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Mapping molecular networks using proteomics: a vision for patient-tailored combination therapy.

Mapping tumor cell protein networks in vivo will be critical for realizing the promise of patient-tailored molecular therapy. Cancer can be defined as a dysregulation or hyperactivity in the network of intracellular and extracellular signaling cascades. These protein signaling circuits are the ultimate targets of molecular therapy. Each patient's tumor may be driven by a distinct series of molecular pathogenic defects. Thus, for any single molecular targeted therapy, only a subset of cancer patients may respond. Individualization of therapy, which tailors a therapeutic regimen to a tumor molecular portrait, may be the solution to this dilemma. Until recently, the field lacked the technology for molecular profiling at the genomic and proteomic level. Emerging proteomic technology, used concomitantly with genomic analysis, promises to meet this need and bring to reality the clinical adoption of molecular stratification. The activation state of kinase-driven signal networks contains important information relative to cancer pathogenesis and therapeutic target selection. Proteomic technology offers a means to quantify the state of kinase pathways, and provides post-translational phosphorylation data not obtainable by gene arrays. Case studies using clinical research specimens are provided to show the feasibility of generating the critical information needed to individualize therapy. Such technology can reveal potential new pathway interconnections, including differences between primary and metastatic lesions. We provide a vision for individualized combinatorial therapy based on proteomic mapping of phosphorylation end points in clinical tissue material.

Antineoplastic Combined Chemotherapy Protocols↗

Similarity of the Escherichia coli proteome upon completion of different biopharmaceutical fermentation processes.

A comprehensive view of the physiological state of Escherichia coli cells at the completion of fermentation processes for biopharmaceutical production was attained via two-dimensional gel electrophoretic analysis of cellular proteins. For high cell density fermentations in which phosphate is depleted to induce recombinant protein expression from the alkaline phosphatase promoter, proteome analysis confirms that phosphate limitation occurs. Known phosphate starvation inducible proteins are observed at high levels; these include the periplasmic phosphate binding protein and the periplasmic phosphonate binding protein. The phn (EcoK) locus of these E. coli K-12 strains remains cryptic, as demonstrated by failure to grow with phosphonate as the sole phosphorus source. Proteome analysis also provided evidence that cells utilize alternative carbon and energy sources during these fermentation processes. To address regulatory issues in the biopharmaceutical industry, comparative electrophoretic analyses were conducted on a qualitative basis for four different fermentation processes. Using this approach, the protein profiles for these processes were found to be highly similar, with the vast majority (85-90%) of proteins detected in all profiles. The observed similarity in proteomes suggests that multiproduct host cell protein immunoassays are a feasible means of quantifying host-derived polypeptides from a variety of biopharmaceutical fermentation processes.

Biopharmaceutics↗

ExPASy: The proteomics server for in-depth protein knowledge and analysis.

The ExPASy (the Expert Protein Analysis System) World Wide Web server (http://www.expasy.org), is provided as a service to the life science community by a multidisciplinary team at the Swiss Institute of Bioinformatics (SIB). It provides access to a variety of databases and analytical tools dedicated to proteins and proteomics. ExPASy databases include SWISS-PROT and TrEMBL, SWISS-2DPAGE, PROSITE, ENZYME and the SWISS-MODEL repository. Analysis tools are available for specific tasks relevant to proteomics, similarity searches, pattern and profile searches, post-translational modification prediction, topology prediction, primary, secondary and tertiary structure analysis and sequence alignment. These databases and tools are tightly interlinked: a special emphasis is placed on integration of database entries with related resources developed at the SIB and elsewhere, and the proteomics tools have been designed to read the annotations in SWISS-PROT in order to enhance their predictions. ExPASy started to operate in 1993, as the first WWW server in the field of life sciences. In addition to the main site in Switzerland, seven mirror sites in different continents currently serve the user community.

Databases, Protein↗

Differential serum proteomic analysis in a model of metabolic disease.

Protein profiling would aid in better understanding the pathophysiology of metabolic disease. Here, we report on differential proteomic analysis using an animal model of diabetes mellitus and associated metabolic disorders (Otsuka Long-Evans Tokushima Fatty rat). Serum was analyzed by a new two-dimensional liquid chromatography system which separated proteins by chromatofocusing and subsequent reversed-phase chromatography. This is the first application of this approach to differential serum proteomics. Differentially expressed proteins, identified with MALDI-TOF mass spectrometry, included apolipoproteins and alpha2-HS-glycoprotein. These findings add to our understanding of the underlying pathophysiology. This new proteomic analysis is a promising tool to elucidate disease mechanisms.

Animals↗

Proteomics and leukocytes: an approach to understanding potential molecular mechanisms of inflammatory responses.

Leukocytes play an important role in the progression of disease and leukocyte-derived proteins are associated with the pathogenesis of the disease. Leukocyte activation causes production of inflammatory mediators, over-expression of cell surface adhesion molecules, and an increase in migration and infiltration, phagocytosis, and degranulation, as well as receptor phosphorylation and signal transduction. An increasing number of studies on the application of leukocyte proteomics have appeared in mapping protein profiles of inflammatory cells, contributing to the understanding of potential mechanisms involved in leukocyte function. Together with improvements in proteomic technology in leukocyte research, leukocyte proteomic analysis becomes more simple, rapid, flexible, sensitive, and specific. This enables proteomic investigation of activated or non-activated leukocytes to be highly focused on defined suborgans or specific signaling pathways. Research in leukocyte proteomics is progressing from fingerprinting to functioning, human cell lines to primary leukocytes, non-activated cells to inflammatory mediator-stimulated cells, in vitro culture to in vivo challenge, and animal models to human disease. A number of newly identified proteins from leukocyte proteomics may offer new mechanism-orientated targets for drug discovery and development.

Dendritic Cells↗

A stochastic model for optimizing composite predictors based on gene expression profiles.

PURPOSE: This project was done to develop a mathematical model for optimizing composite predictors based on gene expression profiles from DNA arrays and proteomics. METHODS: The problem was amenable to a formulation and solution analogous to the portfolio optimization problem in mathematical finance: it requires the optimization of a quadratic function subject to linear constraints. The performance of the approach was compared to that of neighborhood analysis using a data set containing cDNA array-derived gene expression profiles from 14 multiple sclerosis patients receiving intramuscular inteferon-beta1a. RESULTS: The Markowitz portfolio model predicts that the covariance between genes can be exploited to construct an efficient composite. The model predicts that a composite is not needed for maximizing the mean value of a treatment effect: only a single gene is needed, but the usefulness of the effect measure may be compromised by high variability. The model optimized the composite to yield the highest mean for a given level of variability or the least variability for a given mean level. The choices that meet this optimization criteria lie on a curve of composite mean vs. composite variability plot referred to as the "efficient frontier." When a composite is constructed using the model, it outperforms the composite constructed using the neighborhood analysis method. CONCLUSIONS: The Markowitz portfolio model may find potential applications in constructing composite biomarkers and in the pharmacogenomic modeling of treatment effects derived from gene expression endpoints.

Adult↗

Proteomic analysis of the allograft response.

BACKGROUND: As transcriptional profiling techniques appear to provide a useful means to evaluate the allograft response, we have now initiated an attempt to use proteomics to examine the allograft response. METHODS: To this end, we have evaluated the use of Protein Chip technology, coupled with bioinformatics analysis towards discovery of allograft response biomarkers in a mouse skin transplant model. To compare samples obtained from acutely rejecting allograft recipients at days 7, 9, and 21, we treated one group with a potent antirejection regimen. Mean survival time in the fully MHC-mismatched skin graft model using this protocol is more than 100 days. We also studied recipients of nontreated syngenetic grafts. We applied Protein Chip technology toward discovery of allograft response markers in this model. RESULTS: At days 7 and 9, before the clinical appearance of rejection at day 10, several protein biomarker candidates were detected, based on their molecular mass that clearly differentiated between rejection and the nonrejection groups. CONCLUSIONS: Protein profiling of serum as a means to characterize the allografts response of a given host deserves further testing in clinical studies.

Abatacept↗

Synthesis and testing of mechanism-based protein-profiling probes for retaining endo-glycosidases.

New functional proteomics methods are required for targeting and identification of subsets of a proteome in an activity-based fashion. Glycosidases play critical roles in biology, yet a robust method for functional analysis of their activities and identities in biological proteomes is still lacking. An aryl 2-deoxy-2-fluoro xylobioside inactivator was conjugated through cleavable and noncleavable linker arms to a biotin tag, thereby yielding two new active-site-directed reagents for activity-based profiling of retaining beta-glycanases in complex proteomes. Crucially, these tagged reagents possess high specificity for their target enzymes with kinetic parameters similar to those of the untagged reagent. Western blotting showed that these reagents bind and covalently label active retaining beta-glycanases both in pure enzyme samples and in the secreted proteome of the soil bacterium Cellulomonas fimi. Such reagents therefore show great promise for future activity-based targeting of glycanases.

Affinity Labels↗

Peptide libraries: at the crossroads of proteomics and bioinformatics.

Peptide libraries offer a valuable means for providing functional information regarding protein-modifying enzymes and protein interaction domains. Library approaches have become increasingly useful as high-throughput strategies for the analysis of large numbers of new proteins identified as a result of genome-sequencing efforts. Recent developments in the field have produced faster methods with broadened applicability. Crucially, new computational and biochemical tools have emerged that facilitate identification of interaction partners and substrates for proteins on the basis of their peptide selectivity profiles. Such combinations of proteomics-scale experimental approaches with bioinformatics tools hold great promise for the elucidation of protein interaction networks and signal transduction pathways in living cells.

Computational Biology↗

Mass spectrometry-based proteomics.

Recent successes illustrate the role of mass spectrometry-based proteomics as an indispensable tool for molecular and cellular biology and for the emerging field of systems biology. These include the study of protein-protein interactions via affinity-based isolations on a small and proteome-wide scale, the mapping of numerous organelles, the concurrent description of the malaria parasite genome and proteome, and the generation of quantitative protein profiles from diverse species. The ability of mass spectrometry to identify and, increasingly, to precisely quantify thousands of proteins from complex samples can be expected to impact broadly on biology and medicine.

Animals↗

Mass spectrometry-based proteomics combined with bioinformatic tools for bacterial classification.

Timely classification and identification of bacteria is of vital importance in many areas of public health. We present a mass spectrometry (MS)-based proteomics approach for bacterial classification. In this method, a bacterial proteome database is derived from all potential protein coding open reading frames (ORFs) found in 170 fully sequenced bacterial genomes. Amino acid sequences of tryptic peptides obtained by LC-ESI MS/MS analysis of the digest of bacterial cell extracts are assigned to individual bacterial proteomes in the database. Phylogenetic profiles of these peptides are used to create a matrix of sequence-to-bacterium assignments. These matrixes, viewed as specific assignment bitmaps, are analyzed using statistical tools to reveal the relatedness between a test bacterial sample and the microorganism database. It is shown that, if a sufficient amount of sequence information is obtained from the MS/MS experiments, a bacterial sample can be classified to a strain level by using this proteomics method, leading to its positive identification.

Amino Acid Sequence↗

Identification of novel citrullinated autoantigens of synovium in rheumatoid arthritis using a proteomic approach.

Recently, autoantibodies to some citrullinated autoantigens have been reported to be specific for rheumatoid arthritis (RA). However, an entire profile of and autoimmunity of the citrullinated proteins have been poorly understood. To understand the profile, we examined citrullinated autoantigens by a proteomic approach and further investigated the significance of citrullination in antigenicity of one of the autoantigens. Specifically, we detected citrullinated autoantigens in synovial tissue of a patient with RA by two-dimensional electrophoresis and Western blotting by using pooled sera from five patients with RA and anti-citrulline antibodies. After identifying the detected autoantigens by mass spectrometry, we investigated the contribution of citrullination to autoantigenicity by using a recombinant protein with or without citrullination on one of the identified novel citrullinated autoantigens. As a result, we found 51 citrullinated protein spots. Thirty (58.8%) of these spots were autoantigenic. We identified 13 out of the 30 detected citrullinated autoantigenic proteins. They contained three fibrinogen derivatives and several novel citrullinated autoantigens (for example, asporin and F-actin capping protein alpha-1 subunit [CapZalpha-1]). We further analyzed the contribution of citrullination to autoantigenicity in one of the detected citrullinated autoantigens, CapZalpha-1. As a result, frequencies of autoantibodies to non-citrullinated CapZalpha-1 were 36.7% in the RA group tested, 10.7% in the osteoarthritis (OA) group, and 6.5% in healthy donors. On the other hand, those to citrullinated CapZalpha-1 were 53.3% in the RA group, 7.1% in the OA group, and 6.5% in the healthy donors. This shows that autoantigenicity of citrullinated or non-citrullinated CapZalpha-1 is relevant to RA. The antibody titers to the citrullinated CapZalpha-1 were significantly higher than those to the non-citrullinated CapZalpha-1 in 36.7% of patients; however, the other patients showed almost equal antibody titers to both citrullinated and non-citrullinated CapZalpha-1. Therefore, the autoantibodies would target citrulline-related and/or citrulline-unrelated epitope(s) of CapZalpha-1. In conclusion, we report a profile of citrullinated autoantigens for the first time. Even though citrullination is closely related to autoantigenicity, citrullination would not always produce autoantigenicity in RA. Citrullinated and non-citrullinated autoantigens/autoepitopes would have different pathological roles in RA.

Adult↗

Cardiovascular Complications Are Increased in Inflammatory Bowel Disease: A Path Toward Achievement of a Personalized Risk Estimation.

Background/Objectives: The global burden of inflammatory bowel diseases (IBDs) continues to rise, with up to 50% of patients experiencing extraintestinal manifestations. Cardiovascular diseases (CVDs) are of particular concern, ranking as the second leading cause of mortality in this population. Despite a comparatively lower prevalence of traditional cardiovascular (CV) risk factors, the persistent inflammatory milieu and immune dysregulation inherent to IBD may contribute to heightened CVD risk. In this study, following a review of the current literature, an ongoing prospective trial designed to clarify CV risk profiles in IBD patients is detailed. Methods: A cohort of patients with IBD is being enrolled for comprehensive baseline evaluation of CV risk factors, lifestyle metrics, and disease characteristics. The incidence of major adverse cardiovascular events (MACEs) will be tracked and contrasted with a gender- and age-matched non-IBD cohort over a 2-year follow-up period. In cases of MACE occurrence, a multi-omics analysis-including genomic, proteomic, transcriptomic, and microbiome profiling-will be performed, along with a parallel evaluation in matched IBD controls without MACE. An artificial intelligence (AI) framework will support the analysis of this complex dataset. Results: To date, over 150 patients with IBD have been enrolled, and detailed phenotypic data and biological samples have been collected. Conclusions: We aim to introduce an IBD-specific correction factor for existing CV risk scores upon study completion. This is particularly relevant for individuals under 40 years of age, who are often inadequately assessed by current risk stratification models.

Crohn’s disease↗

Isolation and angiogenesis by endothelial progenitors in the fetal liver.

Endothelial progenitor cells (EPCs) have significant therapeutic potential. However, the low quantity of such cells available from bone marrow and their limited capacity to proliferate in culture make their use difficult. Here, we present the first definitive demonstration of the presence of true EPCs in murine fetal liver capable of forming blood vessels in vivo connected to the host's vasculature after transplantation. This population is particularly interesting because it can be obtained at high yield and has a high angiogenic capacity as compared with bone marrow-derived EPCs. The EPC capacity is contained within the CD31+Sca1+ cell subset. We demonstrate that these cells are dependent for survival and proliferation on a feeder cell monolayer derived from the fetal liver. In addition, we describe a novel and easy method for the isolation and ex vivo proliferation of these EPCs. Finally, we used gene expression profiling and tandem mass spectrometry proteomics to examine the fetal liver endothelial progenitors and the feeder cells to identify possible proangiogenic growth factor and endothelial differentiation-associated genes.

Animals↗

Evaluation and Optimization of Different Digestion Strategies for In-Depth Proteomic Characterization of Residual Host Cell Proteins in rAAV-Based Gene Therapy Products.

Recombinant adeno-associated virus vectors (rAAVs) are the most important vectors for in vivo gene therapies, yet their safety relies on low levels of residual host cell proteins (HCPs). While mass spectrometry-based proteomics enables sensitive and untargeted HCP profiling, it faces challenges with matrix interferences from purification buffers and the high dynamic range between abundant viral capsids and trace HCPs. Although sample preparation methods that address these challenges are well-established for antibody products, their adaptation to rAAV purification stages and products remains largely unexplored. In this study, we systematically evaluated three widely used proteomic sample preparation workflows─In-Solution, FASP, and SP3─across different stages of rAAV purification. In addition, each workflow was tested under both standard denatured digestion conditions and a "native" digestion strategy designed to reduce dynamic range by preserving capsid integrity while selectively digesting HCPs. This comparison identified the native FASP protocol as the most effective sample preparation method for overcoming matrix interference and dynamic range challenges, consistently outperforming other workflows in HCP identification across purification stages. Further optimization of the native FASP workflow enhanced its performance, achieving the highest host cell (HC) proteome depth, particularly in highly purified drug substance samples. This optimized sample preparation strategy provides a robust and easy-to-use framework for deep characterization of the host cell proteome in rAAV samples. By enabling deeper insights into the HCP profile, this approach supports improved understanding of the rAAV purification process and facilitates the development of targeted strategies to enhance product quality and safety.

Dependovirus↗

Identification of several proteins involved in regulation of sperm motility by proteomic analysis.

Proteomic technology was used to compare sperm protein expression profiles in asthenozoospermic patients with that of normozoospermic donors and 10 differentially expressed proteins were identified. These proteins may play roles in the regulation of sperm motility, and their characterization could merit further investigation on sperm motility-related male factor infertility.

Asthenozoospermia↗

Effects of oral vitamin C supplementation in hemodialysis patients: a proteomic assessment.

Evidence indicates that oxidative stress is present in dialysis patients, and is associated with vitamin C deficiency. Limited data are available regarding the effects of vitamin C supplementation on oxidative stress and inflammation markers in these patients. Moreover, there are no data available on plasma polypeptide fingerprints by proteome analysis before and after vitamin C supplementation. Therefore, we analyzed plasma samples from a prospective, randomized, open-labeled trial to assess the effects of oral vitamin C supplementation (250 mg three times per week), to define the plasma polypeptide pattern in hemodialysis patients. Our results reveal that more than 30 polypeptides show significant changes in the dialysis patients in comparison to controls with normal renal function, and that several polypeptides are affected/normalized by oral vitamin C supplementation. These results underline the remarkable potential for proteomics to recognize specific peptide profiles in different pathological situations, which might not be detected by classical methods.

Administration, Oral↗