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PubMed2004

Proteomic analysis of the response of Arabidopsis chloroplast proteins to high light stress.

Light is an essential environmental factor in the progression of plant growth and development but prolonged exposure to high levels of light stress can cause cellular damage and ultimately result in the death of the plant. Plants can respond defensively to this stress for a limited period and this involves changes to their gene expression profiles. Proteomic approaches were therefore applied to the study of the response to high light stress in the Arabidopsis thaliana plant species. Wild-type Arabidopsis was grown under normal light (100 micromol photons.m(-2).s(-1)) conditions and then subjected to high light (1000 micromol photons.m(-2).s(-1)) stress. Chloroplasts were then isolated from these plants and both soluble and insoluble proteins were extracted and subjected to two-dimensional (2-D) gel electrophoresis. The resolved proteins were subsequently identified by matrix assisted laser desorption/ionization-time of flight-mass spectrometry (MALDI-TOF-MS) and comparative database analysis. 64 protein spots, which were identified as candidate factors that responded to high light stress, were then selected for analysis and 52 of these were successfully identified using MALDI-TOF-MS analysis. 35 of the 52 identified proteins were found to decrease their expression levels during high light stress and a further 14 of the candidate proteins had upregulated expression levels under these conditions. Most of the proteins that were downregulated during high light stress are involved in photosynthesis pathways. However, many of the 14 upregulated proteins were identified as previously well-known high light stress-related proteins, such as heat shock proteins (HSPs), dehydroascorbate reductase (DHAR), and superoxide dismutase (SOD). Three novel proteins that were more highly expressed during periods of high light stress but had no clear functional relationship to these conditions, were also identified in this study.

Arabidopsis↗

PubMed2003

Protein profiling of the human epidermis from the elderly reveals up-regulation of a signature of interferon-gamma-induced polypeptides that includes manganese-superoxide dismutase and the p85beta subunit of phosphatidylinositol 3-kinase.

Aging of the human skin is a complex process that consists of chronological and extrinsic aging, the latter caused mainly by exposure to ultraviolet radiation (photoaging). Here we present studies in which we have used proteomic profiling technologies and two-dimensional (2D) PAGE database resources to identify proteins whose expression is deregulated in the epidermis of the elderly. Fresh punch biopsies from the forearm of 20 pairs of young and old donors (21-30 and 75-92 years old, respectively) were dissected to yield an epidermal fraction that consisted mainly of differentiated cells. One- to two-mm3 epidermal pieces were labeled with [35S]methionine for 18 h, lysed, and subjected to 2D PAGE (isoelectric focusing and non-equilibrium pH gradient electrophoresis) and phosphorimage autoradiography. Proteins were identified by matching the gels with the master 2D gel image of human keratinocytes (proteomics.cancer.dk). In selected cases 2D PAGE immunoblotting and/or mass spectrometry confirmed the identity. Quantitative analysis of 172 well focused and abundant polypeptides showed that the level of most proteins (148) remains unaffected by the aging process. Twenty-two proteins were consistently deregulated by a factor of 1.5 or more across the 20 sample pairs. Among these we identified a group of six polypeptides (Mx-A, manganese-superoxide dismutase, tryptophanyl-tRNA synthetase, the p85beta subunit of phosphatidylinositol 3-kinase, and proteasomal proteins PA28-alpha and SSP 0107) that is induced by interferon-gamma in primary human keratinocytes and that represents a specific protein signature for the effect of this cytokine. Changes in the expression of the eukaryotic initiation factor 5A, NM23 H2, cyclophilin A, HSP60, annexin I, and plasminogen activator inhibitor 2 were also observed. Two proteins exhibited irregular behavior from individual to individual. Besides arguing for a role of interferon-gamma in the aging process, the biological activities associated with the deregulated proteins support the contention that aging is linked with increased oxidative stress that could lead to apoptosis in vivo.

Adult↗

PubMed2005

Nanoprobe-based affinity mass spectrometry for selected protein profiling in human plasma.

In recent decades, magnetic nanoparticles have emerged as a promising new platform in biomedical applications, particularly bioseparations. We have developed an immunoassay using antibody-conjugated magnetic nanoparticles as an efficient affinity probe to simultaneously preconcentrate and isolate targeted antigens from biological media. We combined this probe with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI MS) to profile proteins in diluted human plasma. The nanoparticles were designed to detect several disease-associated proteins and could be used directly in MALDI MS without an elution step, thereby facilitating multiple antigen screening and the characterization of antigen variants. Plasma antigens bound rapidly (approximately 10 min) to the antibody-conjugated nanoparticles, allowing the assay to be performed within 20 min. With sensitivity of detection in the femtomole range, the nanoscale immunoassay is superior to assays using microscale particles. We applied our method to comparative protein profiling of patients with gastric cancer and healthy individuals and found differential protein expression levels associated with the disease as well as individuals. Given the flexibility of manipulating functional groups on the nanoprobes, their low cost, robustness, and simplicity of the assay, our approach shows promise for targeted proteome profiling in clinical settings.

Antibodies↗

PubMed2026

An Instrumental Optimization of a Label-Free Proteomic Method for Trace Protein Input.

Liquid chromatography-mass spectrometry (LC-MS)-based proteomics of trace-level samples, such as tens of cells or spatially resolved tissue regions, offers unique biological insights but is often constrained by the requirement for specialized, costly instrumentation. In this study, we developed a scalable workflow for the deep proteomic analysis of low- to ultralow-input samples by systematically optimizing a widely adopted Orbitrap and UHPLC platform to maximize sensitivity, precision, and throughput. This optimized workflow identified over 5600 proteins from 5 ng of peptides and 3400 proteins from 20 sorted cells, achieving a throughput of 30 analyses per day while maintaining deep proteome coverage and high quantitative reproducibility. Furthermore, by applying this method to spatially resolved proteomics, we identified over 6100 proteins from microscale regions of interest (ROIs) within a formalin-fixed, paraffin-embedded (FFPE) tissue. A data-driven normalization strategy was employed to correct for variable cellularity across tissue regions, effectively revealing intratumor heterogeneity and distinct molecular and functional signatures, including pathway activations not apparent in parallel spatial transcriptomic analysis. Ultimately, this accessible, high-performance method substantially lowers the instrumentation barrier for the deep proteomic profiling of trace-level biological samples.

Proteomics↗

PubMed2026

Occupationally relevant vibrations and the brain: frequency-dependent proteomics signatures in a rat model.

INTRODUCTION: Occupational exposure to whole-body vibration (WBV), particularly in agricultural environments, has been associated with adverse cognitive and physiological effects. This study examined the neurophysiological impact of WBV in a rat model at 4 Hz and 30 Hz, frequencies representative of off-road and on-road vehicle operation. METHODOLOGY: Forty-four Sprague-Dawley rats were assigned to control (0 Hz), low-frequency (4 Hz), or high-frequency (30 Hz) vibration conditions. After three days of exposure, brain tissues were collected and analyzed using mass spectrometry-based proteomics to identify differentially expressed proteins. RESULTS: Proteomic profiling revealed distinct, frequency-dependent alterations in brain protein expression. Compared with controls, 32 cognition-related proteins were differentially regulated at 4 Hz and 29 at 30 Hz, with 13 differing between the two vibration conditions. Principal component analysis showed clear separation among groups, indicating unique proteomic signatures for each exposure frequency. Functional enrichment and protein-protein interaction analyses demonstrated involvement of synaptic plasticity, cytoskeletal organization, calcium regulation, and neurotransmitter release. Exposure to 4 Hz was associated with the upregulation of proteins involved in calcium homeostasis and synaptic integrity, suggesting potential disruption of cognitive processes. In contrast, 30 Hz increased the expression of proteins related to axonal guidance and neuroprotection, indicating a less clearly adverse response that may reflect adaptive or potentially beneficial effects. DISCUSSION: These findings provide new insight into biological mechanisms underlying WBV-induced cognitive changes and underscore the importance of vibration frequency in shaping neurophysiological outcomes. They also establish a foundation for future studies integrating proteomics with behavioural assessments in animals and humans.

Animals↗

PubMed2003

The proteome of human brain microdialysate.

BACKGROUND: Cerebral microdialysis has been established as a monitoring tool in neurocritically ill patients suffering from severe stroke. The technique allows to sample small molecules in the brain tissue for subsequent biochemical analysis. In this study, we investigated the proteomic profile of human cerebral microdialysate and if the identified proteins might be useful predictors for disease characteristics in stroke for tissue at risk in the contralateral hemisphere. We analysed cerebral protein expression in microdialysate from three stroke patients sampled from the hemisphere contralateral to the lesion. Using a proteomic approach based on two-dimensional gel electrophoresis and subsequent mass spectrometry, we created a protein map for the global protein expression pattern of human microdialyste. RESULTS: We found an average of 158 +/- 24 (N = 18) protein spots in the human cerebral microdialysate and could identify 95 spots, representing 27 individual proteins. Most of these have been detected in human cerebrospinal fluid before, but 10 additional proteins mainly of cerebral intracellular origin were identified exclusively in the microdialysate. CONCLUSIONS: The 10 proteins found exclusively in human cerebral microdialysate, but not in cerebrospinal fluid, indicate the possibility to monitor the progression of the disease towards deterioration. The correlation of protein composition in the human cerebral microdialysate with the patients' clinical condition and results of cerebral imaging may be a useful approach to future applications for neurological stroke diagnosis, prognosis, and treatment.

Journal Article↗

PubMed2005

A novel approach for clustering proteomics data using Bayesian fast Fourier transform.

MOTIVATION: Bioinformatics clustering tools are useful at all levels of proteomic data analysis. Proteomics studies can provide a wealth of information and rapidly generate large quantities of data from the analysis of biological specimens. The high dimensionality of data generated from these studies requires the development of improved bioinformatics tools for efficient and accurate data analyses. For proteome profiling of a particular system or organism, a number of specialized software tools are needed. Indeed, significant advances in the informatics and software tools necessary to support the analysis and management of these massive amounts of data are needed. Clustering algorithms based on probabilistic and Bayesian models provide an alternative to heuristic algorithms. The number of clusters (diseased and non-diseased groups) is reduced to the choice of the number of components of a mixture of underlying probability. The Bayesian approach is a tool for including information from the data to the analysis. It offers an estimation of the uncertainties of the data and the parameters involved. RESULTS: We present novel algorithms that can organize, cluster and derive meaningful patterns of expression from large-scaled proteomics experiments. We processed raw data using a graphical-based algorithm by transforming it from a real space data-expression to a complex space data-expression using discrete Fourier transformation; then we used a thresholding approach to denoise and reduce the length of each spectrum. Bayesian clustering was applied to the reconstructed data. In comparison with several other algorithms used in this study including K-means, (Kohonen self-organizing map (SOM), and linear discriminant analysis, the Bayesian-Fourier model-based approach displayed superior performances consistently, in selecting the correct model and the number of clusters, thus providing a novel approach for accurate diagnosis of the disease. Using this approach, we were able to successfully denoise proteomic spectra and reach up to a 99% total reduction of the number of peaks compared to the original data. In addition, the Bayesian-based approach generated a better classification rate in comparison with other classification algorithms. This new finding will allow us to apply the Fourier transformation for the selection of the protein profile for each sample, and to develop a novel bioinformatic strategy based on Bayesian clustering for biomarker discovery and optimal diagnosis.

Algorithms↗

PubMed2006

Top-down approaches for measuring expression ratios of intact yeast proteins using Fourier transform mass spectrometry.

The extension of quantitation methods for small peptides to ions above 5 kDa, and eventually to global quantitative proteomics of intact proteins, will require extensive refinement of current analytical approaches. Here we evaluate postgrowth Cys-labeling and 14N/15N metabolic labeling strategies for determination of relative protein expression levels and their posttranslational modifications using top-down mass spectrometry (MS). We show that intact proteins that are differentially alkylated with acrylamide (+71 Da) versus iodoacetamide (+57 Da) have substantial chromatographic shifts during reversed-phase liquid chromatography separation (particularly in peak tails), indicating a requirement for stable isotopes in alkylation tags for top-down MS. In the 14N/15N metabolic labeling strategy, we achieve 98% 15N incorporation in yeast grown 10 generations under aerobic conditions and determine 50 expression ratios using Fourier transform ion cyclotron resonance MS in comparing these cells to anaerobically grown control (14N) cells. We devise quantitative methods for top-down analyses, including a correction factor for accurate protein ratio determination based upon the signal-to-noise ratio. Using a database of 200 yeast protein forms identified previously by top-down MS, we verify the intact mass tag concept for protein identification without tandem MS. Overall, we find that top-down MS promises work flows capable of large-scale proteome profiling using stable isotope labeling and the determination of >5 protein ratios per spectrum.

Feasibility Studies↗

PubMed2026

Urban heat island and risk of rheumatoid arthritis: Insights from genetic predisposition and proteomics.

BACKGROUND: Urban heat island (UHI) exposure is an increasingly common consequence of urbanization and climate warming, but its association with rheumatoid arthritis (RA) risk remains unclear. OBJECTIVE: To investigate the association between UHI exposure and incident RA, and to further assess the roles of genetic susceptibility and plasma proteomic profiles in this association. METHODS: This study included 400,628 urban residents with UHI exposure data and free of RA at baseline. Cox proportional hazards models were used to evaluate the association between UHI exposure and incident RA. Polygenic risk scores were used to assess effect modification by genetic susceptibility. Proteomic analyses identified candidate proteins and enriched pathways underlying the association. Mendelian randomization, colocalization, and mediation analyses assessed causal relevance and mediation. RESULTS: Over a median follow-up of 14.05 years, 5397 incident RA cases were documented. Each standard-deviation increase in UHI exposure was associated with a 17% higher risk of RA. This association was more pronounced among older adults and individuals with lower socioeconomic status. An additive interaction was observed between UHI exposure and genetic risk for RA. Proteomic analyses suggested that this association may involve not only canonical immune-inflammatory pathways, but also hypoxia response and protein transport, with CD40, VCAM1, and SUGP1 emerging as potential molecular mediators. CONCLUSIONS: UHI exposure may be a modifiable environmental risk factor for RA and provide new insights into the biological mechanisms underlying this association.

Humans↗

PubMed2006

Global proteomic analysis of microdissected cirrhotic nodules reveals significant biomarkers associated with clonal expansion.

Cirrhosis is a heterogeneous tissue composed of polyclonal regenerative and monoclonal neoplastic, potentially malignant nodules from which hepatocellular carcinoma (HCC) might develop. The aim of this study was to investigate proteomic profile changes associated with clonal expansion of cirrhotic nodules and malignant transformation of monoclonal nodules. Seventy-one cirrhotic nodules from 10 female patients with six HCC were dissected from liver surgical specimen by laser capture microdissection. Clonal status of each nodule was assessed by the study of X-chromosome inactivation pattern using the human androgen receptor. Protein profiles were determined by surface-enhanced laser desorption ionisation-time-of-flight technology using Q10 arrays (Cyphergen ProteinChip). Molecular weight of differentially expressed protein peaks was assessed. An average of 50 protein peaks was obtained for each nodule's profile. Comparison of protein profiles in polyclonal (n=45) and monoclonal cirrhotic nodules (n=26) identified three differentially expressed protein peaks (10,092, 54,025 and 62,133 Da). All were upregulated in monoclonal nodules. Twelve peaks were differentially expressed between monoclonal nodules and HCC with nine proteins upregulated in cancer samples. This study confirms that proteome analysis can be achieved from a limited number of microdissected cells, and provides further insight into the process of clonal expansion and malignant transformation of cirrhotic nodules.

Adult↗

PubMed2024

Myoferlin: A Potential Marker of Response to Radiation Therapy and Survival in Locally Advanced Rectal Cancer.

PURPOSE: Patients with locally advanced rectal cancer often require neoadjuvant chemoradiation therapy to downstage the disease, but the response is variable with no predictive biomarkers. We have previously revealed through proteomic profiling that myoferlin is associated with response to radiation therapy. The aims of this study were to further validate this finding and explore the potential for myoferlin to act as a prognostic and/or therapeutic target. METHODS AND MATERIALS: Immunohistochemical analysis of a tissue microarray (TMA) for 111 patients was used to validate the initial proteomic findings. Manipulation of myoferlin was achieved using small interfering RNA, a small molecular inhibitor (wj460), and a CRISPR-Cas9 knockout cell line. Radiosensitization after treatment was assessed using 2-dimensional clonogenic assays, 3-dimensional spheroid models, and patient-derived organoids. Underlying mechanisms were investigated using electrophoresis, immunofluorescence, and immunoblotting. RESULTS: Analysis of both the diagnostic biopsy and tumor resection samples confirmed that low myoferlin expression correlated with a good response to neoadjuvant long-course chemoradiation therapy. High myoferlin expression was associated with spread to local lymph nodes and worse 5-year survival (P = .01; hazard ratio, 3.5; 95% CI, 1.27-10.04). This was externally validated using the Stratification in Colorectal Cancer database. Quantification of myoferlin using immunoblotting in immortalized colorectal cancer cell lines and organoids demonstrated that high myoferlin expression was associated with increased radioresistance. Biological and pharmacologic manipulation of myoferlin resulted in significantly increased radiosensitivity across all cell lines in 2-dimensional and 3-dimensional models. After irradiation, myoferlin knockdown cells had a significantly impaired ability to repair DNA double-strand breaks. This appeared to be mediated via nonhomologous end-joining. CONCLUSIONS: We have confirmed that high expression of myoferlin in rectal cancer is associated with poor response to neoadjuvant therapy and worse long-term survival. Furthermore, the manipulation of myoferlin led to increased radiosensitivity in vitro. This suggests that myoferlin could be targeted to enhance the sensitivity of patients with rectal cancer to radiation therapy, and further work is required.

Humans↗

PubMed2004

Proteomic analysis of Acinetobacter lwoffii K24 by 2-D gel electrophoresis and electrospray ionization quadrupole-time of flight mass spectrometry.

The MS/MS analysis by Electrospray ionization quadrupole-time of flight mass spectrometry (ESI-Q-TOF MS) was applied to identify proteins in proteome analysis of bacteria whose genomes are not known. The protein identification by ESI-Q-TOF MS was performed sequentially by database search and then de novo sequencing using MS/MS spectra. Soil bacteria having unanalyzed genome, Acinetobacter lwoffii K24 is an aniline degrading bacterium. In this report, we present the results of a comparison between the proteome profile of A. lwoffii K24 cultured in aniline- or succinate-containing media. Protein analysis was performed using two-dimensional gel electrophoresis (2-DE) with pH 3-10 immobilized pH gradient (IPG) strips followed by ESI-Q-TOF MS. More than 780 protein spots were detected by 2-DE from the soluble proteome. Forty-eight of these proteins were expressed exclusively in aniline cultured bacteria, and 81 proteins increased and 162 proteins decreased in aniline-cultured versus succinate cultured A. lwoffii K24. Internal amino acid sequences of 43 major protein spots were successfully determined by ESI-Q-TOF MS to try to identify the bacterial proteins responding to aniline culture condition. Since the A. lwoffii K24 genome is not yet sequenced, many proteins were found to be hypothetical. Comparative proteome analysis of the insoluble protein fractions showed that one novel protein that was strongly induced by succinate-cultured A. lwoffii K24 was repressed under aniline culture conditions. These results suggest that comprehensive analysis of bacterial proteomes by 2-DE and amino acid sequence analysis by ESI-Q-TOF MS is useful for understanding induced novel proteins of biodegrading bacteria.

Acinetobacter↗

PubMed2004

Recent advances in childhood acute lymphoblastic leukemia.

Contemporary risk-directed therapy has advanced the cure rate for childhood acute lymphoblastic leukemia to near 80%. Molecular genetic analyses of leukemic cells, pharmacodynamic studies of antileukemic agents, and pharmacogenetic studies of the host's drug-metabolizing enzymes, drug transporters, and drug targets are providing a rational base for further improvement of treatment efficacy and the reduction of complications. Early treatment response, as defined by the measurement of minimal residual disease, which reflects both the drug responsiveness of leukemic cells and host pharmacodynamics/pharmacogenomics, is the most reliable prognostic indicator for gauging the intensity of treatment. Recent advances in high-throughput biotechnology, including gene expression profiling, proteomics and gene silencing promise to identify molecular targets for specific treatment. The ultimate goal is to elucidate central mechanisms of leukemogenesis so that preventive measures can be devised.

Child↗

PubMed2026

Spectral-Proteomic Integration Analysis (SPIA) Deciphers Molecular Trajectories of Breast Cancer and Enables Multitarget Therapeutic Assessment.

Raman spectroscopy and mass spectrometry-based proteomics offer deeply complementary yet largely disconnected views of cancer biology: the former provides a label-free, real-time biochemical phenotype, while the latter delivers a quantitative inventory of specific protein effectors. Bridging this gap remains a fundamental challenge in analytical biomedicine. Here, we introduce Spectral-Proteomic Integration Analysis (SPIA)─a novel, data-driven integrative framework that systematically links Raman spectroscopic phenotypes with quantitative proteomic profiles through machine learning and statistical correlation. Using a DMBA-induced rat breast cancer model with and without Toremifene (TOR) intervention, SPIA dynamically maps tumor microenvironment remodeling, capturing progressive collagen deposition and lipid metabolic reprogramming. An SVM classifier trained on Raman spectra achieves exceptional diagnostic accuracy (AUC ≥ 99.0%) and successfully predicts TOR therapeutic response. Proteomic analysis identifies 1,350 differentially expressed proteins, with convergent machine learning feature selection (LASSO, Random Forest, XGBoost) pinpointing core regulators including Luc7l2, Nucb1, Cbx3, and Csnk2a1. Crucially, Spearman correlation analysis between key Raman bands and core DEPs reveals strong, statistically robust associations (median ρ ∼ 0.75 in the 1533-1669 cm-1 region), empirically validating SPIA's core integrative logic. Leveraging this multimodal map, we elucidate a multitarget mechanism for TOR involving concurrent suppression of collagen deposition and correction of aberrant lipid metabolism. SPIA establishes a powerful, generalizable paradigm for integrating phenotypic and molecular data, with broad implications for biomarker discovery, drug mechanism elucidation, and precision oncology.

Animals↗

PubMed2005

Proteomics in prostate cancer.

PURPOSE OF REVIEW: State-of-the-art proteomics technologies are currently being assessed for utility in the study of prostatic malignancy. This review aims to provide background information on the current proteomics techniques employed in prostate cancer research, recent reports showing the potential application of proteomics in urological practice, and the future direction of proteomics in prostate cancer research and management. RECENT FINDINGS: Proteomic profiling of serum as a diagnostic tool and a platform for biomarker discovery in prostate cancer continues to draw favorable attention as well as close scrutiny as technological enhancements and multi-center study results are reported. In-vitro studies on prostate cell lines provide positive proof-of-principle results. The application of proteomics to query prostate tissue specimens yields novel prostate cancer biomarkers requiring further validation. The integration of proteomics with immunology also yields promising findings that may translate into clinically relevant biological assays. SUMMARY: The study of proteomics is an emerging research field, and current studies continue to display potential future usage in prostate cancer management. Succeeding scientific investigations will probably yield new diagnostic and prognostic tools for prostate cancer, provide insights into its underlying biology, and contribute to the development of novel treatment strategies.

Gene Expression↗

PubMed2004

Regulation of expression of cellulosomes and noncellulosomal (hemi)cellulolytic enzymes in Clostridium cellulovorans during growth on different carbon sources.

Cellulosomes and noncellulosomal (hemi)cellulolytic enzymes are produced by Clostridium cellulovorans to degrade plant cell walls. To understand their synergistic relationship, changes in mRNA and protein expression in cellulosomes and noncellulosomal (hemi)cellulolytic enzymes (hereafter called noncellulosomal enzymes) of cultures grown on cellobiose, cellulose, pectin, xylan, and corn fiber or mixtures thereof were examined. Cellulase expression, favored particularly by the presence of Avicel, was found with all substrates. Comparison of cellulosome and noncellulosomal enzymes showed that expression profiles were strongly affected by the carbon source. High xylanase or pectate lyase expression was observed when C. cellulovorans was grown on xylan or pectin, respectively. Mixed carbon substrates (cellulose-pectin-xylan mixture or corn fiber) induced a wider variety of enzymes than a single carbon source, such as cellobiose, pectin, or xylan. Cellulosomal proteome profiles were more affected by the carbon source than the noncellulosomal enzymes. Transcription and protein analyses revealed that cellulosomes and noncellulosomal enzymes were expressed simultaneously on mixed carbon sources, but their degree of inducibility varied when the substrate was either cellulose or cellobiose. Cellulosomes and noncellulosomal enzymes had synergistic activity on various carbon substrates. These results indicated that expression of plant cell wall-degrading enzymes is highly influenced by the available carbon source and that synergy between cellulosomes and noncellulosomal enzymes contribute to plant cell wall degradation.

Cellulase↗

PubMed2006

Changes in the serum proteome of patients with sepsis and septic shock.

BACKGROUND: Sepsis is still the leading cause of death in the intensive care unit. Our goal was to elucidate potential early differences in serum between survivors (SURV) and non-survivors (NON-SURV) on day 28. METHODS: We applied proteomic technology to serum samples of patients with sepsis and septic shock. Serum samples from 18 patients with sepsis and septic shock were obtained during the first 12 h after diagnosis of septic shock. Patients were grouped into SURV and NON-SURV on day 28. RESULTS: Seven patients survived and 11 patients died. Using proteome analysis, two-dimensional gel electrophoresis detected more than 200 spots per gel. A differential protein expression was discovered between SURV and NON-SURV, whereby protein alterations not yet described in sepsis were revealed. CONCLUSIONS: Our results show that proteomic profiling is a useful approach for detecting protein expression dynamics in septic patients, and may bring us closer to achieving a comprehensive molecular profiling compared with genetic studies alone.

Adult↗

PubMed2006

Convergence of the proteomic pattern in cancer.

MOTIVATION: On the histological level the differentiation of normal epithelial tissues is well known. The phenomenon of dedifferentiation, which occurs as cells develop towards malignancy is also well described. To identify an epithelial tumor-specific proteomic profile as well as to measure the proximities between we used data from tumor tissue and adjacent normal tissue microdissected from head and neck and colon cancer samples which were analyzed using ProteinChip technology and performed a bioinformatic meta-analysis on the resulting four complex datasets. RESULTS: All four groups could be identified based on their proteomic signatures and the tumor tissues were found to be more similar to one another than to the normal epithelial tissue from which they progressed. This study shows at the proteomic level that changes in the histological features of tumors as compared to the tissues from which they arise are reflected in the convergence of proteomic pattern during the development to cancer.

Cell Differentiation↗