Application of oncoproteomics to aberrant signalling networks in changing the treatment paradigm in acute lymphoblastic leukaemia

Oncoproteomics is an important innovation in the early diagnosis, management and development of personalized treatment of acute lymphoblastic leukaemia (ALL). As inherent factors are not completely known – e.g. age or family history, radiation exposure, benzene chemical exposure, certain viral exposures such as infection with the human T‐cell lymphoma/leukaemia virus‐1, as well as some inherited syndromes may raise the risk of ALL – each ALL patient may modify the susceptibility of therapy. Indeed, we consider these unknown inherent factors could be explained via coupling cytogenetics plus proteomics, especially when proteins are the ones which play function within cells. Innovative proteomics to ALL therapy may help to understand the mechanism of drug resistance and toxicities, which in turn will provide some leads to improve ALL management. Most important of these are shotgun proteomic strategies to unravel ALL aberrant signalling networks. Some shotgun proteomic innovations and bioinformatic tools for ALL therapies will be discussed. As network proteins are distinctive characteristics for ALL patients, unrevealed by cytogenetics, those network proteins are currently an important source of novel therapeutic targets that emerge from shotgun proteomics. Indeed, ALL evolution can be studied for each individual patient via oncoproteomics.     

Biomarkers in cancer screening,research and detection: present and future: a review

Biomarkers provide a powerful and dynamic approach to understanding the spectrum of malignancies with applications in observational and analytic epidemiology, randomized clinical trials, screening, diagnosis and prognosis. Defined as alterations in the constituents of tissues or body fluids, these markers offer a means for homogeneous classification of a disease and risk factor, and they can extend one's basic information about the underlying pathogenesis of disease. The goals in cancer research include finding biomarkers that can be used for the early detection of cancers, design individual therapies, and to identify underlying processes involved in the disease. Because so many myriad processes are involved in the diseased states, the goal is similar to ‘finding a needle in a haystack’. However, the development of many -omic technologies, such as genomics and proteomics, has allowed us to monitor a large number of key cellular pathways simultaneously. This has enabled the identification of biomarkers and signalling molecules associated with cell growth, cell death and cellular metabolism. These are also facilitating in monitoring the functional disturbance, molecular and cellular damage, and damage response. This brief review describes the development of biomarkers in cancer research and detection with emphasis on different proteomic tools for the identification and discovery of new biomarkers, different clinical assays to detect various biomarkers in different specimens, role of biomarkers in cancer screening and last but not the least, the challenges in this direction of cancer research.     

Discovery of regulatory molecular events and biomarkers using 2D capillary chromatography and mass spectrometry

An important component of proteomic research is the high-throughput discovery of novel proteins and protein-protein interactions that control molecular events that contribute to critical cellular functions and human disease. The interactions of proteins are essential for cellular functions. Identifying perturbation of normal cellular protein interactions is vital for understanding the disease process and intervening to control the disease. A second area of proteomics research is the discovery of proteins that will serve as biomarkers for the early detection, diagnosis and drug treatment response for specific diseases. These studies have been referred to as clinical proteomics. To discover biomarkers, proteomics research employs the quantitative comparison of peptide and protein expression in body fluids and tissues from diseased individuals (case) versus normal individuals (control). Methods that couple 2D capillary liquid chromatography (LC) and tandem mass spectrometry (MS/MS) analysis have greatly facilitated this discovery science. Coupling 2D-LC/MS/MS analysis with automated genome-assisted spectra interpretation allows a direct, high-throughput and high-sensitivity identification of thousands of individual proteins from complex biological samples. The systematic comparison of experimental conditions and controls allows protein function or disease states to be modeled. This review discusses the different purification and quantification strategies that have been developed and used in combination with 2D-LC/MS/MS and computational analysis to examine regulatory protein networks and clinical samples.     

Discovery of regulatory molecular events and biomarkers using 2D capillary chromatography and mass spectrometry

An important component of proteomic research is the high-throughput discovery of novel proteins and protein–protein interactions that control molecular events that contribute to critical cellular functions and human disease. The interactions of proteins are essential for cellular functions. Identifying perturbation of normal cellular protein interactions is vital for understanding the disease process and intervening to control the disease. A second area of proteomics research is the discovery of proteins that will serve as biomarkers for the early detection, diagnosis and drug treatment response for specific diseases. These studies have been referred to as clinical proteomics. To discover biomarkers, proteomics research employs the quantitative comparison of peptide and protein expression in body fluids and tissues from diseased individuals (case) versus normal individuals (control). Methods that couple 2D capillary liquid chromatography (LC) and tandem mass spectrometry (MS/MS) analysis have greatly facilitated this discovery science. Coupling 2D-LC/MS/MS analysis with automated genome-assisted spectra interpretation allows a direct, high-throughput and high-sensitivity identification of thousands of individual proteins from complex biological samples. The systematic comparison of experimental conditions and controls allows protein function or disease states to be modeled. This review discusses the different purification and quantification strategies that have been developed and used in combination with 2D-LC/MS/MS and computational analysis to examine regulatory protein networks and clinical samples.     

Redox proteomics: from residue modifications to putative biomarker identification by gel- and LC-MS-based approaches

Quantitative determination of reactive oxygen species and reactive nitrogen species in body fluids, tissues or cells has always been problematic due to their high chemical reactivity and the resulting short half-life. This high reactivity may involve reversible and/or irreversible protein modifications, in particular the covalent oxidative modification of specific amino acid residues. Thus, the occurrence of reactive oxygen species and reactive nitrogen species can be monitored indirectly from the identification of specific protein-chemical footprints. In combination with classical gel-based proteomics or liquid chromatography labeling or label-free techniques, mass spectrometry has emerged as a powerful tool to identify these protein modifications in biological samples. In this review, we present the main methodological approaches for gel-based proteomics and quantitative mass spectrometry applied to oxidative protein modifications, mainly Cys. Representative examples from their application in identifying respective biomarkers in diseases related to oxidative stress are also presented.     

Proteomic contributions to personalized cancer care

Cancer impacts each patient and family differently. Our current understanding of the disease is primarily limited to clinical hallmarks of cancer, but many specific molecular mechanisms remain elusive. Genetic markers can be used to determine predisposition to tumor development, but molecularly targeted treatment strategies that improve patient prognosis are not widely available for most cancers. Individualized care plans, also described as personalized medicine, still must be developed by understanding and implementing basic science research into clinical treatment. Proteomics holds great promise in contributing to the prevention and cure of cancer because it provides unique tools for discovery of biomarkers and therapeutic targets. As such, proteomics can help translate basic science discoveries into the clinical practice of personalized medicine. Here we describe how biological mass spectrometry and proteome analysis interact with other major patient care and research initiatives and present vignettes illustrating efforts in discovery of diagnostic biomarkers for ovarian cancer, development of treatment strategies in lung cancer, and monitoring prognosis and relapse in multiple myeloma patients.     

Biomarkers in cancer screening, research and detection: present and future: a review

Biomarkers provide a powerful and dynamic approach to understanding the spectrum of malignancies with applications in observational and analytic epidemiology, randomized clinical trials, screening, diagnosis and prognosis. Defined as alterations in the constituents of tissues or body fluids, these markers offer a means for homogeneous classification of a disease and risk factor, and they can extend one's basic information about the underlying pathogenesis of disease. The goals in cancer research include finding biomarkers that can be used for the early detection of cancers, design individual therapies, and to identify underlying processes involved in the disease. Because so many myriad processes are involved in the diseased states, the goal is similar to 'finding a needle in a haystack'. However, the development of many -omic technologies, such as genomics and proteomics, has allowed us to monitor a large number of key cellular pathways simultaneously. This has enabled the identification of biomarkers and signalling molecules associated with cell growth, cell death and cellular metabolism. These are also facilitating in monitoring the functional disturbance, molecular and cellular damage, and damage response. This brief review describes the development of biomarkers in cancer research and detection with emphasis on different proteomic tools for the identification and discovery of new biomarkers, different clinical assays to detect various biomarkers in different specimens, role of biomarkers in cancer screening and last but not the least, the challenges in this direction of cancer research.     

Cell‐free microRNAs in blood and other body fluids,as cancer biomarkers

The discovery of cell‐free microRNAs (miRNAs) in serum, plasma and other body fluids has yielded an invaluable potential source of non‐invasive biomarkers for cancer and other non‐malignant diseases. miRNAs in the blood and other body fluids are highly stable in biological samples and are resistant to environmental conditions, such as freezing, thawing or enzymatic degradation, which makes them convenient as potential biomarkers. In addition, they are more easily sampled than tissue miRNAs. Altered levels of cell‐free miRNAs have been found in every type of cancer analysed, and increasing evidence indicates that they may participate in carcinogenesis by acting as cell‐to‐cell signalling molecules. This review summarizes the biological characteristics and mechanisms of release of cell‐free miRNAs that make them promising candidates as non‐invasive biomarkers of cancer.     

Methylated DNA/RNA in Body Fluids as Biomarkers for Lung Cancer

DNA/RNA methylation plays an important role in lung cancer initiation and progression. Liquid biopsy makes use of cells, nucleotides and proteins released from tumor cells into body fluids to help with cancer diagnosis and prognosis. Methylation of circulating tumor DNA (ctDNA) has gained increasing attention as biomarkers for lung cancer. Here we briefly introduce the biological basis and detection method of ctDNA methylation, and review various applications of methylated DNA in body fluids in lung cancer screening, diagnosis, prognosis, monitoring and treatment prediction. We also discuss the emerging role of RNA methylation as biomarkers for cancer.     

O-acetylated sialic acids: Multifaceted role in childhood acute lymphoblastic leukaemia

Childhood acute lymphoblastic leukaemia (ALL), a malignant transformation of the lymphoblasts, is highly responsive to chemotherapy. However, due to certain inadequacy in detection of minimal residual disease (MRD), relapse is a common phenomenon. To address this question, the present review deals with the induction of an unique O-acetyl derivative of sialic acid on a few disease-associated glycoproteins and glycolipids at the onset of childhood ALL, a finding of our group in the last decade. This information has been successfully utilized for diagnosis and prognosis of the disease. Existing literature is included for comparison. Additionally, cell surface overexpression of 9-O-acetylated sialoglycoproteins and antibodies against them present in patients' sera aid the survival of the malignant lymphoblasts and suggest a multifaceted role played by these molecules. Taken together, monitoring these molecules helps not only in unravelling the biology of this paediatric malignancy but also in personalizing the treatment strategies for the betterment of the patient population.     

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.     

Clinical proteomics in obstetrics and neonatology

Clinical proteomics has been applied to the identification of biomarkers of obstetric and neonatal disease. We will discuss a number of encouraging studies that have led to potentially valid biomarkers in the context of Down's syndrome, preterm birth, amniotic infections, preeclampsia, intrauterine growth restriction and obstructive uropathies. Obtaining noninvasive biomarkers (e.g., from the maternal circulation, urine or cervicovaginal fluid) may be more feasible for obstetric diseases than for diseases of the fetus, for which invasive methods are required (e.g., amniotic fluid, fetal urine). However, studies providing validated proteomics-identified biomarkers are limited. Efforts should be made to save well-characterized samples of these invasive body fluids so that many valid biomarkers of pregnancy-related diseases will be identified in the coming years using proteomics based analysis upon adoption of ‘clinical proteomics guidelines’.     

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

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

Clinical and Technical Phosphoproteomic Research

An encouraging approach for the diagnosis and effective therapy of immunological pathologies, which would include cancer, is the identification of proteins and phosphorylated proteins. Disease proteomics, in particular, is a potentially useful method for this purpose. A key role is played by protein phosphorylation in the regulation of normal immunology disorders and targets for several new cancer drugs and drug candidates are cancer cells and protein kinases. Protein phosphorylation is a highly dynamic process. The functioning of new drugs is of major importance as is the selection of those patients who would respond best to a specific treatment regime. In all major aspects of cellular life signalling networks are key elements which play a major role in inter- and intracellular communications. They are involved in diverse processes such as cell-cycle progression, cellular metabolism, cell-cell communication and appropriate response to the cellular environment. A whole range of networks that are involved in the regulation of cell development, differentiation, proliferation, apoptosis, and immunologic responses is contained in the latter. It is so necessary to understand and monitor kinase signalling pathways in order to understand many immunology pathologies. Enrichment of phosphorylated proteins or peptides from tissue or bodily fluid samples is required. The application of technologies such as immunoproteomic techniques, phosphoenrichments and mass spectrometry (MS) is crucial for the identification and quantification of protein phosphorylation sites in order to advance in clinical research. Pharmacodynamic readouts of disease states and cellular drug responses in tumour samples will be provided as the field develops. We aim to detail the current and most useful techniques with research examples to isolate and carry out clinical phosphoproteomic studies which may be helpful for immunology and cancer research. Different phosphopeptide enrichment and quantitative techniques need to be combined to achieve good phosphopeptide recovery and good up- and-down phospho-regulation protein studies.     

Cellular and extracellular miRNAs are blood‐compartment‐specific diagnostic targets in sepsis

Septic shock is a common medical condition with a mortality approaching 50% where early diagnosis and treatment are of particular importance for patient survival. Novel biomarkers that serve as prompt indicators of sepsis are urgently needed. High‐throughput technologies assessing circulating microRNAs represent an important tool for biomarker identification, but the blood‐compartment specificity of these miRNAs has not yet been investigated. We characterized miRNA profiles from serum exosomes, total serum and blood cells (leukocytes, erythrocytes, platelets) of sepsis patients by next‐generation sequencing and RT‐qPCR (n = 3 × 22) and established differences in miRNA expression between blood compartments. In silico analysis was used to identify compartment‐specific signalling functions of differentially regulated miRNAs in sepsis‐relevant pathways. In septic shock, a total of 77 and 103 miRNAs were down‐ and up‐regulated, respectively. A majority of these regulated miRNAs (14 in serum, 32 in exosomes and 73 in blood cells) had not been previously associated with sepsis. We found a distinctly compartment‐specific regulation of miRNAs between sepsis patients and healthy volunteers. Blood cellular miR‐199b‐5p was identified as a potential early indicator for sepsis and septic shock. miR‐125b‐5p and miR‐26b‐5p were uniquely regulated in exosomes and serum, respectively, while one miRNA (miR‐27b‐3p) was present in all three compartments. The expression of sepsis‐associated miRNAs is compartment‐specific. Exosome‐derived miRNAs contribute significant information regarding sepsis diagnosis and survival prediction and could serve as newly identified targets for the development of novel sepsis biomarkers.     

Current strategies and findings in clinically relevant post-translational modification-specific proteomics

Mass spectrometry-based proteomics has considerably extended our knowledge about the occurrence and dynamics of protein post-translational modifications (PTMs). So far, quantitative proteomics has been mainly used to study PTM regulation in cell culture models, providing new insights into the role of aberrant PTM patterns in human disease. However, continuous technological and methodical developments have paved the way for an increasing number of PTM-specific proteomic studies using clinical samples, often limited in sample amount. Thus, quantitative proteomics holds a great potential to discover, validate and accurately quantify biomarkers in body fluids and primary tissues. A major effort will be to improve the complete integration of robust but sensitive proteomics technology to clinical environments. Here, we discuss PTMs that are relevant for clinical research, with a focus on phosphorylation, glycosylation and proteolytic cleavage; furthermore, we give an overview on the current developments and novel findings in mass spectrometry-based PTM research.     

Time‐resolved quantitative proteome profiling of host–pathogen interactions: The response of Staphylococcus aureus RN1HG to internalisation by human airway epithelial cells

Staphylococcus aureus is a versatile Gram‐positive pathogen that gains increasing importance due to the rapid spreading of resistances. Functional genomics technologies can provide new insights into the adaptational network of this bacterium and its response to environmental challenges. While functional genomics technologies, including proteomics, have been extensively used to study these phenomena in shake flask cultures, studies of bacteria from in vivo settings lack behind. Particularly for proteomics studies, the major bottleneck is the lack of sufficient proteomic coverage for low numbers of cells. In this study, we introduce a workflow that combines a pulse‐chase stable isotope labelling by amino acids in cell culture approach with high capacity cell sorting, on‐membrane digestion, and high‐sensitivity MS to detect and quantitatively monitor several hundred S. aureus proteins from a few million internalised bacteria. This workflow has been used in a proof‐of‐principle experiment to reveal changes in levels of proteins with a function in protection against oxidative damage and adaptation of cell wall synthesis in strain RN1HG upon internalisation by S9 human bronchial epithelial cells.     

Discrete logic modelling as a means to link protein signalling networks with functional analysis of mammalian signal transduction

Large‐scale protein signalling networks are useful for exploring complex biochemical pathways but do not reveal how pathways respond to specific stimuli. Such specificity is critical for understanding disease and designing drugs. Here we describe a computational approach—implemented in the free CNO software—for turning signalling networks into logical models and calibrating the models against experimental data. When a literature‐derived network of 82 proteins covering the immediate‐early responses of human cells to seven cytokines was modelled, we found that training against experimental data dramatically increased predictive power, despite the crudeness of Boolean approximations, while significantly reducing the number of interactions. Thus, many interactions in literature‐derived networks do not appear to be functional in the liver cells from which we collected our data. At the same time, CNO identified several new interactions that improved the match of model to data. Although missing from the starting network, these interactions have literature support. Our approach, therefore, represents a means to generate predictive, cell‐type‐specific models of mammalian signalling from generic protein signalling networks.     

Towards targeting signalling networks by functional phosphoproteomics

We present the development of Proteo-Mode, an instrument for automated, high-throughput preparation of phosphoproteins for proteomics analysis of complex cellular signalling networks involving multiple, time-dependent protein phosphorylation events. Proteo-Mode automates all steps in the network analysis of phosphoproteins by proteomics method. This enables the integrated response of complex cellular signalling networks to be analyzed in normal and abnormal (disease) states and provides new perspectives in targeting and evaluation of the effects of therapeutic compounds on such networks.