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      Serum Protein Profile Alterations in Hemodialysis Patients

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          Abstract

          Background: 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. Methods: 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. Results: 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. Conclusion: 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.

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          Most cited references 7

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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
                AJN
                Am J Nephrol
                10.1159/issn.0250-8095
                American Journal of Nephrology
                S. Karger AG
                0250-8095
                1421-9670
                2004
                April 2004
                08 April 2004
                : 24
                : 2
                : 268-274
                Affiliations
                aLawrence Livermore National Laboratory, Livermore, Calif.; bCiphergen Biosystems, Fremont, Calif. and cDiablo Nephrology Medical Group, Inc., Walnut Creek, Calif., USA
                Article
                77409 Am J Nephrol 2004;24:268–274
                10.1159/000077409
                15031630
                © 2004 S. Karger AG, Basel

                Copyright: All rights reserved. No part of this publication may be translated into other languages, reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording, microcopying, or by any information storage and retrieval system, without permission in writing from the publisher. Drug Dosage: The authors and the publisher have exerted every effort to ensure that drug selection and dosage set forth in this text are in accord with current recommendations and practice at the time of publication. However, in view of ongoing research, changes in government regulations, and the constant flow of information relating to drug therapy and drug reactions, the reader is urged to check the package insert for each drug for any changes in indications and dosage and for added warnings and precautions. This is particularly important when the recommended agent is a new and/or infrequently employed drug. Disclaimer: The statements, opinions and data contained in this publication are solely those of the individual authors and contributors and not of the publishers and the editor(s). The appearance of advertisements or/and product references in the publication is not a warranty, endorsement, or approval of the products or services advertised or of their effectiveness, quality or safety. The publisher and the editor(s) disclaim responsibility for any injury to persons or property resulting from any ideas, methods, instructions or products referred to in the content or advertisements.

                Page count
                Figures: 2, Tables: 1, References: 23, Pages: 7
                Product
                Self URI (application/pdf): https://www.karger.com/Article/Pdf/77409
                Categories
                Original Report: Laboratory Investigation

                Cardiovascular Medicine, Nephrology

                Hemodialysis, Protein profiling, Biomarkers, Proteomics, SELDI-TOF-MS

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