Detection of candidate biomarkers of prostate cancer progression in serum: a depletion-free 3D LC/MS quantitative proteomics pilot study

Deciphering Cancer Complexity: Integrative Proteogenomics and Proteomics Approaches for Biomarker Discovery

Proteomics has revolutionized the field of cancer biology because the use of a large number of in vivo (SILAC), in vitro (iTRAQ, ICAT, TMT, stable-isotope Dimethyl, and 18O) labeling techniques or label-free methods (spectral counting or peak intensities) coupled with mass spectrometry enables us to profile and identify dysregulated proteins in diseases such as cancer. These proteome and genome studies have led to many challenges, such as the lack of consistency or correlation between copy numbers, RNA, and protein-level data. This review covers solely mass spectrometry-based approaches used for cancer biomarker discovery. It also touches on the emerging role of oncoproteogenomics or proteogenomics in cancer biomarker discovery and how this new area is attracting the integration of genomics and proteomics areas to address some of the important questions to help impinge on the biology and pathophysiology of different malignancies to make these mass spectrometry-based studies more realistic and relevant to clinical settings.

Enhanced proteomic profiling of human plasma-derived extracellular vesicles through charge-based fractionation to advance biomarker discovery potential

The study introduces a charge-based fractionation method for fractionating plasma-derived extracellular vesicles (EVs) into sub-populations aimed at the improved purification from free plasma proteins to enhance the diagnostic potential of EV sub-populations for specific pathophysiological states. Here, we present a novel approach for EV fractionation that leverages EVs' inherent surface charges, differentiating them from other plasma components and, thus, reducing the sample complexity and increasing the purity of EVs. The developed method was optimized and thoroughly evaluated using proteomic analysis, transmission electron microscopy, nanoparticle tracking, and western blotting of isolated EVs from healthy donors. Subsequently, we pilot-tested the developed technique for its applicability to real-world specimens using a small set of clinical prostate cancer samples and matched controls. The presented technique demonstrates the effective isolation and fractionation of EV sub-populations based on their surface charge, which may potentially help enhance EV-based diagnostics, biomarker discovery, and basic biology research. The method is designed to be straightforward, scalable, easy-to-use, and it does not require specialized skills or equipment.

Increased Expression and Prognostic Significance of BYSL in Melanoma

We evaluated the BYSL content and underlying mechanism in melanoma (SKCM) overall survival (OS). In this study, we used a comprehensive approach combining bioinformatics tools, including miRNA estimation, quantitative real-time polymerase chain reaction (qRT-PCR) of miRNAs, E3 ligase estimation, STRING analysis, TIMER analysis, examination of associated upstream modulators, protein-protein interaction (PPI) analysis, as well as retrospective and survival analyses, alongside clinical sample validation. These methods were used to investigate the content of BYSL, its methylation status, its relation to patient outcome, and its immunologic significance in tumors. Our findings revealed that BYSL expression is negatively regulated by BYSL methylation. Analysis of 468 cases of SKCM RNA sequencing samples demonstrated that enhanced BYSL expression was associated with higher tumor grade. We identified several miRNAs, namely hsa-miR-146b-3p, hsa-miR-342-3p, hsa-miR-511-5p, hsa-miR-3690, and hsa-miR-193a-5p, which showed a strong association with BYSL levels. Furthermore, we predicted the E3 ubiquitin ligase of BYSL and identified CBL, FBXW7, FZR1, KLHL3, and MARCH1 as potential modulators of BYSL. Through our investigation, we discovered that PNO1, RIOK2, TSR1, WDR3, and NOB1 proteins were strongly associated with BYSL expression. In addition, we found a close association between BYSL levels and certain immune cells, particularly dendritic cells (DCs). Notably, we observed a significant negative correlation between miR-146b-3p and BYSL mRNA expression in SKCM sera samples. Collectively, based on the previously shown evidences, BYSL can serve as a robust bioindicator of SKCM patient prognosis, and it potentially contributes to immune cell invasion in SKCM.

Advances in Prostate Cancer Biomarkers and Probes

Prostate cancer is one of the most prevalent malignant tumors in men worldwide, and early diagnosis is essential to improve patient survival. This review provides a comprehensive discussion of recent advances in prostate cancer biomarkers, including molecular, cellular, and exosomal biomarkers. The potential of various biomarkers such as gene fusions (TMPRSS2-ERG), noncoding RNAs (SNHG12), proteins (PSA, PSMA, AR), and circulating tumor cells (CTCs) in the diagnosis, prognosis, and targeted therapies of prostate cancer is emphasized. In addition, this review systematically explores how multi-omics data and artificial intelligence technologies can be used for biomarker discovery and personalized medicine applications. In addition, this review provides insights into the development of specific probes, including fluorescent, electrochemical, and radionuclide probes, for sensitive and accurate detection of prostate cancer biomarkers. In conclusion, this review provides a comprehensive overview of the status and future directions of prostate cancer biomarker research, emphasizing the potential for precision diagnosis and targeted therapy.

Proteomics of prostate cancer serum and plasma using low and high throughput approaches

Despite progress, MS-based proteomics in biofluids, especially blood, faces challenges such as dynamic range and throughput limitations in biomarker and disease studies. In this work, we used cutting-edge proteomics technologies to construct label-based and label-free workflows, capable of quantifying approximately 2,000 proteins in biofluids. With 70µL of blood and a single depletion strategy, we conducted an analysis of a homogenous cohort (n = 32), comparing medium-grade prostate cancer patients (Gleason score: 7(3 + 4); TNM stage: T2cN0M0, stage IIB) to healthy donors. The results revealed dozens of differentially expressed proteins in both plasma and serum. We identified the upregulation of Prostate Specific Antigen (PSA), a well-known biomarker for prostate cancer, in the serum of cancer cohort. Further bioinformatics analysis highlighted noteworthy proteins which appear to be differentially secreted into the bloodstream, making them good candidates for further exploration.

Deciphering Urogenital Cancers through Proteomic Biomarkers: A Systematic Review and Meta-Analysis

Urogenital cancers, which include prostate, bladder, and kidney malignancies, exert a substantial impact on global cancer-related morbidity and mortality. Proteomic biomarkers, emerging as valuable tools, aim to enhance early detection, prognostic accuracy, and the development of personalized therapeutic strategies. This study undertook a comprehensive systematic review and meta-analysis of the existing literature investigating the role and potential of proteomic biomarkers in plasma, tissue, and urine samples in urogenital cancers. Our extensive search across several databases identified 1879 differentially expressed proteins from 37 studies, signifying their potential as unique biomarkers for these cancers. A meta-analysis of the significantly differentially expressed proteins was executed, accentuating the findings through visually intuitive volcano plots. A functional enrichment analysis unveiled their significant involvement in diverse biological processes, including signal transduction, immune response, cell communication, and cell growth. A pathway analysis highlighted the participation of key pathways such as the nectin adhesion pathway, TRAIL signaling pathway, and integrin signaling pathways. These findings not only pave the way for future investigations into early detection and targeted therapeutic approaches but also underscore the fundamental role of proteomics in advancing our understanding of the molecular mechanisms underpinning urogenital cancer pathogenesis. Ultimately, these findings hold remarkable potential to significantly enhance patient care and improve clinical outcomes.

Advancements in Oncoproteomics Technologies: Treading toward Translation into Clinical Practice

Proteomics continues to forge significant strides in the discovery of essential biological processes, uncovering valuable information on the identity, global protein abundance, protein modifications, proteoform levels, and signal transduction pathways. Cancer is a complicated and heterogeneous disease, and the onset and progression involve multiple dysregulated proteoforms and their downstream signaling pathways. These are modulated by various factors such as molecular, genetic, tissue, cellular, ethnic/racial, socioeconomic status, environmental, and demographic differences that vary with time. The knowledge of cancer has improved the treatment and clinical management; however, the survival rates have not increased significantly, and cancer remains a major cause of mortality. Oncoproteomics studies help to develop and validate proteomics technologies for routine application in clinical laboratories for (1) diagnostic and prognostic categorization of cancer, (2) real-time monitoring of treatment, (3) assessing drug efficacy and toxicity, (4) therapeutic modulations based on the changes with prognosis and drug resistance, and (5) personalized medication. Investigation of tumor-specific proteomic profiles in conjunction with healthy controls provides crucial information in mechanistic studies on tumorigenesis, metastasis, and drug resistance. This review provides an overview of proteomics technologies that assist the discovery of novel drug targets, biomarkers for early detection, surveillance, prognosis, drug monitoring, and tailoring therapy to the cancer patient. The information gained from such technologies has drastically improved cancer research. We further provide exemplars from recent oncoproteomics applications in the discovery of biomarkers in various cancers, drug discovery, and clinical treatment. Overall, the future of oncoproteomics holds enormous potential for translating technologies from the bench to the bedside.

Bile Acids: Physiological Activity and Perspectives of Using in Clinical and Laboratory Diagnostics

Bile acids play a significant role in the digestion of nutrients. In addition, bile acids perform a signaling function through their blood-circulating fraction. They regulate the activity of nuclear and membrane receptors, located in many tissues. The gut microbiota is an important factor influencing the effects of bile acids via enzymatic modification. Depending on the rate of healthy and pathogenic microbiota, a number of bile acids may support lipid and glucose homeostasis as well as shift to more toxic compounds participating in many pathological conditions. Thus, bile acids can be possible biomarkers of human pathology. However, the chemical structure of bile acids is similar and their analysis requires sensitive and specific methods of analysis. In this review, we provide information on the chemical structure and the biosynthesis of bile acids, their regulation, and their physiological role. In addition, the review describes the involvement of bile acids in various diseases of the digestive system, the approaches and challenges in the analysis of bile acids, and the prospects of their use in omics technologies.

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

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

Arsenic trioxide increases apoptosis of SK-N-BE (2) cells partially by inducing GPX4-mediated ferroptosis

BACKGROUND

Neuroblastoma (NB) is the most common extracranial tumor in central nervous system threatening children's health with limited therapeutic options. Arsenic trioxide (ATO) has been identified the cytotoxicity in NB cells but the potential mechanism remains unclear. In this study, we attempted to obtain some insight into the mechanisms of cell death induced by ATO in NB cells.

METHODS AND RESULTS

Proteomic analyses found that ATO can affect the signaling pathway associated with ferroptosis, including the upregulation of iron absorption (FTL, FTH1, HO-1), ferritinophagy (LC3, P62, ATG7, NCOA4) and modifier of glutathione synthesis (GCLM); downregulation of glutamine synthetase (GS) and GPX4, which was the critical inhibitor of ferroptosis. Western blot analysis revealing GPX4 expression in SK-N-BE (2) cells decreased after treatment with ATO (7.3 µM), resulting in a loss of GPX4 activity. Furthermore, Ferroptosis inhibitor ferrostatin-1 partially blocked ATO-induced cell death.

CONCLUSIONS

Our study revealed that ATO may induce ferroptosis in neuroblastoma cell SK-N-BE (2) by facilitating the downregulation of GPX4, ultimately resulting in iron-dependent oxidative death.

Role of cystatin C in urogenital malignancy

Urogenital malignancy accounts for one of the major causes of cancer-related deaths globally. Numerous studies have investigated novel molecular markers in the blood circulation, tumor tissue, or urine in order to assist in the clinical identification of tumors at early stages, predict the response of therapeutic strategies, and give accurate prognosis assessment. As an endogenous inhibitor of lysosomal cysteine proteinases, cystatin C plays an integral role in diverse processes. A substantial number of studies have indicated that it may be such a potential promising biomarker. Therefore, this review was intended to provide a detailed overview of the role of cystatin C in urogenital malignancy.

Recent Developments and Applications of Quantitative Proteomics Strategies for High-Throughput Biomolecular Analyses in Cancer Research

Innovations in medical technology and dedicated focus from the scientific community have inspired numerous treatment strategies for benign and invasive cancers. While these improvements often lend themselves to more positive prognoses and greater patient longevity, means for early detection and severity stratification have failed to keep pace. Detection and validation of cancer-specific biomarkers hinges on the ability to identify subtype-specific phenotypic and proteomic alterations and the systematic screening of diverse patient groups. For this reason, clinical and scientific research settings rely on high throughput and high sensitivity mass spectrometry methods to discover and quantify unique molecular perturbations in cancer patients. Discussed within is an overview of quantitative proteomics strategies and a summary of recent applications that enable revealing potential biomarkers and treatment targets in prostate, ovarian, breast, and pancreatic cancer in a high throughput manner.

Identification of Altered Proteins in the Plasma of Rats With Chronic Prostatic Inflammation Induced by Estradiol Benzoate and Sex Hormones

The cause of nonbacterial chronic prostatitis is unknown, yet its prevalence accounts for more than 90% of all prostatitis cases. Whole blood, plasma, and serum have been used to identify prostate cancer biomarkers; however, few studies have performed protein profiling to identify prostatitis biomarkers. The purpose of this study was to identify protein biomarkers altered by chronic prostatitis. To perform the study, we chemically induced chronic prostate inflammation in Sprague Dawley rats using estradiol benzoate (EB), testosterone (T), and estradiol (E) and then examined protein levels in their plasma. Plasma was collected on postnatal days (PNDs) 90, 100, 145, and 200; plasma proteins were profiled using liquid chromatography-tandem mass spectrometry. Chronic inflammation was observed in the rat prostate induced with EB on PNDs 1, 3, and 5. Rats then were dosed with T+E during PNDs 90-200 via subcutaneous implants. We identified time-specific expression for several proteins (i.e., CFB, MYH9, AZGP1). Some altered proteins that were expressed in the prostate (i.e., SERPINF1, CTR9) also were identified in the rat plasma in the EB+T+E group on PNDs 145 and 200. These findings suggest that the identified proteins could be used as biomarkers of chronic prostatitis. Further studies are needed to verify the results in human samples.

Use of a Recombinant Biomarker Protein DDA Library Increases DIA Coverage of Low Abundance Plasma Proteins

Credible detection and quantification of low abundance proteins from human blood plasma is a major challenge in precision medicine biomarker discovery when using mass spectrometry (MS). In this proof-of-concept study, we employed a mixture of selected recombinant proteins in DDA libraries to subsequently identify (not quantify) cancer-associated low abundance plasma proteins using SWATH/DIA. The exemplar DDA recombinant protein spectral library (rPSL) was derived from tryptic digestion of 36 recombinant human proteins that had been previously implicated as possible cancer biomarkers from both our own and other studies. The rPSL was then used to identify proteins from nondepleted colorectal cancer (CRC) EDTA plasmas by SWATH-MS. Most (32/36) of the proteins used in the rPSL were reliably identified from CRC plasma samples, including 8 proteins (i.e., BTC, CXCL10, IL1B, IL6, ITGB6, TGFα, TNF, TP53) not previously detected using high-stringency protein inference MS according to PeptideAtlas. The rPSL SWATH-MS protocol was compared to DDA-MS using MARS-depleted and postdigestion peptide fractionated plasmas (here referred to as a human plasma DDA library). Of the 32 proteins identified using rPSL SWATH, only 12 could be identified using DDA-MS. The 20 additional proteins exclusively identified using the rPSL SWATH approach were almost exclusively lower abundance (i.e., <10 ng/mL) proteins. To mitigate justified FDR concerns, and to replicate a more typical library creation approach, the DDA rPSL library was merged with a human plasma DDA library and SWATH identification repeated using such a merged library. The majority (33/36) of the low abundance plasma proteins added from the rPSL were still able to be identified using such a merged library when high-stringency HPP Guidelines v3.0 protein inference criteria were applied to our data set. The MS data set has been deposited to ProteomeXchange Consortium via the PRIDE partner repository (PXD022361).

Identifying Potential Markers for Monitoring Progression to Ovarian Cancer Using Plasma Label-free Proteomics

Background: Cancer antigen 125 (CA125) is considered to have high sensitivity but poor specificity for ovarian cancer. New biomarkers utilized to early detect and monitor the progression of ovarian cancer patients are critically needed. Methods: A total of 80 patients including 16 early stage, and matched with 17 late stage, 23 benign ovarian tumor (BOT) and 24 uterine fibroid (UF) patients were utilized to perform plasma proteomics analysis using isobaric tag for relative and absolute quantitation (iTRAQ) method to identify differential diagnostic proteins of ovarian cancer patients. A validation set of 9 early stage, 11 late stage, 17 BOT and 16 UF collected by an independent cohort of samples with the same matching principles was examined to confirm the expressed levels of differential expression proteins by ELISA analysis. Results: CRP and ARHGEF 11 were identified as potential diagnostic biomarkers of ovarian cancer. Results of area under the curve (AUC) analysis suggested that combination of diagnostic proteins and CA125 achieved a much higher diagnostic accuracy compared with CA125 alone (AUC values: 0.98 versus 0.80), especially improved the specificity (0.97 versus 0.77). In addition, elevated plasma CRP levels were associated with increased risk of ovarian cancer. Conclusions: Current study found that plasma protein CRP was an indicator for monitoring the progression of ovarian cancer. Combination of plasma protein biomarkers with CA125 could be utilized to early diagnose of ovarian cancer patients.

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

Simple Summary

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

Abstract

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

Clinical proteomics for prostate cancer: understanding prostate cancer pathology and protein biomarkers for improved disease management

Following the introduction of routine Prostate Specific Antigen (PSA) screening in the early 1990's, Prostate Cancer (PCa) is often detected at an early stage. There are also a growing number of treatment options available and so the associated mortality rate is generally low. However, PCa is an extremely complex and heterogenous disease and many patients suffer disease recurrence following initial therapy. Disease recurrence commonly results in metastasis and metastatic PCa has an average survival rate of just 3-5 years. A significant problem in the clinical management of PCa is being able to differentiate between patients who will respond to standard therapies and those who may benefit from more aggressive intervention at an earlier stage. It is also acknowledged that for many men the disease is not life threatenting. Hence, there is a growing desire to identify patients who can be spared the significant side effects associated with PCa treatment until such time (if ever) their disease progresses to the point where treatment is required. To these important clinical needs, current biomarkers and clinical methods for patient stratification and personlised treatment are insufficient. This review provides a comprehensive overview of the complexities of PCa pathology and disease management. In this context it is possible to review current biomarkers and proteomic technologies that will support development of biomarker-driven decision tools to meet current important clinical needs. With such an in-depth understanding of disease pathology, the development of novel clinical biomarkers can proceed in an efficient and effective manner, such that they have a better chance of improving patient outcomes.

Identification of Subtype-Specific Metastasis-Related Genetic Signatures in Sarcoma

Background: Sarcomas are heterogeneous rare malignancies constituting approximately 1% of all solid cancers in adults and including more than 70 histological and molecular subtypes with different pathological and clinical development characteristics.

Method: We identified prognostic biomarkers of sarcomas by integrating clinical information and RNA-seq data from TCGA and GEO databases. In addition, results obtained from cell cycle, cell migration, and invasion assays were used to assess the capacity for Tanespimycin to inhibit the proliferation and metastasis of sarcoma.

Results: Sarcoma samples (N = 536) were divided into four pathological subtypes including DL (dedifferentiated liposarcoma), LMS (leiomyosarcoma), UPS (undifferentiated pleomorphic sarcomas), and MFS (myxofibrosarcoma). RNA-seq expression profile data from the TCGA dataset were used to analyze differentially expressed genes (DEGs) within metastatic and non-metastatic samples of these four sarcoma pathological subtypes with DEGs defined as metastatic-related signatures (MRS). Prognostic analysis of MRS identified a group of genes significantly associated with prognosis in three pathological subtypes: DL, LMS, and UPS. ISG15, NUP50, PTTG1, SERPINE1, and TSR1 were found to be more likely associated with adverse prognosis. We also identified Tanespimycin as a drug exerting inhibitory effects on metastatic LMS subtype and therefore can serve a potential treatment for this type of sarcoma.

Conclusions: These results provide new insights into the pathogenesis, diagnosis, treatment, and prognosis of sarcomas and provide new directions for further study of sarcoma.

Comprehensive plasma proteomic profiling reveals biomarkers for active tuberculosis

BACKGROUNDTuberculosis (TB) kills more people than any other infection, and new diagnostic tests to identify active cases are required. We aimed to discover and verify novel markers for TB in nondepleted plasma.METHODSWe applied an optimized quantitative proteomics discovery methodology based on multidimensional and orthogonal liquid chromatographic separation combined with high-resolution mass spectrometry to study nondepleted plasma of 11 patients with active TB compared with 10 healthy controls. Prioritized candidates were verified in independent UK (n = 118) and South African cohorts (n = 203).RESULTSWe generated the most comprehensive TB plasma proteome to date, profiling 5022 proteins spanning 11 orders-of-magnitude concentration range with diverse biochemical and molecular properties. We analyzed the predominantly low-molecular weight subproteome, identifying 46 proteins with significantly increased and 90 with decreased abundance (peptide FDR ≤ 1%, q ≤ 0.05). Verification was performed for novel candidate biomarkers (CFHR5, ILF2) in 2 independent cohorts. Receiver operating characteristics analyses using a 5-protein panel (CFHR5, LRG1, CRP, LBP, and SAA1) exhibited discriminatory power in distinguishing TB from other respiratory diseases (AUC = 0.81).CONCLUSIONWe report the most comprehensive TB plasma proteome to date, identifying novel markers with verification in 2 independent cohorts, leading to a 5-protein biosignature with potential to improve TB diagnosis. With further development, these biomarkers have potential as a diagnostic triage test.FUNDINGColciencias, Medical Research Council, Innovate UK, NIHR, Academy of Medical Sciences, Program for Advanced Research Capacities for AIDS, Wellcome Centre for Infectious Diseases Research.

Secretome Proteomic Approaches for Biomarker Discovery: An Update on Colorectal Cancer

Searching for new cancer-related biomarkers is a key priority for the early detection of solid tumors, such as colorectal cancer (CRC), in clinically relevant biological fluids. The cell line and/or tumor tissue secretome represents a valuable resource for discovering novel protein markers secreted by cancer cells. The advantage of a secretome analysis is the reduction of the large dynamic range characterizing human plasma/serum, and the simultaneous enrichment of low abundance cancer-secreted proteins, thereby overcoming the technical limitations underlying the direct search in blood samples. In this review, we provided a comprehensive overview of recent studies on the CRC secretome for biomarker discovery, focusing both on methodological and technical aspects of secretome proteomic approaches and on biomarker-independent validation in CRC patient samples (blood and tissues). Secretome proteomics are mainly based on LC-MS/MS analyses for which secretome samples are either in-gel or in-solution trypsin-digested. Adequate numbers of biological and technical replicates are required to ensure high reproducibility and robustness of the secretome studies. Moreover, another major challenge is the accuracy of proteomic quantitative analysis performed by label-free or labeling methods. The analysis of differentially expressed proteins in the CRC secretome by using bioinformatic tools allowed the identification of potential biomarkers for early CRC detection. In this scenario, this review may help to follow-up the recent secretome studies in order to select promising circulating biomarkers to be validated in larger screenings, thereby contributing toward a complete translation in clinical practice.

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

Simple Summary

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

Abstract

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

A different vision of translational research in biomarker discovery: a pilot study on circulatory mitochondrial proteins as Parkinson's disease potential biomarkers

Background

The identification of circulating biomarkers that closely correlate with Parkinson’s Disease (PD) has failed several times in the past. Nevertheless, in this pilot study, a translational approach was conducted, allowing the evaluation of the plasma levels of two mitochondrial-related proteins, whose combination leads to a robust model with potential diagnostic value to discriminate the PD patients from matched controls.

Methods

The proposed translational approach was initiated by the analysis of secretomes from cells cultured under control or well-defined oxidative stress conditions, followed by the identification of proteins related to PD pathologic mechanisms that were altered between the two states. This pipeline was further translated into the analysis of undepleted plasma samples from 28 control and 31 PD patients.

Results

From the secretome analysis, several mitochondria-related proteins were found to be differentially released between control and stress conditions and to be able to distinguish the two secretomes. Similarly, two mitochondrial-related proteins were found to be significantly changed in a PD cohort compared to matched controls. Moreover, a linear discriminant model with potential diagnostic value to discriminate PD patients was obtained using the combination of these two proteins. Both proteins are associated with apoptotic mitochondrial changes, which may correspond to potential indicators of cell death. Moreover, one of these proteins, the VPS35 protein, was reported in plasma for the first time, and its quantification was only possible due to its previous identification in the secretome analysis.

Conclusions

In this work, an adaptation of a translational pipeline for biomarker selection was presented and transposed to neurological diseases, in the present case Parkinson’s Disease. The novelty and success of this pilot study may arise from the combination of: i) a translational research pipeline, where plasma samples are interrogated using knowledge previously obtained from the evaluation of cells’ secretome under oxidative stress; ii) the combined used of statistical analysis and an informed selection of candidates based on their link with relevant disease mechanisms, and iii) the use of SWATH-MS, an untargeted MS method that allows a complete record of the analyzed samples and a targeted data extraction of the quantitative values of proteins previously identified.

Increased plasma CD14 levels 1 year postpartum in women with pre-eclampsia during pregnancy: a case-control plasma proteomics study

Epidemiological data suggest that pre-eclampsia (PE) is associated with an increased risk of post-delivery metabolic dysregulation. The aim of the present case-control observational study was to examine the global plasma proteomic profile 1 year postpartum in women who developed PE during pregnancy (n = 5) compared to controls (n = 5), in order to identify a novel predictive marker linking PE with long-term metabolic imbalance. Key findings were verified with enzyme-linked immunosorbent assay (ELISA) in a separate cohort (n = 17 women with PE and n = 43 controls). One hundred and seventy-two proteins were differentially expressed in the PE vs. control groups. Gene ontology analysis showed that Inflammatory|Immune responses, Blood coagulation and Metabolism were significantly enriched terms. CD14, mapping to the inflammatory response protein network, was selected for verification based on bibliographic evidence. ELISA measurements showed CD14 to be significantly increased 1 year postpartum in women with PE during pregnancy compared to controls [PE group (median ± SD): 296.5 ± 113.6; control group (median ± SD): 128.9 ± 98.5; Mann-Whitney U test p = 0.0078]. Overall, the identified proteins could provide insight into the long-term disease risk among women with PE during pregnancy and highlight the need for their postpartum monitoring. CD14 could be examined in larger cohorts as a predictive marker of insulin resistance and type II diabetes mellitus among women with PE.

Advances in biomarker detection: Alternative approaches for blood-based biomarker detection

In the clinical setting, a blood sample is typically the starting point for biomarker search and discovery. Mass spectrometry (MS) is a highly sensitive and informative method for characterizing a very wide range of metabolites and proteins and is therefore a potentially powerful tool for biomarker discovery. However, the physicochemical characteristics of blood coupled with very large ranges of protein and metabolite concentrations present a significant technical obstacle for resolving and quantifying putative biomarkers by MS. Blood fractionation procedures are being developed to reduce the proteome/metabolome complexity and concentration ranges, allowing a greater diversity of analytes, including those at very low concentrations, to be quantified. In this chapter, several strategies for enriching and/or isolating specific blood components are summarized, including methods for the analysis of low and high molecular weight compounds, usually neglected in this type of assays, extracellular vesicles, and peripheral blood mononuclear cells (PBMCs). For each method, relevant practical information is presented for effective implementation.

Cystatins in cancer progression: More than just cathepsin inhibitors

Cystatins are endogenous and reversible inhibitors of cysteine peptidases that are important players in cancer progression. Besides their primary role as regulators of cysteine peptidase activity, cystatins are involved in cancer development and progression through proteolysis-independent mechanisms. Mechanistic studies of cystatin function revealed that they affect all stages of cancer progression including tumor growth, apoptosis, invasion, metastasis and angiogenesis. Recently, the involvement of cystatins in the antitumor immune responses was reported. In this review, we discuss molecular mechanisms and clinical aspects of cystatins in cancer. Altered expression of cystatins in cancer resulting in harmful excessive cysteine peptidase activity has been a subject of several studies in order to find correlations with clinical outcome and therapy response. However, involvement in anti-tumor immune response and signaling cascades leading to cancer progression designates cystatins as possible targets for development of new anti-tumor drugs.

Analysis of the plasma proteome using iTRAQ and TMT-based Isobaric labeling

Over the past decade, chemical labeling with isobaric tandem mass tags, such as isobaric tags for relative and absolute quantification reagents (iTRAQ) and tandem mass tag (TMT) reagents, has been employed in a wide range of different clinically orientated serum and plasma proteomics studies. In this review the scope of these works is presented with attention to the areas of research, methods employed and performance limitations. These applications have covered a wide range of diseases, disorders and infections, and have implemented a variety of different preparative and mass spectrometric approaches. In contrast to earlier works, which struggled to quantify more than a few hundred proteins, increasingly these studies have provided deeper insight into the plasma proteome extending the numbers of quantified proteins to over a thousand.

Promise and Implementation of Proteomic Prostate Cancer Biomarkers

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

Expression of Indoleamine 2,3-Dioxygenase Induced by IFN-γ and TNF-α as Potential Biomarker of Prostate Cancer Progression

Inflammation has been suggested to play an important role in onset and progression of prostate cancer (PCa). Histological analysis of prostatectomy specimens has revealed focal inflammation in early stage lesions of this malignancy. We addressed the role of inflammatory stimuli in the release of PCa-specific, tumor-derived soluble factors (PCa-TDSFs) already reported to be mediators of PCa morbidity, such as indoleamine 2,3-dioxygenase (IDO) and interleukin (IL)-6. Inflammation-driven production and functions of PCa-TDFSs were tested "in vitro" by stimulating established cell lines (CA-HPV-10 and PC3) with IFN-γ or TNF-α. Expression of genes encoding IDO, IL-6, IFN-γ, TNF-α, and their receptors was investigated in tumor tissues of PCa patients undergoing radical prostatectomy, in comparison with benign prostatic hyperplasia (BPH) specimens. IFN-γ and TNF-α-treatment resulted in the induction of IDO and IL-6 gene expression and release in established cell lines, suggesting that the elicitation of PCa-TDSFs by these cytokines might contribute to progression of cancer into an untreatable phenotype. An analysis based on timing of biochemical recurrence revealed the prognostic value of IDO but not IL-6 gene expression in predicting recurrence-free survival in patients (RFS) with PCa. In addition, a urine-based mRNA biomarker study revealed the diagnostic potential of IDO gene expression in urines of men at risk of PCa development.

Aberrant upregulation of KLK10 promotes metastasis via enhancement of EMT and FAK/SRC/ERK axis in PDAC

Pancreatic Ductal Adenocarcinoma (PADC) metastasis is the leading cause of morality of this severe malignant tumor. Proteases are key players in the degradation of extracellular matrix which promotes the cascade of tumor metastasis. As a kind of serine proteases, the kallikrein family performs vital function on the cancer proteolysis scene, which have been proved in diverse malignant tumors. However, the specific member of kallikrein family and its function in PDAC remain unexplored. In this study, by data mining of GEO datasets, we have identified KLK10 is upregulated gene in PDAC. We found that KLK10 was significantly overexpressed in tissues of pancreatic intraepithelial neoplasia (PanIN) and PDAC from Pdx1-Cre; LSL-KrasG12D/+ mice (KC) and Pdx1-Cre; LSL-KrasG12D/+; LSL-Trp53R172H/+ mice (KPC) by immunohistochemical analysis. Moreover, KLK10 is extremely elevated in the PDAC tissues, especially that from the PDAC patients with lymphatic and distant metastasis. Aberrant KLK10 expression is significantly correlated with poor prognosis and shorter survival by univariable and multivariable analysis. Functionally, knockdown of KLK10 observably inhibits invasion and metastatic phenotype of PDAC cells in vitro and metastasis in vivo. In addition, blockade of KLK10 attenuates epithelial-mesenchymal transition and activation of FAK-SRC-ERK signaling, which explains the mechanism of KLK10 in promoting metastasis. Collectively, KLK10 should be considered as a promising biomarker for diagnosis and potential target for therapy in PDAC.

Quantitative proteomic profiling of primary cancer-associated fibroblasts in oesophageal adenocarcinoma

BACKGROUND

Cancer-associated fibroblasts (CAFs) form the major stromal component of the tumour microenvironment (TME). The present study aimed to examine the proteomic profiles of CAFs vs. normal fibroblasts (NOFs) from patients with oesophageal adenocarcinoma to gain insight into their pro-oncogenic phenotype.

METHODS

CAFs/NOFs from four patients were sub-cultured and analysed using quantitative proteomics. Differentially expressed proteins (DEPs) were subjected to bioinformatics and compared with published proteomics and transcriptomics  datasets.

RESULTS

Principal component analysis of all profiled proteins showed that CAFs had high heterogeneity and clustered separately from NOFs. Bioinformatics interrogation of the DEPs demonstrated inhibition of adhesion of epithelial cells, adhesion of connective tissue cells and cell death of fibroblast cell lines in CAFs vs. NOFs (p < 0.0001). KEGG pathway analysis showed a significant enrichment of the insulin-signalling pathway (p = 0.03). Gene ontology terms related with myofibroblast phenotype, metabolism, cell adhesion/migration, hypoxia/oxidative stress, angiogenesis, immune/inflammatory response were enriched in CAFs vs. NOFs. Nestin, a stem-cell marker up-regulated in CAFs vs. NOFs, was confirmed to be expressed in the TME with immunohistochemistry.

CONCLUSIONS

The identified pathways and participating proteins may provide novel insight on the tumour-promoting properties of CAFs and unravel novel adjuvant therapeutic targets in the TME.

Increased circulating resistin levels in early-onset breast cancer patients of normal body mass index correlate with lymph node negative involvement and longer disease free survival: a multi-center POSH cohort serum proteomics study

BACKGROUND

Early-onset breast cancer (EOBC) affects about one in 300 women aged 40 years or younger and is associated with worse outcomes than later onset breast cancer. This study explored novel serum proteins as surrogate markers of prognosis in patients with EOBC.

METHODS

Serum samples from EOBC patients (stages 1-3) were analysed using agnostic high-precision quantitative proteomics. Patients received anthracycline-based chemotherapy. The discovery cohort (n = 399) either had more than 5-year disease-free survival (DFS) (good outcome group, n = 203) or DFS of less than 2 years (poor outcome group, n = 196). Expressed proteins were assessed for differential expression between the two groups. Bioinformatics pathway and network analysis in combination with literature research were used to determine clinically relevant proteins. ELISA analysis against an independent sample set from the Prospective study of Outcomes in Sporadic versus Hereditary breast cancer (POSH) cohort (n = 181) was used to validate expression levels of the selected target. Linear and generalized linear modelling was applied to determine the effect of target markers, body mass index (BMI), lymph node involvement (LN), oestrogen receptor (ER), progesterone receptor and human epidermal growth factor receptor 2 status on patients' outcome.

RESULTS

A total of 5346 unique proteins were analysed (peptide FDR p ≤ 0.05). Of these, 812 were differentially expressed in the good vs poor outcome groups and showed significant enrichment for the insulin signalling (p = 0.01) and the glycolysis/gluconeogenesis (p = 0.01) pathways. These proteins further correlated with interaction networks involving glucose and fatty acid metabolism. A consistent nodal protein to these metabolic networks was resistin (upregulated in the good outcome group, p = 0.009). ELISA validation demonstrated resistin to be upregulated in the good outcome group (p = 0.04), irrespective of BMI and ER status. LN involvement was the only covariate with a significant association with resistin measurements (p = 0.004). An ancillary in-silico observation was the induction of the inflammatory response, leucocyte infiltration, lymphocyte migration and recruitment of phagocytes (p < 0.0001, z-score > 2). Survival analysis showed that resistin overexpression was associated with improved DFS.

CONCLUSIONS

Higher circulating resistin correlated with node-negative patients and longer DFS independent of BMI and ER status in women with EOBC. Overexpression of serum resistin in EOBC may be a surrogate indicator of improved prognosis.

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

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

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

Prostate cancer proteomics: clinically useful protein biomarkers and future perspectives

INTRODUCTION

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

A new panel of pancreatic cancer biomarkers discovered using a mass spectrometry-based pipeline

Background:

Pancreatic carcinoma (PC) is an aggressive malignancy that lacks strategies for early detection. This study aimed to develop a coherent, high-throughput and non-discriminatory pipeline for the novel clinical biomarker discovery of PC.

Methods:

We combined mass spectrometry (MS)-intensive methods such as isobaric tags for relative and absolute quantitation with two-dimensional liquid chromatography-tandem mass spectrometry (iTRAQ-2DLC-MS/MS), 1D-targeted LC-MS/MS, prime MRM (P-MRM) and stable isotope dilution-based MRM (SID-MRM) to analyse serum samples from healthy people (normal control, NC), patients with benign diseases (BD) and PC patients to identify novel biomarkers of PC.

Results:

On the basis of the newly developed pipeline, we identified >1000 proteins, verified 142 differentially expressed proteins and finally targeted four proteins for absolute quantitation in 100 serum samples. The novel biomarker panel of apolipoprotein E (APOE), inter-alpha-trypsin inhibitor heavy chain H3 (ITIH3), apolipoprotein A-I (APOA1), apolipoprotein L1 (APOL1), combining with CA19-9, statistically-significantly improved the sensitivity (95%) and specificity (94.1%), outperforming CA19-9 alone, for the diagnosis of PC.

Conclusions:

We developed a highly efficient pipeline for biomarker discovery, verification and validation, with each step systematically informing the next. A panel of proteins that might be clinically relevant biomarkers for PC was found.

Gender proteomics II. Which proteins in sexual organs

In continuity with the review dealing with differences by gender in non-sexual organs [1], this review collects data on the proteomes of the sexual organs as involved in human reproduction, under both physiological and pathological conditions. It also collects data on the tissue structures and biological fluids typical of pregnancy, such as placenta and amniotic fluid, as well as what may be tested on preimplantation embryos during medically assisted reproduction. The review includes as well mention to all fluids and secretions connected with sex organs and/or reproduction, including sperm and milk, to exemplify two distinctive items in male and female physiology.

SIGNIFICANCE

The causes of infertility are only incompletely understood; the same holds for the causes, and even the early markers, of the most frequent complications of pregnancy. To these established medical challenges, present day practice adds new issues connected with medically assisted reproduction. Omics approaches, including proteomics, are building the database for basic knowledge to possibly translate into clinical testing and eventually into medical routine in this critical branch of health care.

Sex-specific vitamin D effects on blood coagulation among overweight adults

BACKGROUND

Overweight adults are at increased risk for cardiovascular disease and vitamin D deficiency, whereas an important feature to vitamin D physiology is its sex dependence. The aim of this study was to examine whether vitamin D status improvement exerts a sexually dimorphic effect on serum proteins associated with cardiovascular risk among overweight adults.

MATERIALS AND METHODS

Unprocessed serum from age- and BMI-matched men (n = 26) and premenopausal women (n = 24) with vitamin D deficiency and after they achieved sufficiency through a 12-month nutritional intervention was analysed using our previously published depletion-free quantitative proteomics method. Key findings were verified with ELISA. Differentially expressed proteins were subjected to in silico bioinformatics assessment using principal component analysis, hierarchical clustering and Metacore^™ pathway analysis. All mass spectrometry proteomic data are available via ProteomeXchange (identifier: PXD003663).

RESULTS

A total of 282 proteins were differentially expressed after the intervention between men and women (P-value ≤ 0·05), in which the blood coagulation pathway was significantly enriched. In agreement with the proteomics findings, ELISA measurements showed vitamin K-dependent protein C, von Willebrand factor, fibrinogen gamma chain and multimerin-1 proteins, of relevance to blood coagulation, to be differentially affected (P-value ≤ 0·05) between sexes after vitamin D status correction.

CONCLUSIONS

This study identified novel protein-level molecular indicators on the sexually dimorphic effect of vitamin D status correction associated with blood coagulation among overweight adults. These sex-mediated vitamin D effects should be factored in the design and interpretation of vitamin D observational and interventional studies testing cardiometabolic outcomes.