机构：[1]Department of Basic Research, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, 55 Renmin Ave. Fourth Section, Chengdu, Sichuan 610041, China四川省人民医院四川省肿瘤医院[2]State Key Laboratory of Molecular Oncology, Department of Etiology and Carcinogenesis, Cancer Institute & Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China
Background: The clinical benefit of adjuvant chemotherapy for stage II colorectal cancer (CRC) is controversial. This study aimed to explore novel gene signature to predict outcome benefit of postoperative 5-Fu-based therapy in stage II CRC. Methods: Gene-expression profiles of stage II CRCs from two datasets with 5-Fu-based adjuvant chemotherapy (training dataset, n = 212; validation dataset, n = 85) were analyzed to identify the indicator. A systemic approach by integrating gene-expression and protein-protein interaction (PPI) network was implemented to develop the predictive signature. Kaplan-Meier curves and Cox proportional hazards model were used to determine the survival benefit of adjuvant chemotherapy. Experiments with shRNA knock-down were carried out to confirm the signature identified in this study. Results: In the training dataset, we identified 44 PPI sub-modules, by which we separate patients into two clusters (1 and 2) having different chemotherapeutic benefit. A predictor of 11 PPI sub-modules (11-PPI-Mod) was established to discriminate the two sub-groups, with an overall accuracy of 90.1%. This signature was independently validated in an external validation dataset. Kaplan-Meier curves showed an improved outcome for patients who received adjuvant chemotherapy in Cluster 1 sub-group, but even worse survival for those in Cluster 2 sub-group. Similar results were found in both the training and the validation dataset. Multivariate Cox regression revealed an interaction effect between 11-PPI-Mod signature and adjuvant therapy treatment in the training dataset (RFS, p = 0.007; OS, p = 0.006) and the validation dataset (RFS, p = 0.002). From the signature, we found that PTGES gene was up-regulated in CRC cells which were more resistant to 5-Fu. Knock-down of PTGES indicated a growth inhibition and up-regulation of apoptotic markers induced by 5-Fu in CRC cells. Conclusions: Only a small proportion of stage II CRC patients could benefit from adjuvant therapy. The 11-PPI-Mod as a potential predictor could be helpful to distinguish this sub-group with favorable outcome.
基金：
This work was supported by Sichuan Scientific and Technology Department
Basic Research Fund (grant number, 2015JY0011) to CM Chen; Sichuan Cancer
Hospital Research Fund (grant number, YB2013001) to CM Chen; The National
Natural Science Foundation (grant number, 81602731) to BR Cao; and the
national key research and development program of the Ministry of Science and Technology of China (grant number, 2016YFC0905301) to L Feng.
第一作者机构：[1]Department of Basic Research, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, 55 Renmin Ave. Fourth Section, Chengdu, Sichuan 610041, China
通讯作者：
推荐引用方式(GB/T 7714)：
Bangrong Cao,Liping Luo,Lin Feng,et al.A network-based predictive gene-expression signature for adjuvant chemotherapy benefit in stage II colorectal cancer[J].BMC CANCER.2017,17:doi:10.1186/s12885-017-3821-4.
APA：
Bangrong Cao,Liping Luo,Lin Feng,Shiqi Ma,Tingqing Chen...&Changmin Chen.(2017).A network-based predictive gene-expression signature for adjuvant chemotherapy benefit in stage II colorectal cancer.BMC CANCER,17,
MLA：
Bangrong Cao,et al."A network-based predictive gene-expression signature for adjuvant chemotherapy benefit in stage II colorectal cancer".BMC CANCER 17.(2017)
医学