RT Journal Article
SR Electronic
T1 Gene expression profiling-derived immunohistochemistry signature with high prognostic value in colorectal carcinoma
JF Gut
JO Gut
FD BMJ Publishing Group Ltd and British Society of Gastroenterology
SP 1457
OP 1467
DO 10.1136/gutjnl-2013-305475
VO 63
IS 9
A1 Wenjun Chang
A1 Xianhua Gao
A1 Yifang Han
A1 Yan Du
A1 Qizhi Liu
A1 Lei Wang
A1 Xiaojie Tan
A1 Qi Zhang
A1 Yan Liu
A1 Yan Zhu
A1 Yongwei Yu
A1 Xinjuan Fan
A1 Hongwei Zhang
A1 Weiping Zhou
A1 Jianping Wang
A1 Chuangang Fu
A1 Guangwen Cao
YR 2014
UL http://gut.bmj.com/content/63/9/1457.abstract
AB Objective Gene expression profiling provides an opportunity to develop robust prognostic markers of colorectal carcinoma (CRC). However, the markers have not been applied for clinical decision making. We aimed to develop an immunohistochemistry signature using microarray data for predicting CRC prognosis. Design We evaluated 25 CRC gene signatures in independent microarray datasets with prognosis information and constructed a subnetwork using signatures with high concordance and repeatable prognostic values. Tumours were examined immunohistochemically for the expression of network-centric and the top overlapping molecules. Prognostic values were assessed in 682 patients from Shanghai, China (training cohort) and validated in 343 patients from Guangzhou, China (validation cohort). Median follow-up duration was 58 months. All p values are two-sided. Results Five signatures were selected to construct a subnetwork. The expression of GRB2, PTPN11, ITGB1 and POSTN in cancer cells, each significantly associated with disease-free survival, were selected to construct an immunohistochemistry signature. Patients were dichotomised into high-risk and low-risk subgroups with an optimal risk score (1.55). Compared with low-risk patients, high-risk patients had shorter disease-specific survival (DSS) in the training (HR=6.62; 95% CI 3.70 to 11.85) and validation cohorts (HR=3.53; 95% CI 2.13 to 5.84) in multivariate Cox analyses. The signature better predicted DSS than did tumour-node-metastasis staging in both cohorts. In those who received postoperative chemotherapy, high-risk score predicted shorter DSS in the training (HR=6.35; 95% CI 3.55 to 11.36) and validation cohorts (HR=5.56; 95% CI 2.25 to 13.71). Conclusions Our immunohistochemistry signature may be clinically practical for personalised prediction of CRC prognosis.