| Title |
Integrated Bioinformatics Analysis of Potential Biomarkers for Prostate Cancer
|
|---|---|
| Published in |
Pathology & Oncology Research, December 2017
|
| DOI | 10.1007/s12253-017-0346-8 |
| Pubmed ID | |
| Authors |
Jiufeng Tan, Xuefei Jin, Kaichen Wang |
| Abstract |
The aim was to expound the pathogenesis of prostate cancer and to identify the potentially biomarkers for prostate cancer (PC). DNA methylation microarray data GSE38240 containing 8 prostate cancer metastases and 4 normal prostate samples as well as gene expression profile data GSE26910 containing 6 prostate primary tumors and 6 normal samples were used. Differentially expressed genes (DEGs) and differently methylated sites of PC were screened and the regulatory network was constructed with DEGs-related transcription factors (TFs). The obtained hub genes were subjected to protein-protein interaction network analysis. Enrichment analysis of down-regulated DEGs were performed. Total 351 DEGs including 190 down-regulated and 161 up-regulated genes and 3234 differently methylated sites were identified. In total 69 DEGs-related TFs were found. Regulatory network contained 1301 nodes and 2527 connection pairs and that FOXA1 (forkhead box A1), BZRAP1-AS1 (benzodiazapine receptor associated protein 1 antisense RNA 1) and KRT8 (keratin 8) were the top three nodes of it. The enriched GO terms were mainly biological activity of the blood and cells-related. Total 29 DEGs (such as AGTR1, angiotensin II receptor, type 1) and 57 none-DEGs involved in the PPI network. Biological functions in blood circulation and the involved AGTR1 may play important roles in PC by gene-methylation. Besides, BZRAP1-AS1 may be novel biomarker related with PC. |
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 % |
|---|---|---|
| United States | 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 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 15 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 3 | 20% |
| Researcher | 3 | 20% |
| Student > Bachelor | 2 | 13% |
| Lecturer | 1 | 7% |
| Unknown | 6 | 40% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 3 | 20% |
| Chemical Engineering | 1 | 7% |
| Nursing and Health Professions | 1 | 7% |
| Agricultural and Biological Sciences | 1 | 7% |
| Computer Science | 1 | 7% |
| Other | 1 | 7% |
| Unknown | 7 | 47% |
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 21 December 2017.
All research outputs
#20,456,235
of 23,012,811 outputs
Outputs from Pathology & Oncology Research
#465
of 720 outputs
Outputs of similar age
#376,067
of 440,404 outputs
Outputs of similar age from Pathology & Oncology Research
#10
of 12 outputs
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