Microarray Gene Expression Profiling for Predicting Complete Response to Preoperative Chemoradiotherapy in Patients with Advanced Rectal Cancer |
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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 |
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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 |
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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. |
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Keywords: | Microarray Chemoradiotherapy Prediction Rectal cancer |
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