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Pathway analysis of kidney cancer using proteomics and metabolic profiling.

Pathway analysis of kidney cancer using proteomics and metabolic profiling. Research Abstract Details 

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  • Pathway analysis of kidney cancer using proteomics and metabolic profiling. Abstract Text:

    bertrand perroudBertrand Perroud,jinoo leeJinoo Lee,nelly valkovaNelly Valkova,amy dhirapongAmy Dhirapong,pei-yin linPei-Yin Lin,oliver fiehnOliver Fiehn,dietmar Dietmar ,robert h weissRobert H Weiss,

    BACKGROUND: Renal cell carcinoma (RCC) is the sixth leading cause of cancer death and is responsible for 11,000 deaths per year in the US. Approximately one-third of patients present with disease which is already metastatic and for which there is currently no adequate treatment, and no biofluid screening tests exist for RCC. In this study, we have undertaken a comprehensive proteomic analysis and subsequently a pathway and network approach to identify biological processes involved in clear cell RCC (ccRCC). We have used these data to investigate urinary markers of RCC which could be applied to high-risk patients, or to those being followed for recurrence, for early diagnosis and treatment, thereby substantially reducing mortality of this disease. RESULTS: Using 2-dimensional electrophoresis and mass spectrometric analysis, we identified 31 proteins which were differentially expressed with a high degree of significance in ccRCC as compared to adjacent non-malignant tissue, and we confirmed some of these by immunoblotting, immunohistochemistry, and comparison to published transcriptomic data. When evaluated by several pathway and biological process analysis programs, these proteins are demonstrated to be involved with a high degree of confidence (p values < 2.0 E-05) in glycolysis, propanoate metabolism, pyruvate metabolism, urea cycle and arginine/proline metabolism, as well as in the non-metabolic p53 and FAS pathways. In a pilot study using random urine samples from both ccRCC and control patients, we performed metabolic profiling and found that only sorbitol, a component of an alternative glycolysis pathway, is significantly elevated at 5.4-fold in RCC patients as compared to controls. CONCLUSION: Extensive pathway and network analysis allowed for the discovery of highly significant pathways from a set of clear cell RCC samples. Knowledge of activation of these processes will lead to novel assays identifying their proteomic and/or metabolomic signatures in biofluids of patient at high risk for this disease; we provide pilot data for such a urinary bioassay. Furthermore, we demonstrate how the knowledge of networks, processes, and pathways altered in kidney cancer may be used to influence the choice of optimal therapy.

    Pathway analysis of kidney cancer using proteomics and metabolic profiling. Publishing Authors By Initials

    b perroudB Perroud,j leeJ Lee,n valkovaN Valkova,a dhirapongA Dhirapong,py linPY Lin,o fiehnO Fiehn,d D ,rh weissRH Weiss,

    For similar biological factors: biological markers: tumor markers, biological research abstracts see: biological factors: biological markers: tumor markers, biological research

    PUBMED ID PMID:

    MEDLINE DATE:

    Pathway analysis of kidney cancer using proteomics and metabolic profiling. Journal Published:

    PUBLICATION TYPE: Research Support, Non-U.S. Gov

    Journal: Molecular cancer

    VOLUME: 5

    Page Numbers: 64

    Journal Abbreviation: Mol. Cancer

    ISSN: 1476-4598

    DAY: 24

    MONTH: 11

    YEAR: 2006

    Pathway analysis of kidney cancer using proteomics and metabolic profiling. Information

    Number of References:

    LANGUAGE: eng

    NlmUniqueID: 101147698

    Pathway analysis of kidney cancer using proteomics and metabolic profiling. Keywords Mesh Terms:

    KEYWORDS: Tumor Markers, Biological

    MESH TERMS: urine

    Chemical & Substance for Abstract: Pathway analysis of kidney cancer using proteomics and metabolic profiling. Information

    Substance Name: Pyruvate Kinase

    Registry Number: EC 2.7.1.40

    Grant and Affiliation Information for Pathway analysis of kidney cancer using proteomics and metabolic profiling.

    AFFILIATION: Genome Center, University of California, Davis, CA, USA. bperroud@ucdavis.edu

    Country: England

    England Research Publication

    AGENCY: United States NIDDK

    GRANT: R01DK59470

    ACRONYM: DK

    MEDLINETA: Mol Cancer

    REFSOURCE:

    DATABASENAME:

    ACCESSION NUMBER:

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