Peptidomics of Urine and Other Biofluids for Cancer Diagnostics

Computational peptide discovery with a genetic programming approach

The development of peptides for therapeutic targets or biomarkers for disease diagnosis is a challenging task in protein engineering. Current approaches are tedious, often time-consuming and require complex laboratory data due to the vast search spaces that need to be considered. In silico methods can accelerate research and substantially reduce costs. Evolutionary algorithms are a promising approach for exploring large search spaces and can facilitate the discovery of new peptides. This study presents the development and use of a new variant of the genetic-programming-based POET algorithm, called POETRegex , where individuals are represented by a list of regular expressions. This algorithm was trained on a small curated dataset and employed to generate new peptides improving the sensitivity of peptides in magnetic resonance imaging with chemical exchange saturation transfer (CEST). The resulting model achieves a performance gain of 20% over the initial POET models and is able to predict a candidate peptide with a 58% performance increase compared to the gold-standard peptide. By combining the power of genetic programming with the flexibility of regular expressions, new peptide targets were identified that improve the sensitivity of detection by CEST. This approach provides a promising research direction for the efficient identification of peptides with therapeutic or diagnostic potential.

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.

Origins, Technological Advancement, and Applications of Peptidomics

Peptidomics is the comprehensive characterization of peptides from biological sources instead of heading for a few single peptides in former peptide research. Mass spectrometry allows to detect a multitude of peptides in complex mixtures and thus enables new strategies leading to peptidomics. The term was established in the year 2001, and up to now, this new field has grown to over 3000 publications. Analytical techniques originally developed for fast and comprehensive analysis of peptides in proteomics were specifically adjusted for peptidomics. Although it is thus closely linked to proteomics, there are fundamental differences with conventional bottom-up proteomics. Fundamental technological advancements of peptidomics since have occurred in mass spectrometry and data processing, including quantification, and more slightly in separation technology. Different strategies and diverse sources of peptidomes are mentioned by numerous applications, such as discovery of neuropeptides and other bioactive peptides, including the use of biochemical assays. Furthermore, food and plant peptidomics are introduced similarly. Additionally, applications with a clinical focus are included, comprising biomarker discovery as well as immunopeptidomics. This overview extensively reviews recent methods, strategies, and applications including links to all other chapters of this book.

The Strategy for Peptidomic LC-MS/MS Data Analysis: The Case of Urinary Peptidome Study

The study of urinary peptidome is an important area of research, which concerns the characterization of endogenous peptides, as well as the identification of biomarkers for a wide range of socially significant diseases. First of all, this relates to renal and genitourinary pathologies and/or pathologies associated with proteinuria, such as kidney diseases, bladder, prostate and ovarian cancers, diabetic nephropathy, and pre-eclampsia. Unlike proteins, peptides do not require proteolytic hydrolysis, can be analyzed in their native form and can provide certain information about occurring (patho)physiological processes. Mass spectrometry (MS)-based approaches are the most unbiased and sensitive instruments with high multiplexing capacity and provided most of the current information about endogenous urine peptides. However, despite the large number of urine peptidomic studies, there are certain issues related to the insufficient comparability of their results due to the lack of consistent approaches to their interpretation. Also the development of a custom project-specific protein library for endogenous peptides search and identification is another important point that should be noted in the context of high-throughput peptidomic analysis. Here we propose the custom-specific urinary protein database and the grouping of endogenous urinary peptides with overlapping sequences as useful tools, which can facilitate the acquisition and analysis of LC-MS peptidomic data, as well as the comparison of results of different studies, which should facilitate their more efficient further application.

Advances in neuroproteomics for neurotrauma: unraveling insights for personalized medicine and future prospects

Neuroproteomics, an emerging field at the intersection of neuroscience and proteomics, has garnered significant attention in the context of neurotrauma research. Neuroproteomics involves the quantitative and qualitative analysis of nervous system components, essential for understanding the dynamic events involved in the vast areas of neuroscience, including, but not limited to, neuropsychiatric disorders, neurodegenerative disorders, mental illness, traumatic brain injury, chronic traumatic encephalopathy, and other neurodegenerative diseases. With advancements in mass spectrometry coupled with bioinformatics and systems biology, neuroproteomics has led to the development of innovative techniques such as microproteomics, single-cell proteomics, and imaging mass spectrometry, which have significantly impacted neuronal biomarker research. By analyzing the complex protein interactions and alterations that occur in the injured brain, neuroproteomics provides valuable insights into the pathophysiological mechanisms underlying neurotrauma. This review explores how such insights can be harnessed to advance personalized medicine (PM) approaches, tailoring treatments based on individual patient profiles. Additionally, we highlight the potential future prospects of neuroproteomics, such as identifying novel biomarkers and developing targeted therapies by employing artificial intelligence (AI) and machine learning (ML). By shedding light on neurotrauma's current state and future directions, this review aims to stimulate further research and collaboration in this promising and transformative field.

A Review of Electroactive Nanomaterials in the Detection of Nitrogen-Containing Organic Compounds and Future Applications

Electrochemical and impedimetric detection of nitrogen-containing organic compounds (NOCs) in blood, urine, sweat, and saliva is widely used in clinical diagnosis. NOC detection is used to identify illnesses such as chronic kidney disease (CKD), end-stage renal disease (ESRD), cardiovascular complications, diabetes, cancer, and others. In recent years, nanomaterials have shown significant potential in the detection of NOCs using electrochemical and impedimetric sensors. This potential is due to the higher surface area, porous nature, and functional groups of nanomaterials, which can aid in improving the sensing performance with inexpensive, direct, and quick-time processing methods. In this review, we discuss nanomaterials, such as metal oxides, graphene nanostructures, and their nanocomposites, for the detection of NOCs. Notably, researchers have considered nanocomposite-based devices, such as a field effect transistor (FET) and printed electrodes, for the detection of NOCs. In this review, we emphasize the significant importance of electrochemical and impedimetric methods in the detection of NOCs, which typically show higher sensitivity and selectivity. So, these methods will open a new way to make embeddable electrodes for point-of-detection (POD) devices. These devices could be used in the next generation of non-invasive analysis for biomedical and clinical applications. This review also summarizes recent state-of-the-art technology for the development of sensors for on-site monitoring and disease diagnosis at an earlier stage.

Biomarker Reproducibility Challenge: A Review of Non-Nucleotide Biomarker Discovery Protocols from Body Fluids in Breast Cancer Diagnosis

Breast cancer has now become the most commonly diagnosed cancer, accounting for one in eight cancer diagnoses worldwide. Non-invasive diagnostic biomarkers and associated tests are superlative candidates to complement or improve current approaches for screening, early diagnosis, or prognosis of breast cancer. Biomarkers detected from body fluids such as blood (serum/plasma), urine, saliva, nipple aspiration fluid, and tears can detect breast cancer at its early stages in a minimally invasive way. The advancements in high-throughput molecular profiling (omics) technologies have opened an unprecedented opportunity for unbiased biomarker detection. However, the irreproducibility of biomarkers and discrepancies of reported markers have remained a major roadblock to clinical implementation, demanding the investigation of contributing factors and the development of standardised biomarker discovery pipelines. A typical biomarker discovery workflow includes pre-analytical, analytical, and post-analytical phases, from sample collection to model development. Variations introduced during these steps impact the data quality and the reproducibility of the findings. Here, we present a comprehensive review of methodological variations in biomarker discovery studies in breast cancer, with a focus on non-nucleotide biomarkers (i.e., proteins, lipids, and metabolites), highlighting the pre-analytical to post-analytical variables, which may affect the accurate identification of biomarkers from body fluids.

Molecularly imprinted and cladded polymers for constructing a portable plasmonic immunoassay for peptides in biofluids

Using two molecularly imprinted and cladded polymers (cMIPs), an inexpensive, fast and portable plasmonic immuno-sandwich assay (PISA) was rationally developed for high-specificity and ultra-sensitive detection of C-peptide in urine. The dual cMIPs-based PISA allowed healthy individuals to be distinguished from diabetes patients and exhibited several significant merits over existing immunoassays, holding great promise in clinical diagnosis.

Cell-Free DNA, MicroRNAs, Proteins, and Peptides as Liquid Biopsy Biomarkers in Prostate Cancer and Bladder Cancer

Liquid biopsy, as a novel noninvasive tool for biomarker discovery, has gained a lot of attention and represents a significant innovation in precision medicine. Due to its minimally invasive nature, liquid biopsy has fewer complications and can be scheduled more frequently to provide individualized snapshots of the disease at successive time points. This is particularly valuable in providing simultaneous measurements of tumor burden during treatment and early detection of tumor recurrence or drug resistance. Blood-based liquid biopsy is an attractive, minimally invasive alternative, which has shown promise in diagnosis, risk stratification, disease monitoring, and more. Urine has gained popularity due to its less invasive sampling, the ability to easily repeat samples, and the ability to track tumor evolution in real time, making it a powerful tool for diagnosis and treatment monitoring, especially in urologic cancers. In this review, we provide a detailed discussion on the potential clinical applications of prostate cancer (PCa) and bladder cancer (BCa), with cell-free DNA (cfDNA), microRNAs (miRNAs), proteins, and peptides as liquid biopsy biomarkers.

Paper based microfluidic devices: a review of fabrication techniques and applications

A wide range of applications are possible with paper-based analytical devices, which are low priced, easy to fabricate and operate, and require no specialized equipment. Paper-based microfluidics offers the design of miniaturized POC devices to be applied in the health, environment, food, and energy sector employing the ASSURED (Affordable, Sensitive, Specific, User-friendly, Rapid and Robust, Equipment free and Deliverable to end users) principle of WHO. Therefore, this field is growing very rapidly and ample research is being done. This review focuses on fabrication and detection techniques reported to date. Additionally, this review emphasises on the application of this technology in the area of medical diagnosis, energy generation, environmental monitoring, and food quality control. This review also presents the theoretical analysis of fluid flow in porous media for the efficient handling and control of fluids. The limitations of PAD have also been discussed with an emphasis to concern on the transformation of such devices from laboratory to the consumer.

Clinical applications of plasma proteomics and peptidomics: Towards precision medicine

In the context of precision medicine, disease treatment requires individualized strategies based on the underlying molecular characteristics to overcome therapeutic challenges posed by heterogeneity. For this purpose, it is essential to develop new biomarkers to diagnose, stratify, or possibly prevent diseases. Plasma is an available source of biomarkers that greatly reflects the physiological and pathological conditions of the body. An increasing number of studies are focusing on proteins and peptides, including many involving the Human Proteome Project (HPP) of the Human Proteome Organization (HUPO), and proteomics and peptidomics techniques are emerging as critical tools for developing novel precision medicine preventative measures. Excitingly, the emerging plasma proteomics and peptidomics toolbox exhibits a huge potential for studying pathogenesis of diseases (e.g., COVID-19 and cancer), identifying valuable biomarkers and improving clinical management. However, the enormous complexity and wide dynamic range of plasma proteins makes plasma proteome profiling challenging. Herein, we summarize the recent advances in plasma proteomics and peptidomics with a focus on their emerging roles in COVID-19 and cancer research, aiming to emphasize the significance of plasma proteomics and peptidomics in clinical applications and precision medicine.

Application of peptide biomarkers in life analysis based on liquid chromatography-mass spectrometry technology

Biomedicine is developing rapidly in the 21st century. Among them, the qualitative and quantitative analysis of peptide biomarkers is of considerable importance for the diagnosis and therapy of diseases and the quality evaluation of drugs and food. The identification and quantitative analysis of peptides have been going on for decades. Traditionally, immunoassays or biological assays are generally used to quantify peptides in biological matrices. However, the selectivity and sensitivity of these methods cannot meet the requirements of the application. The separation and analysis technique of liquid chromatography-mass spectrometry (LC-MS) supplies a reliable alternative. In contrast to immunoassays, LC-MS methods are capable of providing the analytical prowess necessary to satisfy the demands of peptide biomarker research in the life sciences arena. This review article provides a historical account of the in-roads made by LC-MS technology for the detection of peptide biomarkers in the past 10 years, with the focus on the qualification/quantification developments and their applications.

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.

Cell affinity screening combined with nanoLC-MS/MS based peptidomics for identifying cancer cell binding peptides from Bufo Bufo gargarizans

Animal venoms contain many peptides with high specificity and selectivity against their protein targets, a characteristic which makes venoms an invaluable source of potential drugs. High-sensitivity mass spectrometry (MS)- based peptidomic platform has evolved as a predominant method for natural peptide drug discovery due to its strength for direct and rapid identification of peptides and peptide-associated post-translational modifications (PTMs). In this study, we used cell-affinity assays combined with nanoLC-MS/MS based peptidomics to identify cancer cell binding peptides (CBPs) from Bufo Bufo gargarizans. We identified 76 potential cell binding peptides and 237 non-affinity peptides in venom extracts from Asiatic toads, and some were verified with MS-parallel reaction monitoring (PRM) mode. These peptides were further analyzed and internalized within human cells and some demonstrated anti-tumor properties in vitro. These specific peptides might be used as templates for peptide-based drug design or optimization.

Urinary peptidomics reveals proteases involved in idiopathic membranous nephropathy

BACKGROUND

Idiopathic membranous nephropathy (IMN) is a cause of nephrotic syndrome that is increasing in incidence but has unclear pathogenesis. Urinary peptidomics is a promising technology for elucidating molecular mechanisms underlying diseases. Dysregulation of the proteolytic system is implicated in various diseases. Here, we aimed to conduct urinary peptidomics to identify IMN-related proteases.

RESULTS

Peptide fingerprints indicated differences in naturally produced urinary peptide components among 20 healthy individuals, 22 patients with IMN, and 15 patients with other kidney diseases. In total, 1,080 peptide-matched proteins were identified, 279 proteins differentially expressed in the urine of IMN patients were screened, and 32 proteases were predicted; 55 of the matched proteins were also differentially expressed in the kidney tissues of IMN patients, and these were mainly involved in the regulation of proteasome-, lysosome-, and actin cytoskeleton-related signaling pathways. The 32 predicted proteases showed abnormal expression in the glomeruli of IMN patients based on Gene Expression Omnibus databases. Western blot revealed abnormal expression of calpain, matrix metalloproteinase 14, and cathepsin S in kidney tissues of patients with IMN.

CONCLUSIONS

This work shown the calpain/matrix metalloproteinase/cathepsin axis might be dysregulated in IMN. Our study is the first to systematically explore the role of proteases in IMN by urinary peptidomics, which are expected to facilitate discovery of better biomarkers for IMN.

Analysis of urinary kallikrein-related peptidase 13 for monitoring bladder cancer

BACKGROUND

Bladder cancer (BC) is one of the 10 most common types of cancer worldwide, with approximately 550,000 new cases each year. Early detection and appropriate diagnosis are important factors in successful treatment of the disease.

MATERIAL AND METHODS

We used specific fluorogenic substrate for the quantitative determination of urine kallikrein 13 (KLK13) activity in healthy (n = 15) and BC (n = 54) patients. The proteolytic activity in individual urine samples was determined by fluorescence measurements. Then, immunoenzymatic analyses (ELISA, Western blot) were performed to confirm the presence of KLK13 in the tested samples.

RESULTS

Urine samples from patients with G2 and G3 grade BC contained proteolytically active KLK13, as confirmed by kinetic analysis and immunochemical detection. KLK13 was not detected in the urine of patients with G1 grade BC.

DISCUSSION

Previous clinical study reveals the KLK13 significance for BC prognosis as increased KLK13 expression was highlighted in bladder tumours compared to normal adjacent tissues. Our findings correlate to the report. KLK13 activity was confirmed in BC patients with G2 and G3 stage of disease development.

CONCLUSIONS

Using specific chromogenic/fluorogenic peptides could be useful for the non-invasive disease monitoring of BC progress.

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.

Peptide profiling in cow urine reveals molecular signature of physiology-driven pathways and in-silico predicted bioactive properties

Peptidomics allows the identification of peptides that are derived from proteins. Urinary peptidomics has revolutionized the field of diagnostics as the samples represent complete systemic changes happening in the body. Moreover, it can be collected in a non-invasive manner. We profiled the peptides in urine collected from different physiological states (heifer, pregnancy, and lactation) of Sahiwal cows. Endogenous peptides were extracted from 30 individual cows belonging to three groups, each group comprising of ten animals (biological replicates n = 10). Nano Liquid chromatography Mass spectrometry (nLC-MS/MS) experiments revealed 5239, 4774, and 5466 peptides in the heifer, pregnant and lactating animals respectively. Urinary peptides of <10 kDa size were considered for the study. Peptides were extracted by 10 kDa MWCO filter. Sequences were identified by scanning the MS spectra ranging from 200 to 2200 m/z. The peptides exhibited diversity in sequences across different physiological states and in-silico experiments were conducted to classify the bioactive peptides into anti-microbial, anti-inflammatory, anti-hypertensive, and anti-cancerous groups. We have validated the antimicrobial effect of urinary peptides on Staphylococcus aureus and Escherichia coli under an in-vitro experimental set up. The origin of these peptides was traced back to certain proteases viz. MMPs, KLKs, CASPs, ADAMs etc. which were found responsible for the physiology-specific peptide signature of urine. Proteins involved in extracellular matrix structural constituent (GO:0005201) were found significant during pregnancy and lactation in which tissue remodeling is extensive. Collagen trimers were prominent molecules under cellular component category during lactation. Homophilic cell adhesion was found to be an important biological process involved in embryo attachment during pregnancy. The in-silico study also highlighted the enrichment of progenitor proteins on specific chromosomes and their relative expression in context to specific physiology. The urinary peptides, precursor proteins, and proteases identified in the study offers a base line information in healthy cows which can be utilized in biomarker discovery research for several pathophysiological studies.

Enhanced specificity of bimetallic ions via mesoporous confinement for phosphopeptides in human saliva

Phosphopeptides were of great significance in disease diagnosis and monitoring its dynamic changes. In this article, we proposed a more efficient method to synthesize a kind of bimetallic mesoporous silica nanomaterials (Fe₃O₄@mSiO₂-PO₃-Ti⁴⁺/Zr⁴⁺) and applied it to the analysis of phosphopeptides in human saliva samples based on IMAC technology. The chelation group was introduced into mesopores at the same time as the formation of mesoporous silica which significantly reduced the synthesis procedure and improved the synthesis efficiency. The as-prepared materials showed great sensitivity, selectivity and size-exclusion performance for phosphopeptides in standard β-casein digests. More importantly, the materials identified 85 phosphopeptides in disease saliva samples which provided a candidate choice in future clinical examination.

Label-Free Quantitative Comparison of Cervical Mucus Peptides in Subjects With Endocervical Adenocarcinoma and Adenocarcinoma in Situ

Purpose:

To uncover potential diagnostic biomarkers for endocervical adenocarcinoma (EAC) and adenocarcinoma in situ (AIS).

Experimental design:

Quantitative label-free liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS) peptidomics strategies were employed to profile 8 cervical mucus (CM) samples, including 3 EAC cases, 2 AIS cases and 3 normal controls (Ctrl).

Results:

Among the 3721 exclusive peptides identified, 12 (5 up-regulated and 7 down-regulated) endogenous peptides were significantly expressed in EAC compared to healthy controls (EAC/Ctrl); 10 (7 up-regulated and 3 down-regulated) endogenous peptides were significantly expressed in AIS compared to healthy controls (AIS/Ctrl); 11 (6 up-regulated and 5 down-regulated) endogenous peptides were significantly expressed in EAC compared to AIS (EAC/AIS) (absolute fold change ≥1.5, Benjamini-Hochberg adjusted p-value ≤0.05). Among these identifications, annexin A1 (ANXA1) was found to be down-regulated both in EAC and AIS, and its unique peptide (FIENEEQEYVQTVK) may be promising indicators for cervical glandular epithelial lesions.

Conclusion:

This is the first study to utilize CM peptidomics in cervical glandular malignancies, which may reveal the novel noninvasive biomarkers for EAC and AIS.

Bioinformatic Analysis of the Wound Peptidome Reveals Potential Biomarkers and Antimicrobial Peptides

Wound infection is a common and serious medical condition with an unmet need for improved diagnostic tools. A peptidomic approach, aided by mass spectrometry and bioinformatics, could provide novel means of identifying new peptide biomarkers for wound healing and infection assessment. Wound fluid is suitable for peptidomic analysis since it is both intimately tied to the wound environment and is readily available. In this study we investigate the peptidomes of wound fluids derived from surgical drainages following mastectomy and from wound dressings following facial skin grafting. By applying sorting algorithms and open source third party software to peptidomic label free tandem mass spectrometry data we provide an unbiased general methodology for analyzing and differentiating between peptidomes. We show that the wound fluid peptidomes of patients are highly individualized. However, differences emerge when grouping the patients depending on wound type. Furthermore, the abundance of peptides originating from documented antimicrobial regions of hemoglobin in infected wounds may contribute to an antimicrobial wound environment, as determined by in silico analysis. We validate our findings by compiling literature on peptide biomarkers and peptides of physiological significance and cross checking the results against our dataset, demonstrating that well-documented peptides of immunological significance are abundant in infected wounds, and originate from certain distinct regions in proteins such as hemoglobin and fibrinogen. Ultimately, we have demonstrated the power using sorting algorithms and open source software to help yield insights and visualize peptidomic data.

Comparison of single-scanner single-protocol quantitative ADC measurements to ADC ratios to detect clinically significant prostate cancer

BACKGROUND

Mean ADC has high predictive value for the presence of clinically significant prostate cancer (sPC). Measurement variability is introduced by different scanners, protocols, intra-and inter-patient variation. Internal calibration by ADC ratios can address such fluctuations however can potentially lower the biological value of quantitative ADC determination by being sensitive to deviations in reference tissue signal.

PURPOSE

To better understand the predictive value of quantitative ADC measurements in comparison to internal reference ratios when measured in a single scanner, single protocol setup.

MATERIALS AND METHODS

284 consecutive patients who underwent 3 T MRI on a single scanner followed by MRI-transrectal ultrasound fusion biopsy were included. A board-certified radiologist retrospectively reviewed all MRIs blinded to clinical information and placed regions of interest (ROI) on all focal lesions and the following reference regions: normal-appearing peripheral zone (PZNL) and transition zone (TZNL), the urinary bladder (BLA), and right and left internal obturator muscle (RIOM, LIOM). ROI-based mean ADC and ADC ratios to the reference regions were compared regarding their ability to predict the aggressiveness of prostate cancer. Spearman's rank correlation coefficient was used to estimate the correlation between ADC parameters, Gleason score (GS) and ADC ratios. The primary endpoint was presence of sPC, defined as a GS ≥ 3 + 4. Univariable and multivariable logistic regression models were constructed to predict sPC. Receiver operating characteristics curves (ROC) were used for visualization; DeLong test was used to evaluate the differences of the area under the curve (AUC). Bias-corrected AUC values and corresponding 95 %-CI were calculated using bootstrapping with 100 bootstrap samples.

RESULTS

After exclusion of patients who received prior treatment, 259 patients were included in the final cohort of which 220 harbored 351 MR lesions. Mean ADC and ADC ratios demonstrated a negative correlation with the GS. Mean ADC had the strongest correlation with ρ of -0.34, followed by ADCratioPZNL (ρ=-0.32). All ADC parameters except ADCratioLIOM (p = 0.07) were associated with sPC p<0.05). Mean ADC and ADCratioPZNL had the highest ROC AUC of all parameters (0.68). Multivariable models with mean ADC improve predictive performance.

CONCLUSIONS

A highly standardized single-scanner mean ADC measurement could not be improved upon using any of the single ADC ratio parameters or combinations of these parameters in predicting the aggressiveness of prostate cancer.

Peptidomics-Driven Strategy Reveals Peptides and Predicted Proteases Associated With Oral Cancer Prognosis

Protease activity has been associated with pathological processes that can lead to cancer development and progression. However, understanding the pathological unbalance in proteolysis is challenging because changes can occur simultaneously at protease, their inhibitor, and substrate levels. Here, we present a pipeline that combines peptidomics, proteomics, and peptidase predictions for studying proteolytic events in the saliva of 79 patients and their association with oral squamous cell carcinoma (OSCC) prognosis. Our findings revealed differences in the saliva peptidome of patients with (pN+) or without (pN0) lymph-node metastasis and delivered a panel of ten endogenous peptides correlated with poor prognostic factors plus five molecules able to classify pN0 and pN+ patients (area under the receiver operating characteristic curve > 0.85). In addition, endopeptidases and exopeptidases putatively implicated in the processing of differential peptides were investigated using cancer tissue gene expression data from public repositories, reinforcing their association with poorer survival rates and prognosis in oral cancer. The dynamics of the OSCC-related proteolysis were further explored via the proteomic profiling of saliva. This revealed that peptidase/endopeptidase inhibitors exhibited reduced levels in the saliva of pN+ patients, as confirmed by selected reaction monitoring-mass spectrometry, while minor changes were detected in the level of saliva proteases. Taken together, our results indicated that proteolytic activity is accentuated in the saliva of patients with OSCC and lymph-node metastasis and, at least in part, is modulated by reduced levels of salivary peptidase inhibitors. Therefore, this integrated pipeline provided better comprehension and discovery of molecular features with implications in the oral cancer metastasis prognosis.

Lessons learned from proteome analysis of perinatal neurovascular pathologies

INTRODUCTION

Perinatal and pediatric diseases related to neurovascular disorders cause significant problems during life, affecting a population with a long life expectancy. Early diagnosis and assessment of the severity of these diseases are crucial to establish an appropriate neuroprotective treatment. Currently, physical examination, neuroimaging and clinical judgment are the main tools for diagnosis, although these tests have certain limitations. There is growing interest in the potential value of noninvasive biomarkers that can be used to monitor child patients at risk of brain damage, allowing accurate, and reproducible measurements.

AREAS COVERED

This review describes potential biomarkers for the diagnosis of perinatal neurovascular diseases and discusses the possibilities they open for the classification and treatment of neonatal neurovascular diseases.

EXPERT OPINION

Although high rates of ischemic and hemorrhagic stroke exist in pediatric populations, most studies have focused on biomarkers of hypoxic-ischemic encephalopathy. Inflammatory and neuronal biomarkers such as S-100B and GFAP, in combination with others yet to be discovered, could be considered as part of multiplex panels to diagnose these diseases and potentially for monitoring response to treatments. Ideally, noninvasive biofluids would be the best source for evaluating these biomarkers in proteomic assays in perinatal patients.

Characterization of colorectal mucus using infrared spectroscopy: a potential target for bowel cancer screening and diagnosis

Biological materials presenting early signs of cancer would be beneficial for cancer screening/diagnosis. In this respect, the suitability of potentially exploiting mucus in colorectal cancer was tested using infrared spectroscopy in combination with statistical modeling. Twenty-six paraffinized colon tissue biopsy sections containing mucus regions from 20 individuals (10 normal and 16 cancerous) were measured using mid-infrared spectroscopic imaging. A digital de-paraffinization, followed by cluster analysis driven digital color-coded multi-staining segmented the infrared images into various histopathological features such as epithelium, connective tissue, stroma, and mucus regions within the tissue sections. Principal component analysis followed by supervised linear discriminant analysis was carried out on pure mucus and epithelial spectra from normal and cancerous regions of the tissue. For the mucus-based classification, a sensitivity of 96%, a specificity of 83%, and an area under the curve performance of 95% was obtained. For the epithelial tissue-based classification, a sensitivity of 72%, a specificity of 88%, and an area under the curve performance of 89% was obtained. The mucus spectral profiles further showed contributions indicative of glycans including that of sialic acid changes between these pathology groups. The study demonstrates that infrared spectroscopic analysis of mucus discriminates colorectal cancers with high sensitivity. This concept could be exploited to develop screening/diagnostic approaches complementary to histopathology.

Magnetic mesoporous silica of loading copper metal ions for enrichment and LC-MS/MS analysis of salivary endogenous peptides

Peptidomics research is of great significance for discovering potential biomarkers and monitoring human diseases. As a kind of common clinical biofluid, saliva known for its noninvasive collection and easy accessibility has been widely used in peptidomics research. In this article, we combined immobilized metal ions affinity chromotography (IMAC) with mesoporous material and proposed the copper ion doped magnetic mesoporous silica material (denoted as Fe₃O₄@mSiO₂-Cu²⁺) which had a large surface area of 221 m² g^-1 and pore volume of 0.20 cm³ g^-1. By immobilizing copper ions onto the mesopore walls, the standard peptide Angiotensin II could be identified in an extremely low concentration of 0.1 fmol μl^-1 and in a mass ratio of 1:500 (Angiotensin II:BSA, m/m), which indicated significant sensitivity and a great size-exclusive ability. In addition, the introduction of polydopamine (PDA) made Fe₃O₄@mSiO₂-Cu²⁺ more hydrophilic and biocompatible which could improve the profiling of endogenous peptides in bio-sample. Finally, 131 endogenous peptides were identified in human saliva after enrichment with Fe₃O₄@mSiO₂-Cu²⁺. Therefore, Fe₃O₄@mSiO₂-Cu²⁺ nanoparticles provided a promising candidate protocol for biomarker discovery.

Degradomics in Biomarker Discovery

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

Evaluation of Protein Profiling in a Cohort of Egyptian Population with Renal Cell Carcinoma and Benign Kidney Neoplasms

Abdominal imaging leads to the detection of a large number of renal tumors without the ability to distinguish the type of tumor detected. It is necessary to find a precise way to know the type of tumor to determine the appropriate treatment. The use of urine samples for detecting new biomarkers especially proteins has a great potential. In this work we assessed the proteomic profiling difference in a cohort of Egyptian population with renal neoplasms. Methods: This cohort study was conducted on 85 subjects. They were classified as 40 RCC, 15 benign kidney patients, and 30 healthy controls. Morning urine samples were used for peptidome separation using magnetic beads. Matrix assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF MS) was applied Using FlexControlTM software. Results: Benign tumors were differentiated from controls by 5 integrated peaks, 12 significant and 2 integrated significant peaks, 17:3,418.8 and 25:4,173.41. While RCC were differentiated from benign by 5 integrated, 28 significant and one integrated significant peak. The RCC group was discriminated from the controls by 5 peaks which were integrated from which 1 was integrated and significant (with mass to charge ratio of 12:3,408.97). The three groups showed protein profiles ranging from 1 to 10 kDa. The external validation was performed for the RCC group versus the control reveled sensitivity of 88.7% and specificity of 73.2% by genetic algorithm. Conclusion: Proteomic approach can be used as a sensitive urinary marker differentiating renal masses in an early diagnostic approach.

The challenges of peptidomics in complementing proteomics in a clinical context

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

Recent advances in the metabolomic study of bladder cancer

INTRODUCTION

Metabolomics is a chemical process, involving the characterization of metabolites and cellular metabolism. Recent studies indicate that numerous metabolic pathways are altered in bladder cancer (BLCA), providing potential targets for improved detection and possible therapeutic intervention. We review recent advances in metabolomics related to BLCA and identify various metabolites that may serve as potential biomarkers for BLCA. Areas covered: In this review, we describe the latest advances in defining the BLCA metabolome and discuss the possible clinical utility of metabolic alterations in BLCA tissues, serum, and urine. In addition, we focus on the metabolic alterations associated with tobacco smoke and racial disparity in BLCA. Expert commentary: Metabolomics is a powerful tool which can shed new light on BLCA development and behavior. Key metabolites may serve as possible markers of BLCA. However, prospective validation will be needed to incorporate these markers into clinical care.

Probing the endogenous peptidomes of cancer for biomarkers: A new endeavor

The life span of cancer patients can be prolonged with appropriate therapies if detected early. Mass screening for early detection of cancer, however, requires sensitive and specific biomarkers obtainable from body fluids such as blood or urine. To date, most biomarker discovery programs focus on the proteome rather than the endogenous peptidome. It has been long-established that tumor cells and stromal cells produce tumor resident proteases (TRPs) to remodel the surrounding tumor microenvironment in support of tumor progression. In fact, proteolytic products of TRPs have been shown to correlate with malignant behavior. Being of low molecular weight, these unique peptides can pass through the endothelial barrier of the vasculature into the bloodstream. As such, the cancer peptidome has increasingly become a focus for biomarker discovery. In this review, we discuss on the various aspects of the peptidome in cancer biomarker research.

Urinary proteomic biomarkers in oncology: ready for implementation?

Introduction: Biomarkers are expected to improve the management of cancer patients by enabling early detection and prediction of therapeutic response. Proteins reflect a molecular phenotype, have high potential as biomarkers, and also are key targets for intervention. Given the ease of collection and proximity to certain tumors, the urinary proteome is a rich source of biomarkers and several proteins have been already implemented. Areas covered: We examined the literature on urine proteins and proteome analysis in oncology from reports published during the last 5 years to generate an overview on the status of urine protein and peptide biomarkers, with emphasis on their actual clinical value. Expert commentary: A few studies report on biomarkers that are ready to be implemented in patient management, among others in bladder cancer and cholangiocarcinoma. These reports are based on multi-marker approaches. A high number of biomarkers, though, has been described in studies with low statistical power. In fact, several of them have been consistently reported across different studies. The latter should be the focus of attention and be tested in properly designed confirmatory and ultimately, prospective investigations. It is expected that multi-marker classifiers for a specific context-of-use, will be the preferred path toward clinical implementation.

Liquid Biopsy Biomarkers in Bladder Cancer: A Current Need for Patient Diagnosis and Monitoring

Bladder Cancer (BC) represents a clinical and social challenge due to its high incidence and recurrence rates, as well as the limited advances in effective disease management. Currently, a combination of cytology and cystoscopy is the routinely used methodology for diagnosis, prognosis and disease surveillance. However, both the poor sensitivity of cytology tests as well as the high invasiveness and big variation in tumour stage and grade interpretation using cystoscopy, emphasizes the urgent need for improvements in BC clinical guidance. Liquid biopsy represents a new non-invasive approach that has been extensively studied over the last decade and holds great promise. Even though its clinical use is still compromised, multiple studies have recently focused on the potential application of biomarkers in liquid biopsies for BC, including circulating tumour cells and DNA, RNAs, proteins and peptides, metabolites and extracellular vesicles. In this review, we summarize the present knowledge on the different types of biomarkers, their potential use in liquid biopsy and clinical applications in BC.

Candidate Urine Peptide Biomarkers for IgA Nephropathy: Where Are We Now?

Early detection, prognosis, and management of IgA nephropathy (IgAN) remain a challenge. Histological examination of renal tissue still comprises the only way to confirm an IgAN diagnosis. It is of great importance to establish noninvasive diagnostic, prognostic, and predictive biomarkers that would improve the clinical care and outcome of patients suffering from IgAN. This review summarises the findings from previous mass spectrometry- (MS-) based studies dedicated to the discovery of urinary peptide profiles specific to IgAN. There is a substantial number of urinary peptides that have been discovered to date, which show promise as biomarkers of IgAN; however, all of them require further, rigorous validation in well-planned studies, involving a large number of subjects who represent diverse and numerous populations.

Origins, Technological Development, and Applications of Peptidomics

Peptidomics is the comprehensive characterization of peptides from biological sources mainly by HPLC and mass spectrometry. Mass spectrometry allows the detection of a multitude of single peptides in complex mixtures. The term first appeared in full papers in the year 2001, after over 100 years of peptide research with a main focus on one or a few specific peptides. Within the last 15 years, this new field has grown to over 1200 publications. Mass spectrometry techniques, in combination with other analytical methods, were developed for the fast and comprehensive analysis of peptides in proteomics and specifically adjusted to implement peptidomics technologies. Although peptidomics is closely linked to proteomics, there are fundamental differences with conventional bottom-up proteomics. The development of peptidomics is described, including the most important implementations for its technological basis. Different strategies are covered which are applied to several important applications, such as neuropeptidomics and discovery of bioactive peptides or biomarkers. This overview includes links to all other chapters in the book as well as recent developments of separation, mass spectrometric, and data processing technologies. Additionally, some new applications in food and plant peptidomics as well as immunopeptidomics are introduced.

Mass Spectrometric Identification of Endogenous Peptides

Peptidomics is an emerging field focused in the analysis of endogenous peptides. Naturally occurring peptides are often endogenously produced protein fragments. Cleavage of precursor proteins by proteases generates peptides that may gain specialized functions not ascribed to their precursors, and which could reflect the state of a cell under certain physiological conditions or pathological processes.Since peptides are found in complex matrices (e.g., serum, tear, urine, cerebrospinal fluid), they need to be isolated from the matrix and concentrated before they can be analyzed on mass spectrometry. This chapter describes methods for sample preparation prior to mass spectrometry analysis. In addition, different peptide fragmentation techniques are described which are complementary when analyzing naturally occurring peptides by liquid chromatography coupled online to tandem mass spectrometry.

The Peptidome Comes of Age: Mass Spectrometry-Based Characterization of the Circulating Cancer Peptidome

Peptides play a seminal role in most physiological processes acting as neurotransmitters, hormones, antibiotics, and immune regulation. In the context of tumor biology, it is hypothesized that endogenous peptides, hormones, cytokines, growth factors, and aberrant degradation of select protein networks (e.g., enzymatic activities, protein shedding, and extracellular matrix remodeling) are fundamental in mediating cancer progression. Analysis of peptides in biological fluids by mass spectrometry holds promise of providing sensitive and specific diagnostic and prognostic information for cancer and other diseases. The identification of circulating peptides in the context of disease constitutes a hitherto source of new clinical biomarkers. The field of peptidomics can be defined as the identification and comprehensive analysis of physiological and pathological peptides. Like proteomics, peptidomics has been advanced by the development of new separation strategies, analytical detection methods such as mass spectrometry, and bioinformatic technologies. Unlike proteomics, peptidomics is targeted toward identifying endogenous protein and peptide fragments, defining proteolytic enzyme substrate specificity, as well as protease cleavage recognition (degradome). Peptidomics employs "top-down proteomics" strategies where mass spectrometry is applied at the proteoform level to analyze intact proteins and large endogenous peptide fragments. With recent advances in prefractionation workflows for separating peptides, mass spectrometry instrumentation, and informatics, peptidomics is an important field that promises to impact on translational medicine. This review covers the current advances in peptidomics, including top-down and imaging mass spectrometry, comprehensive quantitative peptidome analyses (developments in reproducibility and coverage), peptide prefractionation and enrichment workflows, peptidomic data analyses, and informatic tools. The application of peptidomics in cancer biomarker discovery will be discussed.

Current state of the art for enhancing urine biomarker discovery

INTRODUCTION

Urine is a highly desirable biospecimen for biomarker analysis because it can be collected recurrently by non-invasive techniques, in relatively large volumes. Urine contains cellular elements, biochemicals, and proteins derived from glomerular filtration of plasma, renal tubule excretion, and urogenital tract secretions that reflect, at a given time point, an individual's metabolic and pathophysiologic state.

AREAS COVERED

High-resolution mass spectrometry, coupled with state of the art fractionation systems are revealing the plethora of diagnostic/prognostic proteomic information existing within urinary exosomes, glycoproteins, and proteins. Affinity capture pre-processing techniques such as combinatorial peptide ligand libraries and biomarker harvesting hydrogel nanoparticles are enabling measurement/identification of previously undetectable urinary proteins. Expert commentary: Future challenges in the urinary proteomics field include a) defining either single or multiple, universally applicable data normalization methods for comparing results within and between individual patients/data sets, and b) defining expected urinary protein levels in healthy individuals.

An integrated proteomic and peptidomic assessment of the normal human urinome

BACKGROUND

Urine represents an ideal source of clinically relevant biomarkers as it contains a large number of proteins and low molecular weight peptides. The comprehensive characterization of the normal urinary proteome and peptidome can serve as a reference for future biomarker discovery. Proteomic and peptidomic analysis of urine can also provide insight into normal physiology and disease pathology, especially for urogenital diseases.

METHODS

We developed an integrated proteomic and peptidomic analytical protocol in normal urine. We employed ultrafiltration to separate protein and peptide fractions, which were analyzed separately using liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) on the Q-Exactive mass spectrometer.

RESULTS

By analyzing six urines from healthy individuals with advanced age, we identified 1754 proteins by proteomic analysis and 4543 endogenous peptides, arising from 566 proteins by peptidomic analysis. Overall, we identified 2091 non-redundant proteins by this integrated approach. In silico protease activity analysis indicated that metalloproteases are predominantly involved in the generation of the endogenous peptide signature. In addition, a number of proteins that were detected in normal urine have previously been implicated in various urological malignancies, including bladder cancer and renal cell carcinoma (RCC).

CONCLUSIONS

We utilized a highly sensitive proteomics approach that enabled us to identify one of the largest sets of protein identifications documented in normal human urine. The raw proteomics and peptidomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD003595.

The proteomic landscape of renal tumors

INTRODUCTION

Renal cell carcinoma (RCC) is the most fatal of the common urologic cancers, with approximately 35% of patients dying within 5 years following diagnosis. Therefore, there is a need for non-invasive markers that are capable of detecting and determining the severity of small renal masses at an early stage in order to tailor treatment and follow-up. Proteomic studies have proved to be very useful in the study of tumors. Areas covered: In this review, we will detail the current knowledge obtained by the different proteomic approaches, focusing on MS-based strategies, used to investigate RCC biology in order to identify diagnostic, prognostic and predictive biomarkers on tissue, cultured cells and biological fluids. Expert commentary: Currently, no reliable biomarkers or targets for RCC have been translated into the clinical setting. Moreover, despite the efforts of proteomics and other -omics disciplines, only a small number of them have been observed as shared targets between the different analytical platforms and biological specimens. The difficulty to define a specific molecular pattern for RCC and its subtypes highlights a peculiar profile and a heterogeneity that must be taken into account in future studies.

Sample-dependent diagnostic accuracy of prostaglandin D synthase in cerebrospinal fluid leak

BACKGROUND

Prostaglandin D2 synthase, commonly known as β-trace protein (βTP), is an excellent biomarker for the assessment of cerebrospinal fluid (CSF) leaks. Despite being widely used, the limits for the diagnostic values of βTP are not well established to date, and currently suggested cut-off values in literature range from 0.25 to 6.0mg/L. Sample-specific and more accurate thresholds are a current need.

METHODS

A retrospective observational study, performed in a tertiary-care hospital, between January 2006 and January 2014. A total of 74 patients were included, with a definitive diagnosis after initial leak suspicion and at least one determination of βTP using a nephelometry-based assay. A total of 46 CSF samples were included in the control group. Samples were obtained from nasal secretions, ear secretions or spinal surgical injury, directly using sterile Eppendorf tubes. The analysis of 3 different cut-off values was performed and the receiver operating curve (ROC) analyses were calculated.

RESULTS

Initial diagnostic suspicion was confirmed in 51% of cases, most of which were of postoperative origin (51%) and traumatic (26%). The βTP median concentration in different samples was significantly higher in the presence of cerebrospinal fluid fistula, regardless of sample type (22.0mg/L vs. 0.24mg/L, 95% confidence interval: 19.0-30.8 vs. 0.08-0.40; p<0.001). Data from contingency tables show 100% sensitivity and specificity, depending on sample type and the cut-off value used: for rhinorrhea and otorrhea samples, the most appropriate it was 0.7mg/L, while values >2.0mg/L could be used for spine postoperative fluid leakage samples.

CONCLUSIONS

The cut off value for βTP in the diagnosis and follow-up of cerebrospinal fluid leaks should be modified depending on the type of secretion (sample type), for a better diagnostic accuracy.