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A network-based predictive gene-expression signature for adjuvant chemotherapy benefit in stage II colorectal cancer
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 tw...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5729289/ https://www.ncbi.nlm.nih.gov/pubmed/29237416 http://dx.doi.org/10.1186/s12885-017-3821-4 |
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author | Cao, Bangrong Luo, Liping Feng, Lin Ma, Shiqi Chen, Tingqing Ren, Yuan Zha, Xiao Cheng, Shujun Zhang, Kaitai Chen, Changmin |
author_facet | Cao, Bangrong Luo, Liping Feng, Lin Ma, Shiqi Chen, Tingqing Ren, Yuan Zha, Xiao Cheng, Shujun Zhang, Kaitai Chen, Changmin |
author_sort | Cao, Bangrong |
collection | PubMed |
description | 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12885-017-3821-4) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5729289 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-57292892017-12-18 A network-based predictive gene-expression signature for adjuvant chemotherapy benefit in stage II colorectal cancer Cao, Bangrong Luo, Liping Feng, Lin Ma, Shiqi Chen, Tingqing Ren, Yuan Zha, Xiao Cheng, Shujun Zhang, Kaitai Chen, Changmin BMC Cancer Research Article 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12885-017-3821-4) contains supplementary material, which is available to authorized users. BioMed Central 2017-12-13 /pmc/articles/PMC5729289/ /pubmed/29237416 http://dx.doi.org/10.1186/s12885-017-3821-4 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Cao, Bangrong Luo, Liping Feng, Lin Ma, Shiqi Chen, Tingqing Ren, Yuan Zha, Xiao Cheng, Shujun Zhang, Kaitai Chen, Changmin A network-based predictive gene-expression signature for adjuvant chemotherapy benefit in stage II colorectal cancer |
title | A network-based predictive gene-expression signature for adjuvant chemotherapy benefit in stage II colorectal cancer |
title_full | A network-based predictive gene-expression signature for adjuvant chemotherapy benefit in stage II colorectal cancer |
title_fullStr | A network-based predictive gene-expression signature for adjuvant chemotherapy benefit in stage II colorectal cancer |
title_full_unstemmed | A network-based predictive gene-expression signature for adjuvant chemotherapy benefit in stage II colorectal cancer |
title_short | A network-based predictive gene-expression signature for adjuvant chemotherapy benefit in stage II colorectal cancer |
title_sort | network-based predictive gene-expression signature for adjuvant chemotherapy benefit in stage ii colorectal cancer |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5729289/ https://www.ncbi.nlm.nih.gov/pubmed/29237416 http://dx.doi.org/10.1186/s12885-017-3821-4 |
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