Literature DB >> 7397636

Biologic markers in breast carcinoma: clinical correlations with urinary polyamines.

D C Tormey, T P Waalkes, K C Kuo, C W Gehrke.   

Abstract

Urinary polyamine levels were evaluated in patients with breast carcinoma. The individual levels of putrescine, spermidine, spermine, and cadaverine, and the product/precursor levels of putrescine, spermidine, and spermine were analyzed. Elevations of one or more individual polyamines or of the ratios were found in 50% of patients with metastatic disease, 38.5% of preoperative patients, and 35.7% of 5--24 week postoperative N + patients. Sequential sampling of patients with metastatic disease suggested that changes in elevated polyamine levels tend to reflect the clinical course of the disease, especially for the association of treatment failure with rising elevated values. The presence of one or more elevated parameters prior to treatment of metastatic disease tended to be associated with a higher response rate (85.7 vs. 68.4%) than all normal levels. Five of nine patients who recurred postoperatively had preceding postoperative polyamine elevations. In addition, there was a trend for a shorter disease-free time among patients with one of more elevated polyamine parameters between 5--24 weeks postoperatively than among patients with normal parameters. These data suggest that measurement of urinary polyamine levels, including calculation of the product/precursor levels, may be a useful clinical adjunct in the management of patients with breast carcinoma.

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Year:  1980        PMID: 7397636     DOI: 10.1002/1097-0142(19800815)46:4<741::aid-cncr2820460418>3.0.co;2-7

Source DB:  PubMed          Journal:  Cancer        ISSN: 0008-543X            Impact factor:   6.860


  3 in total

1.  An enzymatic differential assay for urinary diamines, spermidine, and spermine.

Authors:  S Otsuji; Y Soejima; K Isobe; H Yamada; S Takao; M Nishi
Journal:  J Cancer Res Clin Oncol       Date:  1985       Impact factor: 4.553

2.  Prediction of breast cancer by profiling of urinary RNA metabolites using Support Vector Machine-based feature selection.

Authors:  Carsten Henneges; Dino Bullinger; Richard Fux; Natascha Friese; Harald Seeger; Hans Neubauer; Stefan Laufer; Christoph H Gleiter; Matthias Schwab; Andreas Zell; Bernd Kammerer
Journal:  BMC Cancer       Date:  2009-04-05       Impact factor: 4.430

3.  Metabolic signature of breast cancer cell line MCF-7: profiling of modified nucleosides via LC-IT MS coupling.

Authors:  Dino Bullinger; Hans Neubauer; Tanja Fehm; Stefan Laufer; Christoph H Gleiter; Bernd Kammerer
Journal:  BMC Biochem       Date:  2007-11-29       Impact factor: 4.059

  3 in total

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