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.     

Recent advances in proteomic technologies applied to cardiovascular disease

In recent years, the diagnosis of cardiovascular disease (CVD) has increased its potential, also thanks to mass spectrometry (MS) proteomics. Modern MS proteomics tools permit analyzing a variety of biological samples, ranging from single cells to tissues and body fluids, like plasma and urine. This approach enhances the search for informative biomarkers in biological samples from apparently healthy individuals or patients, thus allowing an earlier and more precise diagnosis and a deeper comprehension of pathogenesis, development and outcome of CVD to further reduce the enormous burden of this disease on public health. In fact, many differences in protein expression between CVD‐affected and healthy subjects have been detected, but only a few of them have been useful to establish clinical biomarkers because they did not pass the verification and validation tests. For a concrete clinical support of MS proteomics to CVD, it is, therefore, necessary to: ameliorate the resolution, sensitivity, specificity, throughput, precision, and accuracy of MS platform components; standardize procedures for sample collection, preparation, and analysis; lower the costs of the analyses; reduce the time of biomarker verification and validation. At the same time, it will be fundamental, for the future perspectives of proteomics in clinical trials, to define the normal protein maps and the global patterns of normal protein levels, as well as those specific for the different expressions of CVD. J. Cell. Biochem. 114: 7–20, 2012. © 2012 Wiley Periodicals, Inc.     

ProteinSeq: high-performance proteomic analyses by proximity ligation and next generation sequencing

Despite intense interest, methods that provide enhanced sensitivity and specificity in parallel measurements of candidate protein biomarkers in numerous samples have been lacking. We present herein a multiplex proximity ligation assay with readout via realtime PCR or DNA sequencing (ProteinSeq). We demonstrate improved sensitivity over conventional sandwich assays for simultaneous analysis of sets of 35 proteins in 5 μl of blood plasma. Importantly, we observe a minimal tendency to increased background with multiplexing, compared to a sandwich assay, suggesting that higher levels of multiplexing are possible. We used ProteinSeq to analyze proteins in plasma samples from cardiovascular disease (CVD) patient cohorts and matched controls. Three proteins, namely P-selectin, Cystatin-B and Kallikrein-6, were identified as putative diagnostic biomarkers for CVD. The latter two have not been previously reported in the literature and their potential roles must be validated in larger patient cohorts. We conclude that ProteinSeq is promising for screening large numbers of proteins and samples while the technology can provide a much-needed platform for validation of diagnostic markers in biobank samples and in clinical use.     

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.     

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.     

Biomarkers for the lung cancer diagnosis and their advances in proteomics

Over a last decade, intense interest has been focused on biomarker discovery and their clinical uses. This interest is accelerated by the completion of human genome project and the progress of techniques in proteomics. Especially, cancer biomarker discovery is eminent in this field due to its anticipated critical role in early diagnosis, therapy guidance, and prognosis monitoring of cancers. Among cancers, lung cancer, one of the top three major cancers, is the one showing the highest mortality because of failure in early diagnosis. Numerous potential DNA biomarkers such as hypermethylations of the promoters and mutations in K-ras, p53, and protein biomarkers; carcinoembryonic antigen (CEA), CYFRA21-1, plasma kallikrein B1 (KLKB1), Neuron-specific enolase, etc. have been discovered as lung cancer biomarkers. Despite extensive studies thus far, few are turned out to be useful in clinic. Even those used in clinic do not show enough sensitivity, specificity and reproducibility for general use. This review describes what the cancer biomarkers are for, various types of lung cancer biomarkers discovered at present and predicted future advance in lung cancer biomarker discovery with proteomics technology.     

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.     

New circulating biomarkers for predicting cardiovascular death in healthy population

There is interest to analyse newer biomarkers to identify healthy individuals at risk to develop cardiovascular disease (CVD) incidents and death. To determine in healthy individuals new circulating protein biomarkers, whose systemic levels may be associated with the risk of future development of CVD incidents and death. The study was performed in 82 individuals from the Malmö Diet and Cancer study cohort, free from CVD of whom 41 developed CVD and 41 did not. Plasma proteins related to inflammation and thrombo‐coagulating processes were analysed. α1‐antitrypsin isotype 3 plasma levels were significantly higher while apolipoprotein J plasma levels were lower in participants that developed CVD incidents than those that did not develop acute cardiovascular episode. Of 82 participants, 17 died by CVD causes. There were proteins whose expression in plasma was significantly higher in participants suffering CVD death as compared with those that did not die by CVD. These proteins included: fibrinogen β‐chain isotypes 1 and 3, fibrinogen‐γ‐chain isotype 2, vitamin D‐binding protein isotypes 1, 2 and 3, α1‐antitrypsin isotypes 3 and 6, haptoglobin isotypes 3,4,5 and 5, haemopexin isotypes 1 and 2, and Rho/Rac guanine nucleotide exchange factor 2. Moreover, apolipoprotein J plasma levels were found lower in participants that died by cardiovascular cause. Association between plasma levels of proteins and CVD death was independent of age, gender, conventional risk factors and plasma C‐reactive protein levels. Several protein plasma levels and protein isotypes related to inflammation and thrombo‐coagulating phenomena were independently associated with the risk of future CVD death.     

Advancing the sensitivity of selected reaction monitoring-based targeted quantitative proteomics

Selected reaction monitoring (SRM) - also known as multiple reaction monitoring (MRM) - has emerged as a promising high-throughput targeted protein quantification technology for candidate biomarker verification and systems biology applications. A major bottleneck for current SRM technology, however, is insufficient sensitivity for, e.g. detecting low-abundance biomarkers likely present at the low ng/mL to pg/mL range in human blood plasma or serum, or extremely low-abundance signaling proteins in cells or tissues. Herein, we review recent advances in methods and technologies, including front-end immunoaffinity depletion, fractionation, selective enrichment of target proteins/peptides including posttranslational modifications, as well as advances in MS instrumentation which have significantly enhanced the overall sensitivity of SRM assays and enabled the detection of low-abundance proteins at low- to sub-ng/mL level in human blood plasma or serum. General perspectives on the potential of achieving sufficient sensitivity for detection of pg/mL level proteins in plasma are also discussed.     

Amyloid-β as a biomarker for Alzheimer’s disease: quantification methods in body fluids

Alzheimer’s disease (AD) is the most common neurodegenerative disorder, characterized by neuronal impairment leading to dramatic changes in brain. Amyloid-β peptides and tau protein are the most promising biomarkers for AD. Cerebrospinal fluid and plasma are used to determine the concentration of these species. Since the pathological processes of AD start decades before the first symptoms, biomarkers may provide the possibility of early disease detection. The application of rapidly emerging technology, such as mass spectrometry, has opened new avenues to accelerate biomarker discovery, both for diagnostic as well as for prognostic purposes. This review summarizes AD biomarker studies with focus on amyloid-β peptides in biological fluids and their quantification with immunoassays as well as the latest mass spectrometry-based methods.     

P202-S Expanding the Capabilities of Peptide MRM-Based Assays in Plasma Using a Hybrid Triple-Quadrupole Linear Ion-Trap Mass Spectrometer

As the study of protein biomarkers increases in importance, technical limitations to the detection of low-abundance proteins and high-throughput, high-precision quantitation remain to be overcome. The complexity and dynamic range of the plasma proteome makes the task of specific, quantitative detection even more challenging. Multiple reaction monitoring (MRM) capabilities of triple quadrupole MS systems have been explored as solutions to this challenge due to their well-known sensitivity and selectivity for components in complex matrices such as plasma. Recently, a suite of >100 MRMs representing ~50 plasma protein markers were monitored quantitatively in a single assay using the MRM-based technique showing detection of proteins down to the level of L-selectin (~1μg/mL) with minimal sample preparation and no peptide or protein standards for most of the plasma protein markers.¹As more extensive candidate biomarker panels are being identified, MRM assays will need to be more rapidly developed to verify the expression changes of these proteins across larger clinical sample sets. To do this, the unique combination of triple-quadrupole and ion-trapping capabilities of the hybrid triple quadrupole–linear ion trap mass spectrometer have been utilized. A strategy for rapid MRM assay development for larger-scale profiling and qualification of biomarker candidates without having to first prepare synthetic peptide standards is currently being investigated and involves a chemical labeling strategy to create global reference standards to enable quantitative comparisons between clinical samples. Single assays consisting of ~500s of MRM transitions have been developed for this rapid qualification phase, facilitated by intelligent use of retention time windows during an LC analysis, while maintaining an optimum number of data points for improved precision of peak area and quantitative profiling. This presentation will demonstrate the details of this workflow with human plasma examples.     

Low abundance protein enrichment for discovery of candidate plasma protein biomarkers for early detection of breast cancer

Molecular biomarkers of early stage breast cancer may improve the sensitivity and specificity of diagnosis. Plasma biomarkers have additional value in that they can be monitored with minimal invasiveness. Plasma biomarker discovery by genome-wide proteomic methods is impeded by the wide dynamic range of protein abundance and the heterogeneity of protein expression in healthy and disease populations which requires the analysis of a large number of samples. We addressed these issues through the development of a novel protocol that couples a combinatorial peptide ligand library protein enrichment strategy with isobaric label-based 2D LC-MS/MS for the identification of candidate biomarkers in high throughput. Plasma was collected from patients with stage I breast cancer or benign breast lesions. Low abundance proteins were enriched using a bead-based combinatorial library of hexapeptides. This resulted in the identification of 397 proteins, 22% of which are novel plasma proteins. Twenty-three differentially expressed plasma proteins were identified, demonstrating the effectiveness of the described protocol and defining a set of candidate biomarkers to be validated in independent samples. This work can be used as the basis for the design of properly powered investigations of plasma protein expression for biomarker discovery in larger cohorts of patients with complex disease.     

DNA methylation based biomarkers: Practical considerations and applications

A biomarker is a molecular target analyzed in a qualitative or quantitative manner to detect and diagnose the presence of a disease, to predict the outcome and the response to a specific treatment allowing personalized tailoring of patient management. Biomarkers can belong to different types of biochemical molecules such as proteins, DNA, RNA or lipids, whereby protein biomarkers have been the most extensively studied and used, notably in blood-based protein quantification tests or immunohistochemistry. The rise of interest in epigenetic mechanisms has allowed the identification of a new type of biomarker, DNA methylation, which is of great potential for many applications. This stable and heritable covalent modification mostly affects cytosines in the context of a CpG dinucleotide in humans. It can be detected and quantified by a number of technologies including genome-wide screening methods as well as locus- or gene-specific high-resolution analysis in different types of samples such as frozen tissues and FFPE samples, but also in body fluids such as urine, plasma, and serum obtained through non-invasive procedures. In some cases, DNA methylation based biomarkers have proven to be more specific and sensitive than commonly used protein biomarkers, which could clearly justify their use in clinics. However, very few of them are at the moment used in clinics and even less commercial tests are currently available. The objective of this review is to discuss the advantages of DNA methylation as a biomarker, the practical considerations for their development, and their use in disease detection, prediction of outcome or treatment response, through multiple examples mainly focusing on cancer, but also to evoke their potential for complex diseases and prenatal diagnostics.     

A pipeline that integrates the discovery and verification of plasma protein biomarkers reveals candidate markers for cardiovascular disease

We developed a pipeline to integrate the proteomic technologies used from the discovery to the verification stages of plasma biomarker identification and applied it to identify early biomarkers of cardiac injury from the blood of patients undergoing a therapeutic, planned myocardial infarction (PMI) for treatment of hypertrophic cardiomyopathy. Sampling of blood directly from patient hearts before, during and after controlled myocardial injury ensured enrichment for candidate biomarkers and allowed patients to serve as their own biological controls. LC-MS/MS analyses detected 121 highly differentially expressed proteins, including previously credentialed markers of cardiovascular disease and >100 novel candidate biomarkers for myocardial infarction (MI). Accurate inclusion mass screening (AIMS) qualified a subset of the candidates based on highly specific, targeted detection in peripheral plasma, including some markers unlikely to have been identified without this step. Analyses of peripheral plasma from controls and patients with PMI or spontaneous MI by quantitative multiple reaction monitoring mass spectrometry or immunoassays suggest that the candidate biomarkers may be specific to MI. This study demonstrates that modern proteomic technologies, when coherently integrated, can yield novel cardiovascular biomarkers meriting further evaluation in large, heterogeneous cohorts.     

Urinary biomarkers for monitoring disease progression in the Han:SPRD-cy rat model of autosomal-dominant polycystic kidney disease

The Han:SRPD-cy rat is a well-recognized model of human autosomal-dominant polycystic kidney disease. The disease is characterized by the development of progressive renal cysts, leading to declining renal function. Disease progression typically is monitored by measurement of plasma urea concentration. Although plasma urea may be an adequate measure of overall renal function, urinary biomarkers capable of accurately monitoring disease progression may be equally useful. The goal of this study was to assess several urinary biomarkers as potential markers of disease progression in male and female Han:SPRD-cy rats. These biomarkers were compared with changes in plasma urea concentration and morphometric changes as the disease progressed. Urinary activity of N-acetyl-β-D-glucosaminidase and concentration of α-glutathione S-transferase were measured as markers of proximal tubular dysfunction, glutathione S-transferase Yb1 as a distal tubular marker, and collagen IV as a biomarker for glomerular lesions. Urinary albumin was used as biomarker of glomerular or proximal tubular lesions. Albuminuria increased in male rats as the disease progressed, correlating with increasing plasma urea and morphologic changes. Urine concentrations of α-glutathione S-transferase decreased significantly in the male heterozygotic compared with wildtype rats in the later stages of the disease. Urinary concentrations of glutathione S-transferase Yb1 and collagen IV and activity of N-acetyl-β-D-glucosaminidase did not change during disease progression. Measurement of urinary albumin and concentrations of α-glutathione S-transferase may be useful for monitoring disease progression in the male Han:SPRD-cy rat model in future experiments.     

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.     

Plasma protein profiling reveals protein clusters related to BMI and insulin levels in middle-aged overweight subjects

BACKGROUND: Biomarkers that allow detection of the onset of disease are of high interest since early detection would allow intervening with lifestyle and nutritional changes before the disease is manifested and pharmacological therapy is required. Our study aimed to improve the phenotypic characterization of overweight but apparently healthy subjects and to identify new candidate profiles for early biomarkers of obesity-related diseases such as cardiovascular disease and type 2 diabetes. METHODOLOGY/PRINCIPAL FINDINGS: In a population of 56 healthy, middle-aged overweight subjects Body Mass Index (BMI), fasting concentration of 124 plasma proteins and insulin were determined. The plasma proteins are implicated in chronic diseases, inflammation, endothelial function and metabolic signaling. Random Forest was applied to select proteins associated with BMI and plasma insulin. Subsequently, the selected proteins were analyzed by clustering methods to identify protein clusters associated with BMI and plasma insulin. Similar analyses were performed for a second population of 20 healthy, overweight older subjects to verify associations found in population I. In both populations similar clusters of proteins associated with BMI or insulin were identified. Leptin and a number of pro-inflammatory proteins, previously identified as possible biomarkers for obesity-related disease, e.g. Complement 3, C Reactive Protein, Serum Amyloid P, Vascular Endothelial Growth Factor clustered together and were positively associated with BMI and insulin. IL-3 and IL-13 clustered together with Apolipoprotein A1 and were inversely associated with BMI and might be potential new biomarkers. CONCLUSION/ SIGNIFICANCE: We identified clusters of plasma proteins associated with BMI and insulin in healthy populations. These clusters included previously reported biomarkers for obesity-related disease and potential new biomarkers such as IL-3 and IL-13. These plasma protein clusters could have potential applications for improved phenotypic characterization of volunteers in nutritional intervention studies or as biomarkers in the early detection of obesity-linked disease development and progression.     

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.     

A new versatile peptide-based size exclusion chromatography platform for global profiling and quantitation of candidate biomarkers in hepatocellular carcinoma specimens

Disease biomarkers are predicted to be in low abundance; thus, the most crucial step of biomarker discovery is the efficient fractionation of clinical samples into protein sets that define disease stages and/or predict disease development. For this purpose, we developed a new platform that uses peptide-based size exclusion chromatography (pep-SEC) to quantify disease biomarker candidates. This new platform has many advantages over previously described biomarker profiling platforms, including short run time, high resolution, and good reproducibility, which make it suitable for large-scale analysis. We combined this platform with isotope labeling and label-free methods to identify and quantitate differentially expressed proteins in hepatocellular carcinoma (HCC) tissues. When we combined pep-SEC with a gas phase fractionation method, which broadens precursor ion selection, the protein coverage was significantly increased, which is critical for the global profiling of HCC specimens. Furthermore, pep-SEC-LC-MS/MS analysis enhanced the detection of low-abundance proteins (e.g. insulin receptor substrate 2 and carboxylesterase 1) and glycopeptides in HCC plasma. Thus, our pep-SEC platform is an efficient and versatile pre-fractionation system for the large-scale profiling and quantitation of candidate biomarkers in complex disease proteomes.