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Microarray Gene Expression Profiling for Predicting Complete Response to Preoperative Chemoradiotherapy in Patients with Advanced Rectal Cancer
Authors:Il-Jin Kim PhD  Seok-Byung Lim MD  Hio Chung Kang PhD  Hee Jin Chang MD  Sun-A Ahn BS  Hye-Won Park MS  Sang-Geun Jang BS  Jae-Hyun Park MS  Dae Yong Kim MD  Kyung Hae Jung MD  Hyo Seong Choi MD  Seung-Yong Jeong MD  Dae Kyung Sohn MD  Duck-Woo Kim MD  Jae-Gahb Park MD  PhD
Institution:(1) Cancer Research Institute and Cancer Research Center, Seoul National University, 28 Yongon-dong, Chongno-gu, Seoul, 110-744 Seoul, Korea;(2) Research Institute and Hospital, National Cancer Center, Gyeonggi-do, Korea
Abstract:Purpose Preoperative chemoradiotherapy is widely used to improve local control and sphincter preservation in patients with locally advanced rectal cancer. In the present study, we investigated whether microarray gene expression analysis could predict complete response to preoperative chemoradiotherapy in rectal cancer. Methods Tumor tissues were obtained from 46 patients with rectal cancer (31 for training and 15 for validation testing). All patients underwent preoperative chemoradiotherapy involving 50.4 gray radiotherapy, followed by surgical excision 6 weeks later. Response to chemoradiotherapy was evaluated according to Dworak’s tumor regression grade. Tumor regression Grades 1, 2, and 3 were considered partial responses, and tumor regression Grade 4 was considered a complete response. By using the 31 training samples, genes differentially expressed between partial response and complete response were identified, and clustering analysis was performed. Prediction analysis of response to chemoradiotherapy was performed on the 31 training samples by using a selected set of 95 “predictor” genes. Those findings were validated by independent analysis of the 15 test samples. Results The 31 training samples comprised 20 partial response and 11 complete response cases. A primary set of 261 genes was identified as differentiating between partial response and complete response. By supervised clustering using these 261 genes, 30 of 31 training samples were clustered correctly according to tumor response. A gene set comprising the top-ranked 95 genes displaying differential expression between partial response and complete response was applied to predict response to chemoradiotherapy. Complete response and partial response were accurately predicted in 84 percent (26/31) of training samples and 87 percent (13/15) of validation samples. Conclusions Microarray gene expression analysis was successfully used to predict complete responses to preoperative chemoradiotherapy in patients with advanced rectal cancer. Supported by a research grant from the National Cancer Center, Korea, and the BK21 project for Medicine, Dentistry, and Pharmacy. Presented in part and awarded the AACR-ITO EN, Ltd, Scholar-In-Training Award at the meeting of the American Association for Cancer Research, Washington, DC, April 1 to 5, 2006. I-J Kim and S-B Lim contributed equally to this article. Reprints are not available.
Keywords:Microarray  Chemoradiotherapy  Prediction  Rectal cancer
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