Linked Life Data

20845545

Source:http://linkedlifedata.com/resource/pubmed/id/20845545

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2010-9-15
pubmed:abstractText
The authors analysed the value of metabolomic profiles to predict biochemical progression (BP) risk in patients with prostate cancer (PCa) submitted to radical prostatectomy(RP). They retrospectively analysed 183 PCa cases submitted to RP, using an intact-tissue magnetic resonance spectroscopy(MRS) method. A high-resolution, magic-angle, spinning proton MRS was used to investigate a metabolomic analysis of still-intact prostate tissue. This method allows study of chemical metabolites in their native state and control of intact tissue spectra, preserving the tissue for pathologic analysis. In this study, metabolomic profiles analysed by MRS could differentiate cases of PCa with BP after RP from clinical and pathologic-stage matched cases without BP.The major contributing factors to the observed metabolomic profiles were changes in spermine polyamines,phosphoryl choline, glutamine, inositol, and glutamate. The overall accuracy for predicting BP based on metabolomic profiles ranged from 71% to 78%. The suggestion is that PCa metabolic profiles studied at RP with MRS may provide available adjunct parameter to predict the risk of progression after surgery.
pubmed:commentsCorrections
pubmed:language
eng
pubmed:journal
pubmed:status
PubMed-not-MEDLINE
pubmed:month
Aug
pubmed:issn
1873-7560
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
58
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
315
pubmed:year
2010
pubmed:articleTitle
Words of wisdom. Re: Retrospective analysis of prostate cancer recurrence potential with tissue metabolomic profiles. Maxeiner A, Adkins CB, Zhang Y, et al. Prostate 2010;70:710-7.
pubmed:affiliation
Department of Urology Bracci, University Sapienza of Rome, Italy. sciarra.md@libero.it
pubmed:publicationType
Journal Article, Comment