Prediction of Response to Preoperative Chemoradiotherapy in Rectal Cancer by Using Reverse Transcriptase Polymerase Chain Reaction Analysis of Four Genes

放化疗 结直肠癌 医学 微阵列 实时聚合酶链反应 基因表达 逆转录酶 基因 逆转录聚合酶链式反应 微阵列分析技术 肿瘤科 聚合酶链反应 内科学 癌症 生物 遗传学
作者
Toshiaki Watanabe,Takashi Kobunai,Takashi Akiyoshi,Keiji Matsuda,Soichiro Ishihara,Keijiro Nozawa
出处
期刊:Diseases of The Colon & Rectum [Lippincott Williams & Wilkins]
卷期号:57 (1): 23-31 被引量:48
标识
DOI:10.1097/01.dcr.0000437688.33795.9d
摘要

BACKGROUND: Patients with rectal cancer exhibit a wide spectrum of responses to chemoradiotherapy. Several gene expression signatures have been reported to predict the response to chemoradiotherapy in rectal cancer, but the lack of practical assays has restricted the clinical use of this technique. OBJECTIVE: We aimed to identify a set of discriminating genes that can be used for the clinical prediction of response to chemoradiotherapy in rectal cancer. DESIGN AND SETTINGS: This study is a retrospective analysis of tumor samples in a single institute. PATIENTS: Sixty-two patients who underwent preoperative chemoradiotherapy were studied. MAIN OUTCOME MEASURES: Gene expression was initially studied in 46 training samples by microarray analysis, and the association between gene expression and response to chemoradiotherapy was evaluated. Quantitative reverse transcriptase polymerase chain reaction was performed to validate the microarray expression levels of the discriminating genes. We developed a gene expression model for the prediction of response to chemoradiotherapy based on the reverse transcriptase polymerase chain reaction findings and validated it by using 16 independent test samples. RESULTS: We identified 24 discriminating probes with expression levels that differed significantly between responders and nonresponders. Among 18 genes identified by Gene Symbol, real-time reverse transcriptase polymerase chain reaction showed significant differences in the expression of 16 genes between responders and nonresponders. We constructed a predictive model by using different sets of these 16 genes, and the highest accuracy rate (89.1%) was obtained by using LRRIQ3, FRMD3, SAMD5, and TMC7. The predictive accuracy rate of this 4-gene signature in the independent set of 16 patients was 81.3%. LIMITATIONS: Validation in a different and large cohort of patients is necessary. CONCLUSIONS: The 4-gene signature identified in this study is closely associated with response to chemoradiotherapy in rectal cancer.
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