| Co-Investigator(Kenkyū-buntansha) |
TOGE Tetsuya Hiroshima University, Research Institute for Radiation Biology and Medicine, Professor, 原爆放射線医科学研究所, 教授 (40034657)
OHTAKI Megu Hiroshima University, Research Institute for Radiation Biology and Medicine, Professor, 原爆放射線医科学研究所, 教授 (20110463)
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| Research Abstract |
Efforts to promote personalized medicine have led to better tools for prediction of individual response to drugs, in both toxicity and effect, but enormous tasks remain to be done. For efficacy prediction, very few critical markers have been validated to date, and a laboratory analysis system which can simultaneously predict response to several potent drugs or regimes based on understanding the interplay of multiple prediction markers has not yet been developed.
In the present study, we newly developed or demonstrated
1)concise, accurate prediction models of the in vitro activity for 8 anticancer drugs (5-FU,CDDP,MMC,DOX,CPT-11,SN-38,TXL, and TXT), along with individual clinical responses to 5 FU using expression data of 12 genes,
2)novel normalization methods of expression levels in CDNA microarray,
3)important roles of methylation and AP-1 in the transcriptional regulation of DPYD gene, a key gene related to fuluoropyrmidines resoponse,
4)biological roles of BCL-2,DEC1,DEC2, and HIFIα in tumor response to various stress.,
5)genes related to tumor immortalization,
6)roles of CYP3A4,CYP2C8, and UGT1A1 polymorphisms in drug response,
and
7)therapeutic potential of TXT/S-1 in gastric cancer.
These development of a potent therapy and identification of new indicators of individual response to drugs may present the opportunity to establish a novel chemotherapeutic strategy, personalized medicine, which would allow selection of an optimal regimen for each individual based on gene expression profile and/or genomic make-up, in pre-operative adjuvant chemotherapy for gastrointestinal cancers. In parallel with the development of the prediction models for clinical responses to several active combination chemotherapies using clinical samples, a prospective clinical study to clarify the value of the prediction formulae and newly suggested indicators will commence soon.
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