Gene/Protein Disease Symptom Drug Enzyme Compound
Pivot Concepts: Gene/Protein Disease Symptom Drug Enzyme Compound   Target Concepts: Gene/Protein Disease Symptom Drug Enzyme Compound

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Query: UMLS:C0376358 (prostate cancer)
59,338 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Prostate cancer cells metastasize to bone causing a predominantly osteosclerotic response. It has been shown that cells from the human prostate cancer cell line PC3 secrete factors that influence the behavior of osteoblast-like cells. Some of these factors with mitogenic activity have been found to be proteins with molecular weights between 20 and 30 kDa, but the identity of the osteoblastic mitogenic factor or factors produced by prostate cancer cells is still unknown. Therefore, the aim of this study was to characterize the protein profile of conditioned medium (CM) from PC3 cells in the molecular weight range from 5 to 30 kDa using proteome analysis. A protein profile of the CM from PC3 cells was performed by two-dimensional polyacrylamide gel electrophoresis (2D-PAGE). Thirty protein spots with molecular weights ranging from 5 to 30 kDa were analyzed by matrix assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS). One of these spots was identified as galectin-1. We examined whether PC3 CM, recombinant galectin-1 alone, or combined with insulin-like growth factor-I (IGF-I) had any effects on the proliferation or differentiation of human bone marrow stromal (hBMS) cells. Furthermore, we tested whether adhesion of PC3 cells to plastic, laminin, fibronectin, and collagen type I was influenced by lactose, which inhibits galectin-1. Galectin-1 (1000 ng/ml) inhibited the proliferation of hBMS cells up to 70 +/- 12% (treated/control) of control in contrast to PC3 CM, which induced hBMS cell proliferation by 3-fold. This effect was abolished by IGF-I. PC3 CM and galectin-1 in concentrations of 10 and 1000 ng/ml increased the alkaline phosphatase (ALP) activity of hBMS cells up to 175 +/- 27%, 137 +/- 8%, and 131 +/- 11%, respectively, compared with ALP activity of untreated cells, and inhibited the secretion of osteocalcin (OC) up to 81 +/- 3%, 93 +/- 1%, and 58 +/- 2%, respectively, compared with OC secretion of untreated cells. These effects were affected by IGF-I. Lactose inhibited adhesion of PC3 cells to plastic, fibronectin, laminin, and collagen type I up to 58 +/- 4%, 30 +/- 12, 72 +/- 9%, and 86 +/- 4%. In conclusion, galectin-1 modulated osteoblastic proliferation and differentiation. These effects were affected by IGF-I. Thus, galectin-1 is likely be involved in the osteoblastic response, caused by prostate cancer cells metastasizing into bone, by affecting the matrix mineralization.
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PMID:A proteome study of secreted prostatic factors affecting osteoblastic activity: galectin-1 is involved in differentiation of human bone marrow stromal cells. 1256 96

Prostate cancer cells metastasise to bone causing a predominantly osteosclerotic response. It has previously been shown that PC3 cells secrete factors which stimulate the mitogenic activity of human bone marrow stromal (hBMS) cells. Some of these mitogens have been found to be proteins with a molecular weight between 20 and 30 kDa. Even though a number of investigations have been performed to identify the osteoblastic mitogenic factor or factors produced by prostate cancer cells, it is still unknown what causes the mitogenic activation of osteoblasts. Therefore, the aim of this study was to characterise the protein profile of conditioned medium (CM) from PC3 cells in the molecular weight range of 5-30 kDa using proteome analysis. A protein profile of the CM from PC3 cells was performed by two-dimensional polyacrylamide gel electrophoresis (2D-PAGE). Thirty protein spots with molecular weights ranging from 5 to 30 kDa were analysed by matrix-assisted laser desorption/ionisation time of flight mass spectrometry (MALDI-TOF MS). One of these spots was identified as cyclophilin A. We examined whether cyclophilin A alone or in combination with insulin-like growth factor-I (IGF-I) had any effects on the proliferation or differentiation of hBMS cells. Cyclophilin A at 1, 10, and 100 nM and cyclophilin A at 10 nM combined with 10 ng/ml IGF decreased the proliferation of hBMS cells up to 49+/-30, 38+/-29, 50+/-8 and 60+/-16%, respectively [mean (treated/control)+/-standard error of the means (SEM)] of control. IGF-I did not significantly affect these decreases. Cyclophilin A alone or in combination with IGF-I did not have any effect on differentiation (assessed by measuring the activity of alkaline phosphatase (ALP)). In conclusion, these results suggest cyclophilin A is not involved in the osteosclerotic effects seen when prostate cancer metastasises to bone.
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PMID:A proteome study of secreted prostatic factors affecting osteoblastic activity: identification and characterisation of cyclophilin A. 1270 69

Glutathione-S-transferase (GST) genes encode a family of detoxification enzymes that offer protection against endogenous and exogenous sources of reactive oxygen species (ROS). Germline variations in GST genes may alter the catalytic efficiency of GST isoenzymes leading to a potential increase in susceptibility to the genotoxic effects of ROS and electrophilic substances. A nested case-control study design was used to examine the association between the polymorphic GST genes and prostate cancer risk among Finnish male smokers of the ATBC Cancer Prevention Study. A case-case analysis was used to determine the association between these genetic polymorphisms and prostate cancer progression. Germline DNA was obtained from 206 prostate cancer cases and 194 controls frequency matched on age, intervention group and study clinic. Cases and controls were genotyped for three GST genes using MALDI-TOF mass spectrometry or multiplex polymerase chain reaction (PCR). Relative to the wild-type genotype, we observed a 36% reduction in prostate cancer risk associated with the GST-M1-null genotype (odds ratio (OR) 0.64, 95% confidence interval (CI) 0.43, 0.95). Unlike GST-M1, GST-T1-null (OR 0.74, 95% CI 0.42, 1.33) and GST-P1*B (OR 1.10, 95% CI 0.72, 1.69) were not strongly associated with prostate cancer risk. We did not observe any significant associations between the selected polymorphic GST genes and tumour grade or stage. In conclusion, we did not observe a direct association between polymorphic GST-T1 or GST-P1 and prostate cancer risk. Our observation of a relatively strong inverse association between the GST-M1-null genotype and prostate cancer risk needs to be confirmed in larger association studies.
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PMID:Polymorphisms in glutathione-S-transferase genes (GST-M1, GST-T1 and GST-P1) and susceptibility to prostate cancer among male smokers of the ATBC cancer prevention study. 1288 85

The phytochemical resveratrol (trans-3,4',5-trihydroxystilbene) is a naturally occurring polyphenol with a plethora of health-beneficial properties, including a preventive role in cancer. We surmise that resveratrol may exert its diverse biological effects by interacting with specific target proteins, denoted RTPs. To test this possibility, resveratrol was immobilized on epoxy-activated agarose forming a resveratrol affinity column (RAC), which was used to detect and isolate RTPs. Distinct RTPs can be resolved on RAC by fractionation with increasing NaCl, followed by 1mM ATP, and finally, with 1-2mM resveratrol. A 22-kDa polypeptide, RTP-22, eluted with resveratrol was identified by MALDI-TOF MS and cloning/expression in Escherichia coli, as dihydronicotinamide riboside quinone reductase 2 (NQO2). The utility of RAC was additionally explored with extracts derived from different staging prostate cancer cells. NQO2 was most abundant in CWR22Rv1, a model for prostate cancer transition from androgen-dependent to the hormone-refractory state, but was marginally expressed in JCA-1 cells as representing more advanced stage prostate cancer. These results provide evidence for the existence of distinctive RTPs in mammalian cells and that RAC is a facile approach to identify and purify RTPs.
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PMID:Identification and purification of resveratrol targeting proteins using immobilized resveratrol affinity chromatography. 1538 Oct 63

Class prediction using "omics" data is playing an increasing role in toxicogenomics, diagnosis/prognosis, and risk assessment. These data are usually noisy and represented by relatively few samples and a very large number of predictor variables (e.g., genes of DNA microarray data or m/z peaks of mass spectrometry data). These characteristics manifest the importance of assessing potential random correlation and overfitting of noise for a classification model based on omics data. We present a novel classification method, decision forest (DF), for class prediction using omics data. DF combines the results of multiple heterogeneous but comparable decision tree (DT) models to produce a consensus prediction. The method is less prone to overfitting of noise and chance correlation. A DF model was developed to predict presence of prostate cancer using a proteomic data set generated from surface-enhanced laser deposition/ionization time-of-flight mass spectrometry (SELDI-TOF MS). The degree of chance correlation and prediction confidence of the model was rigorously assessed by extensive cross-validation and randomization testing. Comparison of model prediction with imposed random correlation demonstrated biologic relevance of the model and the reduction of overfitting in DF. Furthermore, two confidence levels (high and low confidences) were assigned to each prediction, where most misclassifications were associated with the low-confidence region. For the high-confidence prediction, the model achieved 99.2% sensitivity and 98.2% specificity. The model also identified a list of significant peaks that could be useful for biomarker identification. DF should be equally applicable to other omics data such as gene expression data or metabolomic data. The DF algorithm is available upon request.
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PMID:Using decision forest to classify prostate cancer samples on the basis of SELDI-TOF MS data: assessing chance correlation and prediction confidence. 1559 13

Prostate specific membrane antigen (PSMA) is a well-characterized glycoprotein overexpressed on the surface of prostate cancer cells. The novel radiopharmaceutical 1,4,7,10-tetraazacyclododecane-N,N',N'',N'''-tetraacetic acid (DOTA) radiolabeled with Yttrium (90Y) or Indium (111In) conjugated with anti-PSMA genetically engineered humanized monoclonal antibody (huJ591) has been investigated to target prostate cancer cells. The immunoconjugate of huJ591 with the analog of the cytotoxic drug maytansine, DM1 (N2'-deacetyl-N2'-(3-mercapto-1-oxopropyl)-maytansine) has also been developed at Millennium Pharmaceuticals. Activation of the DOTA molecule, resulting in 1,4,7,10-tetraazacyclododecane-N,N',N'',N'''-tetraacetic acid mono-(N-hydroxysuccinimidyl) ester (DOTA-NHS), allows conjugation with the anti-PSMA antibody through lysine residues in the antibody. The objectives of the study were to characterize the unstable chemical properties of DOTA-NHS before bioconjugation with huJ591, evaluate the binding profiles of DOTA to huJ591, and calculate trace metal elements (which may disturb 90Y or 111In labeling efficacy to the DOTA-huJ591 conjugate). A novel LC/MS/MS (Liquid Chromatography/Mass Spectrometry/Mass Spectrometry) quantitation method was developed to monitor the stability of DOTA-NHS in solid form and its bioconjugation chemistry reactions. Meanwhile, metal analysis was quantified by Inductively Coupled Plasma Mass Spectrometry (ICP/MS) to estimate the amounts of trace metals in DOTA-NHS and ensure radiolabeling efficiency of the conjugate at the radiopharmacy. MALDI-TOF MS (Matrix-Assisted Laser Desorption Ionization Time-of-Flight Mass Spectrometry) was used to identify levels of DOTA or DM1conjugation in DOTA-huJ591 and DM1-huJ591 conjugates, respectively.
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PMID:Mass spectral analyses of labile DOTA-NHS and heterogeneity determination of DOTA or DM1 conjugated anti-PSMA antibody for prostate cancer therapy. 1572 8

We propose a novel method for phenotype identification involving a stringent noise analysis and filtering procedure followed by combining the results of several machine learning tools to produce a robust predictor. We illustrate our method on SELDI-TOF MS prostate cancer data (http://home.ccr.cancer.gov/ncifdaproteomics/ppatterns.asp). Our method identified 11 proteomic biomarkers and gave significantly improved predictions over previous analyses with these data. We were able to distinguish cancer from non-cancer cases with a sensitivity of 90.31% and a specificity of 98.81%. The proposed method can be generalized to multi-phenotype prediction and other types of data (e.g., microarray data).
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PMID:A robust meta-classification strategy for cancer detection from MS data. 1634 41

We examined hypoxia-induced changes in global thiol proteome profile in human prostate cancer cells using a BIAM-based display method. We analyzed the kinetics of protein thiol modification by using a pattern recognition algorithm, self-organizing maps (SOM) clustering, and identified the BIAM-labeled proteins by MALDI-TOF and ESI-tandem mass spectrometry. We found 99 out of 215 of total BIAM-labeled proteins were affected by hypoxia treatment and, yet, with diverse patterns and kinetics of redox modification. Our study proved that proteomics analysis employing the BIAM-labeling method can provide valuable information pertaining to global changes in the redox status of proteins in response to hypoxia.
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PMID:Analysis of protein redox modification by hypoxia. 1642 39

Speed and accuracy are crucial prerequisites in the application of proteomic methods to clinical medicine. We describe a microfluidic-based nanovial array for rapid proteolytic processing linked to MALDI-TOF MS. This microscale format consumes only minute amounts of sample, and it is compatible with rapid bioanalytical protocols and high-sensitivity readouts. Arrays of vials (300 microm in diameter and 25 microm deep), isotropically etched in silicon wafers were electrochemically porosified. Automated picoliter microdispensing was employed for precise fluid handling in the microarray format. Vials were prefilled with trypsin solution, which was allowed to dry. Porosified and nonporosified nanovials were compared for trypsin digestion and subsequent MS identification of three model proteins: lysozyme, alcohol dehydrogenase, and serum albumin at levels of 100 and 20 fmol. In an effort to assess the rapid digestion platform in a context of putative clinical applications, two prostate cancer biomarkers, prostate-specific antigen (PSA) and human glandular kallikrein 2 (hK2), were digested at levels of 100 fmol (PSA), 20 fmol (PSA) and 8 fmol (hK2). All biomarker digestions were completed in less than 30 s, with successful MS identification in the porous nanovial setting.
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PMID:High-speed biomarker identification utilizing porous silicon nanovial arrays and MALDI-TOF mass spectrometry. 1652 54

Over the past couple of years, proteomics pattern analysis has emerged as an effective method for the early diagnosis of diseases such as ovarian, breast, or prostate cancer, without identification of single biomarkers. MALDI-TOF MS, for example, offers a simple approach for fast and reliable protein profiling, especially by using carrier materials with various physical and chemical properties, in combination with a MALDI matrix. This approach is referred to as material-enhanced laser desorption/ionization (MELDI). In this paper, we report the development and application of derivatized carrier materials [cellulose, silica, poly(glycidyl methacrylate/divinylbenzene) (GMA/DVB) particles, and diamond powder] for fast and direct MALDI-TOF MS protein profiling. The applicability of MELDI for rapid protein profiling was evaluated with human serum samples. These carriers, having various hydrophobicities, resulted in characteristic mass fingerprints, even if all materials were derivatized with iminodiacetic acid (IDA) to yield an immobilized metal affinity chromatography (IMAC) functionality. Our study demonstrates that analyzing complex biological samples, such as human serum, by employing different MELDI carrier materials yielded type- and size-dependent performance variation.
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PMID:Material-enhanced laser desorption/ionization (MELDI)--a new protein profiling tool utilizing specific carrier materials for time of flight mass spectrometric analysis. 1676 19


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