Linked Life Data

21707281

Source:http://linkedlifedata.com/resource/pubmed/id/21707281

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
6
pubmed:dateCreated
2011-6-28
pubmed:abstractText
Evaluation of: Smith SC, Baras AS, Dancik G et al. A 20-gene model for molecular nodal staging of bladder cancer: development and prospective assessment. Lancet Oncol. 12, 137-143 (2011). Accurate identification of nodal status in patients with bladder cancer is important in determining their prognosis and administration of perioperative chemotherapy. In this article, we review the study by Smith and colleagues, documenting the identification of a 20-gene model that can predict nodal stage in patients with bladder cancer based on the profiles of their primary tumors. The gene-expression model generated in this study was able to identify node-positive disease based on tumor tissues obtained from patients in a Phase III bladder cancer trial cohort. The model was able to predict nodal status independent of standard clinicopathologic prognostic criteria. This study adds the agnostic profiling dimension to prior investigations that have attempted to define molecular signatures that predict nodal metastasis in bladder cancer patients based on the primary tumors' gene-expression profiles.
pubmed:commentsCorrections
pubmed:language
eng
pubmed:journal
pubmed:status
PubMed-not-MEDLINE
pubmed:month
Jun
pubmed:issn
1744-8328
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
11
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
849-52
pubmed:year
2011
pubmed:articleTitle
Molecular signatures that predict nodal metastasis in bladder cancer: does the primary tumor tell tales?
pubmed:affiliation
University of Southern California Keck School of Medicine, Center for Personalized Medicine, 4650 Sunset Blvd, SRT 1014, Los Angeles, CA 90027, USA.
pubmed:publicationType
Journal Article, Comment