| Project/Area Number |
18591769
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (C)
|
| Allocation Type | Single-year Grants |
|---|
| Section | 一般 |
|---|
| Research Field |
Urology
|
|---|
| Research Institution | Iwate Medical University |
|---|
Principal Investigator |
FUJIOKA Tomoaki Iwate Medical University, School of Medicine, Professor (80173409)
|
|---|
| Co-Investigator(Kenkyū-buntansha) |
SUGIMURA Jun Iwate Medical University, School of Medicine, Lecturer (80306018)
OBARA Wataru Iwate Medical University, School of Medicine, Lecturer (90337155)
RYO Takata Iwate Medical University, School of Medicine, Professor (00438467)
|
|---|
| Project Period (FY) |
2006 – 2007
|
| Project Status |
Completed (Fiscal Year 2007)
|
| Budget Amount *help |
¥3,980,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥480,000)
Fiscal Year 2007: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
Fiscal Year 2006: ¥1,900,000 (Direct Cost: ¥1,900,000)
|
|---|
| Keywords | Bladder Cancer / MVAC chemotherapy / Prediction of Chemosensitivity / Gene expression profiles / Personalized medicine / Real-time PCR / M-VAC化学療法 / 術前化学療法 / 個別化医療 / C-VAC療法 |
|---|
| Research Abstract |
To predict the efficacy of the M-VAC neoadjuvant chemotherapy for invasive bladder cancers, we previously established the method to calculate the prediction score on the basis of expression profiles of 14 predictive genes. This time, we constructed the prediction system using handy, cheap, real-time PCR method for a clinical application. First, we designed primers and probes that were able to detect 14 genes that strongly related to response of MVAC chemotherapy. Afterwards, expression level of each gene was analyzed by real-time PCR We used CCT6A as internal control. The obtained level of the gene expression was highly correlated with that of microarrays. We did quantitative real-time RT-CR of the 14 predictive genes for 15 learning cases, and calculated the prediction score for each case. When we estimated these scores by the leave-one-out cross validation test, all cases were placed correctly according to their response to M-VAC. We showed further that the responses of test cases were also predicted with accuracy 'lb examine the possibility of adapting our prediction system for clinical use, we attempted to establish a perdiction "card" system using Taqman Low Density Aarray (TLDA; Applied biosystems). We examined the chemosensitivity of 38 cases with the card, and predicted accurately by the sensitivity of 80% or more. We can predict response within one week when we use this card, and technical burden will be reduced. At present, we began a clinical research employing our prediction system with the card. This research is expected to become the precursors of personalized medicine.
|
