GPDE: A biological proteomic database for biomarker discovery and evaluation

Clinical proteomics faces extremely complex and variable data. Here, we present an updated version of the Griss Proteomics Database Engine (GPDE): A free biological proteomic database specifically designed for clinical proteomics and biomarker discovery (http://gpde.sourceforge.net). It combines experiments based on investigated cell types thereby supporting customizable biological meta-analyses. Through the new features described here, the GPDE now became a powerful yet easy-to-use tool to support the fast identification and reliable evaluation of biomarker candidates.     

High-performance proteomics as a tool in biomarker discovery

Biomarkers allowing early detection of disease or therapy control have a huge influence in curing a disease. A wide variety of methods were applied to find new biomarkers. In contrast to methods focused on DNA or mRNA techniques, approaches considering proteins as potential biomarker candidates have the advantage that proteins are more diverse than DNA or RNA and are more reflective of a biological system. Here, we present an approach for the identification of new biomarkers relying on our experience from the past 10 years of proteomics, outlining a concept of "high-performance proteomics" This approach is based on quantitative proteome analysis using a sufficient number of clinical samples and statistical validation of proteomics data by independent methods, such as Western blot analysis or immunohistochemistry.     

Recent advances in atherosclerosis-based proteomics: new biomarkers and a future perspective

Vascular proteomics is providing two main types of data: proteins that actively participate in vascular pathophysiological processes and novel protein candidates that can potentially serve as useful clinical biomarkers. Although both types of proteins can be identified by similar proteomic strategies and methods, it is important to clearly distinguish biomarkers from mediators of disease. A particular protein, or group of proteins, may participate in a pathogenic process but not serve as an effective biomarker. Alternatively, a useful biomarker may not mediate pathogenic pathways associated with disease (i.e., C-reactive protein). To date, there are no clear successful examples in which discovery proteomics has led to a novel useful clinical biomarker in cardiovascular diseases. Nevertheless, new sources of biomarkers are being explored (i.e., secretomes, circulating cells, exosomes and microparticles), an increasing number of novel proteins involved in atherogenesis are constantly described, and new technologies and analytical strategies (i.e., quantitative proteomics) are being developed to access low abundant proteins. Therefore, this presages a new era of discovery and a further step in the practical application to diagnosis, prognosis and early action by medical treatment of cardiovascular diseases.     

Multiplex targeted proteomic assay for biomarker detection in plasma: a pancreatic cancer biomarker case study

Biomarkers are most frequently proteins that are measured in the blood. Their development largely relies on antibody creation to test the protein candidate performance in blood samples of diseased versus nondiseased patients. The creation of such antibody assays has been a bottleneck in biomarker progress due to the cost, extensive time, and effort required to complete the task. Targeted proteomics is an emerging technology that is playing an increasingly important role to facilitate disease biomarker development. In this study, we applied a SRM-based targeted proteomics platform to directly detect candidate biomarker proteins in plasma to evaluate their clinical utility for pancreatic cancer detection. The characterization of these protein candidates used a clinically well-characterized cohort that included plasma samples from patients with pancreatic cancer, chronic pancreatitis, and healthy age-matched controls. Three of the five candidate proteins, including gelsolin, lumican, and tissue inhibitor of metalloproteinase 1, demonstrated an AUC value greater than 0.75 in distinguishing pancreatic cancer from the controls. In addition, we provide an analysis of the reproducibility, accuracy, and robustness of the SRM-based proteomics platform. This information addresses important technical issues that could aid in the adoption of the targeted proteomics platform for practical clinical utility.     

Streamlined Development of Targeted Mass Spectrometry‐Based Method Combining Scout‐MRM and a Web‐Based Tool Indexed with Scout Peptides

MS‐based targeted proteomics is a relevant technology for sensitive and robust relative or absolute quantification of proteins biomarker candidates in complex human biofluids or tissue extracts. Performing a multiplex assay imposes time scheduling of peptide monitoring only around their expected retention time that needs to be defined with synthetic peptide. Time‐scheduled monitoring is clearly a constraint that precludes from straightforward assay transfer between biological matrices or distinct experimental setup. Any unexpected retention time (RT) shift challenges assay robustness and its implementation for large‐scale analysis. Recently, Scout‐multiple reaction monitoring that fully releases multiplexed targeted acquisition from RT scheduling by successively monitoring complex transition groups triggered with sentinel molecules called Scout has been introduced. It is herein documented how Peptide Selector database and tool streamlines the building of a multiplexed method thanks to RT indexation relative to Scout peptides. This case study deals with surrogate peptides of biomarker candidates related to drug‐induced liver and vascular injury, running such on‐line built method (eight Scouts triggering the monitoring of a total of 692 transitions) enables 100% recovery of a panel of 93 spiked‐in heavy labeled standards, despite significant RT shifts between serum, plasma, or urine. This result illustrates the simplicity of automatically building and deploying robust proteomics targeted assay.     

Identification of novel biomarker candidates for immunohistochemical diagnosis to distinguish low‐grade chondrosarcoma from enchondroma

Chondrosarcoma is the third most common primary bone cancer, requiring surgical resection. However, differentiation of low‐grade chondrosarcoma (grade 1) from enchondroma that is benign and only requires regular follow‐up is one of the most frequent diagnostic dilemmas facing orthopedic oncologists in clinical management. Although multiple techniques are applied to make the distinction, immunohistochemistry is an important ancillary technique, especially when a histopathological stain of specimen must be obtained in order to guarantee an accurate confirmation. Currently, no adequate immunohistochemical diagnostic protein biomarkers are available to distinguish low‐grade chondrosarcoma from enchondroma. To discover novel protein biomarker candidates, an LC‐MS/MS approach was applied to directly compare formalin‐fixed, paraffin‐embedded low‐grade chondrosarcoma with enchondroma tissue samples. The proteomics analysis revealed 17 protein biomarker candidates. A principle was developed to prioritize the candidates using category and ranking. An algorithm, prioritization index of biomarker candidates for immunohistochemistry on tissue specimens, was developed to rank the candidates inside each category. Using the proteomics data and bioinformatics results, the prioritization index of biomarker candidates for immunohistochemistry on tissue revealed periostin as a top candidate. Immunohistochemical staining of periostin in 23 low‐grade chondrosarcoma and 31 enchondroma tissue specimens disclosed 87% specificity and 70% sensitivity.     

Targeted proteomics: a bridge between discovery and validation

New technologies in mass spectrometry are beginning to mature and show unique advantages for the identification and quantitation of proteins. In recent years, one of the significant goals of clinical proteomics has been to identify biomarkers that can be used for clinical diagnosis. As technology has progressed, the list of potential biomarkers has grown. However, the verification and validation of these potential biomarkers is increasingly challenging and require high-throughput quantitative assays, targeting specific candidates. Targeted proteomics bridges the gap between biomarker discovery and the development of clinically applicable biomarker assays.     

Targeted mass spectrometry approaches for protein biomarker verification

The search for protein biomarkers has been a highly pursued topic in the proteomics community in the last decade. This relentless search is due to the constant need for validated biomarkers that could facilitate disease risk stratification, disease diagnosis, prognosis, monitoring as well as drug development, which ultimately would improve our quality of life. The recent development of proteomic technologies including the advancement of mass spectrometers with high sensitivity and speed has greatly advanced the discovery of potential biomarkers. One of the bottlenecks lies in the development of well-established verification assays to screen the biomarker candidates identified in the discovery stage. Recently, absolute quantitation using multiple-reaction monitoring mass spectrometry (MRM-MS) in combination with isotope-labeled internal standards has been extensively investigated as a tool for high-throughput protein biomarker verification. In this review, we describe and discuss recent developments and applications of MRM-MS methods for biomarker verification.     

Lessons from the proteomic study of osteoarthritis

Osteoarthritis is the most common rheumatic pathology and one of the leading causes of disability worldwide. It is a very complex disease whose etiopathogenesis is not fully understood. Furthermore, there are serious limitations for its management, since it lacks specific and sensitive biomarkers for early diagnosis, prognosis and therapeutic monitoring. Proteomic approaches performed in the last few decades have contributed to the knowledge on the molecular mechanisms that participate in this pathology and they have also led to interesting panels of putative biomarker candidates. In the next few years, further efforts should be made for translating these findings into the clinical routines. It is expected that targeted proteomics strategies will be highly valuable for the verification and qualification of biomarkers of osteoarthritis.     

Proteomics approach and techniques in identification of reliable biomarkers for diseases

Biomarkers, also called biological markers, are indicators to identify a biological case or situation as well as detecting any presence of biological activities and processes. Proteins are considered as a type of biomarkers based on their characteristics. Therefore, proteomics approach is one of the most promising approaches in this field. The purpose of this review is to summarize the use of proteomics approach and techniques to identify proteins as biomarkers for different diseases. This review was obtained by searching in a computerized database. So, different researches and studies that used proteomics approach to identify different biomarkers for different diseases were reviewed. Also, techniques of proteomics that are used to identify proteins as biomarkers were collected. Techniques and methods of proteomics approach are used for the identification of proteins' activities and presence as biomarkers for different types of diseases from different types of samples. There are three essential steps of this approach including: extraction and separation of proteins, identification of proteins, and verification of proteins. Finally, clinical trials for new discovered biomarker or undefined biomarker would be on.     

So, you want to look for biomarkers (introduction to the special biomarkers issue)

The burgeoning field of proteomics plays a powerful and relevant role in the discovery of biomarkers, which are biometric measurements that convey information about the biological condition of the subject being tested. Biomarkers have changed the manner in which we diagnose disease, monitor the effect of therapy, classify disease, detect toxicity, and develop new drugs. The central part that proteins command in both disease etiology and treatment make them prime biomarker candidates. Indeed, the majority of clinical tests in use today measure proteins. This perspective introduces the Journal of Proteome Research Special Issue on Proteomics and Biomarkers. It outlines the major applications of biomarkers, discusses the basics of statistically assessing them and considers the crucial choice of sample type. Central considerations of biomarker discovery and validation, particularly with respect to their intended clinical and research applications, are highlighted.     

Antibody‐based proteomics and biomarker research—Current status and limitations

Antibody‐based proteomics play a very important role in biomarker discovery and validation, facilitating the high‐throughput evaluation of candidate markers. Most proteomics‐driven discovery is nowadays based on the use of MS. MS has many advantages, including its suitability for hypothesis‐free biomarker discovery, since information on protein content of a sample is not required prior to analysis. However, MS presents one main caveat which is the limited sensitivity in complex samples, especially for body fluids, where protein expression covers a huge dynamic range. Antibody‐based technologies remain the main solution to address this challenge since they reach higher sensitivity. In this article, we review the benefits and limitations of antibody‐based proteomics in preclinical and clinical biomarker research for discovery and validation in body fluids and tissue. The combination of antibodies and MS, utilizing the best of both worlds, opens new avenues in biomarker research.     

Proteomics of colorectal cancer: Overview of discovery studies and identification of commonly identified cancer-associated proteins and candidate CRC serum markers

Colorectal cancer (CRC) is a common cause of cancer-related mortality in the developed world. Improved methods for early detection and disease management are urgently needed. Many efforts in the past 5 years have been devoted to protein biomarker discovery for early detection of CRC. Here, we discuss identity-based studies employing tandem mass spectrometry that analyzed clinical material as well as model systems. Through meta-analysis we provide a list of CRC-associated tissue proteins discovered in multiple studies, with the greater majority being 2D gel-based discoveries coupled to MS/MS. So far only a limited number of CRC-associated proteins have been validated in serum for non-invasive testing for CRC. This list includes several intracellular and nuclear proteins that a priori would not have been considered candidate biomarkers based on their predicted subcellular localization. Finally, we highlight promising new directions that combine targeted analyses of subcellular proteomes, like the cell surface, secretome, exosome, and nuclear matrix, with nanoLC-MS/MS-based proteomics. We anticipate that in the near future, these novel mass spectrometry-based in-depth approaches will uncover many novel, specific CRC marker candidates in clinical tissues and that their targeted validation with multi-reaction monitoring MS will speed up development of non-invasive tests in feces and serum/plasma.     

The selected reaction monitoring/multiple reaction monitoring-based mass spectrometry approach for the accurate quantitation of proteins: clinical applications in the cardiovascular diseases

Selected reaction monitoring, also known as multiple reaction monitoring, is a powerful targeted mass spectrometry approach for a confident quantitation of proteins/peptides in complex biological samples. In recent years, its optimization and application have become pivotal and of great interest in clinical research to derive useful outcomes for patient care. Thus, selected reaction monitoring/multiple reaction monitoring is now used as a highly sensitive and selective method for the evaluation of protein abundances and biomarker verification with potential applications in medical screening. This review describes technical aspects for the development of a robust multiplex assay and discussing its recent applications in cardiovascular proteomics: verification of promising disease candidates to select only the highest quality peptides/proteins for a preclinical validation, as well as quantitation of protein isoforms and post-translational modifications.     

4th International Peptide Symposium in conjunction with the 7th Australian Peptide Symposium and the 2nd Asia–Pacific International Peptide Symposium

The identification and clinical use of more sensitive and specific biomarkers in the field of solid organ transplantation is an urgent need in medicine. Solid organ transplantation has seen improvements in the short-term survival of transplanted organs due to recent advancements in immunosuppressive therapy. However, the currently available methods of allograft monitoring are not optimal. Recent advancements in assaying methods for biomolecules such as genes, mRNA and proteins have helped to identify surrogate biomarkers that can be used to monitor the transplanted organ. These high-throughput ‘omic’ methods can help researchers to significantly speed up the identification and the validation steps, which are crucial factors for biomarker discovery efforts. Still, the progress towards identifying more sensitive and specific biomarkers remains a great deal slower than expected. In this article, we have evaluated the current status of biomarker discovery using proteomics tools in different solid organ transplants in recent years. This article summarizes recent reports and current status, along with the hurdles in efficient biomarker discovery of protein biomarkers using proteomics approaches. Finally, we will touch upon personalized medicine as a future direction for better management of transplanted organs, and provide what we think could be a recipe for success in this field.     

Recent advances in biomarker discovery in solid organ transplant by proteomics

The identification and clinical use of more sensitive and specific biomarkers in the field of solid organ transplantation is an urgent need in medicine. Solid organ transplantation has seen improvements in the short-term survival of transplanted organs due to recent advancements in immunosuppressive therapy. However, the currently available methods of allograft monitoring are not optimal. Recent advancements in assaying methods for biomolecules such as genes, mRNA and proteins have helped to identify surrogate biomarkers that can be used to monitor the transplanted organ. These high-throughput 'omic' methods can help researchers to significantly speed up the identification and the validation steps, which are crucial factors for biomarker discovery efforts. Still, the progress towards identifying more sensitive and specific biomarkers remains a great deal slower than expected. In this article, we have evaluated the current status of biomarker discovery using proteomics tools in different solid organ transplants in recent years. This article summarizes recent reports and current status, along with the hurdles in efficient biomarker discovery of protein biomarkers using proteomics approaches. Finally, we will touch upon personalized medicine as a future direction for better management of transplanted organs, and provide what we think could be a recipe for success in this field.     

Current progress in protein profiling of complex samples

Accurate cancer biomarkers are needed for early detection, disease classification, prediction of therapeutic response and monitoring treatment. While there appears to be no shortage of candidate biomarker proteins, a major bottleneck in the biomarker pipeline continues to be their verification by enzyme linked immunosorbent assays. Multiple reaction monitoring (MRM), also known as selected reaction monitoring, is a targeted mass spectrometry approach to protein quantitation and is emerging to bridge the gap between biomarker discovery and clinical validation. Highly multiplexed MRM assays are readily configured and enable simultaneous verification of large numbers of candidates facilitating the development of biomarker panels which can increase specificity. This review focuses on recent applications of MRM to the analysis of plasma and serum from cancer patients for biomarker verification. The current status of this approach is discussed along with future directions for targeted mass spectrometry in clinical biomarker validation.     

An integrated quantification method to increase the precision,robustness, and resolution of protein measurement in human plasma samples

Background

Current quantification methods for mass spectrometry (MS)-based proteomics either do not provide sufficient control of variability or are difficult to implement for routine clinical testing.

Results

We present here an integrated quantification (InteQuan) method that better controls pre-analytical and analytical variability than the popular quantification method using stable isotope-labeled standard peptides (SISQuan). We quantified 16 lung cancer biomarker candidates in human plasma samples in three assessment studies, using immunoaffinity depletion coupled with multiple reaction monitoring (MRM) MS. InteQuan outperformed SISQuan in precision in all three studies and tolerated a two-fold difference in sample loading. The three studies lasted over six months and encountered major changes in experimental settings. Nevertheless, plasma proteins in low ng/ml to low μg/ml concentrations were measured with a median technical coefficient of variation (CV) of 11.9% using InteQuan. The corresponding median CV using SISQuan was 15.3% after linear fitting. Furthermore, InteQuan surpassed SISQuan in measuring biological difference among clinical samples and in distinguishing benign versus cancer plasma samples.

Conclusions

We demonstrated that InteQuan is a simple yet robust quantification method for MS-based quantitative proteomics, especially for applications in biomarker research and in routine clinical testing.

Electronic supplementary material

The online version of this article (doi:10.1186/1559-0275-12-3) contains supplementary material, which is available to authorized users.     

Integrated pipeline for mass spectrometry-based discovery and confirmation of biomarkers demonstrated in a mouse model of breast cancer

Despite their potential to impact diagnosis and treatment of cancer, few protein biomarkers are in clinical use. Biomarker discovery is plagued with difficulties ranging from technological (inability to globally interrogate proteomes) to biological (genetic and environmental differences among patients and their tumors). We urgently need paradigms for biomarker discovery. To minimize biological variation and facilitate testing of proteomic approaches, we employed a mouse model of breast cancer. Specifically, we performed LC-MS/MS of tumor and normal mammary tissue from a conditional HER2/Neu-driven mouse model of breast cancer, identifying 6758 peptides representing >700 proteins. We developed a novel statistical approach (SASPECT) for prioritizing proteins differentially represented in LC-MS/MS datasets and identified proteins over- or under-represented in tumors. Using a combination of antibody-based approaches and multiple reaction monitoring-mass spectrometry (MRM-MS), we confirmed the overproduction of multiple proteins at the tissue level, identified fibulin-2 as a plasma biomarker, and extensively characterized osteopontin as a plasma biomarker capable of early disease detection in the mouse. Our results show that a staged pipeline employing shotgun-based comparative proteomics for biomarker discovery and multiple reaction monitoring for confirmation of biomarker candidates is capable of finding novel tissue and plasma biomarkers in a mouse model of breast cancer. Furthermore, the approach can be extended to find biomarkers relevant to human disease.