Wenjun Chang1, Xianhua Gao2, Yifang Han1, Yan Du1, Qizhi Liu2, Lei Wang3, Xiaojie Tan1, Qi Zhang4, Yan Liu5, Yan Zhu6, Yongwei Yu6, Xinjuan Fan3, Hongwei Zhang1, Weiping Zhou7, Jianping Wang3, Chuangang Fu2, Guangwen Cao1. 1. Department of Epidemiology, Second Military Medical University, Shanghai, China. 2. Department of Colorectal Surgery, Changhai Hospital, Second Military Medical University, Shanghai, China. 3. Department of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China. 4. Department of Epidemiology, Second Military Medical University, Shanghai, China Department of Colorectal Surgery, Changhai Hospital, Second Military Medical University, Shanghai, China Department of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China Department of Pathology, Changhai Hospital, Second Military Medical University, Shanghai, China Department of Surgery, Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, Shanghai, China. 5. Department of Epidemiology, Second Military Medical University, Shanghai, China Department of Epidemiology, Second Military Medical University, Shanghai, China. 6. Department of Pathology, Changhai Hospital, Second Military Medical University, Shanghai, China. 7. Department of Surgery, Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, Shanghai, China.
Abstract
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. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
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. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.