Proteomic patterns as a diagnostic tool for early-stage cancer: a review of its progress to a clinically relevant tool.

The pace of development in novel technologies that promise improvements in the early diagnosis of disease is truly impressive. One such technology at the forefront of this revolution is mass spectrometry. New capabilities in mass spectrometry have provided the means for the development of proteomics, and the race is on to find innovative ways to apply this powerful technology to solving the problems faced in clinical medicine. One area that has garnered much attention over the past few years is the use of mass spectral patterns for cancer diagnostics. The use of these so-called 'proteomic patterns' for disease diagnosis relies fundamentally on the pattern of signals observed within a mass spectrum rather than the more conventional identification and quantitation of a biomarker such as in the case of cancer antigen-125- or prostate-specific antigen. The inherent throughput of proteomic pattern technology enables the analysis of hundreds of clinical samples per day. Currently, there are two primary means by which proteomic patterns can be acquired, surface-enhanced laser desorption/ionization (SELDI) and an electrospray ionization (ESI) method that has been popularized under the name, OvaCheck. In this review, an historical perspective on the development of proteomic patterns for the diagnosis of early-stage cancers is described. In addition, a critical assessment of the overall technology is presented with an emphasis on the steps required to enable proteomic pattern analysis to become a viable clinical tool for diagnosing early-stage cancers.     

Serum protein fingerprinting

The core technologies in the rapidly expanding field of proteomics have matured to the point where quantitative measurements of thousands of proteins can be conducted, enabling truly global measurements of protein expression. This advent has brought with it the hope of discovering novel biomarkers that promise a renaissance in clinical medicine. To meet this need, many proteomic studies have focused on the identification and subsequent comparative analysis of the thousands of proteins that populate complex biological systems such as serum and tissues. A novel application of mass spectrometry has been in proteomic pattern analysis, which has emerged as an effective method for the early diagnosis of diseases. In stark contrast to 'classical' proteomics, proteomic pattern analysis relies on the pattern of proteins observed, rather than on the discrete identification of a protein. Proteomic pattern technology allows hundreds of clinical samples to be analyzed per day and promises to be a novel, highly sensitive predictive clinical tool to improve diagnostic and prognostic medicine.     

Direct-tissue SELDI-TOF mass spectrometry analysis: a new application for clinical proteomics

BACKGROUND: New molecular profiling technologies can aid in analysis of small pathologic samples obtained by minimally invasive biopsy and may enable the discovery of key biomarkers synergistic with anatomopathologic analysis related to prognosis, therapeutic response, and innovative target validation. Thus proteomic analysis at the histologic level in healthy and pathologic settings is a major issue in the field of clinical proteomics. METHODS: We used surface-enhanced laser desorption ionization-time-of-flight mass spectrometry (SELDI-TOF MS) technology with surface chromatographic subproteome enrichment and preservation of the spatial distribution of proteomic patterns to detect discrete modifications of protein expression. We performed in situ proteomic profiling of mouse tissue and samples of human cancer tissue, including brain and lung cancer. RESULTS: This approach permitted the discrimination of glioblastomas from oligodendrogliomas and led to the identification of 3 potential markers. CONCLUSION: Direct tissue proteomic analysis is an original application of SELDI-TOF MS technology that can expand the use of clinical proteomics as a complement to the anatomopathological diagnosis.     

The use of proteomics for the assessment of clinical samples in research

Proteomics, the analysis of expressed proteins, has been an important developing area of research for the past two decades [Anderson, NG, Anderson, NL. Twenty years of two-dimensional electrophoresis: past, present and future. Electrophoresis 1996;17:443-453]. Advances in technology have led to a rapid increase in applications to a wide range of samples; from initial experiments using cell lines, more complex tissues and biological fluids are now being assessed to establish changes in protein expression. A primary aim of clinical proteomics is the identification of biomarkers for diagnosis and therapeutic intervention of disease, by comparing the proteomic profiles of control and disease, and differing physiological states. This expansion into clinical samples has not been without difficulties owing to the complexity and dynamic range in plasma and human tissues including tissue biopsies. The most widely used techniques for analysis of clinical samples are surface-enhanced laser desorption/ionisation mass spectrometry (SELDI-MS) and 2-dimensional gel electrophoresis (2-DE) coupled to matrix-assisted laser desorption ionisation [Person, MD, Monks, TJ, Lau, SS. An integrated approach to identifying chemically induced posttranslational modifications using comparative MALDI-MS and targeted HPLC-ESI-MS/MS. Chem. Res. Toxicol. 2003;16:598-608]-mass spectroscopy (MALDI-MS). This review aims to summarise the findings of studies that have used proteomic research methods to analyse samples from clinical studies and to assess the impact that proteomic techniques have had in assessing clinical samples.     

The clinical application of proteomics

BACKGROUND: Proteomics is defined as a scientific approach used to elucidate all protein species within a cell or tissue, and many researchers are taking advantage of proteomic technology to elucidate protein changes between healthy and diseased states. METHODS: The application of proteomic techniques and strategies to the field of medicine is slowly transforming the way biomarker discovery is conducted. However, the complexity of serum is the source of both its promise to clinical applications and its challenge to proteomic analysis. Like any new technology when it is first introduced, proteomics has been touted with much hope and promise. RESULTS AND CONCLUSIONS: We provide a review of the clinical application of proteomics with the emphasis on current practical issues and challenges facing proteomic research.     

FTICR mass spectrometry in proteomics

Analytical tools that allow rapid screening, low sample consumption and accurate protein identification are of great importance in studies of complex biological samples. Today, mass spectrometry (MS) is a key analytical tools with applications in a wide variety of fields, reaching from the analysis of elemental compositions in various materials to the identification of large protein complexes. One of the fastest growing fields of MS applications is proteomics, or the study of protein expression in an organism. In the traditional proteomic approach, two-dimensional sodium dodecylsulfate polyacrylamide gel electrophoresis is applied for the separation and visualization of proteins. In this review, the use of high resolution Fourier transform ion cyclotron resonance mass spectrometry, including up-front multidimensional liquid separations for 'top down' or 'bottom up' proteomic approaches, are presented.     

The application of clinical proteomics to cancer and other diseases.

The term "clinical proteomics" refers to the application of available proteomics technologies to current areas of clinical investigation. The ability to simultaneously and comprehensively examine changes in large numbers of proteins in the context of disease or other changes in physiological conditions holds great promise as a tool to unlock the solutions to difficult clinical research questions. Proteomics is a rapidly growing field that combines high throughput analytical methodologies such as two-dimensional gel electrophoresis and SELDI mass spectrometry methods with complex bioinformatics to study systems biology--the system of interest is defined by the investigator. Even with all its potential, however, studies must be carefully designed in order to differentiate true clinical differences in protein expression from differences originating from variation in sample collection, variation in experimental condition, and normal biological variability. Proteomic analyses are already widely in use for clinical studies ranging from cancer to other diseases such as cardiovascular disease, organ transplant, and pharmacodynamic studies.     

The molecular make-up of a tumour: proteomics in cancer research

The enormous progress in proteomics, enabled by recent advances in MS (mass spectrometry), has brought protein analysis back into the limelight of cancer research, reviving old areas as well as opening new fields of study. In this review, we discuss the basic features of proteomic technologies, including the basics of MS, and we consider the main current applications and challenges of proteomics in cancer research, including (i) protein expression profiling of tumours, tumour fluids and tumour cells; (ii) protein microarrays; (iii) mapping of cancer signalling pathways; (iv) pharmacoproteomics; (v) biomarkers for diagnosis, staging and monitoring of the disease and therapeutic response; and (vi) the immune response to cancer. All these applications continue to benefit from further technological advances, such as the development of quantitative proteomics methods, high-resolution, high-speed and high-sensitivity MS, functional protein assays, and advanced bioinformatics for data handling and interpretation. A major challenge will be the integration of proteomics with genomics and metabolomics data and their functional interpretation in conjunction with clinical results and epidemiology.     

Effects of pretreatment protocols on human amniotic fluid protein profiling with SELDI-TOF MS using protein chips and magnetic beads

BackgroundThere is increasing interest in the use of human amniotic fluid (AF) proteomics with surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) for diagnosing pregnancy-associated abnormalities. A critical parameter of diagnostic biomarkers is the accuracy and reproducibility of protein patterns. We evaluated the effects of common pretreatment protocols on protein patterns generated using SELDI mass spectrometry with two different protein capture strategies (including functional protein chips and functionalized magnetic beads prior to MS analysis) in AF.MethodVarious extrinsic factors involved in processing and storing amniotic fluid, including matrix composition, sample storage time, temperature and freeze–thaw cycles, were analyzed regarding their impact on AF protein patterns using SELDI mass spectrometry with 2 different protein capture strategies.ResultsThree extrinsic factors (sample storage for 3 days at either room temperature or 4 °C or freeze–thawing the sample 5 times) significantly decreased the number or intensities of protein peaks detected in AF. Matrix dilutions also changed the spectra of AF, with more peaks and higher intensities observed with 50% α-cyano-4-hydroxycinnamic acid (CHCA). Moreover, protein chips captured more proteins or peptides than magnetic beads on SELDI-TOF MS profiling of AF.ConclusionsThese results suggest that extrinsic factors must be taken into account for valid data interpretation to ensure good reproducibility of AF profiling by SELDI mass spectrometry.     

Proteomics: the next revolution in laboratory medicine?

BACKGROUND: The identification of specific genetic alterations and protein profiles associated with disease offers a unique opportunity to develop proteomics-based assays for early diagnosis. By identifying proteins in serum/plasma, a minimally invasive tool is used to assess the presence of disease and to monitor response to treatment and/or disease progression. The potential clinical applications of this tool are broad-based, including the diagnosis not only of cancer but also cardiovascular and neuromuscular diseases, organ transplantation associated conditions, and infertility. METHODS: A number of competing chromatographic techniques have been proposed for overcoming the complexity and labor-intensive manipulations associated with the traditional technique for proteomic analysis, which is based on two-dimensional gel electrophoretic techniques. However, mass spectrometry has now assumed a central role in most proteomic workflows, and several combinations of ionization sources, analyzers and fragmentations devices have been described and developed. RESULTS: Thanks to proteomic applications in the diagnosis of cancer, several research groups have identified proteomic patterns associated with ovarian, prostatic, colorectal and other cancers. While the sensitivity and specificity of these patterns are highly satisfactory, there are still some open questions concerning the standardization, reproducibility, and inter-laboratory agreement of these data. CONCLUSIONS: Proteomics, and, in particular, serum mass spectroscopic proteomic pattern diagnostics, is a rapid expanding field of research. The plasma proteoma has an important position at the intersection between genes and diseases, and clinical laboratories must adapt to a new era of tests based on proteomics and genomics. In the future, mass spectrometry will become an essential tool in the clinical laboratory.     

Vascular proteomic mapping in vivo

Summary.  Molecular targeting of drugs and imaging agents remain important yet elusive goals in modern medicine. Technological advancements in genomics and proteomics methods have detected differentially expressed genes and proteins, uncovering many new candidate targets in a wide array of diseases and tissues. However, methods to validate potential targets in vivo tend to be quite laborious so that the validation and testing phase has become rate-limiting in bringing treatments to the clinic. There is a critical need for integrated approaches combining state-of-the-art methodologies in proteomics and in vivo imaging to accelerate validation of newly discovered vascular targets for nanomedicines, drugs, imaging agents, and gene vectors. This paper is a review of vascular targeting and proteomics, and will present recent developments in proteomic imaging. A new in vivo organellar proteomic imaging platform will be discussed, which combines subcellular fractionation, mass spectrometry, bioinformatic database interrogation, monoclonal antibody technology and a battery of imaging modalities to rapidly discover and validate tissue-specific endothelial protein targets in vivo . Technological advancements are permitting large-scale proteomic mapping to be performed. New targets have been discovered that permit organ-specific targeting in vivo . Improvements in imaging are creating standards for validation of targets in vivo . Tumor imaging and radioimmunotherapy have also been improved through these efforts. Although we are moving towards a comprehensive mapping of the protein expression by the endothelium, much more needs to be done.     

Solid-phase hexapeptide ligand libraries open up new perspectives in the discovery of biomarkers in human plasma

BackgroundPre-treatment of plasma with hexapeptide ligand libraries prior to proteomic analysis is well documented. However, the maintenance of biomarker abundance throughout the different pre-analytical steps is required for a potential application of differential proteomics in clinical studies.MethodsWe combined the use of an amino-terminal hexapeptide ligand library and its carboxyl-terminal version with a sequential elution strategy of the proteins/peptides bound to the beads, followed by either mass spectrometry or 2D electrophoresis analyses.ResultsWe show the maintenance of C-reactive protein abundance (a marker of inflammation) throughout the process (including hexapeptide bead treatment and proteomic analysis) in patients presenting high and low levels of this protein.In parallel, we assessed the contribution of this workflow to increasing the number of potential biomarkers detected and its suitability for a clinical study on approximately a hundred samples, as well as the reproducibility of the process.ConclusionsPre-treatment with hexapeptide ligand librairies opens up new perspectives in the discovery of biomarkers in human plasma by improving the detection of new species while maintaining their original differential abundance. This approach is also suitable for an application in a clinical proteomic study of at least 100 samples.     

Mass spectrometry-based membrane proteomics in cancer biomarker discovery

Membrane proteins are involved in central processes such as cell signaling, cell–cell interactions and communication, ion and metabolite transport and in general play a crucial role in cell homeostasis. Cancer and cancer metastasis have been correlated to protein expression levels and dysfunction, with membrane proteins playing an important role, and are thus used as drug targets and potential biomarkers for prognostic or diagnostic purposes. Despite the critical biological significance of membrane proteins, proteomic analysis has been a challenging task due to their hydrophobicity. In this review, recent advances in the proteomic analysis of membrane proteins are presented, focusing on membrane fraction enrichment techniques combined with labeled or label-free shotgun proteomics approaches for the identification of potential cancer biomarkers.     

High-content affinity-based proteomics: unlocking protein biomarker discovery

Single protein biomarkers measured with antibody-based affinity assays are the basis of molecular diagnostics in clinical practice today. There is great hope in discovering new protein biomarkers and combinations of protein biomarkers for advancing medicine through monitoring health, diagnosing disease, guiding treatment, and developing new therapeutics. The goal of high-content proteomics is to unlock protein biomarker discovery by measuring many (thousands) or all (～23,000) proteins in the human proteome in an unbiased, data-driven approach. High-content proteomics has proven technically difficult due to the diversity of proteins, the complexity of relevant biological samples, such as blood and tissue, and large concentration ranges (in the order of 10(12) in blood). Mass spectrometry and affinity methods based on antibodies have dominated approaches to high-content proteomics. For technical reasons, neither has achieved adequate simultaneous performance and high-content. Here we review antibody-based protein measurement, multiplexed antibody-based protein measurement, and limitations of antibodies for high-content proteomics due to their inherent cross-reactivity. Finally, we review a new affinity-based proteomic technology developed from the ground up to solve the problem of high content with high sensitivity and specificity. Based on a new generation of slow off-rate modified aptamers (SOMAmers), this technology is unlocking biomarker discovery.     

Pharmacoproteomic approach to the study of drug mode of action, toxicity, and resistance: applications in diabetes and cancer

Proteomics is a powerful technique for investigating protein expression profiles in biological systems and their modifications in response to stimuli or to particular physiological or pathophysiological conditions. It is therefore a technique of choice for the study of drug mode of action, side-effects, toxicity and resistance. It is also a valuable approach for the discovery of new drug targets. All these proteomic applications to pharmacological issues may be called pharmacoproteomics. The pharmacoproteomic approach could be particularly useful for the identification of molecular alterations implicated in type 2 diabetes and for further characterization of existing or new drugs. In oncology, proteomics is widely used for the identification of tumour-specific protein markers, and pharmacoproteomics is used for the evaluation of chemotherapy, particularly for the characterization of drug-resistance mechanisms. The large amount of data generated by pharmacoproteomic screening requires the use of bioinformatic tools to insure a pertinent interpretation. Herein, we review the applications of pharmacoproteomics to the study of type 2 diabetes and to chemoresistance in different types of cancer and the current state of this technology in these pathologies. We also suggest a number of bioinformatic solutions for proteomic data management.     

SELDI proteinchip MS: a platform for biomarker discovery and cancer diagnosis

Identification and understanding the structures, interactions and functions of all of a cell's proteins is one of the major goals of the postgenome era. The genome project has produced a wealth of information that is greatly expounding the genetic basis of cancer. However, it falls short in not allowing for accurate prediction of what is happening at the protein level in a cancer cell or a body fluid proteome. It is the hope that, by deciphering the alterations in the cancer proteome, biomarkers and patterns of biomarkers will be found that will lead to improvements in early detection, diagnosis and treatment monitoring. To achieve this goal, rapid high-throughput proteomic technologies will be required. The SELDI ProteinChip Biomarker mass spectrometry system appears to have potential in this effort, both for biomarker discovery and as a potential clinical diagnostic assay platform.     

Comprehensive proteomic analysis of protein changes during platelet storage requires complementary proteomic approaches

BACKGROUND: Proteomics methods may be used to analyze changes occurring in stored blood products. These data sets can identify processes leading to storage-associated losses of blood component quality such as the platelet (PLT) storage lesion (PSL). The optimal strategy to perform such analyses to obtain the most informative data sets, including which proteomics methods, is undefined. This study addresses relative differences among proteomics approaches to the analysis of the PLT storage lesion. STUDY DESIGN AND METHODS: Changes to the PLT proteome between Days 1 and 7 of storage were analyzed with three complementary proteomic approaches with final mass spectrometry analysis: two-dimensional (2D) gel electrophoresis/differential gel electrophoresis (DIGE), isotope tagging for relative and absolute quantitation (iTRAQ), and isotope-coded affinity tagging (ICAT). Observed changes in concentration during storage of selected proteins were confirmed by immunoblotting. RESULTS: In total, 503 individual proteins changed concentration over a 7-day storage period. By method, a total of 93 proteins were identified by 2D gel/DIGE, 355 by iTRAQ, and 139 by ICAT. Less than 16 percent of the 503 proteins, however, were identified by not more than at least two proteomic approaches. Only 5 proteins were identified by all approaches. Membrane protein changes were not reliably detected with 2D gel/DIGE methods. CONCLUSION: Although proteomics analyses identified many storage-associated protein changes, these varied significantly by method suggesting that a combination of protein-centric (2D gel or DIGE) and peptide-centric (iTRAQ or ICAT) approaches are essential to acquire adequate data. The use of one proteomics method to study changes in stored blood products may give insufficient information.     

Serum proteomic fingerprints of adult patients with severe acute respiratory syndrome

BACKGROUND: Severe acute respiratory syndrome (SARS) is an emerging infectious disease caused by a new coronavirus strain, SARS-CoV. Specific proteomic patterns might be present in serum in response to the infection and could be useful for early detection of the disease. METHODS: Using surface-enhanced laser desorption/ionization (SELDI) ProteinChip technology, we profiled and compared serum proteins of 39 patients with early-stage SARS infection and 39 non-SARS patients who were suspected cases during the SARS outbreak period. Proteomic patterns associated with SARS were identified by bioinformatic and biostatistical analyses. Features of interest were then purified and identified by tandem mass spectrometry. RESULTS: Twenty proteomic features were significantly different between the 2 groups. Fifteen were increased in the SARS group, and 5 were decreased. Their concentrations were correlated with 2 or more clinical and/or biochemical variables. Two were correlated with the SARS-CoV viral load. Hierarchical clustering analysis showed that a majority of the SARS patients (95%) had similar serum proteomic profiles and identified 2 subgroups with poor prognosis. ROC curve analysis identified individual features as potential biomarkers for SARS diagnosis (areas under ROC curves, 0.733-0.995). ROC curve areas were largest for an N-terminal fragment of complement C3c alpha chain (m/z 28 119) and an internal fragment of fibrinogen alpha-E chain (m/z 5908). Immunoglobulin kappa light chain (m/z 24 505) positively correlated with viral load. CONCLUSIONS: Specific proteomic fingerprints in the sera of adult SARS patients could be used to identify SARS cases early during onset with high specificity and sensitivity.     

Serum, salivary and tissue proteomics for discovery of biomarkers for head and neck cancers

Initial clinically oriented applications of emerging proteomic technologies that aim to identify biomarkers for head and neck squamous cell carcinoma diagnostics have yielded promising results. The development of new proteomic diagnostics remains critical for the early detection of head and neck squamous cell carcinoma at more treatable stages. Prognostic markers for disease recurrence and treatment sensitivities are also required. In this overview of current biomarker identification strategies for head and neck squamous cell carcinoma, different combinations of mass spectrometry platforms, laser capture microscopy and 2D gel electrophoresis procedures are summarized as applied to readily available clinical specimens (tissue, blood and saliva). Issues related to assay reproducibility, management of large data sets and future improvements in clinical proteomics are also addressed.     

Proteomics and cancer diagnosis: the potential of mass spectrometry

Proteomic approaches to the identification of novel biomarkers for cancer diagnosis and staging have traditionally relied on the identification of differentially expressed proteins between tumor cells and their normal counterparts based on the patterns of protein expression observed by two-dimensional gel electrophoresis (2D-PAGE). Recent advances in mass spectrometry and in the informatics and statistical tools necessary to interpret mass spectrometric data have revolutionized the approach to defining new tumor markers. The combinations of SELDI mass spectrometry, retentate affinity chromatography, and statistical algorithms for pattern recognition have engendered a great deal of interest in 'proteomic profiling' as a diagnostic tool. However, the ability of new mass spectrometers to provide unambiguous identification of low abundance proteins from mixtures as complex as human serum also provides a mechanism for the discovery and mechanistic validation of small sets of specific proteins that are amenable to more traditional formats for clinical assays.