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Gene Expression Profile Prospectively Predicts Peritoneal Relapse After Curative Surgery of Gastric Cancer
Authors:Atsushi Takeno MD  Ichiro Takemasa MD  Shigeto Seno PhD  Makoto Yamasaki MD  Masaaki Motoori MD  Hiroshi Miyata MD  Kiyokazu Nakajima MD  Shuji Takiguchi MD  Yoshiyuki Fujiwara MD  Toshiro Nishida MD  Toshitsugu Okayama PhD  Kenichi Matsubara PhD  Yoichi Takenaka PhD  Hideo Matsuda PhD  Morito Monden MD  Masaki Mori MD  Yuichiro Doki MD
Institution:1. Department of Gastroenterological Surgery, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan
2. Department of Bioinformatic Engineering, Graduate School of Information Science and Technology, Osaka University, Toyonaka, Osaka, Japan
3. Department of Surgery, Osaka Medical Center for Cancer and Cardiovascular Diseases, Higashinari, Osaka, Japan
4. BioInformation Technology & Science (BITS) Co., Ltd, Suntou, Shizuoka, Japan
5. DNA Chip Research Inc., Yokohama, Kanagawa, Japan
Abstract:

Background

Peritoneal relapse is the most common pattern of tumor progression in advanced gastric cancer. Clinicopathological findings are sometimes inadequate for predicting peritoneal relapse. The aim of this study was to identify patients at high risk of peritoneal relapse in a prospective study based on molecular prediction.

Methods

RNA samples from 141 primary gastric cancer tissues after curative surgery were profiled using oligonucleotide microarrays covering 30,000 human probes. Firstly, we constructed a molecular prediction system and validated its robustness and prognostic validity by 500 times multiple validation by repeated random sampling in a retrospective set of 56 (38 relapse-free and 18 peritoneal-relapse) patients. Secondly, we applied this prediction to 85 patients of the prospective set to assess predictive accuracy and prognostic validity.

Results

In the retrospective phase, repeated random validation yielded ~68% predictive accuracy and a 22-gene expression profile associated with peritoneal relapse was identified. The prediction system identified patients with poor prognosis. In the prospective phase, the molecular prediction yielded 76.9% overall accuracy. Kaplan–Meier analysis of peritoneal-relapse-free survival showed a significant difference between the “good signature group” and “poor signature group” (log-rank p = 0.0017). Multivariate analysis by Cox regression hazards model identified the molecular prediction as the only independent prognostic factor for peritoneal relapse.

Conclusions

Gene expression profile inherent to primary gastric cancer tissues can be useful in prospective prediction of peritoneal relapse after curative surgery, potentially allowing individualized postoperative management to improve the prognosis of patients with advanced gastric cancer.
Keywords:
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