Accelerate Biomarker Discovery Research Articles

Interaction modes and approaches to glycopeptide and glycoprotein enrichment

Protein glycosylation has received increased attention for its critical role in cell biology and diseases. Developing new methodologies to discern phenotype-dependent glycosylation will not only elucidate the mechanistic aspects of cell signaling cascades but also accelerate biomarker discovery for disease diagnosis or prognosis. In the analytical pipeline, enrichment at either the protein or peptide level is the most critical prerequisite for analyzing heterogeneous glycan composition, linkage, site occupancy and carrier proteins. Because the critical factor for choosing a suitable enrichment method is primarily a particular technique's selectivity and affinity towards target glycoproteins/glycopeptides, it is important to fully understand the working principles for the different approaches. For mechanistic insight into the enrichment protocol, we focused on the fundamental chemical and physical processes for the commonly used approaches based on: (a) glycan/peptide physicochemical properties (hydrophilic interactions, chelation/coordination chemistry) and (b) glycan-specific recognition (lectin-based affinity, covalent bond formation by hydrazide/boronic acid). Various interaction modes, such as hydrogen bonding, van der Waals interaction, multivalency, and metal- or water-mediated stabilization, are discussed in detail. In addition, we will review the design of and modifications to such methods, hyphenated approaches, and glycoproteomic applications. Finally, we will outline challenges to existing strategies and offer novel proposals for glycoproteome enrichment.

Plasma Proteome Database as a resource for proteomics research: 2014 update

Plasma Proteome Database (PPD; http://www.plasmaproteomedatabase.org/) was initially described in the year 2005 as a part of Human Proteome Organization’s (HUPO’s) pilot initiative on Human Plasma Proteome Project. Since then, improvements in proteomic technologies and increased throughput have led to identification of a large number of novel plasma proteins. To keep up with this increase in data, we have significantly enriched the proteomic information in PPD. This database currently contains information on 10 546 proteins detected in serum/plasma of which 3784 have been reported in two or more studies. The latest version of the database also incorporates mass spectrometry-derived data including experimentally verified proteotypic peptides used for multiple reaction monitoring assays. Other novel features include published plasma/serum concentrations for 1278 proteins along with a separate category of plasma-derived extracellular vesicle proteins. As plasma proteins have become a major thrust in the field of biomarkers, we have enabled a batch-based query designated Plasma Proteome Explorer, which will permit the users in screening a list of proteins or peptides against known plasma proteins to assess novelty of their data set. We believe that PPD will facilitate both clinical and basic research by serving as a comprehensive reference of plasma proteins in humans and accelerate biomarker discovery and translation efforts.

PROGgene: gene expression based survival analysis web application for multiple cancers

BackgroundIdentification of prognostic mRNA biomarkers has been done for various cancer types. The data that are published from such studies are archived in public repositories. There are hundreds of such datasets available for multiple cancer types in public repositories. Wealth of such data can be utilized to study prognostic implications of mRNA in different cancers as well as in different populations or subtypes of same cancer.DescriptionWe have created a web application that can be used for studying prognostic implications of mRNA biomarkers in a variety of cancers. We have compiled data from public repositories such as GEO, EBI Array Express and The Cancer Genome Atlas for creating this tool. With 64 patient series from 18 cancer types in our database, this tool provides the most comprehensive resource available for survival analysis to date. The tool is called PROGgene and it is available at http://www.compbio.iupui.edu/proggene.ConclusionsWe present this tool as a hypothesis generation tool for researchers to identify potential prognostic mRNA biomarkers to follow up with further research. For this reason, we have kept the web application very simple and straightforward. We believe this tool will be useful in accelerating biomarker discovery in cancer and quickly providing results that may indicate disease-specific prognostic value of specific biomarkers.

Urinary exosomes and diabetic nephropathy: a proteomic approach

Urinary exosomes (UE) are nanovesicles released by every epithelial cell facing the urinary space and they are considered a promising source of molecular markers for renal dysfunction and structural injury. Exosomal proteomics has emerged as a powerful tool for understanding the molecular composition of exosomes and has potential to accelerate biomarker discovery. We employed this strategy in the study of diabetic nephropathy (DN) and the consequent end stage renal disease, which represent the dramatic evolution of diabetes, often leading the patients to dialysis or kidney transplantation. The identification of DN biomarkers is likely to help monitoring the disease onset and progression. A label free LC-MS/MS approach was applied to investigate the alteration of the proteome of urinary exosomes isolated from the Zucker diabetic fatty rats (ZDF), as a model of type 2 DN. We collected 24 hour urine samples from 7 ZDF and from 7 control rats at different ages (6, 12 and 20 weeks old) to monitor the development of DN. Exosomes were isolated by ultracentrifugation and their purity assessed by immunoblotting for known exosomal markers. Exosomal proteins from urine samples of 20 week old rats were pooled and analyzed by nLC-ESI-UHR-QToF-MS/MS after pre-filtration and tryptic digestion, leading to the identification and label free quantification of 286 proteins. Subcellular localization and molecular functions were assigned to each protein by UniprotKB, showing that the majority of identified proteins were membrane-associated or cytoplasmic and involved in transport, signalling and cellular adhesion, typical functions of exosomal proteins. We further validated label free mass spectrometry results by immunoblotting, as exemplified by: Xaa-Pro dipeptidase, Major Urinary Protein 1 and Neprilysin, which resulted increased, decreased and not different, respectively, in exosomes isolated from diabetic urine samples compared to controls, by both techniques. In conclusion we show the potential of exosome proteomics for DN biomarker discovery.

Proteomic analysis of urine exosomes by multidimensional protein identification technology (MudPIT)

Exosomes are membrane vesicles that are secreted by cells upon fusion of multivesicular bodies with the plasma membrane. Exosomal proteomics has emerged as a powerful approach to understand the molecular composition of exosomes and has potential to accelerate biomarker discovery. Different proteomic analysis methods have been previously employed to establish several exosome protein databases. In this study, TFE solution-phase digestion was compared with in-gel digestion and found to yield similar results. Proteomic analysis of urinary exosomes was performed by multidimensional protein identification technology (MudPIT) after TFE digestion. Nearly, 3280 proteins were identified from nine human urine samples with 31% overlap among nine samples. Gene ontology (GO) analysis, coupled with detection of all of the members of ESCRT machinery complex, supports the multivesicular origin of these particles. These results significantly expand the existing database of urinary exosome proteins. Our results also indicate that more than 1000 proteins can be detected from exosomes prepared from as little as 25 mL of urine. This study provides the largest set of proteins present in human urinary exosome proteomes, provides a valuable reference for future studies, and provides methods that can be applied to exosomal proteomic analysis from other tissue sources.

Anti-cancer drug resistance: Understanding the mechanisms through the use of integrative genomics and functional RNA interference

Primary or acquired drug resistance remains a fundamental cause of therapeutic failure in cancer therapy. Post-hoc analyses of clinical trials have revealed the importance of selecting patients with the appropriate molecular phenotype for maximal therapeutic benefit, as well as the requirement to avoid exposure and potential harm for those who have drug resistant disease, particularly with respect to targeted agents. Unravelling drug resistance mechanisms not only facilitates rational treatment strategies to overcome existing limitations in therapeutic efficacy, but will enhance biomarker discovery and the development of companion diagnostics. Advances in genomics coupled with state-of-the-art biomarker platforms such as multi-parametric functional imaging and molecular characterisation of circulating tumour cells are expanding the scope of clinical trials – providing unprecedented opportunities for translational objectives that inform on both treatment response and disease biology. In this review, we propose a shift towards innovative trial designs, which are prospectively set up to answer key biological hypotheses in parallel with the RNA interference elucidation of drug resistance pathways in monotherapy pre-operative or ‘window of opportunity’ early phase trials. Systematic collection of paired clinical samples before and after treatment amenable to genomics analysis in such studies is mandated. With concurrent functional RNA interference analysis of drug response pathways, the identification of robust predictive biomarkers of response and clinically relevant resistance mechanisms may become feasible. This represents a rational approach to accelerate biomarker discovery, maximising the potential for therapeutic benefit and minimising the health economic cost of ineffective therapy.

Abstract PL01-02: The Breast International Group (BIG): Building on an accelerated path to tailored adjuvant cancer therapy

Abstract The Breast International Group (BIG) : building an accelerated path to tailored adjuvant cancer therapy M. Piccart-Gebhart Today only 1 in 20 oncologic drugs that are tested in human subjects are ultimately shown to be efficacious and approved for widespread use. The vast majority of novel agents fail in advanced stages of clinical testing. Preliminary data suggests that the success rate is only marginally better for the family of targeted kinase inhibitors. After more than 40 years of clinical research in breast cancer, hormonal receptors and HER-2 status are the only predictive therapeutic markers that are routinely used in clinical decision-making. These markers have good negative predictive values but unsatisfactory positive predictive values. There is an exciting array of novel targeted therapies designed to inhibit aberrant pathways in the cancer cell currently in clinical testing. Many of these agents may only be effective in patients with specific molecular alterations. However, demonstrating differential activity in breast cancer subtypes and developing reliable predictive assays to select patients for novel targeted therapy remains a great challenge. The traditional model of establishing initial activity in patients with advanced refractory disease with subsequent retrospective biomarker discovery and validation in the adjuvant setting has failed to establish truly tailored therapies for use in the clinic. As a result, efforts are underway to move the discovery and validation of predictive biomarkers into earlier phases of drug development in the neoadjuvant setting. The NeoBIG program is being developed by the Breast International Group (BIG) to accelerate biomarker discovery and drug development in early breast cancer. Under this platform, a series of neo-adjuvant randomized phase II clinical trials (each with 300-600 patients) will be concomitantly launched to evaluate promising novel targeted therapies in different molecular breast cancer subtypes. Short-term endpoints, including pathological remission, proliferation markers, and imaging response, will be used to establish efficacy. These studies will integrate emerging technologies, such as genomics, proteomics, metabolomics, pharmacogenetics and functional imaging, to develop predictive markers of efficacy that can be validated in a subsequent adjuvant registration trial. In addition to addressing the need for accelerated development of more effective and less toxic therapies, modern trials should lead to an improved mechanistic understanding of the underlying biology of disease in specific patient populations. The NEO-BIG program will collaborate with basic science laboratories to improve our understanding of the biology of HER2 positive, triple negative and luminal B cancers. Citation Format: Martine J. Piccart-Gebhart. The Breast International Group (BIG): Building on an accelerated path to tailored adjuvant cancer therapy [abstract]. In: Proceedings of the AACR 101st Annual Meeting 2010; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr PL01-02

Nanodevices in diagnostics

The real-time, personalized and highly sensitive early-stage diagnosis of disease remains an important challenge in modern medicine. With the ability to interact with matter at the nanoscale, the development of nanotechnology architectures and materials could potentially extend subcellular and molecular detection beyond the limits of conventional diagnostic modalities. At the very least, nanotechnology should be able to dramatically accelerate biomarker discovery, as well as facilitate disease monitoring, especially of maladies presenting a high degree of molecular and compositional heterogeneity. This article gives an overview of several of the most promising nanodevices and nanomaterials along with their applications in clinical practice. Significant work to adapt nanoscale materials and devices to clinical applications involving large interdisciplinary collaborations is already underway with the potential for nanotechnology to become an important enabling diagnostic technology.

Application of mass spectrometry-based proteomics for biomarker discovery in neurological disorders.

Mass spectrometry-based quantitative proteomics has emerged as a powerful approach that has the potential to accelerate biomarker discovery, both for diagnostic as well as therapeutic purposes. Proteomics has traditionally been synonymous with 2D gels but is increasingly shifting to the use of gel-free systems and liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS). Quantitative proteomic approaches have already been applied to investigate various neurological disorders, especially in the context of identifying biomarkers from cerebrospinal fluid and serum. This review highlights the scope of different applications of quantitative proteomics in understanding neurological disorders with special emphasis on biomarker discovery.

An Immunoproteomic Approach for Identification of Clinical Biomarkers for Monitoring Disease: Application to Cystic Fibrosis

Circulating antibodies can be used to probe protein arrays of body fluids, prepared by two-dimensional gel electrophoresis, for antigenic biomarker detection. However, detected proteins, particularly low abundance antigens, often remain unidentifiable due to proteome complexity and limiting sample amounts. Using a novel enrichment approach exploiting patient antibodies for isolation of antigenic biomarkers, we demonstrate how immunoproteomic strategies can accelerate biomarker discovery. Application of this approach as a means of identifying biomarkers was demonstrated for cystic fibrosis (CF) lung disease by isolation and identification of inflammatory-associated autoantigens, including myeloperoxidase and calgranulin B from sputum of subjects with CF. The approach was also exploited for isolation of proteins expressed by the Pseudomonas aeruginosa strain PA01. Capture of PA01 antigens using circulating antibodies from CF subjects implicated in vivo expression of Pseudomonas proteins. All CF subjects screened, but not controls, were immunoreactive against immunocaptured Pseudomonas proteins, representing stress (GroES and ferric iron-binding protein HitA), immunosuppressive (thioredoxin), and alginate synthetase pathway (nucleoside-diphosphate kinase) proteins, implicating their clinical relevance as biomarkers of infection.