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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A network-based predictive gene-expression signature for adjuvant chemotherapy benefit in stage II colorectal cancer
|
|---|---|
| Published in |
BMC Cancer, December 2017
|
| DOI | 10.1186/s12885-017-3821-4 |
| Pubmed ID | |
| Authors |
Bangrong Cao, Liping Luo, Lin Feng, Shiqi Ma, Tingqing Chen, Yuan Ren, Xiao Zha, Shujun Cheng, Kaitai Zhang, Changmin Chen |
| Abstract |
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. 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. 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. 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. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Italy | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 32 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 16% |
| Student > Bachelor | 5 | 16% |
| Student > Ph. D. Student | 4 | 13% |
| Student > Master | 4 | 13% |
| Professor > Associate Professor | 2 | 6% |
| Other | 4 | 13% |
| Unknown | 8 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 5 | 16% |
| Agricultural and Biological Sciences | 4 | 13% |
| Computer Science | 4 | 13% |
| Engineering | 3 | 9% |
| Nursing and Health Professions | 2 | 6% |
| Other | 4 | 13% |
| Unknown | 10 | 31% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 November 2020.
All research outputs
#20,459,801
of 23,016,919 outputs
Outputs from BMC Cancer
#6,531
of 8,359 outputs
Outputs of similar age
#374,623
of 439,212 outputs
Outputs of similar age from BMC Cancer
#144
of 180 outputs
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So far Altmetric has tracked 8,359 research outputs from this source. They receive a mean Attention Score of 4.3. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 180 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.