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      Call for Papers: Green Renal Replacement Therapy: Caring for the Environment

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      Serum protein profile alterations in hemodialysis patients.

      American journal of nephrology
      Adult, Blood Proteins, analysis, Female, Humans, Male, Middle Aged, Renal Dialysis, Renal Insufficiency, blood, therapy

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          Abstract

          Serum protein profiling patterns can reflect the pathological state of a patient and therefore may be useful for clinical diagnostics. Here, we present results from a pilot study of proteomic expression patterns in hemodialysis patients designed to evaluate the range of serum proteomic alterations in this population. Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) was used to analyze serum obtained from patients on periodic hemodialysis treatment and healthy controls. Serum samples from patients and controls were first fractionated into six eluants on a strong anion exchange column, followed by application to four array chemistries representing cation exchange, anion exchange, metal affinity and hydrophobic surfaces. A total of 144 SELDI-TOF-MS spectra were obtained from each serum sample. The overall profiles of the patient and control samples were consistent and reproducible. However, 30 well-defined protein differences were observed; 15 proteins were elevated and 15 were decreased in patients compared to controls. Serum from 1 patient exhibited novel protein peaks suggesting possible additional changes due to a secondary disease process. SELDI-TOF-MS demonstrated consistent serum protein profile differences between patients and controls. Similarity in protein profiles among dialysis patients suggests that patient physiological responses to end-stage renal disease and/or dialysis therapy have a major effect on serum protein profiles. Copyright 2004 S. Karger AG, Basel

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          Use of proteomic patterns in serum to identify ovarian cancer.

          New technologies for the detection of early-stage ovarian cancer are urgently needed. Pathological changes within an organ might be reflected in proteomic patterns in serum. We developed a bioinformatics tool and used it to identify proteomic patterns in serum that distinguish neoplastic from non-neoplastic disease within the ovary. Proteomic spectra were generated by mass spectroscopy (surface-enhanced laser desorption and ionisation). A preliminary "training" set of spectra derived from analysis of serum from 50 unaffected women and 50 patients with ovarian cancer were analysed by an iterative searching algorithm that identified a proteomic pattern that completely discriminated cancer from non-cancer. The discovered pattern was then used to classify an independent set of 116 masked serum samples: 50 from women with ovarian cancer, and 66 from unaffected women or those with non-malignant disorders. The algorithm identified a cluster pattern that, in the training set, completely segregated cancer from non-cancer. The discriminatory pattern correctly identified all 50 ovarian cancer cases in the masked set, including all 18 stage I cases. Of the 66 cases of non-malignant disease, 63 were recognised as not cancer. This result yielded a sensitivity of 100% (95% CI 93--100), specificity of 95% (87--99), and positive predictive value of 94% (84--99). These findings justify a prospective population-based assessment of proteomic pattern technology as a screening tool for all stages of ovarian cancer in high-risk and general populations.
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            Disease proteomics.

            Sam Hanash (2003)
            The sequencing of the human genome and that of numerous pathogens has opened the door for proteomics by providing a sequence-based framework for mining proteomes. As a result, there is intense interest in applying proteomics to foster a better understanding of disease processes, develop new biomarkers for diagnosis and early detection of disease, and accelerate drug development. This interest creates numerous opportunities as well as challenges to meet the needs for high sensitivity and high throughput required for disease-related investigations.
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              From genomics to proteomics.

              Proteomics is the study of the function of all expressed proteins. Tremendous progress has been made in the past few years in generating large-scale data sets for protein-protein interactions, organelle composition, protein activity patterns and protein profiles in cancer patients. But further technological improvements, organization of international proteomics projects and open access to results are needed for proteomics to fulfil its potential.
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                Author and article information

                Journal
                15031630
                10.1159/000077409

                Chemistry
                Adult,Blood Proteins,analysis,Female,Humans,Male,Middle Aged,Renal Dialysis,Renal Insufficiency,blood,therapy
                Chemistry
                Adult, Blood Proteins, analysis, Female, Humans, Male, Middle Aged, Renal Dialysis, Renal Insufficiency, blood, therapy

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