You Guo1, Weizhong Jiang2, Lu Ao3, Kai Song4, Huxing Chen3, Qingzhou Guan3, Qiao Gao2, Jun Cheng3, Huaping Liu3, Xianlong Wang3, Guoxian Guan5, Zheng Guo6. 1. Department of Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, China; Department of Preventive Medicine, Gannan Medical University, China. 2. Department of Colorectal Surgery, Fujian Medical University Union Hospital, China. 3. Department of Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, China. 4. College of Bioinformatics Science and Technology, Harbin Medical University, China. 5. Department of Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, China. Electronic address: gy_8637@fjmu.edu.cn. 6. Department of Bioinformatics, Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, China; College of Bioinformatics Science and Technology, Harbin Medical University, China. Electronic address: guoz@ems.hrbmu.edu.cn.
Abstract
BACKGROUND AND PURPOSE: The standard therapy for locally advanced rectal cancers (LARCs) is neoadjuvant chemoradiation (nCRT) followed by surgical resection. Pathological response to nCRT varies among patients, and it remains a challenge to predict pathological response to nCRT in LARCs. MATERIAL AND METHODS: Using 42 samples as the training cohort, we searched a signature by screening the gene pairs whose within-sample relative expression orderings are significantly correlated with the pathological response. The signature was validated in both a public cohort of 46 samples and a cohort of 33 samples measured at our laboratory. RESULTS: A signature consisting of 27 gene pairs was identified in the training cohort with an accuracy of 92.86% and an area under the receiver operating characteristic curve (AUC) of 0.95. The accuracy was 89.13% for the public test cohort and 90.91% for the private test cohort, with AUC being 0.95 and 0.91, respectively. Furthermore, the signature was used to predict disease-free survival benefits from 5Fu-based chemotherapy in 285 locally advanced colorectal cancers. CONCLUSIONS: The signature consisting of 27 gene pairs can robustly predict clinical response of LARCs to nCRT.
BACKGROUND AND PURPOSE: The standard therapy for locally advanced rectal cancers (LARCs) is neoadjuvant chemoradiation (nCRT) followed by surgical resection. Pathological response to nCRT varies among patients, and it remains a challenge to predict pathological response to nCRT in LARCs. MATERIAL AND METHODS: Using 42 samples as the training cohort, we searched a signature by screening the gene pairs whose within-sample relative expression orderings are significantly correlated with the pathological response. The signature was validated in both a public cohort of 46 samples and a cohort of 33 samples measured at our laboratory. RESULTS: A signature consisting of 27 gene pairs was identified in the training cohort with an accuracy of 92.86% and an area under the receiver operating characteristic curve (AUC) of 0.95. The accuracy was 89.13% for the public test cohort and 90.91% for the private test cohort, with AUC being 0.95 and 0.91, respectively. Furthermore, the signature was used to predict disease-free survival benefits from 5Fu-based chemotherapy in 285 locally advanced colorectal cancers. CONCLUSIONS: The signature consisting of 27 gene pairs can robustly predict clinical response of LARCs to nCRT.