Targeted plasma proteomic analysis uncovers a high-performance biomarker panel for early diagnosis of gastric cancer

BACKGROUND

Gastric cancer (GC) is characterized by high morbidity, high mortality and low early diagnosis rate. Early diagnosis plays a crucial role in radically treating GC. The aim of this study was to identify plasma biomarkers for GC and early GC diagnosis.

METHODS

We quantified 369 protein levels with plasma samples from discovery cohort (n = 88) and validation cohort (n = 50) via high-throughput proximity extension assay (PEA) utilizing the Olink-Explore-384-Cardiometabolic panel. The multi-protein signatures were derived from LASSO and Ridge regression models.

RESULTS

In the discovery cohort, 13 proteins (GDF15, ITIH3, BOC, DPP7, EGFR, AMY2A, CCDC80, CD163, GPNMB, LTBP2, CTSZ, CCL18 and NECTIN2) were identified to distinguish GC (Stage I-IV) and early GC (HGIN-I) groups from control group with AUC of 0.994 and AUC of 0.998, severally. The validation cohort yielded AUC of 0.930 and AUC of 0.818 for GC and early GC, respectively.

CONCLUSIONS

This study identified a multi-protein signature with the potential to benefit clinical GC diagnosis, especially for Asian and early GC patients, which may contribute to the development of a less-invasive, convenient, and efficient early screening tool, promoting early diagnosis and treatment of GC and ultimately improving patient survival.

Recent developments in mass-spectrometry-based targeted proteomics of clinical cancer biomarkers

Routine measurement of cancer biomarkers is performed for early detection, risk classification, and treatment monitoring, among other applications, and has substantially contributed to better clinical outcomes for patients. However, there remains an unmet need for clinically validated assays of cancer protein biomarkers. Protein tumor markers are of particular interest since proteins carry out the majority of biological processes and thus dynamically reflect changes in cancer pathophysiology. Mass spectrometry-based targeted proteomics is a powerful tool for absolute peptide and protein quantification in biological matrices with numerous advantages that make it attractive for clinical applications in oncology. The use of liquid chromatography-tandem mass spectrometry (LC-MS/MS) based methodologies has allowed laboratories to overcome challenges associated with immunoassays that are more widely used for tumor marker measurements. Yet, clinical implementation of targeted proteomics methodologies has so far been limited to a few cancer markers. This is due to numerous challenges associated with paucity of robust validation studies of new biomarkers and the labor-intensive and operationally complex nature of LC-MS/MS workflows. The purpose of this review is to provide an overview of targeted proteomics applications in cancer, workflows used in targeted proteomics, and requirements for clinical validation and implementation of targeted proteomics assays. We will also discuss advantages and challenges of targeted MS-based proteomics assays for clinical cancer biomarker analysis and highlight some recent developments that will positively contribute to the implementation of this technique into clinical laboratories.

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

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

Periostin as a blood biomarker of muscle cell fibrosis, cardiomyopathy and disease severity in myotonic dystrophy type 1

BACKGROUND AND PURPOSE

Myotonic dystrophy type 1 (DM1) is the most common form of adult-onset muscular dystrophy and is caused by an repeat expansion [r(CUG)^exp] located in the 3' untranslated region of the DMPK gene. Symptoms include skeletal and cardiac muscle dysfunction and fibrosis. In DM1, there is a lack of established biomarkers in routine clinical practice. Thus, we aimed to identify a blood biomarker with relevance for DM1-pathophysiology and clinical presentation.

METHODS

We collected fibroblasts from 11, skeletal muscles from 27, and blood samples from 158 DM1 patients. Moreover, serum, cardiac, and skeletal muscle samples from DMSXL mice were included. We employed proteomics, immunostaining, qPCR and ELISA. Periostin level were correlated with CMRI-data available for some patients.

RESULTS

Our studies identified Periostin, a modulator of fibrosis, as a novel biomarker candidate for DM1: proteomic profiling of human fibroblasts and murine skeletal muscles showed significant dysregulation of Periostin. Immunostaining on skeletal and cardiac muscles from DM1 patients and DMSXL mice showed an extracellular increase of Periostin, indicating fibrosis. qPCR studies indicated increased POSTN expression in fibroblasts and muscle. Quantification of Periostin in blood samples from DMSXL mice and two large validation cohorts of DM1 patients showed decreased levels in animals and diseased individuals correlating with repeat expansion and disease severity and presence of cardiac symptoms identified by MRI. Analyses of longitudinal blood samples revealed no correlation with disease progression.

CONCLUSIONS

Periostin might serve as a novel stratification biomarker for DM1 correlating with disease severity, presence of cardiac malfunction and fibrosis.

Proteomics-Based Analysis and Diagnosis of Formalin-Fixed Paraffin-Embedded Amyloidosis Samples

Amyloidosis is a group of rare pathologies characterized by abnormal folding and deposition of susceptible proteins in tissues and organs. Diagnosis of amyloidosis often relies on immunohistochemistry of formalin-fixed paraffin-embedded (FFPE) patient samples; however, dependency on antibodies for protein staining is one of the major pitfalls of this approach, especially for the detection of rare amyloidosis types. In recent years, mass spectrometry-based proteomics has emerged as a promising alternative for adequate detection and amyloid typing, despite the fact that preparing FFPE samples for proteomics remains a challenging task. Major hurdles are removal of formalin-induced protein cross-links and water-insoluble paraffin prior to mass spectrometry analysis. With the recent development of the suspension trapping protocol, enabling the use of high concentrations of SDS, these obstacles can be overcome. In this chapter, we describe the implementation of suspension trapping for FFPE sample processing and its application to analyze human amyloidosis samples, comparing a standard procedure with probe sonication with a more advanced workflow based on ultrasonication.

Clinical Proteomics: Liquid Chromatography-Mass Spectrometry (LC-MS) Purification Systems

Liquid chromatography/mass spectrometry (LC/MS) has become a routine powerful technology in clinical proteomic studies for protein identification, protein characterization, and the discovery of biomarkers. In this chapter, we describe two protocol methods to analyze clinical patient samples using a resin-based depletion column followed by either protein In-Gel enzymatic digestion or protein In-Solution enzymatic digestion using a simple kit-based approach (i.e., using the PreOmics iST sample preparation kit), followed by analysis using one-dimensional reverse-phase chromatography (RPC) or high pH reversed-phase peptide fractionation.

Automated Sample Preparation for Mass Spectrometry-Based Clinical Proteomics

Mass spectrometry (MS)-based proteomics is a rapidly maturing discipline, thus gaining momentum for routine molecular profiling of clinical specimens to improve disease classification, diagnostics, and therapy development. Yet, hurdles need to be overcome to enhance reproducibility in preanalytical sample processing, especially in large, quantity-limited sample cohorts. Therefore, automated sonication and single-pot solid-phase-enhanced sample preparation (autoSP3) was developed as a streamlined workflow that integrates all tasks from tissue lysis and protein extraction, protein cleanup, and proteolysis. It enables the concurrent processing of 96 clinical samples of any type (fresh-frozen or FFPE tissue, liquid biopsies, or cells) on an automated liquid handling platform, which can be directly interfaced to LC-MS for proteome analysis of clinical specimens with high sensitivity, high reproducibility, and short turn-around times.

Systematic evaluation and optimization of protein extraction parameters in diagnostic FFPE specimens

Objectives

Formalin-fixed paraffin-embedded (FFPE) tissue is the standard material for diagnostic pathology but poses relevant hurdles to accurate protein extraction due to cross-linking and chemical alterations. While numerous extraction protocols and chemicals have been described, systematic comparative analyses are limited. Various parameters were thus investigated in their qualitative and quantitative effects on protein extraction (PE) efficacy. Special emphasis was put on preservation of membrane proteins (MP) as key subgroup of functionally relevant proteins.

Methods

Using the example of urothelial carcinoma, FFPE tissue sections were subjected to various deparaffinization, protein extraction and antigen retrieval protocols and buffers as well as different extraction techniques. Performance was measured by protein concentration and western blot analysis of cellular compartment markers as well as liquid chromatography-coupled mass spectrometry (LC–MS).

Results

Commercially available extraction buffers showed reduced extraction of MPs and came at considerably increased costs. On-slide extraction did not improve PE whereas several other preanalytical steps could be simplified. Systematic variation of temperature and exposure duration demonstrated a quantitatively relevant corridor of optimal antigen retrieval.

Conclusions

Preanalytical protein extraction can be optimized at various levels to improve unbiased protein extraction and to reduce time and costs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12014-022-09346-0.

In Vitro Oxygen Glucose Deprivation Model of Ischemic Stroke: A Proteomics-Driven Systems Biological Perspective

Oxygen glucose deprivation (OGD) of brain cells is the commonest in vitro model of ischemic stroke that is used extensively for basic and preclinical stroke research. Protein mass spectrometry is one of the most promising and rapidly evolving technologies in biomedical research. A systems-level understanding of cell-type-specific responses to oxygen and glucose deprivation without systemic influence is a prerequisite to delineate the response of the neurovascular unit following ischemic stroke. In this systematic review, we summarize the proteomics studies done on different OGD models. These studies have followed an expression or interaction proteomics approach. They have been primarily used to understand the cellular pathophysiology of ischemia-reperfusion injury or to assess the efficacy of interventions as potential treatment options. We compile the limitations of OGD model and downstream proteomics experiment. We further show that despite having limitations, several proteins shortlisted as altered in in vitro OGD-proteomics studies showed comparable regulation in ischemic stroke patients. This showcases the translational potential of this approach for therapeutic target and biomarker discovery. We next discuss the approaches that can be adopted for cell-type-specific validation of OGD-proteomics results in the future. Finally, we briefly present the research questions that can be addressed by OGD-proteomics studies using emerging techniques of protein mass spectrometry. We have also created a web resource compiling information from OGD-proteomics studies to facilitate data sharing for community usage. This review intends to encourage preclinical stroke community to adopt a hypothesis-free proteomics approach to understand cell-type-specific responses following ischemic stroke.

Proteomic Profiling of Cerebrospinal Fluid by 16-Plex TMT-Based Mass Spectrometry

Mass spectrometry (MS) has become a mainstream platform for comprehensive profiling of proteome, especially with the improvement of multiplexed tandem mass tag labeling coupled with two-dimensional liquid chromatography and tandem mass spectrometry (TMT-LC/LC-MS/MS). Recently, we have established a robust method for direct profiling of undepleted cerebrospinal fluid (CSF) proteome with the 16-plex TMTpro method, in which we optimized parameters in experimental steps of sample preparation, TMT labeling, LC/LC fractionation, tandem mass spectrometry, and computational data processing. The extensive LC fractionation not only enhances proteome coverage of the CSF but also alleviates ratio distortion of TMT quantification. The crucial quality control steps and improvements specific for the TMT16 analysis are highlighted. More than 3000 proteins can be quantified in a single experiment from 16 different CSF samples. This multiplexed method offers a powerful tool for profiling a variety of complex biofluids samples such as CSF, serum/plasma, and other clinical specimens.

Data-Independent Acquisition Mass Spectrometry-Based Deep Proteome Analysis for Hydrophobic Proteins from Dried Blood Spots Enriched by Sodium Carbonate Precipitation

Dried blood spots (DBS) are widely used for screening molecular profiles, including enzymatic activity. However, hydrophilic proteins present in large amounts in blood inhibit detection of other proteins in DBS by liquid chromatography-mass spectrometry (LC-MS/MS) without preenrichment. Sodium carbonate precipitation (SCP) can concentrate hydrophobic proteins from DBS and effectively remove soluble hydrophilic proteins. Furthermore, SCP combination with data-independent acquisition (DIA) for quantitative LC-MS/MS enhanced the proteome analysis sensitivity and quantification limits. In this protocol, we have described in detail a simple preenrichment method using SCP and a deep proteome analysis method for LC-MS/MS data using DIA.

Implementation of Clinical Phosphoproteomics and Proteomics for Personalized Medicine

The identification of biomarkers for companion diagnostics is revolutionizing the development of treatments tailored to individual patients in different disease areas including cancer. Precision medicine is most frequently based on the detection of genomic markers that correlate with the efficacy of selected targeted therapies. However, since nongenetic mechanisms also contribute to disease biology, there is a considerable interest of using proteomic techniques as additional source of biomarkers to personalize therapies. In this chapter, we describe label-free mass spectrometry methods for proteomic and phosphoproteomic analysis compatible with routine analysis of clinical samples. We also outline bioinformatic pipelines based on statistical learning that use these proteomics datasets as input to quantify kinase activities and predict drug responses in cancer cells.

Proteomics for the study of new biomarkers in Fabry disease: State of the art

Nephropathy represents a major complication of Fabry Disease and its accurate characterization is of paramount importance in predicting the disease progression and assessing the therapeutic responses. The diagnostic process still relies on performing renal biopsy, nevertheless many efforts have been made to discover early reliable biomarkers allowing us to avoid invasive procedures. In this field, proteomics offers a sensitive and fast method leading to an accurate detection of specific pathological proteins and the discovery of diagnostic and prognostic biomarkers that reflect disease progression and facilitate the evaluation of therapeutic responses. Here, we report a review of selected literature focusing on the investigation of several proteomic techniques highlighting their advantages, limitations and future perspectives in their application in the routine study of Fabry Nephropathy.

Ethical principles, opportunities and constraints in clinical proteomics

Recent advances in MS-based proteomics have vastly increased the quality and scope of biological information that can be derived from human samples. These advances have rendered current workflows increasingly applicable in biomedical and clinical contexts. As proteomics is poised to take an important role in the clinic, associated ethical responsibilities increase in tandem with the impact on the health, privacy, and well-being of individuals. Here we conducted and report a systematic literature review of ethical issues in clinical proteomics. We add our perspectives from a background of bioethics, the results of our accompanying paper extracting individual-sensitive results from patient samples, and the literature addressing similar issues in genomics. The spectrum of potential issues ranges from patient re-identification to incidental findings of clinical significance. The latter can be divided into actionable and unactionable findings. Some of these have the potential to be employed in discriminatory or privacy-infringing ways. However, incidental findings may also have great positive potential. A plasma proteome profile, for instance, could inform on the general health or disease status of an individual regardless of the narrow diagnostic question that prompted it. We suggest that early discussion of ethical issues in clinical proteomics is important to ensure that eventual regulations reflect the considered judgment of the community as well as to anticipate opportunities and problems that may arise as the technology matures further.

Novel Proteome Extraction Method Illustrates a Conserved Immunological Signature of MSI-H Colorectal Tumors

Using a simple, environment friendly proteome extraction (TOP), we were able to optimize the analysis of clinical samples. Using our TOP method we analyzed a clinical cohort of microsatellite stable (MSS) and unstable (MSI-H) colorectal carcinoma (CRC). We identified a tumor cell specific, STAT1-centered, immune signature expressed by the MSI-H tumor cells. We then showed that long, but not short, exposure to Interferon-γ induces a similar signature in vitro We identified 10 different temporal protein expression patterns, classifying the Interferon-γ protein temporal regulation in CRC. Our data sheds light on the changes that tumor cells undergo under long-term immunological pressure in vivo, the importance of STAT proteins in specific biological scenarios. The data generated could help find novel clinical biomarkers and therapeutic approaches.

The development and clinical applications of proteomics: an Indian perspective

INTRODUCTION

Proteomic research has been extensively used to identify potential biomarkers or targets for various diseases. Advances in mass spectrometry along with data analytics have led proteomics to become a powerful tool for exploring the critical molecular players associated with diseases, thereby, playing a significant role in the development of proteomic applications for the clinic.

AREAS COVERED

This review presents recent advances in the development and clinical applications of proteomics in India toward understanding various diseases including cancer, metabolic diseases, and reproductive diseases. Keywords combined with 'clinical proteomics in India' 'proteomic research in India' and 'mass spectrometry' were used to search PubMed.

EXPERT OPINION

The past decade has seen a significant increase in research in clinical proteomics in India. This approach has resulted in the development of proteomics-based marker technologies for disease management in the country. The majority of these investigations are still in the discovery phase and efforts have to be made to address the intended clinical use so that the identified potential biomarkers reach the clinic. To move toward this necessity, there is a pressing need to establish some key infrastructure requirements and meaningful collaborations between the clinicians and scientists which will enable more effective solutions to address health issues specific to India.

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

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

Proteomics for hematopoietic stem cell transplantation

Introduction: After the genomic era, the analysis of the proteome has gained increasing importance. Peptides and/or proteins present in tissue or body fluids can depict health and are prone to change during disease, not only in configuration but also in abundance. Early on, high throughput proteome analysis was implemented in the diagnostic of therapy-linked or induced complications arising after allogeneic hematopoietic stem cell transplantation (HSCT). Several proteomic approaches are currently used in the prediction or diagnosis of acute and/or chronic graft-versus-host disease (GvHD).Areas covered: This review will report on two high throughput proteomics technologies used in the clinical setting to date, namely enzyme-linked-immunosorbent assays (ELISA) for key proteins involved in the pathogenesis of acute GvHD and on capillary electrophoresis coupled on-line to mass spectrometry (CE-MS). Here, we summarize the current data and discuss the strength as well as the limitations of each method and compare the usefulness and practicability in the post-HSCT setting for prediction and diagnosis of acute GvHD.Expert commentary: Both technologies are applied in the clinic and have been tested on several hundred patients after HSCT. The data from both technologies may complement each other in diagnosis of GvHD.

Data Imputation in Merged Isobaric Labeling-Based Relative Quantification Datasets

The data-dependent acquisition in mass spectrometry-based proteomics combined with quantitative analysis using isobaric labeling (iTRAQ and TMT) inevitably introduces missing values in proteomic experiments where a number of LC-runs are combined, especially in the growing field of shotgun clinical proteomics, where the protein profiles from the proteomics analysis of several hundred patient samples are compared and correlated to clinical traits such as a specific disease or disease treatment in order to link specific outcomes to one or more proteins. In the context of clinical research it is evident that missing values in such datasets reduce the power of the downstream statistical analysis therefore may hampers the linking of the expression of disease traits to the expression of specific proteins that may be useful for prognostic, diagnostic, or predictive purposes. In our study, we tested three data imputation approaches initially developed for microarray data for the imputation of missing values in datasets that are generated by several runs of shotgun proteomic experiments and where the data were relative protein abundances based on isobaric tags (iTRAQ and TMT). Our conclusion is that imputation methods based on k Nearest Neighbors successfully impute missing values in datasets with up to 50% missing values.

Immune Monitoring of Human Mucosal-Associated Invariant T Cells by Quantitative Proteomics

Molecular phenotypes of mucosal-associated invariant T (MAIT) cells are correlating with individual susceptibilities and outcomes in human diseases. Quantitative proteome strategies can examine such variations in the functional and druggable inventory of MAIT cells comprehensively, but protocols for the support of translational and clinical studies are still rare. Here, we describe a protocol in which MR1-restricted MAIT cells were isolated from blood donations by FACS and are then characterized by quantitative proteomics (iTRAQ-LC-MS/MS) to complement information about their unique effector phenotype and to investigate donor-/patient- or disease-specific variations in protein networks with high precision.

Clinical protein science in translational medicine targeting malignant melanoma

Melanoma of the skin is the sixth most common type of cancer in Europe and accounts for 3.4% of all diagnosed cancers. More alarming is the degree of recurrence that occurs with approximately 20% of patients lethally relapsing following treatment. Malignant melanoma is a highly aggressive skin cancer and metastases rapidly extend to the regional lymph nodes (stage 3) and to distal organs (stage 4). Targeted oncotherapy is one of the standard treatment for progressive stage 4 melanoma, and BRAF inhibitors (e.g. vemurafenib, dabrafenib) combined with MEK inhibitor (e.g. trametinib) can effectively counter BRAFV600E-mutated melanomas. Compared to conventional chemotherapy, targeted BRAFV600E inhibition achieves a significantly higher response rate. After a period of cancer control, however, most responsive patients develop resistance to the therapy and lethal progression. The many underlying factors potentially causing resistance to BRAF inhibitors have been extensively studied. Nevertheless, the remaining unsolved clinical questions necessitate alternative research approaches to address the molecular mechanisms underlying metastatic and treatment-resistant melanoma. In broader terms, proteomics can address clinical questions far beyond the reach of genomics, by measuring, i.e. the relative abundance of protein products, post-translational modifications (PTMs), protein localisation, turnover, protein interactions and protein function. More specifically, proteomic analysis of body fluids and tissues in a given medical and clinical setting can aid in the identification of cancer biomarkers and novel therapeutic targets. Achieving this goal requires the development of a robust and reproducible clinical proteomic platform that encompasses automated biobanking of patient samples, tissue sectioning and histological examination, efficient protein extraction, enzymatic digestion, mass spectrometry-based quantitative protein analysis by label-free or labelling technologies and/or enrichment of peptides with specific PTMs. By combining data from, e.g. phosphoproteomics and acetylomics, the protein expression profiles of different melanoma stages can provide a solid framework for understanding the biology and progression of the disease. When complemented by proteogenomics, customised protein sequence databases generated from patient-specific genomic and transcriptomic data aid in interpreting clinical proteomic biomarker data to provide a deeper and more comprehensive molecular characterisation of cellular functions underlying disease progression. In parallel to a streamlined, patient-centric, clinical proteomic pipeline, mass spectrometry-based imaging can aid in interrogating the spatial distribution of drugs and drug metabolites within tissues at single-cell resolution. These developments are an important advancement in studying drug action and efficacy in vivo and will aid in the development of more effective and safer strategies for the treatment of melanoma. A collaborative effort of gargantuan proportions between academia and healthcare professionals has led to the initiation, establishment and development of a cutting-edge cancer research centre with a specialisation in melanoma and lung cancer. The primary research focus of the European Cancer Moonshot Lund Center is to understand the impact that drugs have on cancer at an individualised and personalised level. Simultaneously, the centre increases awareness of the relentless battle against cancer and attracts global interest in the exceptional research performed at the centre.

Simultaneous Improvement in the Precision, Accuracy, and Robustness of Label-free Proteome Quantification by Optimizing Data Manipulation Chains

The label-free proteome quantification (LFQ) is multistep workflow collectively defined by quantification tools and subsequent data manipulation methods that has been extensively applied in current biomedical, agricultural, and environmental studies. Despite recent advances, in-depth and high-quality quantification remains extremely challenging and requires the optimization of LFQs by comparatively evaluating their performance. However, the evaluation results using different criteria (precision, accuracy, and robustness) vary greatly, and the huge number of potential LFQs becomes one of the bottlenecks in comprehensively optimizing proteome quantification. In this study, a novel strategy, enabling the discovery of the LFQs of simultaneously enhanced performance from thousands of workflows (integrating 18 quantification tools with 3,128 manipulation chains), was therefore proposed. First, the feasibility of achieving simultaneous improvement in the precision, accuracy, and robustness of LFQ was systematically assessed by collectively optimizing its multistep manipulation chains. Second, based on a variety of benchmark datasets acquired by various quantification measurements of different modes of acquisition, this novel strategy successfully identified a number of manipulation chains that simultaneously improved the performance across multiple criteria. Finally, to further enhance proteome quantification and discover the LFQs of optimal performance, an online tool (https://idrblab.org/anpela/) enabling collective performance assessment (from multiple perspectives) of the entire LFQ workflow was developed. This study confirmed the feasibility of achieving simultaneous improvement in precision, accuracy, and robustness. The novel strategy proposed and validated in this study together with the online tool might provide useful guidance for the research field requiring the mass-spectrometry-based LFQ technique.

Proteomic Analysis of Vocal Fold Fibroblasts Exposed to Cigarette Smoke Extract: Exploring the Pathophysiology of Reinke's Edema

Reinke's edema is a smoking-associated, benign, mostly bilateral lesion of the vocal folds leading to difficulties in breathing and voice problems. Pronounced histological changes such as damaged microvessels or immune cell infiltration have been described in the vocal fold connective tissue, the lamina propria Thus, vocal fold fibroblasts, the main cell type of the lamina propria, have been postulated to play a critical role in disease mediation. Yet information about the pathophysiology is still scarce and treatment is only surgical, i.e. symptomatic. To explore the pathophysiology of Reinke's edema, we exposed near-primary human vocal fold fibroblasts to medium conditioned with cigarette smoke extract for 24 h as well as 4 days followed by quantitative mass spectrometry.Proteomic analyses after 24 h revealed that cigarette smoke increased proteins previously described to be involved in oxidative stress responses in other contexts. Correspondingly, gene sets linked to metabolism of xenobiotics and reactive oxygen species were significantly enriched among cigarette smoke-induced proteins. Among the proteins most downregulated by cigarette smoke, we identified fibrillar collagens COL1A1 and COL1A2; this reduction was validated by complementary methods. Further, we found a significant increase of UDP-glucose 6-dehydrogenase, generating a building block for biosynthesis of hyaluronan, another crucial component of the vocal fold lamina propria In line with this result, hyaluronan levels were significantly increased because of cigarette smoke exposure. Long term treatment of 4 days did not lead to significant changes.The current findings corroborate previous studies but also reveal new insights in possible disease mechanisms of Reinke's edema. We postulate that changes in the composition of the vocal folds' extracellular matrix -reduction of collagen fibrils, increase of hyaluronan- may lead to the clinical findings. This might ease the identification of better, disease-specific treatment options.

Analysis of 1508 Plasma Samples by Capillary-Flow Data-Independent Acquisition Profiles Proteomics of Weight Loss and Maintenance

Comprehensive, high throughput analysis of the plasma proteome has the potential to enable holistic analysis of the health state of an individual. Based on our own experience and the evaluation of recent large-scale plasma mass spectrometry (MS) based proteomic studies, we identified two outstanding challenges: slow and delicate nano-flow liquid chromatography (LC) and irreproducibility of identification of data-dependent acquisition (DDA). We determined an optimal solution reducing these limitations with robust capillary-flow data-independent acquisition (DIA) MS. This platform can measure 31 plasma proteomes per day. Using this setup, we acquired a large-scale plasma study of the diet, obesity and genes dietary (DiOGenes) comprising 1508 samples. Proving the robustness, the complete acquisition was achieved on a single analytical column. Totally, 565 proteins (459 identified with two or more peptide sequences) were profiled with 74% data set completeness. On average 408 proteins (5246 peptides) were identified per acquisition (319 proteins in 90% of all acquisitions). The workflow reproducibility was assessed using 34 quality control pools acquired at regular intervals, resulting in 92% data set completeness with CVs for protein measurements of 10.9%.The profiles of 20 apolipoproteins could be profiled revealing distinct changes. The weight loss and weight maintenance resulted in sustained effects on low-grade inflammation, as well as steroid hormone and lipid metabolism, indicating beneficial effects. Comparison to other large-scale plasma weight loss studies demonstrated high robustness and quality of biomarker candidates identified. Tracking of nonenzymatic glycation indicated a delayed, slight reduction of glycation in the weight maintenance phase. Using stable-isotope-references, we could directly and absolutely quantify 60 proteins in the DIA.In conclusion, we present herein the first large-scale plasma DIA study and one of the largest clinical research proteomic studies to date. Application of this fast and robust workflow has great potential to advance biomarker discovery in plasma.

Identification of Candidate Plasma Protein Biomarkers for Cervical Cancer Using the Multiplex Proximity Extension Assay

Human papillomavirus (HPV) is recommended as the primary test in cervical cancer screening, with co-testing by cytology for HPV-positive women to identify cervical lesions. Cytology has low sensitivity and there is a need to identify biomarkers that could identify dysplasia that are likely to progress to cancer. We searched for plasma proteins that could identify women with cervical cancer using the multiplex proximity extension assay (PEA). The abundance of 100 proteins were measured in plasma collected at the time of diagnosis of patients with invasive cervical cancer and in population controls using the Olink Multiplex panels CVD II, INF I, and ONC II. Eighty proteins showed increased levels in cases compared with controls. We identified a signature of 11 proteins (PTX3, ITGB1BP2, AXIN1, STAMPB, SRC, SIRT2, 4E-BP1, PAPPA, HB-EGF, NEMO and IL27) that distinguished cases and controls with a sensitivity of 0.96 at a specificity of 1.0. This signature was evaluated in a prospective replication cohort with samples collected before, at or after diagnosis and achieved a sensitivity of 0.78 and a specificity 0.56 separating samples collected at the time of diagnosis of invasive cancer from samples collected prior to diagnosis. No difference in abundance was seen between samples collected prior to diagnosis or after treatment as compared with population controls, indicating that this protein signature is mainly informative close to time of diagnosis. Further studies are needed to determine the optimal window in time prior to diagnosis for these biomarker candidates.

Detecting post-translational modification signatures as potential biomarkers in clinical mass spectrometry

INTRODUCTION

Numerous diseases are caused by changes in post-translational modifications (PTMs). Therefore, the number of clinical proteomics studies that include the analysis of PTMs is increasing. Combining complementary information-for example changes in protein abundance, PTM levels, with the genome and transcriptome (proteogenomics)-holds great promise for discovering important drivers and markers of disease, as variations in copy number, expression levels, or mutations without spatial/functional/isoform information is often insufficient or even misleading. Areas covered: We discuss general considerations, requirements, pitfalls, and future perspectives in applying PTM-centric proteomics to clinical samples. This includes samples obtained from a human subject, for instance (i) bodily fluids such as plasma, urine, or cerebrospinal fluid, (ii) primary cells such as reproductive cells, blood cells, and (iii) tissue samples/biopsies. Expert commentary: PTM-centric discovery proteomics can substantially contribute to the understanding of disease mechanisms by identifying signatures with potential diagnostic or even therapeutic relevance but may require coordinated efforts of interdisciplinary and eventually multi-national consortia, such as initiated in the cancer moonshot program. Additionally, robust and standardized mass spectrometry (MS) assays-particularly targeted MS, MALDI imaging, and immuno-MALDI-may be transferred to the clinic to improve patient stratification for precision medicine, and guide therapies.

Stable-protein Pair Analysis as A Novel Strategy to Identify Proteomic Signatures: Application To Seminal Plasma From Infertile Patients

Our aim was to define seminal plasma proteome signatures of infertile patients categorized according to their seminal parameters using TMT-LC-MS/MS. To that extent, quantitative proteomic data was analyzed following two complementary strategies: (1) the conventional approach based on standard statistical analyses of relative protein quantification values; and (2) a novel strategy focused on establishing stable-protein pairs. By conventional analyses, the abundance of some seminal plasma proteins was found to be positively correlated with sperm concentration. However, this correlation was not found for all the peptides within a specific protein, bringing to light the high heterogeneity existing in the seminal plasma proteome because of both the proteolytic fragments and/or the post-translational modifications. This issue was overcome by conducting the novel stable-protein pairs analysis proposed herein. A total of 182 correlations comprising 24 different proteins were identified in the normozoospermic-control population, whereas this proportion was drastically reduced in infertile patients with altered seminal parameters (18 in patients with reduced sperm motility, 0 in patients with low sperm concentration and 3 in patients with no sperm in the ejaculate). These results suggest the existence of multiple etiologies causing the same alteration in seminal parameters. Additionally, the repetition of the stable-protein pair analysis in the control group by adding the data from a single patient at a time enabled to identify alterations in the stable-protein pairs profile of individual patients with altered seminal parameters. These results suggest potential underlying pathogenic mechanisms in individual infertile patients, and might open up a window to its application in the personalized diagnostic of male infertility.

Characterization of the Sperm Proteome and Reproductive Outcomes with in Vitro, Fertilization after a Reduction in Male Ejaculatory Abstinence Period

Semen samples from men after a short ejaculatory abstinence show improved sperm quality and result in increased pregnancy rates, but the underlying mechanisms remain unclear. Herein, we report that ejaculates from short (1-3 h) compared with long (3-7 days) periods of abstinence showed increases in motile sperm count, sperm vitality, normal sperm morphology, acrosome reaction capacity, total antioxidant capacity, sperm mitochondrial membrane potential, high DNA stainability, and a decrease in the sperm DNA fragmentation index (p, < 0.05). Sperm proteomic analysis showed 322 differentially expressed proteins (minimal fold change of ±1.5 or greater and p, < 0.05), with 224 upregulated and 98 downregulated. These differentially expressed proteins are profoundly involved in specific cellular processes, such as motility and capacitation, oxidative stress, and metabolism. Interestingly, protein trimethyllysine modification was increased, and butyryllysine, propionyllysine, and malonyllysine modifications were decreased in ejaculates from a short versus, long abstinence (p, < 0.05). Finally, the rates of implantation, clinical pregnancy, and live births from in vitro, fertilization treatments were significantly increased in semen samples after a short abstinence. Our study provides preliminary mechanistic insights into improved sperm quality and pregnancy outcomes associated with spermatozoa retrieved after a short ejaculatory abstinence.

Changes in Synaptic Proteins Precede Neurodegeneration Markers in Preclinical Alzheimer's Disease Cerebrospinal Fluid

A biomarker of synapse loss, an early event in Alzheimer's disease (AD) pathophysiology that precedes neuronal death and symptom onset, would be a much-needed prognostic biomarker. With direct access to the brain interstitial fluid, the cerebrospinal fluid (CSF) is a potential source of synapse-derived proteins. In this study, we aimed to identify and validate novel CSF biomarkers of synapse loss in AD. Discovery: Combining shotgun proteomics of the CSF with an exhaustive search of the literature and public databases, we identified 251 synaptic proteins, from which we selected 22 for further study. Verification: Twelve proteins were discarded because of poor detection by Selected Reaction Monitoring (SRM). We confirmed the specific expression of 9 of the remaining proteins (Calsynytenin-1, GluR2, GluR4, Neurexin-2A, Neurexin-3A, Neuroligin-2, Syntaxin-1B, Thy-1, Vamp-2) at the human synapse using Array Tomography microscopy and biochemical fractionation methods. Exploration: Using SRM, we monitored these 9 synaptic proteins (20 peptides) in a cohort of CSF from cognitively normal controls and subjects in the pre-clinical and clinical AD stages (n = 80). Compared with controls, peptides from 8 proteins were elevated 1.3 to 1.6-fold (p < 0.04) in prodromal AD patients. Validation: Elevated levels of a GluR4 peptide at the prodromal stage were replicated (1.3-fold, p = 0.04) in an independent cohort (n = 60). Moreover, 7 proteins were reduced at preclinical stage 1 (0.6 to 0.8-fold, p < 0.04), a finding that was replicated (0.7 to 0.8-fold, p < 0.05) for 6 proteins in a third cohort (n = 38). In a cross-cohort meta-analysis, 6 synaptic proteins (Calsyntenin-1, GluR4, Neurexin-2A, Neurexin-3A, Syntaxin-1B and Thy-1) were reduced 0.8-fold (p < 0.05) in preclinical AD, changes that precede clinical symptoms and CSF markers of neurodegeneration. Therefore, these proteins could have clinical value for assessing disease progression, especially in preclinical stages of AD.

Proteomic Maps of Human Gastrointestinal Stromal Tumor Subgroups

Gastrointestinal stromal tumor (GIST) is a common sarcoma of gastrointestinal tract (GIT) with high metastatic and recurrence rates, but the proteomic features are still less understood. Here we performed systematic quantitative proteome profiling of GIST from 13 patients classified into very low/low, intermediate and high risk subgroups. An extended cohort of GIST (n = 131) was used for immunohistochemical validation of proteins of interest. In total, 9177 proteins were quantified, covering 55.9% of the GIT transcriptome from The Human Protein Altas. Out of the 9177 quantified proteins, 4930 proteins were observed in all 13 cases with 517 upregulated and 187 downregulated proteins in tumorous tissues independent of risk stage. Pathway analysis showed that the downregulated proteins were mostly enriched in metabolic pathway, whereas the upregulated proteins mainly belonged to spliceosome pathway. In addition, 131 proteins showed differentially expressed patterns among GIST subgroups with statistical significance. The 13 GIST cases were classified into 3 subgroups perfectly based on the expression of these proteins. The intensive comparison of molecular phenotypes and possible functions of quantified oncoproteins, tumor suppressors, phosphatases and kinases between GIST subgroups was carried out. Immunohistochemical analysis of the phosphatase PTPN1 (n = 117) revealed that the GIST patients with high PTPN1 expression had low chances of developing metastasis. Collectively, this work provides valuable information for understanding the inherent biology and evolution of GIST.

Correlation between chronic venous ulcer exudate proteins and clinical profile: A cross-sectional study

Chronic venous ulcers affect the quality of life of patients around the world. The aims of this study were to identify the proteins expressed in chronic venous ulcer exudates, to categorize them according to their roles and to correlate them with the clinical and epidemiological aspects of the disease. The study population consisted of 37 ulcers from 28 patients, and the inflammatory exudates of these thirty-seven ulcers were subjected to tryptic digestion and mass spectrometry analysis. Twenty-three patients were female (62.2%), and five (37.8%) were male. The patients had a mean age of 70 (±10.1) years. Of the patients, 73% adhered to compression and rest, 81.1% reported a history of primary varices, 54.1% reported a history of systemic arterial hypertension, 54.1% reported a history of devitalized tissue in the wound bed and 64.9% reported ulcers with more than ten years of evolution. Seventy-six proteins were identified, and they were grouped according to their primary role in the healing process. Eight correlations between clinical and epidemiological data and protein expression were noteworthy: diabetes mellitus vs. Ig gamma-2 and apolipoprotein-A1 and albumin; congestive heart failure vs. Ig lambda-2; colonization vs. actin; compressive therapy vs. Ig kappa; systemic arterial hypertension vs. alpha-2-macroglobulin and apolipoprotein-A1; area of ulcer vs. apolipoprotein-A1; race vs. heavy chain Ig and Ig γ-1 chain; age and race vs. Ig γ-1 chain. These associations may help to elucidate the prognosis and chronicity of chronic venous ulcers based on secreted proteins.

A Novel LC System Embeds Analytes in Pre-formed Gradients for Rapid, Ultra-robust Proteomics

Because of low throughput and limited robustness, nano-scale liquid chromatography has been a bottleneck for advancing proteomics in biomedical research. Here, we developed and evaluated two new LC concepts—“pre-formed gradients” and “offset gradients for peptide re-focusing”—that are both implemented in the Evosep One instrument. We evaluated robustness with more than 2000 HeLa runs, demonstrated absence of cross-contamination with crude plasma samples, high proteome coverage by fractionated HeLa and routinely measuring more than 5000 proteins/sample in just 21 minutes.

To further integrate mass spectrometry (MS)-based proteomics into biomedical research and especially into clinical settings, high throughput and robustness are essential requirements. They are largely met in high-flow rate chromatographic systems for small molecules but these are not sufficiently sensitive for proteomics applications. Here we describe a new concept that delivers on these requirements while maintaining the sensitivity of current nano-flow LC systems. Low-pressure pumps elute the sample from a disposable trap column, simultaneously forming a chromatographic gradient that is stored in a long storage loop. An auxiliary gradient creates an offset, ensuring the re-focusing of the peptides before the separation on the analytical column by a single high-pressure pump. This simplified design enables robust operation over thousands of sample injections. Furthermore, the steps between injections are performed in parallel, reducing overhead time to a few minutes and allowing analysis of more than 200 samples per day. From fractionated HeLa cell lysates, deep proteomes covering more than 130,000 sequence unique peptides and close to 10,000 proteins were rapidly acquired. Using this data as a library, we demonstrate quantitation of 5200 proteins in only 21 min. Thus, the new system - termed Evosep One - analyzes samples in an extremely robust and high throughput manner, without sacrificing in depth proteomics coverage.

Preparation and Immunoaffinity Depletion of Fresh Frozen Tissue Homogenates for Mass Spectrometry-Based Proteomics in the Context of Drug Target/Biomarker Discovery

The discovery of novel drug targets and biomarkers via mass spectrometry (MS)-based proteomic analysis of clinical specimens has proven to be challenging. The wide dynamic range of protein concentration in clinical specimens and the high background/noise originating from highly abundant proteins in tissue homogenates and serum/plasma encompass two major analytical obstacles. Immunoaffinity depletion of highly abundant blood-derived proteins from serum/plasma is a well-established approach adopted by numerous researchers; however, the utilization of this technique for immunodepletion of tissue homogenates obtained from fresh frozen clinical specimens is lacking. We first developed immunoaffinity depletion of highly abundant blood-derived proteins from tissue homogenates, using renal cell carcinoma as a model disease, and followed this study by applying it to different tissue types. Tissue homogenate immunoaffinity depletion of highly abundant proteins may be equally important as is the recognized need for depletion of serum/plasma, enabling more sensitive MS-based discovery of novel drug targets, and/or clinical biomarkers from complex clinical samples. Provided is a detailed protocol designed to guide the researcher through the preparation and immunoaffinity depletion of fresh frozen tissue homogenates for two-dimensional liquid chromatography, tandem mass spectrometry (2D-LC-MS/MS)-based molecular profiling of tissue specimens in the context of drug target and/or biomarker discovery.

Identification of multiple proteoforms biomarkers on clinical samples by routine Top-Down approaches

Top-Down approaches have an extremely high biological relevance, especially when it comes to biomarker discovery, but the necessary pre-fractionation constraints are not easily compatible with the robustness requirements and the size of clinical sample cohorts. We have demonstrated that intact protein profiling studies could be run on UHR-Q-ToF with limited pre-fractionation (Schmit et al., 2017) [1]. The dataset presented herein is an extension of this research. Proteoforms known to play a role in the pathophysiology process of Alzheimer's disease were identified as candidate biomarkers. In this article, mass spectrometry performance of these candidates are demonstrated.

Direct Assessment of Plasma/Serum Sample Quality for Proteomics Biomarker Investigation

Blood proteome analysis for biomarker discovery represents one of the most challenging tasks to be achieved through clinical proteomics due to the sample complexity, such as the extreme heterogeneity of proteins in very dynamic concentrations, and to the observation of proper sampling and storage conditions. Quantitative and qualitative proteomics profiling of plasma and serum could be useful both for the early detection of diseases and for the evaluation of pathological status. Two main sources of variability can affect the precision and accuracy of the quantitative experiments designed for biomarker discovery and validation. These sources are divided into two categories, pre-analytical and analytical, and are often ignored; however, they can contribute to consistent errors and misunderstanding in biomarker research. In this chapter, we review critical pre-analytical and analytical variables that can influence quantitative proteomics. According to guidelines accepted by proteomics community, we propose some recommendations and strategies for a proper proteomics analysis addressed to biomarker studies.

Clinical proteomic analysis of scrub typhus infection

Background

Scrub typhus is an acute and febrile infectious disease caused by the Gram-negative α-proteobacterium Orientia tsutsugamushi from the family Rickettsiaceae that is widely distributed in Northern, Southern and Eastern Asia. In the present study, we analysed the serum proteome of scrub typhus patients to investigate specific clinical protein patterns in an attempt to explain pathophysiology and discover potential biomarkers of infection.

Methods

Serum samples were collected from three patients (before and after treatment with antibiotics) and three healthy subjects. One-dimensional sodium dodecyl sulphate–polyacrylamide gel electrophoresis followed by liquid chromatography-tandem mass spectrometry was performed to identify differentially abundant proteins using quantitative proteomic approaches. Bioinformatic analysis was then performed using Ingenuity Pathway Analysis.

Results

Proteomic analysis identified 236 serum proteins, of which 32 were differentially expressed in normal subjects, naive scrub typhus patients and patients treated with antibiotics. Comparative bioinformatic analysis of the identified proteins revealed up-regulation of proteins involved in immune responses, especially complement system, following infection with O. tsutsugamushi, and normal expression was largely rescued by antibiotic treatment.

Conclusions

This is the first proteomic study of clinical serum samples from scrub typhus patients. Proteomic analysis identified changes in protein expression upon infection with O. tsutsugamushi and following antibiotic treatment. Our results provide valuable information for further investigation of scrub typhus therapy and diagnosis.

Electronic supplementary material

The online version of this article (10.1186/s12014-018-9181-5) contains supplementary material, which is available to authorized users.

Introduction to Clinical Proteomics

Within the context of this section, biomarkers are defined as a panel of proteins and peptides that are predictive of the risk for developing a pathological condition. It is important to note here that the use of the descriptor 'panel' is purposeful in that single "biomarkers" are rarely sufficient to permit accurate prediction of a pathological condition. More specifically, the primary application of a biomarker panel is that it serves as a molecular indicator of the severity of a disease or its early response to treatment. In this way, biomarkers enable the application of precision medicine, an approach that tailors specific interventions to those individuals that would most benefit. For a recent comprehensive review of the proteomic-based biomarker development process with a focus on bladder cancer, the reader is directed to Frantzi et al. [Clin Transl Med 3:7, 2014], or a special issue with multiple reviews [Stuhler and Poschmann, Biochim Biophys Acta Proteins Proteomics 1844:859-1058, Elsevier, B V, 2014].

An iTRAQ-based proteomic analysis reveals dysregulation of neocortical synaptopodin in Lewy body dementias

Lewy body dementias are the second most common cause of neurodegenerative dementia in the elderly after Alzheimer's disease (AD). The two clinical subgroups of Lewy body dementias, namely, dementia with Lewy bodies (DLB) and Parkinson's disease dementia (PDD), are differentiated by the chronology of cognitive symptoms relative to parkinsonism. At present, there remains a debate on whether DLB and PDD are separate disease entities, or fall within the same spectrum of Lewy body dementias. In this study, we compared the detergent-soluble proteome via an 8-plex isobaric tag for relative and absolute quantitation (iTRAQ) analysis of pooled lysates from the prefrontal cortex (BA9) of DLB (n = 19) and PDD (n = 21) patients matched a priori for amyloid (total Aβ42) burden, semi-quantitative scores for Lewy bodies and neurofibrillary tangles together with age-matched control (n = 21) subjects. A total of 1914 proteins were confidently identified by iTRAQ (false discovery rate = 0%). None of the proteins showed a significant yet opposite regulation in between DLB and PDD when compared to aged controls in the proteomic data set as well as following immunoblot analysis of the pooled and individual lysates involving all 61 subjects. The postsynaptic protein, synaptopodin (SYNPO) was significantly down-regulated in both DLB and PDD subgroups, suggesting a defective synaptic transmission in the demented patients. In conclusion, the largely similar proteome of DLB and PDD matched for amyloid burden suggests that variations in concomitant AD-related pathology, abnormal post-translational modifications or protein-protein interactions, defective intracellular trafficking or misfolding of proteins could play a part in driving the clinically observed differences between these two subgroups of Lewy body dementias. This further indicates that amyloid-targeting therapeutic strategies may show different efficacies in DLB versus PDD.

WITHDRAWN: Quantitative mass spectrometry analysis of PD-L1 protein expression, N-glycosylation and expression stoichiometry with PD-1 and PD-L2 in human melanoma

This article has been withdrawn by the authors. We discovered an error after this manuscript was published as a Paper in Press. Specifically, we learned that the structures of glycans presented for the PD-L1 peptide were drawn and labeled incorrectly. We wish to withdraw this article and submit a corrected version for review.

Identification of differentially expressed proteins in retinoblastoma tumors using mass spectrometry-based comparative proteomic approach

In India, retinoblastoma is among the top five childhood cancers. Children mostly present with extraocular extension and high risk features that results in unsatisfactory treatment and low survival rate. In addition, lack of potential therapeutic and prognostic targets is another challenge in the management of retinoblastoma. We studied comparative proteome of retinoblastoma patients (HPV positive and negative (n=4 each) and controls (n=4), in order to identify potential retinoblastoma-specific protein targets. 2D-DIGE coupled MALDI-TOF/TOF mass spectrometry identified 39 unique proteins. Highly deregulated proteins were GFAP,RBP3,APOA1,CRYAA,CRABP1,SAG and TF. Gene ontology (Panther 7.0) revealed majority of proteins to be associated with metabolic processes (26%) and catalytic activity (38%). 8 proteins were significantly upregulated in HPV positive vis-a-vis HPV negative cases. Patient group exhibited 12 upregulated and 18 downregulated proteins compared to controls. Pathway and network analysis (IPA software) revealed CTNNB1 as most significantly regulated signalling pathway in HPV positive than HPV negative retinoblastoma. The trends in transcriptional change of 9 genes were consistent with those at proteomic level. The Western blot analysis confirmed the expression pattern of RBP3,GFAP and CRABP1. We suggest GFAP,RBP3,CRABP1,CRYAAA,APOA1 and SAG as prospective targets that could further be explored as potential candidates in therapy and may further assist in studying the disease mechanism.

SIGNIFICANCE

In this study we evaluated tumor tissue specimens from retinoblastoma patients and identified 39 differentially regulated proteins compared to healthy retina. From these, we propose RBP3, CRABP1, GFAP, CRYAA, APOA1 and SAG as promising proteomic signatures that could further be explored as efficient prognostic and therapeutic targets in retinoblastoma. The present study is not only a contribution to the ongoing endeavour for the discovery of proteomic signatures in retinoblastoma, but, may also act as a starting point for future studies aimed at uncovering novel targets for further therapeutic interventions and improving patient outcomes.

Clinical Proteomics: Liquid Chromatography-Mass Spectrometry (LC-MS) Purification Systems

Liquid chromatography-mass spectrometry (LC-MS) has become a routine powerful technology in clinical proteomic studies for protein identification, protein characterization and the discovery of biomarkers. In this chapter, we describe two protocol methods to analyze clinical patient samples using a resin based depletion column followed by either protein In-gel enzymatic digestion or protein in-solution enzymatic digestion and then analysis by one-dimensional reverse-phase chromatography or two-dimensional strong cation exchange (SCX)-reverse-phase chromatography (RPC).

Cardiovascular proteomics in the era of big data: experimental and computational advances

Proteomics plays an increasingly important role in our quest to understand cardiovascular biology. Fueled by analytical and computational advances in the past decade, proteomics applications can now go beyond merely inventorying protein species, and address sophisticated questions on cardiac physiology. The advent of massive mass spectrometry datasets has in turn led to increasing intersection between proteomics and big data science. Here we review new frontiers in technological developments and their applications to cardiovascular medicine. The impact of big data science on cardiovascular proteomics investigations and translation to medicine is highlighted.

Proteomics in India: the clinical aspect

Proteomics has emerged as a highly promising bioanalytical technique in various aspects of applied biological research. In Indian academia, proteomics research has grown remarkably over the last decade. It is being extensively used for both basic as well as translation research in the areas of infectious and immune disorders, reproductive disorders, cardiovascular diseases, diabetes, eye disorders, human cancers and hematological disorders. Recently, some seminal works on clinical proteomics have been reported from several laboratories across India. This review aims to shed light on the increasing use of proteomics in India in a variety of biological conditions. It also highlights that India has the expertise and infrastructure needed for pursuing proteomics research in the country and to participate in global initiatives. Research in clinical proteomics is gradually picking up pace in India and its future seems very bright.

Clinical proteomics in cancer: Where we are

Proteomics has emerged as a promising field in the post-genomic era. Notwithstanding the great advances provided by gene expression analysis in cancer, the lack of a correlation between gene expression and protein levels has highlighted the need for a proteomic focus on cancer. Although the increasing knowledge regarding cancer biology, a reliable marker to improve diagnosis, prognosis and treatment for cancer patients is not a reality at present. In this review, we address the main considerations regarding proteomics-based studies and their clinical applications on cancer research, highlighting some considerations related to strengths and limitations of proteomics-based studies and its application to clinical practice.

Proteomic analysis of differentially expressed proteins in vitreous humor of patients with retinoblastoma using iTRAQ-coupled ESI-MS/MS approach

There is close proximity of vitreous humor with the tumor bulk in eyes with retinoblastoma. This renders vitreous humor a promising source to evaluate disease-specific protein targets in retinoblastoma. We studied the differential proteome of vitreous fluid in retinoblastoma tumors (n = 4) as compared to controls (n = 4). The vitreous humor was depleted off the high abundant fraction using MARS-6 affinity column. Subsequently, the tryptic peptides were derivatised with iTRAQ labels. The labelled peptides were pooled and subjected to fractionation using bRPLC. This was followed by protein identification and quantification using electrospray ionisation mass spectrometry (ESI-MS/MS) approach. The identified proteins were subjected to bioinformatics analysis utilizing PANTHER 7.0 and IPA software. Four hundred and thirty-one non-redundant (362 upregulated and 69 downregulated) proteins (≥2 unique peptides, ± 1.5 folds, p < 0.05) were identified. The majority of the proteins were cytoplasmic (40 %), majorly involved in catalytic (32.7 %) and binding activities (26.3 %). Highly deregulated proteins included MMP2, TNC, CD44, SUZ12 and CRABP1. The protein expression of GFAP, CRABP1, MMP2 and TNC was validated by western blotting. Pathway and network analyses revealed p38MAPK and Akt signalling to be the most significantly regulated pathways in retinoblastoma. This is the first report of differential vitreous proteome of retinoblastoma and highlights novel protein targets, such as MMP2, TNC and CRABP1. Further investigations into unravelling the biological role of the proteins and their prospects of being utilised as potential candidates in therapeutics are warranted.

Platelet clinical proteomics: Facts, challenges, and future perspectives

In recent years, proteomics has been applied to platelet clinical research. Platelets are small enucleated cells that play a fundamental role in hemostasis. In a pathological context, unwanted platelet activation is related to various diseases, primarily thrombosis, but also cancer metastasis, inflammation, immunity, and neurodegenerative diseases. The absence of a nucleus is one of the reasons why proteomics can be considered an ideal analytical tool for platelet research. Indeed, platelet proteomics has allowed the identification of many novel signaling proteins and receptors, several of which are being pursued as potential therapeutic targets. Encouraged by this success, several research groups have recently initiated clinical proteomics studies covering diseases where platelets are involved in some way, such as coronary artery disease, storage pool diseases, uremia, cystic fibrosis, and Alzheimer disease. The goal was to identify platelet biomarkers and drug targets that can help to improve the treatment/diagnosis of the disease and provide further mechanistic evidences of the role platelets play in the pathology. The present article will comment on the recent progress of clinical proteomics in the context of platelet research, challenges, and perspectives for the future ahead.

Clinical proteomics-driven precision medicine for targeted cancer therapy: current overview and future perspectives

Cancer is a common disease that is a leading cause of death worldwide. Currently, early detection and novel therapeutic strategies are urgently needed for more effective management of cancer. Importantly, protein profiling using clinical proteomic strategies, with spectacular sensitivity and precision, offer excellent promise for the identification of potential biomarkers that would direct the development of targeted therapeutic anticancer drugs for precision medicine. In particular, clinical sample sources, including tumor tissues and body fluids (blood, feces, urine and saliva), have been widely investigated using modern high-throughput mass spectrometry-based proteomic approaches combined with bioinformatic analysis, to pursue the possibilities of precision medicine for targeted cancer therapy. Discussed in this review are the current advantages and limitations of clinical proteomics, the available strategies of clinical proteomics for the management of precision medicine, as well as the challenges and future perspectives of clinical proteomics-driven precision medicine for targeted cancer therapy.

Systemic amyloidoses and proteomics: The state of the art

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Proteomics is an established approach for diagnostic amyloid typing.

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Mass spectrometry-based methods to analyze amyloid precursors have been developed.

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Proteomic studies are ongoing to identify novel biomarkers and clarify disease mechanisms.

Systemic amyloidoses are caused by misfolding-prone proteins that polymerize in tissues, causing organ dysfunction. Since proteins are etiological agents of these diseases, proteomics was soon recognized as a privileged instrument for their investigation. Mass spectrometry-based proteomics has acquired a fundamental role in management of systemic amyloidoses, being now considered a gold standard approach for amyloid typing. In parallel, approaches for analyzing circulating amyloid precursors have been developed. Moreover, differential and functional proteomics hold promise for identifying novel biomarkers and clarifying disease mechanisms. This review discusses recent proteomics achievements in systemic amyloidoses, providing a perspective on its present and future applications.

Applications of targeted proteomics in systems biology and translational medicine

Biological systems are composed of numerous components of which proteins are of particularly high functional significance. Network models are useful abstractions for studying these components in context. Network representations display molecules as nodes and their interactions as edges. Because they are difficult to directly measure, functional edges are frequently inferred from suitably structured datasets consisting of the accurate and consistent quantification of network nodes under a multitude of perturbed conditions. For the precise quantification of a finite list of proteins across a wide range of samples, targeted proteomics exemplified by selected/multiple reaction monitoring (SRM, MRM) mass spectrometry has proven useful and has been applied to a variety of questions in systems biology and clinical studies. Here, we survey the literature of studies using SRM-MS in systems biology and clinical proteomics. Systems biology studies frequently examine fundamental questions in network biology, whereas clinical studies frequently focus on biomarker discovery and validation in a variety of diseases including cardiovascular disease and cancer. Targeted proteomics promises to advance our understanding of biological networks and the phenotypic significance of specific network states and to advance biomarkers into clinical use.