Proteomics in human cancer research

Proteomics is now widely employed in the study of cancer. Many laboratories are applying the rapidly emerging technologies to elucidate the underlying mechanisms associated with cancer development, progression, and severity in addition to developing drugs and identifying patients who will benefit most from molecular targeted compounds. Various proteomic approaches are now available for protein separation and identification, and for characterization of the function and structure of candidate proteins. In spite of significant challenges that still exist, proteomics has rapidly expanded to include the discovery of novel biomarkers for early detection, diagnosis and prognostication (clinical application), and for the identification of novel drug targets (pharmaceutical application). To achieve these goals, several innovative technologies including 2-D-difference gel electrophoresis, SELDI, multidimensional protein identification technology, isotope-coded affinity tag, solid-state and suspension protein array technologies, X-ray crystallography, NMR spectroscopy, and computational methods such as comparative and de novo structure prediction and molecular dynamics simulation have evolved, and are being used in different combinations. This review provides an overview of the field of proteomics and discusses the key proteomic technologies available to researchers. It also describes some of the important challenges and highlights the current pharmaceutical and clinical applications of proteomics in human cancer research.     

Quantitative proteomics for identification of cancer biomarkers

Quantitative proteomics can be used for the identification of cancer biomarkers that could be used for early detection, serve as therapeutic targets, or monitor response to treatment. Several quantitative proteomics tools are currently available to study differential expression of proteins in samples ranging from cancer cell lines to tissues to body fluids. 2-DE, which was classically used for proteomic profiling, has been coupled to fluorescence labeling for differential proteomics. Isotope labeling methods such as stable isotope labeling with amino acids in cell culture (SILAC), isotope-coded affinity tagging (ICAT), isobaric tags for relative and absolute quantitation (iTRAQ), and (18) O labeling have all been used in quantitative approaches for identification of cancer biomarkers. In addition, heavy isotope labeled peptides can be used to obtain absolute quantitative data. Most recently, label-free methods for quantitative proteomics, which have the potential of replacing isotope-labeling strategies, are becoming popular. Other emerging technologies such as protein microarrays have the potential for providing additional opportunities for biomarker identification. This review highlights commonly used methods for quantitative proteomic analysis and their advantages and limitations for cancer biomarker analysis.     

Mass spectrometry-based proteomics of endoscopically collected pancreatic fluid in chronic pancreatitis research

MS-based investigation of pancreatic fluid enables the high-throughput identification of proteins present in the pancreatic secretome. Pancreatic fluid is a complex admixture of digestive, inflammatory, and other proteins secreted by the pancreas into the duodenum, and thus is amenable to MS-based proteomic analysis. Recent advances in endoscopic techniques, in particular the endoscopic pancreatic function test (ePFT), have improved the collection methodology of pancreatic fluid for proteomic analysis. Here, we provide an overview of MS-based proteomic techniques as applied to the study of pancreatic fluid. We address sample collection, protein extraction, MS sample preparation and analysis, and bioinformatic approaches, and summarize current MS-based investigations of pancreatic fluid. We then examine the limitations and the future potential of such technologies in the investigation of pancreatic disease. We conclude that pancreatic fluid represents a rich reservoir of potential biomarkers and that the study of the molecular mechanisms of chronic pancreatitis may benefit substantially from MS-based proteomics.     

Phosphoproteomics: A possible route to novel biomarkers of breast cancer

Proteomics is rapidly transforming the way that cancer and other pathologies are investigated. The ability to identify hundreds of proteins and to compare their abundance in different clinical samples presents a unique opportunity for direct identification of novel disease markers. Furthermore, recent advances allow us to analyse and compare PTMs. This gives an additional dimension for defining a new class of protein biomarker based not only on abundance and expression but also on the occurrence of covalent modifications specific to a disease state or therapy response. Such modifications are often a consequence of the activation/inactivation of a particular disease related pathway. In this review we evaluate the available information on breast cancer related protein-phosphorylation events, illustrating the rationale for investigating this PTM as a target for breast cancer research with eventual clinical relevance. We present a critical survey of the published experimental strategies to study protein phosphorylation on a system wide scale and highlight recent specific advances in breast cancer phosphoproteomics. Finally we discuss the feasibility of establishing novel biomarkers for breast cancer based on the detection of patterns of specific protein phosphorylation events.     

Breast cancer biomarker measurements and standards

Cancer is a heterogeneous disease characterized by changes in the levels and activities of important cellular proteins, including oncogenes and tumor suppressors. Genetic mutations cause changes in protein activity and protein expression levels that result in the altered metabolism, proliferation, and metastasis seen in cancer cells. The identification of the critical biochemical changes in cancer has led to advances in its detection and treatment. An important example of this is the measurement of human epidermal growth factor receptor 2 (HER2), where increased expression occurs in approximately 20–30% of breast cancer tumors. HER2 is a member of the epidermal growth factor receptor family and is an important biomarker expressed on the cell surface. Measurement of the HER2 levels in tumor cells provides diagnostic, prognostic, and treatment information, because a targeted therapeutic is available. The most common methods to measure HER2 levels are immunohistochemistry and in situ hybridization assays. The accurate and reliable measurements of the specific changes in protein biomarkers for detection and treatment of cancer are important challenges. This review is focused on efforts to improve the quantitation and reliability of cancer biomarkers by using standards and reference materials.     

Proteomic and other analyses to determine the functional consequences of deregulated kallikrein-related peptidase (KLK) expression in prostate and ovarian cancer

Rapidly developing proteomic tools are improving detection of deregulated kallikrein-related peptidase (KLK) expression, at the protein level, in prostate and ovarian cancer, as well as facilitating the determination of functional consequences downstream. MS-driven proteomics uniquely allows for the detection, identification, and quantification of thousands of proteins in a complex protein pool, and this has served to identify certain KLKs as biomarkers for these diseases. In this review, we describe applications of this technology in KLK biomarker discovery and elucidate MS-based techniques that have been used for unbiased, global screening of KLK substrates within complex protein pools. Although MS-based KLK degradomic studies are limited to date, they helped to discover an array of novel KLK substrates. Substrates identified by MS-based degradomics are reported with improved confidence over those determined by incubating a purified or recombinant substrate and protease of interest, in vitro. We propose that these novel proteomic approaches represent the way forward for KLK research, in order to correlate proteolysis of biological substrates with tissue-related consequences, toward clinical targeting of KLK expression and function for cancer diagnosis, prognosis, and therapies.     

Mass spectrometry in clinical proteomics - from the present to the future

MS is an important analytical tool in clinical proteomics, primarily in the disease-specific discovery, identification and characterisation of proteomic biomarkers and patterns. MS-based proteomics is increasingly used in clinical validation and diagnostic method development. The latter departs from the typical application of MS-based proteomics by exchanging some of the high performance of analysis for the throughput, robustness and simplicity required for clinical diagnostics. Although conventional MS-based proteomics has become an important field in clinical applications, some of the most recent MS technologies have not yet been extensively applied in clinical proteomics. In this review, we will describe the current state of MS in clinical proteomics and look to the future of this field.     

Biomarker discovery in asthma and COPD by proteomic approaches

Asthma and chronic obstructive pulmonary disease (COPD) are multifactorial respiratory diseases, characterized by reversible and irreversible airway obstruction, respectively. Even if the primary causes of these diseases remain unknown, inflammation is a central feature that leads to progressive and permanent pulmonary tissue damage (airway remodeling) up to the total loss of lung function. Therefore, the elucidation of the inflammation mechanisms and the characterization of the biological pathways, involved in asthma and COPD pathogenesis, are relevant in finding new possible diagnostic/prognostic biomarkers and for the validation of new drug targets. In this context, current advances in proteomic approaches, especially those based on MS, provide new tools to facilitate the discovery-driven studies of new biomarkers in respiratory diseases and improve the clinical reliability of the next generation of biomarkers for these diseases consisting of multiple phenotypes. This review will report an overview of the current proteomic methods applied to the discovery of candidate biomarkers for asthma and COPD, giving a special emphasis to emerging MS-based techniques.     

Targeted proteomics strategy applied to biomarker evaluation

The evaluation of biomarker candidates, involving quantitative measurement of a large number of proteins in bodily fluids, remains the main obstruction in the development of a biomarker validation pipeline. Although immunoassays are commonly used, high-throughput and multiplex-capable methods are required for expediting the evaluation process. MS-based approaches employing targeted proteomic strategies provide not only a sensitive, but in addition a precise quantification tool, which is versatile, systematic, and scalable. Its capability of multiplexing hundreds of targets facilitate a cost-effective and rapid evaluation and is especially useful during the early stage of the process where a large list of candidate biomarkers must be triaged before entering validation studies. The robustness requirement for the methods also mandates a high degree of selectivity to analyze complex clinical samples. Improvement in the selectivity of LC-MS methods has been achieved by adopting high-resolution and high-accuracy mass analyzers to perform quantitative analyses with a novel method called parallel reaction monitoring. This article discusses the design and performance of biomarker evaluation studies using targeted proteomics strategies and the implementation of recent technology developments.     

Application of quantitative proteomics technologies to the biomarker discovery pipeline for multiple sclerosis

Multiple sclerosis is an inflammatory-mediated demyelinating disorder most prevalent in young Caucasian adults. The various clinical manifestations of the disease present several challenges in the clinic in terms of diagnosis, monitoring disease progression and response to treatment. Advances in MS-based proteomic technologies have revolutionized the field of biomarker research and paved the way for the identification and validation of disease-specific markers. This review focuses on the novel candidates discovered by the application of quantitative proteomics to relevant disease-affected tissues in both the human context and within the animal model of the disease known as experimental autoimmune encephalomyelitis. The role of targeted MS approaches for biomarker validation studies, such as multiple reaction monitoring will also be discussed.     

Immunoproteomics: From biomarker discovery to diagnostic applications

Circulating antibodies reflect a molecular imprint of antigens that are related to autoimmune diseases, cancer or infection. Importantly, serum antibodies are useful clinical markers as they carry diagnostic information from all around the human body. Moreover, the amplification cascade governed by the humoral immune system causes a surplus of circulating antibodies after appearance of the corresponding (low abundance) antigen. In combination with the fact that antibodies are highly stable compared to many other serum proteins, they seem ideal to be implemented in clinical diagnostic assays for the detection of antigen-associated diseases. This review summarises advances in immunoproteomics with respect to technologies for biomarker discovery, with special emphasis on recently developed gel-free MS-based approaches, and looks forward to potential immunoproteomic applications in diagnostic medicine.     

SEREX, Proteomex, AMIDA, and beyond: Serological screening technologies for target identification

Despite the great body of knowledge about the aetiology, pathogenesis, risk factors, and associated molecular processes, cancer remains a prime health concern. Over the past decades scientific and medical research focused on the identification of biomarkers and target molecules for the diagnosis and therapy of cancer. Such markers may allow for improved and early diagnosis, as well as for immunotherapeutic approaches for cancer treatment. A plethora of technologies dedicated to the identification of target molecules was developed including those relying on a humoral response against tumour-associated antigens (TAA) in diseased individuals. As for other diseases, cancers elicit immune responses that result in the induction of T and B lymphocytes specific for tumour-associated proteins, largely self-antigens, but also those comprising viral and bacterial proteins. Cancer-specific serum antibodies are of great use for the isolation and subsequent identification of their cognate antigens. The present review will concentrate on three major serological target identification methods, i.e. SEREX, Proteomex, and AMIDA, concluding with a summary of the milestones in the clinical advancement and applications of serological TAA.     

Biomarkers of colorectal cancer: Recent advances and future challenges

Colorectal cancer (CRC) is a common malignancy and it contributes significantly to cancer mortality. Outcomes in colorectal cancer vary between patients and this is due to the complexity of colorectal carcinogenesis. Interactions between tumor cells and their microenvironment, genetic alterations, and changes in intracellular signalling networks are just some of the abnormal pathways involved in colorectal cancer development. Recent research has targeted components of all of these systems in order to develop biomarkers to aid in the early diagnosis of CRC and to assist in prognostic stratification. Proteomic analysis of tissue or blood-derived samples from CRC patients has proven to be a valuable technique for the identification of potentially informative biomarkers. Such biomarkers may prove to be clinically applicable and could offer greater patient acceptability when compared to conventional methods such as fecal-based testing. In this article we review the recent advances in the development of protein biomarkers of CRC with an emphasis on biomarkers available in the patient's serum and from tissue-based samples. Future challenges in terms of the development of accurate diagnostic, prognostic, and predictive biomarkers of CRC and the importance of validation and patient acceptability are also discussed.     

Quantitative proteomics in cardiovascular research: Global and targeted strategies

Extensive technical advances in the past decade have substantially expanded quantitative proteomics in cardiovascular research. This has great promise for elucidating the mechanisms of cardiovascular diseases and the discovery of cardiac biomarkers used for diagnosis and treatment evaluation. Global and targeted proteomics are the two major avenues of quantitative proteomics. While global approaches enable unbiased discovery of altered proteins via relative quantification at the proteome level, targeted techniques provide higher sensitivity and accuracy, and are capable of multiplexed absolute quantification in numerous clinical/biological samples. While promising, technical challenges need to be overcome to enable full utilization of these techniques in cardiovascular medicine. Here, we discuss recent advances in quantitative proteomics and summarize applications in cardiovascular research with an emphasis on biomarker discovery and elucidating molecular mechanisms of disease. We propose the integration of global and targeted strategies as a high-throughput pipeline for cardiovascular proteomics. Targeted approaches enable rapid, extensive validation of biomarker candidates discovered by global proteomics. These approaches provide a promising alternative to immunoassays and other low-throughput means currently used for limited validation.     

Searching for potential biomarkers of cisplatin resistance in human ovarian cancer using a label-free LC/MS-based protein quantification method

Platinum-based chemotherapy, such as cisplatin, is the primary treatment for ovarian cancer. However, drug resistance has become a major impediment to the successful treatment of ovarian cancer. To date, the molecular mechanisms of resistance to platinum-based chemotherapy remain unclear. In this study, we applied an LC/MS-based protein quantification method to examine the global protein expression of two pairs of ovarian cancer cell lines, A2780/A2780-CP (cisplatin-sensitive/cisplatin-resistant) and 2008/2008-C13*5.25 (cisplatin-sensitive/cisplatin-resistant). We identified and quantified over 2000 proteins from these cell lines and 760 proteins showed significant expression changes with a false discovery rate of less than 5% between paired groups. Based on the results we obtained, we suggest several potential pathways that may be involved in cisplatin resistance in human ovarian cancer. This study provides not only a new proteomic platform for large-scale quantitative protein analysis, but also important information for discovery of potential biomarkers of cisplatin resistance in ovarian cancer. Furthermore, these results may be clinically relevant for diagnostics, prognostics, and therapeutic improvement for ovarian cancer treatment.     

Characterisation of tumoral markers correlated with ErbB2 (HER2/Neu) overexpression and metastasis in breast cancer

The receptor tyrosine kinase ErbB2 (HER2/neu) is overexpressed in ?30% of breast cancers and is associated with poor prognosis and an increased likelihood of metastasis. Clinical treatments such as trastuzumab are effective in less than 35% of women diagnosed as ErbB2‐positive, highlighting the necessity of searching for novel targets and alternative therapies. Herein, a proteomic screening strategy combining quantitative‐based gel electrophoresis and MS was used to compare the protein expression of 48 normal human breast and tumour tissues differing in ErbB2 expression and lymph node status. The aim was to identify proteins associated with the aggressive phenotype of ErbB2‐positive breast cancer which could be potential biomarkers of the disease as well as therapy targets. In total, 177 protein isoforms (107 gene products) differentially expressed between tissue groups were identified. Immunohistochemical staining of a tissue‐microarray was used for validation of selected protein candidates. We found that expression of HSP90α, laminin and GSTP1 significantly correlated with ErbB2 expression, while others such as AGR2, NM23H1 and Annexin 2 were overexpressed in greater than 40% of tumours. Finally, knocking‐down the expression by RNA interference of three candidates, AGR2, Transgelin2 and NM23H1 resulted in an enhanced invasive capacity of MDA‐MB435 cells. These data support the involvement of these targets in tumour progression and identify them as novel biomarkers of the disease.     

Surface enhanced Raman spectroscopy and its application to molecular and cellular analysis

In this paper, we review the state-of-the-art in surface-enhanced Raman scattering (SERS) based optical detection techniques with an application focus on cancer diagnostics. As we describe herein, SERS has several analytical, biological and engineering advantages over other methods including extremely high sensitivity, inherent molecular specificity of unlabeled targets, and narrow spectral bands. We review advances in both in vitro and in vivo applications of SERS and examine how technical issues with the technology are being addressed. A special technology focus is given to emerging optofluidic devices which aim to merge microfluidic and optical detection technologies into simple packages. We conclude with a brief discussion of some of the emerging challenges in the field and some of the approaches that are likely to enhance their application. Y. S. Huh and A. J. Chung contributed equally.     

Clinical applications of capillary electrophoresis coupled to mass spectrometry in biomarker discovery: Focus on bladder cancer

A major requirement in the application of proteins as clinical biomarkers is that they provide a highly sensitive and specific result in disease assessment. Since single biomarkers are generally of limited accuracy, a group or panel of well-characterized biomarkers appears appropriate, providing a more robust and sensitive MS-based analytical platform. CE coupled to MS has been successfully used in biomarker discovery and application, as it enables the selective detection of peptides and small proteins, combining the high separation capacity of CE with the advanced sensitivity of MS. CE-MS allows the characterization of highly complex samples (such as urine, plasma, and other biofluids) in a consistent and reproducible way. It has a range of applications, many focusing especially in studies on urinary peptide biomarkers in kidney and cardiovascular diseases. Another major field of interest has been malignancy of the genitourinary system. In the first part of this review, we cover technical aspects and performance characteristics of CE-MS, with special focus on the requirements for biomarker discovery and clinical application. In the second part, we review the potential and development of CE-MS in the management of genitourinary cancers, especially bladder cancer. CE-MS has been employed in several studies aimed at discovering biomarkers for bladder cancer that may be useful in diagnosis, monitoring for recurrence, and prediction of the risk for the muscle-invasive stage. In the last part of the review, we discuss current challenges and provide an outlook for ongoing and possible future developments.     

Proteomics studies of pancreatic cancer

Pancreatic cancer is the fourth leading cause of cancer death in the United States, with 4% survival 5 years after diagnosis. Biomarkers are desperately needed to improve earlier, more curable cancer diagnosis and to develop new effective therapeutic targets. The development of quantitative proteomics technologies in recent years offers great promise for understanding the complex molecular events of tumorigenesis at the protein level, and has stimulated great interest in applying the technology for pancreatic cancer studies. Proteomic studies of pancreatic tissues, juice, serum/plasma, and cell lines have recently attempted to identify differentially expressed proteins in pancreatic cancer to dissect the abnormal signaling pathways underlying oncogenesis, and to detect new biomarkers. It can be expected that the continuing evolution of proteomics technology with better resolution and sensitivity will greatly enhance our capability in combating pancreatic cancer.     

Ensembles of protein termini and specific proteolytic signatures as candidate biomarkers of disease

Early accurate diagnosis and personalized treatment are essential in order to treat complex or fatal diseases such as cancer and autoimmune, cardiovascular and neurodegenerative diseases. To realize this vision, new diagnostic and prognostic biomarkers are urgently required. MS-based proteomics is the most promising approach for protein biomarker identification, but suffers in clinical translation of biomarker candidates that show only quantitative differences from normal tissue. Indeed, success in translating proteomic data to biomarkers in the clinic has been disappointing. Here, we propose that protein termini provide a new opportunity for biomarker discovery due to qualitative differences in intact and new protein termini between diseased and normal tissues. Altered proteolysis occurs in most pathologies. Disease- and process-specific protein modifications, including proteolytic processing and subsequent modification of the terminal amino acids, frequently lead to altered protein activity that plays key roles in the disease process. Thus, mapping of ensembles of characteristic protein termini provides a proteolytic signature of high information content that shows both quantitative and most importantly qualitative differences in different diseases and stage of disease. These unique protein biomarkers have the added benefit of being mechanistically informative by revealing the activity state of the bioactive protein. Moreover, proteome-wide isolation of protein termini leads to generalized sample simplification, thereby enabling up to three orders of magnitude lower LODs compared to traditional shotgun proteomic approaches. We introduce the potential of protein termini for biomarker discovery, briefly review methods enabling large-scale studies of protein termini, and discuss how these may be integrated into a termini-oriented biomarker discovery pipeline from discovery to clinical application.