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- Title
A network-based predictive gene-expression signature for adjuvant chemotherapy benefit in stage II colorectal cancer.
- Authors
Bangrong Cao; Liping Luo; Lin Feng; Shiqi Ma; Tingqing Chen; Yuan Ren; Xiao Zha; Shujun Cheng; Kaitai Zhang; Changmin Chen; Cao, Bangrong; Luo, Liping; Feng, Lin; Ma, Shiqi; Chen, Tingqing; Ren, Yuan; Zha, Xiao; Cheng, Shujun; Zhang, Kaitai; Chen, Changmin
- Abstract
<bold>Background: </bold>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.<bold>Methods: </bold>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.<bold>Results: </bold>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.<bold>Conclusions: </bold>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.
- Subjects
COLON cancer treatment; GENE expression; CANCER chemotherapy; ADJUVANT treatment of cancer; PROTEIN-protein interactions; POSTOPERATIVE care; CELL lines; CLUSTER analysis (Statistics); COLON tumors; COMBINED modality therapy; DATABASES; METABOLISM; RECTUM tumors; RESEARCH funding; RETROSPECTIVE studies; GENE expression profiling
- Publication
BMC Cancer, 2017, Vol 17, p1
- ISSN
1471-2407
- Publication type
journal article
- DOI
10.1186/s12885-017-3821-4