2007 Fiscal Year Final Research Report Summary
Prediction of sensitivity of rectal cancer in response to preoperative radiotherapy and chemoradiotherapy by DNA microarray analysis-Anew strategy for individualized tailored therapy ofrectal cancer
| Project/Area Number |
18390361
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Digestive surgery
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| Research Institution | Teikyo University |
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Principal Investigator |
WATANABE Toshiaki Teikyo University, School of Medicine, Professor (80210920)
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| Co-Investigator(Kenkyū-buntansha) |
MATSUDA Keiji Teikyo University, School of Medicine, Lecturer (90302728)
NOZAWA Kejiro Teikyo University, School ofMedicine, Assistant Professor (90317686)
IINUMA Hisae Teikyo University, School of Medicine, Lecturer (30147102)
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| Project Period (FY) |
2006 – 2007
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| Keywords | Rectal Cancer / DNA Microarrav / Prediction of response / Radiotherapy / Chemo radiotheranv |
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| Research Abstract |
Local recurrence is one of the major forms of recurrence after surgery for rectal cancer. Preoperative radiotherapy has been widely used to improve local control of disease and to improve survival in the treatment of rectal cancer. However, in the clinical settings, the response to radiotherapy differs among individual tumors. Therefore, to select patients who respond to radiotherapy is very important to perform radiotherapy effectively. We aimed to identify a set of discriminating genes that can be used for characterization and prediction of response to radiotherapy in rectal cancer. Fifty-two rectal cancer patients who underwent preoperative radiotherapy were studied. Biopsy specimens were obtained from rectal cancer before preoperative radiotherapy. Response to radiotherapy was determined by histopathologic examination of surgically resected specimens and classified as responders or nonresponders. By determining gene expression profiles using human U95Av2 Gene Chip, we identified 33
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novel discriminating genes of which the expression differed significantly between responders and nonresponders. Using this gene set, we were able to establish a new model to predict response to radiotherapy in rectal cancer with an accuracy of 82.4%. Using the same strategy, we further performed a study to build a predictive model for chemoradiotherapy for rectal cancer. We examined a total of 15 patients who underwent preoperative chemoradiotherapy for rectal cancer. The patients underwent surgery after chemoradiotherapy using oral 5-FU(Fluorouracil) drugs. Response to chemoradiotherapy was determined by histological examination of surgically resected specimens as described above. By gene expression analysis, we could build a model which could predict the response to chemoradiotherapy with an accuracy of 100%. Although the number of examined patients is not large, these results suggested the possibility that gene expression profiling may be useful in predicting response to radiotherapy and chemoradiotherapy to establish an individualized tailored therapy for rectal cancer. Less
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