Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Cao, Bangrong, Luo, Liping, Feng, Lin, Ma, Shiqi, Chen, Tingqing, Ren, Yuan, Zha, Xiao, Cheng, Shujun, Zhang, Kaitai, Chen, Changmin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
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
_version_ 1783286162626969600
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
work_keys_str_mv AT caobangrong anetworkbasedpredictivegeneexpressionsignatureforadjuvantchemotherapybenefitinstageiicolorectalcancer
AT luoliping anetworkbasedpredictivegeneexpressionsignatureforadjuvantchemotherapybenefitinstageiicolorectalcancer
AT fenglin anetworkbasedpredictivegeneexpressionsignatureforadjuvantchemotherapybenefitinstageiicolorectalcancer
AT mashiqi anetworkbasedpredictivegeneexpressionsignatureforadjuvantchemotherapybenefitinstageiicolorectalcancer
AT chentingqing anetworkbasedpredictivegeneexpressionsignatureforadjuvantchemotherapybenefitinstageiicolorectalcancer
AT renyuan anetworkbasedpredictivegeneexpressionsignatureforadjuvantchemotherapybenefitinstageiicolorectalcancer
AT zhaxiao anetworkbasedpredictivegeneexpressionsignatureforadjuvantchemotherapybenefitinstageiicolorectalcancer
AT chengshujun anetworkbasedpredictivegeneexpressionsignatureforadjuvantchemotherapybenefitinstageiicolorectalcancer
AT zhangkaitai anetworkbasedpredictivegeneexpressionsignatureforadjuvantchemotherapybenefitinstageiicolorectalcancer
AT chenchangmin anetworkbasedpredictivegeneexpressionsignatureforadjuvantchemotherapybenefitinstageiicolorectalcancer
AT caobangrong networkbasedpredictivegeneexpressionsignatureforadjuvantchemotherapybenefitinstageiicolorectalcancer
AT luoliping networkbasedpredictivegeneexpressionsignatureforadjuvantchemotherapybenefitinstageiicolorectalcancer
AT fenglin networkbasedpredictivegeneexpressionsignatureforadjuvantchemotherapybenefitinstageiicolorectalcancer
AT mashiqi networkbasedpredictivegeneexpressionsignatureforadjuvantchemotherapybenefitinstageiicolorectalcancer
AT chentingqing networkbasedpredictivegeneexpressionsignatureforadjuvantchemotherapybenefitinstageiicolorectalcancer
AT renyuan networkbasedpredictivegeneexpressionsignatureforadjuvantchemotherapybenefitinstageiicolorectalcancer
AT zhaxiao networkbasedpredictivegeneexpressionsignatureforadjuvantchemotherapybenefitinstageiicolorectalcancer
AT chengshujun networkbasedpredictivegeneexpressionsignatureforadjuvantchemotherapybenefitinstageiicolorectalcancer
AT zhangkaitai networkbasedpredictivegeneexpressionsignatureforadjuvantchemotherapybenefitinstageiicolorectalcancer
AT chenchangmin networkbasedpredictivegeneexpressionsignatureforadjuvantchemotherapybenefitinstageiicolorectalcancer