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PubMed2006

Identification of protein biomarkers for schizophrenia and bipolar disorder in the postmortem prefrontal cortex using SELDI-TOF-MS ProteinChip profiling combined with MALDI-TOF-PSD-MS analysis.

This paper describes the high-throughput proteomic analysis of the dorsolateral prefrontal cortex (DLPFC) from schizophrenia (SCHIZ), bipolar (BD), and normal control cohorts from the Harvard Brain Tissue Resource Center performed using ProteinChip technology based on the surface-enhanced laser desorption/ionization time of flight mass spectrometry (SELDI-TOF-MS). The resultant profiles were utilized in classification-tree algorithms for selection of protein biomarker peaks contributing maximally to the differentiation between the examined diagnostic cohorts. Twenty-four such protein biomarker peaks were identified. All of them had lower levels in the SCHIZ cohort as compared to the BD cohort. Also, 21 of these peaks were down-regulated in the SCHIZ cohort vs. the control cohort, and 7 peaks were up-regulated in the BD cohort vs. the control cohort. The proteins constituting these biomarker peaks were recognized via matrix-assisted laser desorption time of flight/postsource decay mass spectrometry (MALDI-TOF-PSD-MS). These proteins represent a wide range of functional groups involved in cell metabolism, signaling cascades, regulation of gene transcription, protein and RNA chaperoning, and other aspects of cellular homeostasis. Finally, after statistical evaluation suggesting that the selected protein biomarkers are not significantly impacted by epidemiological/tissue storage parameters (although, influence of antipsychotic and mood stabilizing drugs could not be fully excluded), the ProteinChip-based profiling was engaged again to demonstrate that the detected SCHIZ-associated changes in the levels of our protein biomarkers could also be seen in DLPFC samples from the brain collection of the Mount Sinai Medical School/Bronx Veteran Affairs Medical Center. This study demonstrates the usefulness of ProteinChip-based SELDI-TOF protein profiling in gaining insight into the molecular pathology of SCHIZ and BD as it points to changes in protein levels characterizing these diseases.

Aged↗
PubMed2000

Expression of an estrogen receptor alpha variant protein in cell lines and tumors.

Human estrogen receptor alpha (ER) mRNA is a mixture of wild type and alternatively spliced variants. Many studies have examined the potential of ER mRNA profiles to serve as diagnostic/prognostic cancer biomarkers, but only a few have attempted to correlate ER mRNA profiles with protein expression. Representative ER mRNA pools were reproduced from the cDNAs of MCF-7 cells, a human breast tumor and human uterus and translated in a protease-free environment by reticulocyte lysates to determine relative translation efficiencies between the various ER mRNA transcripts and to facilitate identification of translated proteins. Cell line and tumor extracts were then examined for expression of the ER variant proteins identified in reticulocyte lysate translations. Each of the ER mRNA pools were translated by reticulocyte lysates into two ER proteins with molecular weights of approximately 60 and 52 kD. Western immunoblotting with various C- and N-terminal-directed, anti-ER antibodies and comparison with expressed ER protein standards established that the 52 kD protein (ERDelta7P) was translated from the predominant splice variant mRNA in each pool, which is missing exon 7. The 60 kD protein contained wild type ER sequence minus 61 C-terminal amino acids lost due to an intentional run off truncation. ERDelta7P expression was subsequently demonstrated in MCF-7 cells by Western immunoblotting with the site-directed antibodies. A protein corresponding to ERDelta7P was also detected in other ER positive breast tumor cell lines, and extracts of ER positive breast and uterine tumors. This widespread expression of ERDelta7P in vivo suggests that it may have some biological function. ERDelta7P may also affect immunohistochemical evaluation of ER positivity in tumors depending upon the level of its expression and the antibody used.

Alternative Splicing↗
PubMed2000

Expression of an estrogen receptor alpha variant protein in cell lines and tumors.

Human estrogen receptor alpha (ER) mRNA is a mixture of wild type and alternatively spliced variants. Many studies have examined the potential of ER mRNA profiles to serve as diagnostic/prognostic cancer biomarkers, but only a few have attempted to correlate ER mRNA profiles with protein expression. Representative ER mRNA pools were reproduced from the cDNAs of MCF-7 cells, a human breast tumor and human uterus and translated in a protease-free environment by reticulocyte lysates to determine relative translation efficiencies between the various ER mRNA transcripts and to facilitate identification of translated proteins. Cell line and tumor extracts were then examined for expression of the ER variant proteins identified in reticulocyte lysate translations. Each of the ER mRNA pools were translated by reticulocyte lysates into two ER proteins with molecular weights of approximately 60 and 52 kD. Western immunoblotting with various C- and N-terminal-directed, anti-ER antibodies and comparison with expressed ER protein standards established that the 52 kD protein (ERDelta7P) was translated from the predominant splice variant mRNA in each pool, which is missing exon 7. The 60 kD protein contained wild type ER sequence minus 61 C-terminal amino acids lost due to an intentional run off truncation. ERDelta7P expression was subsequently demonstrated in MCF-7 cells by Western immunoblotting with the site-directed antibodies. A protein corresponding to ERDelta7P was also detected in other ER positive breast tumor cell lines, and extracts of ER positive breast and uterine tumors. This widespread expression of ERDelta7P in vivo suggests that it may have some biological function. ERDelta7P may also affect immunohistochemical evaluation of ER positivity in tumors depending upon the level of its expression and the antibody used.

Alternative Splicing↗
PubMed2006

The hemodynamic and metabolic profiles of Zucker diabetic fatty rats treated with a single molecule triple vasopeptidase inhibitor, CGS 35601.

CGS 35601 is a triple vasopeptidase inhibitor (VPI) of angiotensin converting enzyme (ACE), neutral endopeptidase (NEP), and endothelin (ET) converting enzyme-1 (ECE-1), with respective IC(50) values of 22, 2, and 55 nM. The aim of the present study was to establish the hemodynamic profile of Zucker diabetic fatty (Zdf)-Fatty rats, a high-fat diet gene-prone model developing spontaneous Type 2 diabetes (T2D) and the effects of CGS 35601. Male Zdf-Fatty (14 weeks, n = 17-23), Zdf-Lean (14 weeks, n = 8-10), and Wistar (14 weeks, n = 9-10) rats on distinct diets were implanted with a catheter in the left carotid and placed individually in a metabolic cage for 30 days. The hemodynamic profile and some metabolic biomarkers were assessed daily. After a 7-day stabilization period, the Zdf-Fatty rats were divided into two groups: Group 1, controls (n = 7-10) receiving vehicle-saline (250 microl/hr) and Group 2, (n = 10-13) receiving increasing doses of CGS 35601 (0.1, 1, and 5 mg/kg/day x 6 days each, intra-arterially) followed by a 5-day washout period. Mean arterial blood pressure (MABP) of young Zdf-Fatty rats was compared with age-matched Zdf-Lean and Wistar rats, which were found similar. MABP decreased by 5.9% (from baseline at 102 +/- 5 to 96 +/- 4 mmHg), 12.7% (to 89 +/- 6 mmHg) and 21.6% (to 80 +/- 4 mmHg), at 0.1, 1, and 5 mg/kg/day, respectively, in CGS 35601-treated Zdf-Fatty rats. Systolic and diastolic blood pressures were similarly reduced. The heart rate was not affected. Hyperglycemic status and insulin-resistance were not modulated by short-term treatment. CGS 35601 presented an excellent short-term safety profile. This novel molecule and class of VPI may be of interest for lowering vascular tone. Further long-term studies, once cardiovascular and renal complications have developed in this T2D rat model are warranted to define the efficacy of this class of VPI.

Animals↗
PubMed2003

Comparison of statistical methods for classification of ovarian cancer using mass spectrometry data.

MOTIVATION: Novel methods, both molecular and statistical, are urgently needed to take advantage of recent advances in biotechnology and the human genome project for disease diagnosis and prognosis. Mass spectrometry (MS) holds great promise for biomarker identification and genome-wide protein profiling. It has been demonstrated in the literature that biomarkers can be identified to distinguish normal individuals from cancer patients using MS data. Such progress is especially exciting for the detection of early-stage ovarian cancer patients. Although various statistical methods have been utilized to identify biomarkers from MS data, there has been no systematic comparison among these approaches in their relative ability to analyze MS data. RESULTS: We compare the performance of several classes of statistical methods for the classification of cancer based on MS spectra. These methods include: linear discriminant analysis, quadratic discriminant analysis, k-nearest neighbor classifier, bagging and boosting classification trees, support vector machine, and random forest (RF). The methods are applied to ovarian cancer and control serum samples from the National Ovarian Cancer Early Detection Program clinic at Northwestern University Hospital. We found that RF outperforms other methods in the analysis of MS data.

Algorithms↗
PubMed2005

Towards characterization of the human urinary peptidome.

Biomarker discovery in human urine has become an evolving and potentially valuable topic in relation to renal function and diseases of the urinary tract. In order to deliver on the promises and to facilitate the development of validated biomarkers or biomarker panels, protein and peptide profiling techniques need high sample throughput, speed of analysis, and reproducibility of results. Here, we outline the performance characteristics of the liquid chromatography/MALDI-TOF-MS based differential peptide display (DPD(1)) approach for separating, detecting, abundance profiling and identification of native peptides derived from human urine. The typical complexity of peptides in human urine (resolution of the technique with respect to detectable number of peptides), the reproducibility (coefficient of variation for abundance profiles of all peptides detected in biological samples) and dynamic range of the technique as well as the lower limit of detection were characterized. A substantial number of peptides present in normal human urine were identified and compared to findings in four published proteome studies. In an explorative approach, pathological urines from patients suffering from post-renal-filtration diseases were qualitatively compared to normal urine. In conclusion, the peptidomics technology as shown here has a great potential for high throughput and high resolution urine peptide profiling analyses. It is a promising tool to study not only renal physiology and pathophysiology and to determine new biomarkers of renal diseases; it also has the potential to study remotely localized or systemic aberrations within human biology.

Adult↗
PubMed2004

Protein profiling in respiratory disease: techniques and impact.

Multifactorial diseases such as respiratory disease call for a global analysis of such disorders. Recent advances in protein profiling techniques may allow for early diagnosis of respiratory disease, which is crucial for intervention and treatment. In order to reduce false-positive rates, clinical diagnosis requires a high degree of sensitivity and specificity to be an effective screening tool. Protein profiles identified by ProteinChip (Ciphergen Biosystems) technology coupled with mass spectrometry affords a global analysis of clinical samples and is beginning to reach acceptable levels of sensitivity and specificity. Combining the profile with another diagnostic tool enhances the effectiveness of protein profiles to classify disease. Although current efforts have centered on serum protein profiling, the local environment of the lung may be better reflected in proteins of bronchoalveolar lavage or sputum. Identification of biomarkers of disease by protein profiling analyses may lead to an understanding of the mechanisms of this disease and contribute to the discovery of new therapeutics for the prevention and treatment of disease. Advancing these analyses are techniques such as ProteinChip mass spectrometry, laser capture microdissection, tissue microarrays and fluorescently labeled antibody bead arrays, which enable the direct global analysis of complex mixtures. Effective high-throughput and ease of use of clinical testing will arrive with improvements in bioinformatics and decreases in instrumentation costs.

Antibodies↗
PubMed2006

Concentrated red grape juice exerts antioxidant, hypolipidemic, and antiinflammatory effects in both hemodialysis patients and healthy subjects.

BACKGROUND: Patients treated with hemodialysis frequently experience cardiovascular complications attributed, among other causes, to dyslipidemia, increased oxidative stress, and inflammation. OBJECTIVE: The aim of the study was to study the effects of dietary supplementation with concentrated red grape juice (RGJ), a source of polyphenols, on lipoprotein profile, antioxidant capacity, LDL oxidation, and inflammatory biomarkers. DESIGN: Twenty-six patients receiving hemodialysis and 15 healthy subjects were instructed to drink 100 mL RGJ/d for 14 d. Blood was drawn at baseline, twice during RGJ supplementation, and twice during the 6-mo follow-up period. As a control, 12 other randomly recruited hemodialysis patients not receiving RGJ were studied. Lipids, apolipoproteins, oxidized LDL, and antioxidant vitamins were measured in plasma. The bioavailability of RGJ polyphenols was assessed in healthy subjects. RESULTS: The maximum plasma concentration of quercetin was achieved 3 h after RGJ ingestion, which indicates that supplement-derived polyphenols are rapidly absorbed. In both healthy subjects and hemodialysis patients, RGJ consumption increased the antioxidant capacity of plasma without affecting concentrations of uric acid or ascorbic acid; reduced the concentration of oxidized LDL; and increased the concentration of cholesterol-standardized alpha-tocopherol. RGJ supplementation also caused a significant decrease in LDL-cholesterol and apolipoprotein B-100 concentrations, while increasing the concentrations of HDL cholesterol and apolipoprotein A-I. In a further study in hemodialysis patients, RGJ supplementation for 3 wk significantly reduced plasma monocyte chemoattractant protein 1, an inflammatory biomarker associated with cardiovascular disease risk. CONCLUSION: Dietary supplementation with concentrated RGJ improves the lipoprotein profile, reduces plasma concentrations of inflammatory biomarkers and oxidized LDL, and may favor a reduction in cardiovascular disease risk.

Adult↗
PubMed2005

Biomarker metabolites capturing the metabolite variance present in a rice plant developmental period.

BACKGROUND: This study analyzes metabolomic data from a rice tillering (branching) developmental profile to define a set of biomarker metabolites that reliably captures the metabolite variance of this plant developmental event, and which has potential as a basis for rapid comparative screening of metabolite profiles in relation to change in development, environment, or genotype. Changes in metabolism, and in metabolite profile, occur as a part of, and in response to, developmental events. These changes are influenced by the developmental program, as well as external factors impinging on it. Many samples are needed, however, to characterize quantitative aspects of developmental variation. A biomarker metabolite set could benefit screening of quantitative plant developmental variation by providing some of the advantages of both comprehensive metabolomic studies and focused studies of particular metabolites or pathways. RESULTS: An appropriate set of biomarker metabolites to represent the plant developmental period including the initiation and early growth of rice tillering (branching) was obtained by: (1) determining principal components of the comprehensive metabolomic profile, then (2) identifying clusters of metabolites representing variation in loading on the first three principal components, and finally (3) selecting individual metabolites from these clusters that were known to be common among diverse organisms. The resultant set of 21 biomarker metabolites was reliable (P = 0.001) in capturing 83% of the metabolite variation in development. Furthermore, a subset of the biomarker metabolites was successful (P = 0.05) in correctly predicting metabolite change in response to environment as determined in another rice metabolomics study. CONCLUSION: The ability to define a set of biomarker metabolites that reliably captures the metabolite variance of a plant developmental event was established. The biomarker metabolites are all commonly present in diverse organisms, so studies of their quantitative relationships can provide comparative information concerning metabolite profiles in relation to change in plant development, environment, or genotype.

Amino Acids↗
PubMed2005

Pregnancy-associated plasma protein-A levels in patients with acute coronary syndromes: comparison with markers of systemic inflammation, platelet activation, and myocardial necrosis.

OBJECTIVES: The goal of this study was to determine the predictive value of pregnancy-associated plasma protein-A (PAPP-A) in patients with acute coronary syndromes (ACS). BACKGROUND: Pregnancy-associated plasma protein-A is a zinc-binding matrix metalloproteinase abundantly expressed in eroded and ruptured plaques and may serve as a marker of plaque destabilization. METHODS: In 547 patients with angiographically validated ACS and in a heterogeneous emergency room population of 644 patients with acute chest pain, respectively, PAPP-A as well as markers of myocardial necrosis (troponin T [TnT]), ischemia (vascular endothelial growth factor [VEGF]), inflammation (high-sensitivity C-reactive protein [hsCRP]), anti-inflammatory activity (interleukin [IL]-10), and platelet activation (soluble CD40 ligand [sCD40L]) were determined. Patients were followed for the occurrence of death or myocardial infarction. RESULTS: In patients with ACS, elevated PAPP-A levels (>12.6 mIU/l) indicated an increased risk (odds ratio 2.44 [95% confidence interval (CI) 1.43 to 4.15]; p = 0.001). When the analysis was restricted to TnT-negative patients, PAPP-A still identified a subgroup of high-risk patients (odds ratio [OR] 2.72 [95% confidence interval (CI) 1.25 to 5.89]; p = 0.009). In a multivariable model, PAPP-A (OR 2.01; p = 0.015), sCD40L (OR 2.37; p = 0.003), IL-10 (OR 0.43; p = 0.003), and VEGF (OR 2.19; p = 0.018) were independent predictors. Prospective validation in patients with chest pain confirmed that PAPP-A levels reliably identify high-risk patients (adjusted OR 2.32 [95% CI 1.32 to 4.26]; p = 0.008). Patients negative for all three markers (TnT, sCD40L, and PAPP-A) were at very low cardiac risk (30 days: 3.0% event rate; no death). CONCLUSIONS: The PAPP-A level as a marker of plaque instability is a strong independent predictor of cardiovascular events in patients with ACS. Simultaneous determination of biomarkers with distinct pathophysiological profiles appears to remarkably improve risk stratification in patients with ACS.

Adult↗
PubMed2025

Integrative multi-omics profiling deciphers tumor microenvironment heterogeneity and immunotherapy vulnerabilities in lung neuroendocrine carcinomas.

INTRODUCTION: Lung neuroendocrine carcinomas (Lu-NECs) are rare, highly aggressive lung tumors with poor prognosis and limited therapeutic options. Understanding the tumor immune microenvironment (TIME) is crucial towards personalized therapeutic strategies. OBJECTIVES: This study aims to systematically characterize the heterogeneity and complexity of the TIME in Lu-NECs by integrating proteomic, transcriptomic, and genomic data. METHODS: We performed comprehensive immune-proteomic profiling of 76 Lu-NECs across diverse histopathological subtypes to elucidate intra-tumoral TIME heterogeneity at the proteomic level. Validation was conducted in multiple independent cohorts, including 112 Lu-NECs using immunohistochemistry, 147 Lu-NECs, and 17 small cell lung carcinoma samples using transcriptomics. We integrated proteomic, transcriptomic, genomic, and clinical data to assess molecular, immunological, and clinical features, as well as therapeutic vulnerabilities across different immune subtypes. RESULTS: We delineated the immuno-proteomic landscape of Lu-NECs and identified two major immuno-proteomic clusters with distinct immunological, molecular, and clinical characteristics. IPC1 was characterized by high immune cell infiltration, while IPC2 exhibited sparse immune cell presence. Genomic analysis revealed distinct mutational patterns, with IPC1 showing a higher incidence of APOBEC-associated mutation signatures and IPC2 being enriched for mutations associated with defective DNA mismatch repair and tobacco-related mutagens. Functional analyses indicated that IPC1 was related to immune and oncogenic signaling activity, whereas IPC2 was associated with cancer stemness and proliferation-related features. Furthermore, IPC1 and IPC2 demonstrated histological subtype-specific clinical benefits from postoperative chemotherapy. Finally, we developed a machine learning model (iPROM) to predict Lu-NECs immune classification and improve risk stratification, which was validated across multiple independent cohorts. CONCLUSIONS: This study advances the understanding of the tumor immune microenvironment in Lu-NECs through multi-omics characterization and highlights potential personalized therapeutic vulnerabilities tailored to the specific immune landscapes of Lu-NECs.

Humans↗
PubMed2025

Colorectal Liver Metastasis Pathomics Model: Integrating Single-Cell and Spatial Transcriptome Analysis With Pathomics for Predicting Liver Metastasis in Colorectal Cancer.

The liver is the primary target organ for hematologic metastasis of colorectal cancer (CRC), and CRC liver metastasis (CRLM) often precludes radical resection, making it the leading cause of death in patients with CRC. To improve the identification and prediction of liver metastasis risk, we identified a cell type of liver metastasis--triggering malignant cells (LMTMCs) through integrating single-cell RNA sequencing and spatial transcriptome analysis. Multiomics cell communication analysis indicated that the interaction between fibroblasts and LMTMCs through the COL1A1-CD44/SDC4 and LAMA4-CD44 signaling axes could promote CRLM. By applying the one-class logistic regression algorithm, we developed a CRLM scoring system in the bulk RNA-sequencing data according to the abundance of LMTMCs in each individual. Using the grouping labels derived from the CRLM scoring system in the bulk data and the corresponding whole-slide images without any manual annotations at the region or pixel level, processed via slide-level weakly supervised learning, a deep-learning model based on the ResNet18 architecture, called Colorectal Liver Metastasis Pathomics Model, was developed to predict the risk of liver metastasis in patients with CRC. The Colorectal Liver Metastasis Pathomics Model achieved an area under the curve of 0.84 at the internal test set of The Cancer Genome Atlas-CRC histology images. In the external independent validation sets, namely the Affiliated Hospital of Southwest Medical University and the Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University cohorts, the areas under the curve were 0.89 and 0.72, respectively, indicating effective classification performances. This study provided new insights and tools for the early identification of CRLM and demonstrated the potential of combining multiomics with deep learning-based pathomics in cancer research.

Humans↗
PubMed2006

microRNAs as oncogenes and tumor suppressors.

microRNAs (miRNAs) are a new class of non-protein-coding, endogenous, small RNAs. They are important regulatory molecules in animals and plants. miRNA regulates gene expression by translational repression, mRNA cleavage, and mRNA decay initiated by miRNA-guided rapid deadenylation. Recent studies show that some miRNAs regulate cell proliferation and apoptosis processes that are important in cancer formation. By using multiple molecular techniques, which include Northern blot analysis, real-time PCR, miRNA microarray, up- or down-expression of specific miRNAs, it was found that several miRNAs were directly involved in human cancers, including lung, breast, brain, liver, colon cancer, and leukemia. In addition, some miRNAs may function as oncogenes or tumor suppressors. More than 50% of miRNA genes are located in cancer-associated genomic regions or in fragile sites, suggesting that miRNAs may play a more important role in the pathogenesis of a limited range of human cancers than previously thought. Overexpressed miRNAs in cancers, such as mir-17-92, may function as oncogenes and promote cancer development by negatively regulating tumor suppressor genes and/or genes that control cell differentiation or apoptosis. Underexpressed miRNAs in cancers, such as let-7, function as tumor suppressor genes and may inhibit cancers by regulating oncogenes and/or genes that control cell differentiation or apoptosis. miRNA expression profiles may become useful biomarkers for cancer diagnostics. In addition, miRNA therapy could be a powerful tool for cancer prevention and therapeutics.

Animals↗
PubMed2001

Response of river otters to experimental exposure of weathered crude oil: fecal porphyrin profiles.

Profiles of porphyrins were characterized in fecal samples from river otters (Lontra canadensis) experimentally exposed to weathered crude oil to determine effects on heme synthesis. Fifteen male river otters were randomly assigned to three groups of five individuals each representing a control group, a low-dosage group that received 5 mg/kg body mass of oil per day, and a high-dosage group that received 50 mg/kg body mass of oil per day. Mean levels of coproporphyrin III (CoproIII) and protoporphyrin IX (ProtoIX) in fecal samples collected from all experimental river otters were higher throughout the experimental period than levels of CoproIII and ProtoIX in fecal samples collected previously at two field sites. No statistically significant differences in levels of CoproIII and ProtoIX were observed between treatment groups, although a trend of reduction in variability in CoproIII was observed in the low- and high-dose groups. We found no relation between levels of CoproIII and ProtoIX, suggesting that the process of disruption that leads to oxidation of the precursors of porphyrins is probably nonlinear. Our results also indicate that the interaction between oiled induced reduction in hemoglobin levels and induction of CYP1A1 corresponded with significantly lower levels of ProtoIX in the fecal samples, possibly representing high demand for ProtoIX. Therefore, while this experiment does not support the use of porphyrin profiles as an individual biomarker, it does suggest that the latter may be valuable when a weight of evidence is used in an ecotoxicological risk assessment in which the interactions between several biomarkers are explored.

Animals↗
PubMed2006

Comparative profiling of the mammalian mitochondrial proteome: multiple aconitase-2 isoforms including N-formylkynurenine modifications as part of a protein biomarker signature for reactive oxidative species.

The activity of mitochondria induces, as a byproduct, a variety of post-translational modifications in associated proteins, which have functional downstream consequences for processes such as apoptosis, autophagy, and plasticity; e.g., reactive oxygen species (ROS), which induce N-formyl-kynurenine from oxidized tryptophans in certain mitochondrial proteins which are localized in close spatial proximity to their source. This type of fast molecular changes has profound influence on cell death and survival with implications in a number of pathologies. The quantitative and differential analysis of bovine heart mitochondria by four 2D-PAGE methods, including 2D-PAGE with high-resolution IEF as first dimension, revealed that due to limited resolution, those methods employing blue native-, tricine-urea-, and 16-BAC-PAGE as the first dimension are less applicable for the differential quantitative analysis of redundant protein spots which might give insight into post-translational modifications that are relevant in age- and stress-related changes. Moreover, 2D-PAGE with high resolution IEF was able to resolve a surprisingly large number of membrane proteins from mitochondrial preparations. For aconitase-2, an enzyme playing an important role in mitochondrial aging, a more thorough molecular analysis of all separable isoforms was performed, leading to the identification of two particular N-formylkynurenine modifications. Next to protein redundancy, native protein-protein interactions, with the potential of relating certain post-translational modification patterns to distinct oligomeric states, e.g., oxidative phosphorylation super complexes, might provide novel and (patho-) physiologically relevant information. Among proteins identified, 14 new proteins (GenBank entries), previously not associated with mitochondria, were found.

Aconitate Hydratase↗
PubMed2007

A new analytical material-enhanced laser desorption ionization (MELDI) based approach for the determination of low-mass serum constituents using fullerene derivatives for selective enrichment.

60]fullerene derivatives (dioctadecyl methano[60]fullerene, [60]fullerenoacetic acid, and IDA-[60]fullerene) were prepared and subjected to a comprehensive characterization study including protein binding properties and capacity. These fullerene derivatives were successfully applied as material-enhanced laser desorption/ionization (MELDI) carrier materials. It is shown that diverse functionalities result in characteristic human serum peak patterns (m/z 2000-20 000) in terms of signal intensity as well as the number of detectable masses. In addition, the fullerene derivatives clearly provided differences in the low molecular weight mass region (m/z 1000-4000) after elution of the adsorbed serum constituents, and [60]fullerenoacetic acid was the most effective carrier material. Novel high-speed, monolithic, high-resolution capillary columns, prepared by thermally initiated copolymerization of methylstyrene (MSt) and 1,2-bis(p-vinylphenyl)ethane (BVPE) were employed for eluate separation and target spotting. Thus, serum compounds in the low-mass range were successfully fractionated and subjected to MALDI-MS/MS analysis. This contribution, hence, proposes a new "top-down" strategy for proteome research enabling protein profiling as well as biomarker identification in the low-mass range using selective enrichment, high-resolution separation, and offline MALDI-MS/MS evaluation.

Adsorption↗
PubMed2006

Combination therapy with aromatase inhibitors: the next era of breast cancer treatment?

Long-term endocrine therapy with either aromatase inhibitors (AIs) or tamoxifen may lead to endocrine resistance and disease progression. Recent years have seen advances in our understanding of the complex biological mechanisms associated with resistance. Growth factor signaling pathways appear to be upregulated in hormone-resistant tumours and interact with oestrogen-receptor (ER) signaling, which remains functional even after long-term endocrine deprivation. Signaling through the human epidermal and insulin-like growth-factor receptor (HER and IGFR, respectively) pathways may promote ligand-independent ER gene transcription and stimulate growth factor signaling. Therapeutic agents that inhibit these signal transduction pathways, when combined with AIs, may offer breast cancer patients new hope for more robust, longer-term remissions. Preliminary data from phase II studies of combination therapies are encouraging. There is a large programme of ongoing randomised, controlled trials, the results of which should pave the way for integrating combination therapies into clinical practice. To identify which patients will respond best to particular combinations of treatments, biomarkers and gene expression profiles are being investigated as predictors of sensitivity or resistance. In time, breast cancer treatment will become truly individualised because physicians will be able to match patients with a variety of disease phenotypes to optimal combination therapies.

Antineoplastic Agents, Hormonal↗
PubMed2001

The polycyclic aromatic hydrocarbon and geochemical biomarker composition of sediments from voes and coastal areas in the Shetland and Orkney Islands.

Marine sediments from coastal areas and voes in the Shetland and Orkney Islands were analysed for parent and branched 2- to 6-ring polycyclic aromatic hydrocarbons (PAHs) and geochemical biomarkers. Where possible 14 sediment samples were collected at random from each of 17 Shetland and 9 Orkney sites. The wide range of total PAH concentrations in sediments (i.e., < LOD up to 22619 ng g(-1) dry weight) was indicative of a variety of anthropogenic activities and different sediment types associated with the specific locations. Low PAH concentrations were determined in sandy sediments from areas of limited boat activity. The highest PAH concentrations were found in muddy sediment close to a boat repair yard. PAH concentration ratios were consistent with the main source of these compounds, in most areas, being pyrolysis. Geochemical biomarker (triterpane and sterane) profiles from the sediment were indicative, for some areas, of limited petrogenic input. Punds Voe was the only voe to show evidence of North Sea oil. PAH profiles were similar across sites within each island group, with any differences attributable to known local sources of PAHs. However, there was a clear difference in the PAH profiles of Shetland and Orkney sediments, with Orkney sediments having a higher proportion of the lighter alkylated PAHs.

Environmental Monitoring↗