Quantitative mass spectrometry for colorectal cancer proteomics

This review documents the uses of quantitative MS applied to colorectal cancer (CRC) proteomics for biomarker discovery and molecular pathway profiling. Investigators are adopting various labeling and label-free MS approaches to quantitate differential protein levels in cells, tumors, and plasma/serum. We comprehensively review recent uses of this technology to examine mouse models of CRC, CRC cell lines, their secretomes and subcellular fractions, CRC tumors, CRC patient plasma/serum, and stool samples. For biomarker discovery these approaches are uncovering proteins with potential diagnostic and prognostic utility, while in vitro cell culture experiments are characterizing proteomic and phosphoproteomic responses to disrupted signaling pathways due to mutations or to inhibition of drugable enzymes.     

Neuroproteomics in stem cell differentiation

The term "proteome" is used to describe the entire complement of proteins in a given organism or in a system at a given time. Proteome analysis in neuroscience, also called "neuroproteomics" or "neuromics" is in its initial stage, and shows a deficit of studies in the context of brain development. It is the main objective of this review to illustrate the potential of neuroproteomics as a tool to unravel the differentiation of neural stem or progenitor cells to terminally differentiated neurons. Experimental results regarding the rat striatal progenitor model cell line ST14A are presented to illustrate the large rearrangements of the proteome during the differentiation process of neural progenitor cells and their modification by neurotrophic factors like the glial cell line-derived neurotrophic factor (GDNF). Thereby native stem cells and cells transfected with GDNF gene were investigated at the proliferative state and at seven time points up to 72?h after induction of differentiation. In addition, the immortalized human fetal midbrain stem cell line ReNcell VM was analyzed in order to detect stem cell differentiation associated changes of the protein profile. This review gives also an outlook on technical improvements and perspectives of application of neural stem cell proteomics.     

Proteomic expression analysis and comparison of protein and mRNA expression profiles in human malignant gliomas

Gliomas are highly heterogeneous and therapy resistant tumors with a poor prognosis. Novel experimental therapeutic approaches have shown some promising results, but often target specific molecular mechanisms or antigens, and careful characterization of the molecular subgroup of the tumors will therefore likely be important. Thorough investigations of gene and protein alterations are also important to better understand the tumorigenic mechanisms. We have undertaken a proteomic approach, using 2-D DIGE and LC-MS/MS protein identification, to investigate 38 human gliomas and normal brains. We show that the proteome profile can discriminate between normal brain and tumors, and between tumors of varying grade by a supervised classifier. Furthermore, an analysis of the identified proteins shows an enrichment of proteins associated to pathways known to be central in gliomas, such as MEK/Erk signaling and actin cytoskeleton. It also shows a shift between different glial fibrillary acidic protein (GFAP) representatives in different grades. In a previous study the gene expression profile was characterized in an almost identical set of tumors, which enabled a paired analysis of the gene and protein expression profiles. We show that there is often a weak correlation between the mRNA and protein level. This, together with the ability of proteomics to identify PTMs, emphasizes the benefit of characterization on a protein level.     

Biomarkers for the central nervous system complications of sickle cell disease: are we there yet?

Sickle cell disease (SCD, OMIM #603903), an autosomal recessively inherited β-hemoglobinopathy, was the first human disorder delineated at a molecular level. The putative single nucleotide mutation in the HBB gene generates an abnormal hemoglobin species, which polymerizes in deoxygenated conditions causing irreversible changes in erythrocyte shape and function. Sickling erythrocytes are in turn responsible for microvascular vaso-occlusion, hemolysis and a systemic vasculopathy in patients. SCD has represented an attractive field for proteomic investigation since its methodological infancy. Clinically actionable biomarkers, especially for the prevention of cerebrovascular complications in children with the condition, are urgently needed and their discovery remains a major challenge. In this issue, Lance and colleagues report of their unbiased proteomic studies on samples from the participants of the landmark prospective, randomized, single-blind SIT trial (NEJM 2014). Their results reveal numerous brain-enriched plasma proteins specific for SCD, and for silent cerebral infarcts in this disorder, and further analyses highlight novel cellular mechanisms behind the brain damage in SCD. Although the goal of identifying reliable biomarker candidates for cerebrovascular complications could not be met, the dataset produced by the authors constitutes a significant contribution to the field and opens new horizons for further clinical and laboratory investigation.     

Cardiovascular proteomics: translational studies to develop novel biomarkers in heart failure and left ventricular remodeling

Heart failure (HF) remains a severe disease with a poor prognosis. HF biomarkers may include demographic features, cardiac imaging, or genetic polymorphisms but this term is commonly applied to circulating serum or plasma analytes. Biomarkers may have at least three clinical uses in the context of HF: diagnosis, risk stratification, and guidance in the selection of therapy. Proteomic studies on HF biomarkers can be designed as case/control using clinical endpoints; alternatively, left ventricular remodeling can be used as a surrogate endpoint. The type of samples (tissue, cells, serum or plasma) used for proteomic analysis is a key factor in the research of biomarkers. Since the final aim is the discovery of circulating biomarkers, and since plasma and serum samples are easily accessible, proteomic analysis is frequently used for blood samples. However, standardization of sampling and access to low-abundance proteins remains problematic. Although, proteomics is playing a major role in the discovery phase of biomarkers, validation in independent populations is necessary by using more specific methods. The knowledge of new HF biomarkers may allow a more personalized medicine in the future.     

Proteomics of endometrial cancer diagnosis,treatment, and prognosis

This review discusses the current status of proteomics technology in endometrial cancer diagnosis, treatment and prognosis. The first part of this review focuses on recently identified biomarkers for endometrial cancer, their importance in clinical use as well as the proteomic methods used in their discovery. The second part highlights some of the emerging mass spectrometry based proteomic technologies that promise to contribute to a better understanding of endometrial cancer by comparing the abundance of hundreds or thousands of proteins simultaneously.     

Identification of melanoma‐specific serological markers using proteomic analyses

The discovery of novel melanoma markers for not only early detection but also monitoring disease status is promising to improve the clinical outcome of patients. In the present study, we performed proteomic comparative analysis of plasma proteins between healthy volunteers and melanoma patients using NanoLC and MALDI‐TOF‐MS. As a result, we were successful in identifying nine proteins that were specifically expressed in melanoma plasma compared with healthy plasma, most of which had not previously been identified as plasma markers of melanoma. The mRNA expression levels of four proteins [pro‐platelet basic protein precursor (PPBP), serum amyloid A2 (SAA2), complement factor H‐related protein 1 precursor (FHR1), inter‐alpha‐trypsin inhibitor heavy chain H4 precursor (IAIH4)] were prominently up‐regulated in several melanoma cell lines compared with melanocytes. Moreover, two proteins (PPBP, SAA) were shown to be expressed in tumor specimens from melanoma patients. In the survival time analysis regarding melanoma patients, the semi‐quantified plasma PPBP levels were statistically negatively correlated with the survival time. Most interestingly, the significant survival benefit was seen in low PBPP level group (< index 20) versus high level (≥ index 20) group. The results suggest that PPBP might be a novel promising serological marker and a prognostic factor specific to melanomas.     

Human kidney glomerulus proteome and biomarker discovery of kidney diseases

The kidney glomerulus is the site of plasma filtration and production of primary urine in the kidney. The structure not only plays a pivotal role in ultrafiltration of plasma into urine but also is the locus of kidney diseases progressing to chronic renal failure. Patients afflicted with these glomerular diseases frequently progress to irreversible loss of renal function and inevitably require replacement therapies. The diagnosis and treatment of glomerular diseases are now based on clinical manifestations, urinary protein excretion level, and renal pathology of needle biopsy specimens. The molecular mechanisms underlying the progression of glomerular diseases are still obscure despite a great number of clinical and experimental studies. Proteomics is a particularly promising approach for the discovery of proteins relevant to physiological and pathophysiological processes, and has been recently employed in nephrology. Although until now most efforts of proteomic analysis have been conducted with urine, the biological fluid that is easily collected without invasive procedures, proteomic analysis of the glomerulus, the tissue most proximal to the disease loci, is the most straightforward approach. In this review, we attempt to outline the current status of clinical proteomics of the glomerulus and provide a perspective of protein biomarker discovery of glomerular diseases.     

Challenges and opportunities for cell line secretomes in cancer proteomics

Cancer cell lines are the most widely used experimental models in cancer research. Their advantages of easy growth and manipulation are unfortunately paralleled by their limitations derived from long-term growth in isolation from the rest of the tumor, and hence, lack of tumor microenvironment. We are however currently witnessing novel and transformative advances that are making cell lines more reflective of the human biology and therefore, better experimental models for cancer research. Beyond the experimental model used, the choice of cellular proteome is key in proteomics-based biomarker discovery. Over the last decade, cell line secretomes have been proposed as an alternative for tumor biomarker discovery due to the difficulties posed by plasma in terms of complexity and low abundance of tumor-specific biomarkers. Cell line secretomes are enriched with proteins already linked to tumorigenesis, which also have a good chance of being present in biological fluids. In this review, we will provide an overview of the main technical and biological issues related to cell line secretome analysis, and briefly discuss both the challenges and opportunities in its use for tumor biomarker discovery.     

Proteomics in the investigation of HIV-1 interactions with host proteins

Productive HIV-1 infection depends on host machinery, including a broad array of cellular proteins. Proteomics has played a significant role in the discovery of HIV-1 host proteins. In this review, after a brief survey of the HIV-1 host proteins that were discovered by proteomic analyses, I focus on analyzing the interactions between the virion and host proteins, as well as the technologies and strategies used in those proteomic studies. With the help of proteomics, the identification and characterization of HIV-1 host proteins can be translated into novel antiretroviral therapeutics.     

Proteomic analysis of serum, plasma, and lymph for the identification of biomarkers

Probably no topic has generated more excitement in the world of proteomics than the search for biomarkers. This excitement has been generated by two realities: the constant need for better biomarkers that can be used for disease diagnosis and prognosis, and the recent developments in proteomic technologies that are capable of scanning the individual proteins within varying complex clinical samples. Ideally a biomarker would be assayable from a noninvasively collected sample, therefore, much of the focus in proteomics has been on the analysis of biofluids such as serum, plasma, urine, cerebrospinal fluid, lymph, etc. While the discovery of biomarkers has been elusive, there have been many advances made in the understanding of the proteome content of various biofluids, and in the technologies used for their analysis, that continues to point the research community toward new methods for achieving the ultimate goal of identifying novel disease-specific biomarkers. In this review, we will describe and discuss many of the proteomic approaches taken in an attempt to find novel biomarkers in serum, plasma, and lymph.     

Proteomic approaches to the study of malignant lymphoma: Analyses on patient samples

We describe the application of proteomic techniques for protein profiling and biomarker discovery in malignant lymphoma. Hematologic malignancies are primarily characterized by their clinical, morphological, immunophenotypical, and molecular-genetic features. However, when based on these parameters, apparently identical lymphomas may show distinct clinical courses, suggesting underlying biological heterogeneity. Recent proteomic analyses have identified differences in protein expression both with regard to subclassification of the malignant lymphoma entities, as well as in correlation with clinical outcome. In this review, studies on quantification of differential protein expression in and between malignant lymphoma entities are included. Studies are included that are based on patient samples, that is, serum/plasma or cytological specimens, as well as intact tumor tissues, together with studies that focus on tumor cells alone, or in conjunction with the tumor microenvironment. For biomarker discovery in malignant lymphoma, these approaches are used to uncover the underlying biological mechanisms and identify proteins with potential diagnostic and prognostic utility, either as predictive biomarkers or as novel future treatment targets.     

Identification of glial-cell-line-derived neurotrophic factor-regulated proteins of striatum in mouse model of Parkinson disease

Glial-cell-line-derived neurotrophic factor (GDNF) is a potent survival factor for dopaminergic neurons, and hence serves as a therapeutic candidate for the treatment of Parkinson's disease. However, despite the potential clinical and physiological importance of GDNF, its mechanism of action is unclear. Therefore, we employed a state-of-the-art proteomic technique, DIGE, along with MS and a bioinformatics tool called Database for Annotation, Visualization and Integrated Discovery (DAVID), to profile proteome changes in the parkinsonian mouse striatum after GDNF challenge. Forty-six unique differentially expressed proteins were successfully identified, which were found either up-regulated and/or down-regulated at the two time points 4 and 72 h compared with the control. Proteins involved in cell differentiation and system development formed the largest part of the proteins regulated under GDNF. Furthermore, the aberrant expression of HSPs and mitochondria-associated proteins were noticeable. Moreover, mitochondrial stress 70 protein and heat shock cognate 71 kDa protein, whose relative levels increased significantly in GDNF-treated striatum, were further evaluated with Western blot and RT-PCR, demonstrating a good agreement with quantitative proteomic data. These data will provide some clues for understanding the mechanisms by which GDNF promotes the survival of dopaminergic neurons.     

Neuroproteomics and systems biology-based discovery of protein biomarkers for traumatic brain injury and clinical validation

The rapidly growing field of neuroproteomics has expanded to track global proteomic changes underlying various neurological conditions such as traumatic brain injury (TBI), stroke, and Alzheimer's disease. TBI remains a major health problem with approximately 2?million incidents occurring annually in the United States, yet no affective treatment is available despite several clinical trials. The absence of brain injury diagnostic biomarkers was identified as a significant road-block to therapeutic development for brain injury. Recently, the field of neuroproteomics has undertaken major advances in the area of neurotrauma research, where several candidate markers have been identified and are being evaluated for their efficacy as biological biomarkers in the field of TBI. One scope of this review is to evaluate the current status of TBI biomarker discovery using neuroproteomics techniques, and at what stage we are at in their clinical validation. In addition, we will discuss the need for strengthening the role of systems biology and its application to the field of neuroproteomics due to its integral role in establishing a comprehensive understanding of specific brain disorder and brain function in general. Finally, to achieve true clinical input of these neuroproteomic findings, these putative biomarkers should be validated using preclinical and clinical samples and linked to clinical diagnostic assays including ELISA or other high-throughput assays.     

Lysosomal proteomics and disease

A recent trend in proteomic studies has been to analyze macromolecular complexes such as subcellular organelles instead of complete cells or tissues. This "divide and conquer" approach circumvents some of the formidable problems associated with whole proteome analyses and allows focus on a subset of proteins that may be involved in a particular process or disease of interest. One organelle that has been the focus of considerable attention in proteomic studies is the lysosome, an acidic, membrane-delimited compartment that plays an essential role in the degradation and recycling of biological macromolecules. Lysosomal proteomics have been driven in part by the well-established involvement of this organelle in numerous human diseases, but also by the availability of approaches to selectively visualize and/or isolate subsets of lysosomal proteins. In terms of clinical application, proteomic studies of the lysosome have led to the identification of gene defects in three human hereditary diseases. This review summarizes past progress, current limitations and future directions in the field of lysosomal proteomics.     

Quantitative proteomic approaches for biomarker discovery

The rapid advances in proteomic technologies have made possible systematic analysis of hundreds to thousands of proteins in clinical samples with the promise of uncovering novel protein biomarkers for various disease conditions. We will discuss in this review article current MS and protein chip-based quantitative proteomic approaches and their application in biomarker discovery. The emphasis will be placed on new quantification strategies employing stable isotopic labeling coupled with MS/MS, and antibody-based protein chips and nanodevices. The strength and weakness of each technology are briefly highlighted.     

Plasma prefractionation methods for proteomic analysis and perspectives in clinical applications

Plasma is a rich source of biomarkers with clinical relevance. However, the wide dynamic range of protein concentration hinders the detection of low abundance proteins. Plasma prefractionation methods serve as indispensable tools to reduce plasma complexity, allowing the opportunity to explore tissue‐derived proteins which leak into the circulation. This review summarizes common approaches in plasma prefractionation methods for proteomic analysis and then discusses some considerations in plasma prefractionation for clinical applications, reviewing some examples of its use in clinical situations.     

Application of proteomics in the study of rodent models of cancer

The molecular and cellular mechanisms underlying the multistage processes of cancer progression and metastasis are complex and strictly depend on the interplay between tumor cells and surrounding tissues. Identification of protein aberrations in cancer pathophysiology requires a physiologically relevant experimental model. The mouse offers such a model to identify protein changes associated with tumor initiation and progression, metastasis development, tumor/microenvironment interplay, and treatment responses. Furthermore, the mouse model offers the ability to collect samples at any stage in tumor development from highly matched disease cases and controls with identical environmental and genetic backgrounds, thus providing an excellent method for biomarker discovery. Xenograft and genetically engineered mouse models have been widely used to identify proteomic patterns in tumor tissues and plasma samples associated with different stages of human cancer, including early cancer detection and development of metastasis. Here, we review proteomic strategies to identify proteins involved in key cancer processes within such animal models as well as biomarkers for diagnosis, prognosis, and monitoring of cancer progression and treatment response. Central to such studies is the ability to ensure at an early stage that the identified proteins are of clinical relevance by examining relevant specimens from larger cohorts of cancer patients.