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

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      About Blood Purification: 3.0 Impact Factor I 5.6 CiteScore I 0.83 Scimago Journal & Country Rank (SJR)

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      Proteomics in nephrology: current status and future directions.

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      Journal: American journal of nephrology
      Keywords: Animals, Biological Markers, analysis, Forecasting, Humans, Kidney, physiology, Kidney Diseases, physiopathology, Nephrology, trends, Proteomics

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          Abstract

          Proteomics is one among various 'OMICS' fields that have been growing rapidly in the postgenomic era. During the past few years, proteomics has been extensively applied to several fields of medicine to better understand normal physiology, to define the pathophysiology of diseases, and to identify novel biomarkers and new therapeutic targets. This review focuses on current status and future directions of proteomics in the nephrology field. Recent studies of renal proteome, proteomes of individual intrarenal structures (i.e., glomerular, vascular, tubular, brush border membrane, mesangial, and podocyte proteomes), urinary proteome, and protein profiles in dialysate or ultrafiltrate removed by renal replacement therapy are summarized. Copyright 2004 S. Karger AG, Basel

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          A generic protein purification method for protein complex characterization and proteome exploration.

          G Rigaut, A. Shevchenko, B Rutz … (1999)
          We have developed a generic procedure to purify proteins expressed at their natural level under native conditions using a novel tandem affinity purification (TAP) tag. The TAP tag allows the rapid purification of complexes from a relatively small number of cells without prior knowledge of the complex composition, activity, or function. Combined with mass spectrometry, the TAP strategy allows for the identification of proteins interacting with a given target protein. The TAP method has been tested in yeast but should be applicable to other cells or organisms.
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            Protein kinases and phosphatases: the yin and yang of protein phosphorylation and signaling.

            Tony Hunter (1995)
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              Use of proteomic patterns in serum to identify ovarian cancer.

              Emanuel Petricoin, Ali M. Ardekani, Ben Hitt … (2002)
              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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                Author and article information

                Journal
                PubMed ID:: 15205555
                DOI:: 10.1159/000079148

                ScienceOpen disciplines: Chemistry
                Keywords: Animals,Biological Markers,analysis,Forecasting,Humans,Kidney,physiology,Kidney Diseases,physiopathology,Nephrology,trends,Proteomics
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                ScienceOpen disciplines: Chemistry
                Keywords: Animals, Biological Markers, analysis, Forecasting, Humans, Kidney, physiology, Kidney Diseases, physiopathology, Nephrology, trends, Proteomics

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