC controls; 72 patients with LC, 57 with non-cirrhotic liver disease and 9 with normal liver function. Analysis of the urine samples was performed by capillary electrophoresis (CE) coupled to mass spectrometry (MS). Peptide sequences were obtained and 31 specific peptide markers for HCC were identified and further integrated into a multivariate classification model. The peptide model demonstrated 79.5% sensitivity and 85.1% specificity (95% CI: 0.81–0.93, p < 0.0001) for HCC and 4.1-fold increased risk of death (95% CI: 1.7–9.8, p = 0.0005). Proteases potentially involved in HCC progression were mapped to the N- and C-terminal sequence motifs of the CE-MS peptide markers. In silico protease prediction revealed that kallikrein-6 (KLK6) elicits increased activity, whilst Meprin A subunit α (MEP1A) has reduced activity in HCC compared to the controls. Tissue expression of KLK6 and MEP1A was subsequently verified by immunohistochemistry.

Proteomic profiling of bladder cancer for precision medicine in the clinical setting: A review for the busy urologist

At present, proteomic methods have successfully identified potential biomarkers of urological malignancies, such as prostate cancer (PC), bladder cancer (BC), and renal cell carcinoma (RCC), reflecting different numbers of key cellular processes, including extracellular environment modification, invasion and metastasis, chemotaxis, differentiation, metabolite transport, and apoptosis. The potential application of proteomics in the detection of clinical markers of urological malignancies can help improve patient assessment through early cancer detection, prognosis, and treatment response prediction. A variety of proteomic studies have already been carried out to find prognostic BC biomarkers, and a large number of potential biomarkers have been reported. It is worth noting that proteomics research has not been applied to the study of predictive markers; this may be due to the incompatibility between the number of measured variables and the available sample size, which has become particularly evident in the study of therapeutic response. On the contrary, prognostic correlation is more common, which is also reflected in existing research. We are now entering an era of clinical proteomics. Driven by proteomic-based workflows, computing tools, and the applicability of cross-correlation of proteomic data, it is now feasible to use proteomic analysis to support personalized medicine. In this paper, we will summarize the current emerging technologies for advanced discovery, targeted proteomics, and proteomic applications in BC, particularly in discovery of human-based biomarkers.

Assessment of Immunological Features in Muscle-Invasive Bladder Cancer Prognosis Using Ensemble Learning

The clinical staging and prognosis of muscle-invasive bladder cancer (MIBC) routinely includes the assessment of patient tissue samples by a pathologist. Recent studies corroborate the importance of image analysis in identifying and quantifying immunological markers from tissue samples that can provide further insight into patient prognosis. In this paper, we apply multiplex immunofluorescence to MIBC tissue sections to capture whole-slide images and quantify potential prognostic markers related to lymphocytes, macrophages, tumour buds, and PD-L1. We propose a machine-learning-based approach for the prediction of 5 year prognosis with different combinations of image, clinical, and spatial features. An ensemble model comprising several functionally different models successfully stratifies MIBC patients into two risk groups with high statistical significance (p value < 1×10-5). Critical to improving MIBC survival rates, our method correctly classifies 71.4% of the patients who succumb to MIBC, which is significantly more than the 28.6% of the current clinical gold standard, the TNM staging system.

Liquid Biopsy Biomarkers in Urine: A Route towards Molecular Diagnosis and Personalized Medicine of Bladder Cancer

Bladder cancer (BC) is characterized by high incidence and recurrence rates together with genomic instability and elevated mutation degree. Currently, cystoscopy combined with cytology is routinely used for diagnosis, prognosis and disease surveillance. Such an approach is often associated with several side effects, discomfort for the patient and high economic burden. Thus, there is an essential demand of non-invasive, sensitive, fast and inexpensive biomarkers for clinical management of BC patients. In this context, liquid biopsy represents a very promising tool that has been widely investigated over the last decade. Liquid biopsy will likely be at the basis of patient selection for precision medicine, both in terms of treatment choice and real-time monitoring of therapeutic effects. Several different urinary biomarkers have been proposed for liquid biopsy in BC, including DNA methylation and mutations, protein-based assays, non-coding RNAs and mRNA signatures. In this review, we summarized the state of the art on different available tests concerning their potential clinical applications for BC detection, prognosis, surveillance and response to therapy.

MCM5 urine expression (ADXBLADDER) is a reliable biomarker of high-risk non- muscle-invasive bladder cancer recurrence: A prospective matched case-control study

BACKGROUND

Mini Chromosome Maintenance 5 (MCM5) is considered as a urinary biomarker of bladder cancer. ADXBLADDER is a commercially available test to detect MCM5 antibodies.

OBJECTIVE

External validation of ADXBLADDER test as a urinary biomarker of histopathologically confirmed non-muscle invasive bladder cancer (NMIBC) recurrence.

METHODS

The study enrolled 119 consecutive patients with a history of NMIBC and 37 healthy volunteers matched as controls. Single, full-void urine samples were collected from patients before cystoscopy ± TUR. To measure MCM5 expression, Arquer Diagnostics ADXBLADDER test was used. The study protocol was registered within the clinical trials database (NCT03796299).

RESULTS

Among patients with NMIBC history, recurrence was diagnosed in 83 patients (69.7%). ADXBLADDER demonstrated sensitivity of 73.5% (95% confidence interval (CI) 62.7%-82.6%), specificity of 33.3% (95% CI 18.6% to 51%), overall negative predictive value (NPV) of 35.3% (95% CI 23.3% to 49.5%) and overall positive predictive value of 71.8% (95% CI 66.1% to 76.8%) for detecting recurrence. In a control group, false positive ADXBLADDER results were noticed in 18 patients (48.6%). The sensitivity and NPV were the highest in invasive tumors (100% and 100%, respectively) and in high-grade recurrences (81.8% and 94.1%, respectively).

CONCLUSIONS

ADXBLADDER has a moderate sensitivity and poor specificity in detecting NMIBC recurrence. However, it properly diagnoses patients with T1+ stage recurrence or high-grade tumors.

Clinical Value of Postoperative Neutrophil-to-Lymphocyte Ratio Change as a Detection Marker of Bladder Cancer Recurrence

Purpose

This study investigated the clinical significance of postoperative neutrophil-to-lymphocyte ratio (NLR) changes in bladder cancer recurrence.

Patients and Methods

For evaluating the predictive value of postoperative dynamic change of NLR, a retrospective cohort study was performed to analyze 213 patients with bladder cancer who underwent surgical treatment from January 2013 to December 2019 at the Affiliated Tumor Hospital of Guangxi Medical University. Baseline characteristics and recurrence-free survival (RFS) were statistically compared, and a multivariate analysis was used to identify prognostic factors.

Results

Compared with preoperative NLR levels, postoperative decreased NLR in 130 patients and postoperative increased NLR in 83 patients were detected. The 1-, 3- and 5-year RFS rates were 88.0%, 75.4% and 75.4% in the decreased postoperative NLR group, respectively, and 51.2%, 25.8% and 16.1% in the increased postoperative NLR group, respectively (P < 0.05). Kaplan–Meier curves showed that the cumulative DFS rate in the increased group was significantly lower than that in the decreased group (P < 0.05). The preoperative NLR showed significant difference with postoperative NLR in the total cohort, high-grade non-muscle-invasive bladder cancer (HG-NMIBC) and muscle-invasive bladder cancer (MIBC) group, while there was no significant difference between postoperative NLR and NLR of recurrence or last follow-up. Multivariate analysis suggested that postoperative-preoperative NLR was an independent predictor for RFS (HR=6.206, 95% CI: 3.826–10.067, P < 0.001) in the total cohort, RFS (HR=9.373, 95% CI: 2.724–32.245, P < 0.001) in the LG-NMIBC group, RFS rates (HR=6.873, 95% CI: 2.486–18.999, P < 0.001) in the HG-NMIBC group and RFS rates (HR=6.109, 95% CI: 2.847–13.109, P < 0.001) in the MIBC group.

Conclusion

The dynamic change of postoperative NLR is a potential marker for the early detection of bladder cancer recurrence. Patients with increased NLR after surgery tend to have higher risk of recurrence.

Comparison of the amniotic fluid and fetal urine peptidome for biomarker discovery in renal developmental disease

Production of amniotic fluid (AF) is view as predominately driven by excretion of fetal urine (FU). However, the origin of AF peptides, often considered as potential biomarkers of developmental diseases, has never been investigated. Here, we evaluated the FU origin of AF peptides and if the AF peptide content can be used as a surrogate of FU. The abundance of endogenous peptides was analyzed by capillary electrophoresis coupled to mass spectrometry in 216 AF and 64 FU samples. A total of 2668 and 3257 peptides was found in AF and FU respectively. The AF peptidome largely overlapped with the FU peptidome, ranging from 54% in the second pregnancy trimester to 65% in the third trimester. Examination of a subset of 16 paired AF and FU samples revealed that 67 peptides displayed a significant positively correlated abundance in AF and FU, strongly suggesting that their presence in AF was directly associated to FU excretion. As proof-of-concept we showed that measuring the AF abundance of these 67 peptides of FU origin allowed prediction of postnatal renal survival in fetuses with posterior urethral valves. These results demonstrate that the AF peptidome can be considered as a good surrogate of the FU peptidome.

Profiling Analysis Reveals the Crucial Role of the Endogenous Peptides in Bladder Cancer Progression

Background

Peptide drugs provide promising regimes in bladder cancer. In order to identify potential bioactive peptides involved in bladder cancer, we performed the present study.

Methods

Liquid chromatography/mass spectrometry assay was used to compare the endogenous peptides between bladder cancer and normal control. The potential biological functions of these dysregulated peptides are assessed by GO analysis and KEGG pathway analysis of their precursors. The SMART and UniProt databases are used to identify the sequences of the dysregulated peptides located in the functional domains. The Open Targets Platform database was used to investigate the precursors related to metabolic diseases.

Results

A total of 9 up-regulated peptides and 110 down-regulated peptides in bladder cancer compared with normal control were identified (fold change > 1.2, P < 0.05). The MW of these dysregulated peptides ranged from 500 Da to 2500 Da and the MW of all identified peptides was below 3500 Da. The GO and KEGG pathway analysis indicated that these dysregulated peptides could play an important role in bladder cancer. Our further analysis revealed that ⁴⁵HFNPRFNAHGDAN ⁵⁷ derived from LGALS1 and those peptides derived from P4HB and SERPINA1 might be the promising diagnostic biomarkers and therapeutic targets of bladder cancer.

Conclusion

In the present study, we have identified the profile of the peptides significantly dysregulated in bladder cancer. Moreover, using bioinformatic analysis, we found the peptides derived from LGALS1, P4HB and SERPINA1 could be the promising diagnostic biomarkers and therapeutic targets of bladder cancer.

Cancer cell detection device for the diagnosis of bladder cancer from urine

Bladder cancer is common and has one of the highest recurrence rates. Cystoscopy, the current gold standard diagnosis approach, has recently benefited from the introduction of blue light assisted photodynamic diagnostic (PDD). While blue light cystoscopy improves diagnostic sensitivity, it remains a costly and invasive approach. Here, we present a microfluidic-based platform for non-invasive diagnosis which combines the principle of PDD with whole cell immunocapture technology to detect bladder cancer cells shed in patient urine ex vivo. Initially, we demonstrate with model cell lines that our non-invasive approach achieves highly specific capture rates of bladder cancer cells based on their Epithelial Cell Adhesion Molecule expression (>90%) and detection by the intensity levels of Hexaminolevulinic Acid-induced Protoporphyrin IX fluorescence. Then, we show in a pilot study that the biosensor platform successfully discriminates histopathologically diagnosed cancer patients (n = 10) from non-cancer controls (n = 25). Our platform can support the development of a novel non-invasive diagnostic device for post treatment surveillance in patients with bladder cancer and cancer detection in patients with suspected bladder cancer.

Profilin choreographs actin and microtubules in cells and cancer

Actin and microtubules play essential roles in aberrant cell processes that define and converge in cancer including: signaling, morphology, motility, and division. Actin and microtubules do not directly interact, however shared regulators coordinate these polymers. While many of the individual proteins important for regulating and choreographing actin and microtubule behaviors have been identified, the way these molecules collaborate or fail in normal or disease contexts is not fully understood. Decades of research focus on Profilin as a signaling molecule, lipid-binding protein, and canonical regulator of actin assembly. Recent reports demonstrate that Profilin also regulates microtubule dynamics and polymerization. Thus, Profilin can coordinate both actin and microtubule polymer systems. Here we reconsider the biochemical and cellular roles for Profilin with a focus on the essential cytoskeletal-based cell processes that go awry in cancer. We also explore how the use of model organisms has helped to elucidate mechanisms that underlie the regulatory essence of Profilin in vivo and in the context of disease.

Circulating proteomic signature for detection of biomarkers in bladder cancer patients

The identification of clinically-relevant early diagnostic and prognostic protein biomarkers is essential to maximize therapeutic efficacy and prevent cancer progression. The aim of the current study is to determine whether aberrant plasma protein profile can be applied as a surrogate tool for early diagnosis of bladder carcinoma. Plasma samples from patients with low grade non-muscle invasive bladder cancer and healthy controls were analyzed using combined 2D-DIGE and mass-spectrometry to identify differentially expressed proteins. Validation was performed using western blotting analysis in an independent cohort of cancer patients and controls. Fifteen differentially-expressed proteins were identified of which 12 were significantly up-regulated and three were significantly down-regulated in tumors compared to controls. The Ingenuity Pathways Analysis revealed functional connection between the differentially-expressed proteins and immunological disease, inflammatory disease and cancer mediated through chemokine and cytokine signaling pathway and NF-kB transcription factor. Among the three validated proteins, haptoglobin was able to distinguish between patients with low grade bladder cancer and the controls with high sensitivity and specificity (AUC > 0.87). In conclusion, several biomarker proteins were identified in bladder cancer. Haptoglobin is a potential candidate that merit further investigation to validate its usefulness and functional significance as potential biomarkers for early detection of bladder cancer.

Shedding Light on Bladder Cancer Diagnosis in Urine

Blue light cystoscopy (BLC) is the most recent clinical approach in the detection and diagnosis of bladder cancer, a common type of cancer with a high rate of recurrence. Representing a significant advance over previous approaches, this photodynamic diagnostic technique uses a photosensitiser prodrug as an adjunct to white light cystoscopy to enhance the in vivo detection of malignant tissues in the bladder based on their distinctive fluorescence. Whilst it does improve detection rates, BLC remains an invasive and costly procedure. Meanwhile, a variety of noninvasive urine detection methods and related microdevices have been developed, none of which have yet entered routine clinical use due to unsatisfactory sensitivity. Following a brief description of the current approaches and their limitations, we provide here a systematic review of a newer niche research aiming to develop a noninvasive adaptation of photodynamic diagnosis. The research to date surrounding the ex situ use of photosensitiser prodrugs for urinary diagnosis of bladder cancer is also discussed.

Proteomic research and diagnosis in bladder cancer: state of the art review

Purpose:

Proteomic biomarkers have been emerging as alternative methods to the gold standard procedures of cystoscopy and urine cytology in the diagnosis and surveillance of bladder cancer (BC). This review aims to update the state of the art of proteomics research and diagnosis in BC.

Materials and Methods:

We reviewed the current literature related to BC research on urinary, tissue, blood and cell line proteomics, using the Pubmed database.

Findings:

Two urinary protein biomarkers are FDA-approved (NMP22® and BTA® tests), only if performed along with cystoscopy for surveillance after initial diagnosis, but not in the primary diagnostic setting due to high false-positive rates in case of infections, stones and hematuria. There are a great number of non-FDA approved proteins being studied, with good preliminary results; panels of proteins seem valuable tools to be refined in ongoing trials. Blood proteins are a bigger challenge, because of the complexity of the serum protein profile and the scarcity of blood proteomic studies in BC. Previous studies with the BC tissue proteome do not correlate well with the urinary proteome, likely due to the tumor heterogeneity. Cell line proteomic research helps in the understanding of basic mechanisms that drive BC development and progression; the main difficulty is culturing low-grade tumors in vitro, which represents the majority of BC tumors in clinical practice.

Conclusion:

Protein biomarkers have promising value in the diagnosis, surveillance and prognostic of BC. Urine is the most appropriate body fluid for biomarker research in BC due to its easiness of sampling, stability and enrichment of shed and secreted tumor-specific proteins. Panels of biomarkers may exhibit higher sensitivity than single proteins in the diagnosis of BC at larger populations due to clinical and tumor heterogeneity. Prospective clinical trials are warranted to validate the relevance of proteomic data in the clinical management of BC.

Urinary protein biomarkers for pediatric medulloblastoma

OBJECTIVE

To identify candidate urinary protein biomarkers to distinguish medulloblastoma (MB) patients from healthy patients or benign brain disease control patients.

METHODS

The tandem mass tag (TMT)-labeled quantitative proteomics approach was used to identify differential proteins in the urinary proteome of 9 pre- and postsurgery MB patients and 9 healthy control patients, respectively. Ingenuity pathway analysis was used for functional annotation of differential proteins. The biomarker candidates were validated by the parallel reaction monitoring (PRM) method in 112 samples (29 pre- and postsurgery MB patients, 26 healthy control patients, and 28 benign brain disease control patients). Receiver operating characteristic (ROC) curves were developed to evaluate candidate biomarkers.

RESULTS

A total of 114 differential proteins were found. Bioinformatic analysis revealed that the urinary proteome could reflect changes in MB. Seventeen candidate biomarkers were validated by PRM. The combination of CADH1, FGFR4 and FIBB could be used to discriminate MB patients from healthy control patients with an area under the curve (AUC) of 0.973, and the combination of CADH1 and FIBB showed good discriminative power for differentiating MB from benign brain disease with an AUC of 0.884.

CONCLUSION

This report describes the first application of a TMT-PRM workflow to identify and validate MB-specific biomarkers in urine. These findings might contribute to the application of urinary proteomics for detecting and monitoring MB.

BIOLOGICAL SIGNIFICANCE

Medulloblastoma (MB) is among the most common pediatric brain malignancies. This tumor has a highly aggressive clinical course with a high tendency for relapses. Magnetic resonance imaging (MRI) is the major means of diagnosis and for radiographic surveillance after surgery. In MRI, sedation is often required in young children, which could expose them to a series of risks, including airway obstruction and even death. Aside from MRI, there is no reliable biomarker for clinical screening or monitoring of the disease. These facts introduce the clinical need of noninvasive biomarkers for early screening or monitoring of MB. This study is focused on the investigation of a marker panel based on urinary proteome, as a tool for the detection of MB in selected patients at risk. Upon evaluation of the marker model in an independent blinded set of 112 samples, the panel (CADH1, FGFR4 and FIBB) could be used to discriminate MB patients from healthy control patients with an area under the curve (AUC) of 0.973, and the combination of CADH1 and FIBB showed good discriminative power for differentiating MB from benign brain disease with an AUC of 0.884.

Recent advances in mass spectrometry based clinical proteomics: applications to cancer research

Cancer biomarkers have transformed current practices in the oncology clinic. Continued discovery and validation are crucial for improving early diagnosis, risk stratification, and monitoring patient response to treatment. Profiling of the tumour genome and transcriptome are now established tools for the discovery of novel biomarkers, but alterations in proteome expression are more likely to reflect changes in tumour pathophysiology. In the past, clinical diagnostics have strongly relied on antibody-based detection strategies, but these methods carry certain limitations. Mass spectrometry (MS) is a powerful method that enables increasingly comprehensive insights into changes of the proteome to advance personalized medicine. In this review, recent improvements in MS-based clinical proteomics are highlighted with a focus on oncology. We will provide a detailed overview of clinically relevant samples types, as well as, consideration for sample preparation methods, protein quantitation strategies, MS configurations, and data analysis pipelines currently available to researchers. Critical consideration of each step is necessary to address the pressing clinical questions that advance cancer patient diagnosis and prognosis. While the majority of studies focus on the discovery of clinically-relevant biomarkers, there is a growing demand for rigorous biomarker validation. These studies focus on high-throughput targeted MS assays and multi-centre studies with standardized protocols. Additionally, improvements in MS sensitivity are opening the door to new classes of tumour-specific proteoforms including post-translational modifications and variants originating from genomic aberrations. Overlaying proteomic data to complement genomic and transcriptomic datasets forges the growing field of proteogenomics, which shows great potential to improve our understanding of cancer biology. Overall, these advancements not only solidify MS-based clinical proteomics' integral position in cancer research, but also accelerate the shift towards becoming a regular component of routine analysis and clinical practice.

Prospective evaluation of a urinary biomarker panel to detect and predict recurrence of non-muscle-invasive bladder cancer

PURPOSE

To perform a feasibility phase study of a panel of putative protein biomarkers and determine whether it can identify and predict tumor recurrence in patients with non-muscle-invasive bladder cancer (NMIBC) on follow-up.

METHODS

We prospectively analyzed the urine of 152 patients previously treated for NMIBC. Quantitative expression of plasminogen activator inhibitor-1 (PAI-1), DJ-1, apolipoprotein A-I (apoA-1), matrix metallopeptidase-9 (MMP-9), and interleukin-8 (IL-8) was assessed by enzyme-linked immunosorbent assay and compared amongst patients with and without bladder cancer recurrence at urine collection and during 3 years of follow-up. Tumor recurrence was confirmed by pathologic analysis. We performed a prediction analysis, excluding patients with recurrence at the start of the study, and assessed the influence of previous use of intravesical BCG on the level of biomarkers.

RESULTS

Median follow-up time was 47 months (interquartile range 39-50 months). Sixteen patients (10.5%) were diagnosed with recurrence at the start of the study, and 21 (15.4%) were diagnosed during the study. Three biomarker proteins (apoA-1, MMP-9, and IL-8) appear to hold diagnostic potential [odds ratio (OR) = 12.9; 95% CI 3.5-47.4]; while, PAI-1 and IL-8 predict recurrence (OR = 4.1; 95% CI 1.4-11.4). Previous use of intravesical BCG did not affect biomarker levels.

CONCLUSION

In the feasibility phase, the panel of urine biomarkers analyzed detected and predicted recurrence of NMIBC and provided reliable results in patients who had previously used intravesical BCG. Validation studies are required to confirm the panel clinical utility.

Update on urine as a biomarker in cancer: a necessary review of an old story

Introduction: Cancer causes thousands of deaths worldwide each year. Therefore, monitoring of health status and the early diagnosis of cancer using noninvasive assays, such as the analysis of molecular biomarkers in urine, is essential. However, effective biomarkers for early diagnosis of cancer have not been established in many types of cancer.Areas covered: In this review, we discuss recent findings with regard to the use of urine composition as a biomarker in eleven types of cancer. We also highlight the use of urine biomarkers for improving early diagnosis.Expert opinion: Urinary biomarkers have been applied for clinical application of early diagnosis. The main limitation is a lack of integrated approaches for identification of new biomarkers in most cancer. The utilization of urinary biomarker detection will be promoted by improved detection methods and new data from different types of cancers. With the development of precision medicine, urinary biomarkers will play an increasingly important clinical role. Future early diagnosis would benefit from changes in the utilization of urinary biomarkers.

Detection of bladder cancer using urinary cell-free DNA and cellular DNA

Background

The present study sought to identify a panel of DNA markers for noninvasive diagnosis using cell-free DNA (cfDNA) from urine supernatant or cellular DNA from urine sediments of hematuria patients. A panel of 48 bladder cancer-specific genes was selected. A next-generation sequencing-based assay with a cfDNA barcode-enabled single-molecule test was employed. Mutation profiles of blood, urine, and tumor sample from 16 bladder cancer patients were compared. Next, urinary cellular DNA and cfDNA were prospectively collected from 125 patients (92 bladder cancer cases and 33 controls) and analyzed using the 48-gene panel. The individual gene markers and combinations of markers were validated according to the pathology results. The mean areas under the receiver operating characteristic (ROC) curves (AUCs) obtained with the various modeling approaches were calculated and compared.

Results

This pilot study of 16 bladder cancer patients demonstrated that gene mutations in urine supernatant and sediments had better concordance with cancer tissue as compared with plasma. Logistic analyses suggested two powerful combinations of genes for genetic diagnostic modeling: five genes for urine supernatant (TERT, FGFR3, TP53, PIK3CA, and KRAS) and seven genes for urine sediments (TERT, FGFR3, TP53, HRAS, PIK3CA, KRAS, and ERBB2). The accuracy of the five-gene panel and the seven-gene panel in the validation cohort yielded AUCs of 0.94 [95% confidence interval (CI) 0.91–0.97] and 0.91 (95% CI 0.86–0.96), respectively. With the addition of age and gender, the diagnostic power of the urine supernatant five-gene model and the urine sediment seven-gene model improved as the revised AUCs were 0.9656 (95% CI 0.9368–0.9944) and 0.9587 (95% CI 0.9291–0.9883).

Conclusions

cfDNA from urine bears great diagnostic potential. A five-gene panel for urine supernatant and a seven-gene panel for urine sediments are promising options for identifying bladder cancer in hematuria patients.

Bile and urine peptide marker profiles: access keys to molecular pathways and biological processes in cholangiocarcinoma

Background

Detection of cholangiocarcinoma (CCA) remains a diagnostic challenge. We established diagnostic peptide biomarkers in bile and urine based on capillary electrophoresis coupled to mass spectrometry (CE-MS) to detect both local and systemic changes during CCA progression. In a prospective cohort study we recently demonstrated that combined bile and urine proteome analysis could further improve diagnostic accuracy of CCA diagnosis in patients with unknown biliary strictures. As a continuation of these investigations, the aim of the present study was to investigate the pathophysiological mechanisms behind the molecular determinants reflected by bile and urine peptide biomarkers.

Methods

Protease mapping and gene ontology cluster analysis were performed for the previously defined CE-MS based biomarkers in bile and urine. For that purpose, bile and urine peptide profiles (from samples both collected at the date of endoscopy) were investigated from a representative cohort of patients with benign (n = 76) or CCA-associated (n = 52) biliary strictures (verified during clinical follow-up). This was supplemented with a literature search for the association of the individual biomarkers included in the proteomic patterns with CCA or cancer progression.

Results

For most of the peptide markers, association to CCA has been described in literature. Protease mapping revealed ADAMTS4 activity in cleavage of both bile and urine CCA peptide biomarkers. Furthermore, increased chymase activity in bile points to mast cell activation at the tumor site. Gene ontology cluster analysis indicates cellular response to chemical stimuli and stress response as local and extracellular matrix reorganization by tissue destruction and repair as systemic events. The analysis further supports that the mapped proteases are drivers of local and systemic events.

Conclusions

The study supports connection of the CCA-associated peptide biomarkers to the molecular pathophysiology and indicates an involvement in epithelial-to-mesenchymal transition, generation of cancer-associated fibroblasts and activation of residual immune cells. Proteases, extracellular matrix components, inflammatory cytokines, proangiogenic, growth and vasoactive factors released from the tumor microenvironment are drivers of systemic early events during CCA progression.

Urinary markers in the surveillance of non-muscle invasive bladder cancer. A literature review

BACKGROUND

The surveillance of non-muscle-invasive bladder cancer (NMIBC) is usually performed by cystoscopy and cytology. Until today, no effective urinary biomarker has been used to reduce the morbidity and cost associated with these procedures.

OBJECTIVE

To describe the performance of urinary biomarkers in the surveillance of NMIBC.

EVIDENCE ACQUISITION

on August 1, 2018, a bibliographic search was carried out in Pubmed, Embase and Cochrane Library, limited to the last 10 years, with the terms: bladder cancer, recurrence, detection and urine marker.973 registers were obtained, and 27 publications were selected following the PRISMA recommendations.

EVIDENCE SYNTHESIS

The negative predictive values (NPV) of several assays could reduce the number of cystoscopies in NMIBC surveillance. Six transcription-factor trials had an NPV rate greater than 90%, and one of them can be performed at the control point. Six transcription-factors evaluations describe anticipated diagnosis between 68% and 83% of their "false positives". Two transcription factors and one protein assays proved reduction between 23% and 35% of surveillance cystoscopies. Nowadays, cell-based assays are restricted to reflex test after doubtful cytologies.

CONCLUSION

There are few studies analysing the improvement of the NMIBC surveillance protocols. Several transcription factor assays are more precise and allow anticipatory diagnosis. Currently, there are no comparative studies between alternative surveillance protocols and classic ones.

Urinary peptide panel for prognostic assessment of bladder cancer relapse

Non-invasive tools stratifying bladder cancer (BC) patients according to the risk of relapse are urgently needed to guide clinical intervention. As a follow-up to the previously published study on CE-MS-based urinary biomarkers for BC detection and recurrence monitoring, we expanded the investigation towards BC patients with longitudinal data. Profiling datasets of BC patients with follow-up information regarding the relapse status were investigated. The peptidomics dataset (n = 98) was split into training and test set. Cox regression was utilized for feature selection in the training set. Investigation of the entire training set at the single peptide level revealed 36 peptides being strong independent prognostic markers of disease relapse. Those features were further integrated into a Random Forest-based model evaluating the risk of relapse for BC patients. Performance of the model was assessed in the test cohort, showing high significance in BC relapse prognosis [HR = 5.76, p-value = 0.0001, c-index = 0.64]. Urinary peptide profiles integrated into a prognostic model allow for quantitative risk assessment of BC relapse highlighting the need for its incorporation in prospective studies to establish its value in the clinical management of BC.

CE-MS-based urinary biomarkers to distinguish non-significant from significant prostate cancer

Background

Prostate cancer progresses slowly when present in low risk forms but can be lethal when it progresses to metastatic disease. A non-invasive test that can detect significant prostate cancer is needed to guide patient management.

Methods

Capillary electrophoresis/mass spectrometry has been employed to identify urinary peptides that may accurately detect significant prostate cancer. Urine samples from 823 patients with PSA (<15 ng/ml) were collected prior to biopsy. A case–control comparison was performed in a training set of 543 patients (n_Sig = 98; n_non-Sig = 445) and a validation set of 280 patients (n_Sig = 48, n_non-Sig = 232). Totally, 19 significant peptides were subsequently combined by a support vector machine algorithm.

Results

Independent validation of the 19-biomarker model in 280 patients resulted in a 90% sensitivity and 59% specificity, with an AUC of 0.81, outperforming PSA (AUC = 0.58) and the ERSPC-3/4 risk calculator (AUC = 0.69) in the validation set.

Conclusions

This multi-parametric model holds promise to improve the current diagnosis of significant prostate cancer. This test as a guide to biopsy could help to decrease the number of biopsies and guide intervention. Nevertheless, further prospective validation in an external clinical cohort is required to assess the exact performance characteristics.