Antibody microarray-based oncoproteomics

The driving force behind oncoproteomics is the belief that certain protein signatures or patterns exist that are associated with a particular malignancy. If so, the correlation of clinical parameters with defined protein expression patterns would allow us to predict disease progression and perhaps even postulate improved therapeutic modalities. The technological challenges to achieve these goals are significant, as the human proteome is not defined. No general methodological approach exists today, and human cancer can, furthermore, be divided into several disease subgroups. One potential solution to finding cancer-associated protein signatures is the emerging technology of affinity proteomics. This approach addresses some of the shortcomings of traditional proteomics and combines it with the power of microarrays. The present review focuses on the role of antibody microarrays in oncoproteomics and its potential to provide a truly proteome-wide analytical approach.     

Reverse-phase protein microarrays for tissue-based analysis

The deciphering of the human genome has elucidated our biological structural design and has generated insights into disease development and pathogenesis. At the same time, knowledge of genetic changes during disease processes has demonstrated the need to move beyond genomics towards proteomics and a systems biology approach to science. Analyzing the proteome comprises more than just a numeration of proteins. In fact, it characterizes proteins within cells in the context of their functional status and interactions in their physiological micro- and macroenvironments. As dysregulated signaling often underpins most human diseases, an overarching goal of proteomics is to profile the working state of signaling pathways, to develop 'circuit maps' of normal and diseased protein networks and identify hyperactive, defective or inoperable transduction pathways. Reverse-phase protein microarrays represent a new technology that can generate a multiplex readout of dozens of phosphorylated events simultaneously to profile the state of a signaling pathway target even after the cell is lyzed and the contents denatured.     

Use of proteomic analysis to monitor responses to biological therapies

Proteomics has the potential to revolutionise diagnosis and disease management. Serum protein pattern profiling by surface-enhanced laser desorption/ionisation time of flight (SELDI-TOF) mass spectrometry is emerging as a novel approach to discover protein patterns capable of distinguishing disease and disease-free states with high sensitivity and specificity. This method has shown great promise for early diagnosis of ovarian cancer and is being applied to a range of pathological states. Protein microarray technology is being evaluated as a new means to track biological responses to therapy. Through the measurement of key protein phosphorylation sites at different stages of disease progression or before and after treatment, protein signal pathways can be mapped and thus become the starting point for individualised therapy. Laser capture microdissection (LCM) coupled with immunostaining of protein microarrays allows isolation of pure cell populations and relative quantitation of phosphorylated and non-phosphorylated forms of the cell’s key signalling proteins. This technology is currently in use at the National Institutes of Health in Phase II clinical trials of metastatic breast and ovarian cancer. Cell survival and apoptotic protein pathways are monitored as biological markers of disease progression in these clinical trials. Proteomic technologies, such as serum protein pattern profiling, combined with protein microarray technologies, constitute a new paradigm for detecting disease and monitoring disease response to therapy. Ultimately, proteomics and genomics will become integrated into cancer patient management through the design and tracking of individualised therapy.     

Use of proteomic analysis to monitor responses to biological therapies

Proteomics has the potential to revolutionise diagnosis and disease management. Serum protein pattern profiling by surface-enhanced laser desorption/ionisation time of flight (SELDI-TOF) mass spectrometry is emerging as a novel approach to discover protein patterns capable of distinguishing disease and disease-free states with high sensitivity and specificity. This method has shown great promise for early diagnosis of ovarian cancer and is being applied to a range of pathological states. Protein microarray technology is being evaluated as a new means to track biological responses to therapy. Through the measurement of key protein phosphorylation sites at different stages of disease progression or before and after treatment, protein signal pathways can be mapped and thus become the starting point for individualised therapy. Laser capture microdissection (LCM) coupled with immunostaining of protein microarrays allows isolation of pure cell populations and relative quantitation of phosphorylated and non-phosphorylated forms of the cell's key signalling proteins. This technology is currently in use at the National Institutes of Health in Phase II clinical trials of metastatic breast and ovarian cancer. Cell survival and apoptotic protein pathways are monitored as biological markers of disease progression in these clinical trials. Proteomic technologies, such as serum protein pattern profiling, combined with protein microarray technologies, constitute a new paradigm for detecting disease and monitoring disease response to therapy. Ultimately, proteomics and genomics will become integrated into cancer patient management through the design and tracking of individualised therapy.     

High-throughput proteomics using antibody microarrays: an update

Antibody-based microarrays are a rapidly emerging technology that has advanced from the first proof-of-concept studies to demanding serum protein profiling applications during recent years, displaying great promise within disease proteomics. Miniaturized micro- and nanoarrays can be fabricated with an almost infinite number of antibodies carrying the desired specificities. While consuming only minute amounts of reagents, multiplexed and ultrasensitive assays can be performed targeting high- as well as low-abundance analytes in complex nonfractionated proteomes. The microarray images generated can then be converted into protein expression profiles or protein atlases, revealing a detailed composition of the sample. The technology will provide unique opportunities for fields such as disease diagnostics, biomarker discovery, patient stratification, predicting disease recurrence and drug target discovery. This review describes an update of high-throughput proteomics, using antibody-based microarrays, focusing on key technological advances and novel applications that have emerged over the last 3 years.     

Oncoproteomics

Researchers have long acknowledged that changes in genes or gene activity lead to cancer. However, it was difficult to understand the function of such specific genes and their interaction in communication networks and the roles played by their protein products in molecular pathways. Protein molecules have direct influences on the development of cancer as it fundamentally arises due to aberrant signaling pathways. Identifying and understanding these changes is the primary theme of cancer proteomics, also termed as oncoproteomics. The ultimate objective of oncoproteomics is to acclimatize proteomic technologies for regular use in clinical laboratories for the purpose of diagnostic and prognostic categorization of disease condition, as well as in assessing drug toxicity and efficiency. Information gained from such technologies may soon exert a spectacular change in cancer research and impact dramatically on the care of cancer patients. Investigations of tumor-specific proteomic profiles may also allow better understanding of tumor development and the identification of novel targets for cancer therapy. In this review, we have tried to offer a wide perspective on recent progresses in proteomic research strategies, their applications in the discovery of novel tumor markers and drug targets and their role in illustrating action mechanisms of biomarkers and anticancer drugs including drug resistance.     

Gene expression-driven diagnostics and pharmacogenomics in cancer

The advancement of microarray technologies for characterizing tumors at the gene expression level has made a significant impact on the field of oncology. Profiling gene expression of various human tumors has led to the identification of gene expression patterns or signatures related to tumor classification, disease outcome and response to therapy. This technology can also be used to study the mechanism of action of specific therapeutics. Routine application of microarrays in clinical practice will require significant efforts to standardize the array manufacturing techniques, assay protocols and analytical methods used to interpret the data. Extensive, independent validation using large, statistically sound datasets will also be necessary. Studies on gene expression profiling of clinically relevant tissue samples with the aim of finding gene markers to support disease prognosis and therapy decisions are reviewed.     

Understanding proteomics

The purpose of this article is to describe proteomics, to discuss the importance of proteomics, to review different methods for protein measurement, and to illustrate how knowledge of proteomics might improve patient care. Among common laboratory determinations are those involving enzymatic (protein) function. Although the presence or activity of proteins may be seen clinically as incidental, proteins represent the engines through which critical life processes ensue. A selected review of the literature is presented to define and explain proteomics and to review the various techniques to measure proteins. A case-study approach is used to illustrate how proteomics can be utilized for detecting and monitoring disease. The human genome has been completely sequenced and proteomics has emerged as a way to unravel the biochemical and physiological mechanisms of diseases at the functional level. This review includes the recent discoveries regarding proteomics and its importance in the detection and treatment of disease.     

Functional proteomics: mapping protein-protein interactions and pathways

The function of a protein is defined by its interactions with other proteins and molecules. Mapping of protein interactions can highlight new functionalities for a known protein or can even define the function of novel proteins. With the draft sequence of the human genome now available, it is possible to perform high-throughput mapping of protein-protein interactions in humans, which is termed as functional proteomics. The developments in functional proteomics are particularly timely since pharmaceutical companies are searching for technologies that will strengthen their genomic efforts and prioritize their drug discovery pipeline. In this article we review recent developments in functional proteomics.     

组织芯片技术的发展及应用

组织芯片技术为进行多种肿瘤的多指标(DNA、mRNA、蛋白指标)高通量原位分析提供了时间、空间和资源的可行性并最大程度上保证实验条件的一致，可广泛应用于肿瘤候选基因及其临床特性的确定、肿瘤预后的判断、肿瘤免疫治疗效果的评价以及肿瘤的分子诊断、肿瘤治疗靶点的筛选，显著加速基因组学和蛋白组学成果在肿瘤临床中的应用。     

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 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.     

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.     

DNA diagnosis in hematologic malignancies

Genetic microarrays applied to hematologic malignancies identified a number of subgroups with a defined gene expression pattern, which were not identified by morphology, cytogenetics or molecular genetics. In many cases, these expression patterns links tumor cells to the normal developmental counterpart, and represent distinct disease subgroups with different clinical presentations and outcomes. Furthermore, genetic microarrays will be useful in predicting prognosis and identifying novel target of therapy.     

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.     

Oral cancer proteomics

Proteomics is a novel molecular profiling technology that may significantly accelerate human cancer research. This review summarizes recent progress in oral cancer proteomics and discusses potential applications in this emerging field. With the rapid development of proteomics tools, this technology platform will be utilized to discover highly sensitive and specific protein markers for cancer diagnosis and prognosis, elucidate the molecular determinants and key signal pathways underlying the disease mechanism, identify novel therapeutic targets and assess drug efficacy and toxicity, and to monitor treatment response and the relapse of the cancer. These proteomic applications may collectively facilitate the early detection and successful treatment of this devastating disease in the future.     

Urine proteomics and biomarkers in renal disease

The application of urine proteomics is a useful approach to the study of the proteins involved in healthy and diseased kidneys and may provide a noninvasive approach to assess disease activity and to monitor clinical response in patients with renal diseases. This technique may provide an additional tool in clinical trials and for the assessment of prognosis for patients. Both soluble proteins and membrane-bound (exosomal) proteins may be studied, and multiple approaches are available. Discovery proteomics is an unbiased approach to detect novel proteins in urine samples. Mass spectrometry (MS) is often needed to identify specific protein fragments. Targeted proteomics often involves specific immunoassays or modified MS, which enables a hypothesis-based design. These approaches may be integrated. For example, specific proteins may be identified by the discovery approach or laboratory study of disease mechanisms. These proteins will then be studied further by targeted proteomics. In order to translate to clinical practice, the specific assays need vigorous validation by means of sufficiently statistically powered clinical trials.     

Urinary proteomics

Protein measurement in urine has been used for many years for the diagnosis and monitoring of renal disease. The pattern of urinary protein excretion can be used to identify the cause of the disease and to classify proteinuria. In recent years, proteomics has proven to be a powerful tool in investigation and clinical medicine. Proteomics employs a protein separation method and the identification of proteins using mass spectrometry. One of the objectives of clinical proteomics is the identification of biological markers of disease. To accomplish this, it is necessary to have a normal proteome of the medium in question, which in our case is urine. Comparison of the normal urinary proteome with the urinary proteome from patients with a defined disease can detect proteins expressed differentially from one another. The aim of this review is to present the situation of urinary proteomics, putting special emphasis on its application in the diagnosis of glomerular diseases, renal allograft rejection, urological cancers and urolithiasis.