Linked Life Data

16596231

Source:http://linkedlifedata.com/resource/pubmed/id/16596231

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
5
pubmed:dateCreated
2006-4-5
pubmed:abstractText
Esophageal cancer is a highly lethal disease and the optimal therapy remains unclear. Since adjuvant chemotherapy gives a better chance of survival, we attempted to develop a chemosensitivity prediction model to improve individual responses to therapy. Comprehensive gene expression analyses (cDNA and oligonucleotide microarrays) and MTT assay of 8 drugs in 20 KYSE squamous cell carcinoma cell lines were performed to distinguish candidate marker genes whose expression levels reproducibly correlated with cellular drug sensitivities. After confirmation with real-time RT-PCR, we performed multiple regression analyses to develop drug-sensitivity prediction formulae using the quantified expression data of selected marker genes. Using the same sets of genes, we also constructed prediction models for individual clinical responses to 5-FU-based chemotherapy using 18 cases. We selected 5 better marker genes, known as drug sensitivity determinants, identified 9 novel predictive genes for 4 of 8 anticancer drugs [5-FU, CDDP, DOX, and CPT-11 (SN-38)], and developed highly predictive formulae of in vitro sensitivities to the 4 drugs and clinical responses to 5-FU-based adjuvant chemotherapies in terms of overall and disease-free survivals. Our selected genes are likely to be effective drug-sensitivity markers and formulae using the 9 novel genes would provide advantages in prediction.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
May
pubmed:issn
1019-6439
pubmed:author
pubmed:issnType
Print
pubmed:volume
28
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1153-62
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
2006
pubmed:articleTitle
Chemosensitivity prediction in esophageal squamous cell carcinoma: novel marker genes and efficacy-prediction formulae using their expression data.
pubmed:affiliation
Department of Translational Cancer Research, Research Institute for Radiation Biology and Medicine, Hiroshima University, Hiroshima 734-8553, Japan.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't