| Title |
Integrated network model provides new insights into castration-resistant prostate cancer
|
|---|---|
| Published in |
Scientific Reports, November 2015
|
| DOI | 10.1038/srep17280 |
| Pubmed ID | |
| Authors |
Yanling Hu, Yinmin Gu, Huimin Wang, Yuanjie Huang, Yi Ming Zou |
| Abstract |
Castration-resistant prostate cancer (CRPC) is the main challenge for prostate cancer treatment. Recent studies have indicated that extending the treatments to simultaneously targeting different pathways could provide better approaches. To better understand the regulatory functions of different pathways, a system-wide study of CRPC regulation is necessary. For this purpose, we constructed a comprehensive CRPC regulatory network by integrating multiple pathways such as the MEK/ERK and the PI3K/AKT pathways. We studied the feedback loops of this network and found that AKT was involved in all detected negative feedback loops. We translated the network into a predictive Boolean model and analyzed the stable states and the control effects of genes using novel methods. We found that the stable states naturally divide into two obvious groups characterizing PC3 and DU145 cells respectively. Stable state analysis further revealed that several critical genes, such as PTEN, AKT, RAF, and CDKN2A, had distinct expression behaviors in different clusters. Our model predicted the control effects of many genes. We used several public datasets as well as FHL2 overexpression to verify our finding. The results of this study can help in identifying potential therapeutic targets, especially simultaneous targets of multiple pathways, for CRPC. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 25% |
| South Africa | 1 | 25% |
| Unknown | 2 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 50% |
| Science communicators (journalists, bloggers, editors) | 1 | 25% |
| Scientists | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 4% |
| Unknown | 24 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 9 | 36% |
| Other | 3 | 12% |
| Student > Doctoral Student | 2 | 8% |
| Researcher | 2 | 8% |
| Librarian | 1 | 4% |
| Other | 4 | 16% |
| Unknown | 4 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 6 | 24% |
| Medicine and Dentistry | 4 | 16% |
| Biochemistry, Genetics and Molecular Biology | 3 | 12% |
| Mathematics | 1 | 4% |
| Unspecified | 1 | 4% |
| Other | 2 | 8% |
| Unknown | 8 | 32% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 23 September 2016.
All research outputs
#14,179,146
of 22,834,308 outputs
Outputs from Scientific Reports
#67,010
of 123,302 outputs
Outputs of similar age
#200,782
of 386,751 outputs
Outputs of similar age from Scientific Reports
#1,413
of 2,630 outputs
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