| Title |
Highly and moderately aggressive mouse ovarian cancer cell lines exhibit differential gene expression
|
|---|---|
| Published in |
Tumor Biology, March 2016
|
| DOI | 10.1007/s13277-015-4518-4 |
| Pubmed ID | |
| Authors |
Fengkun Du, Yan Li, Wensheng Zhang, Shubha P. Kale, Harris McFerrin, Ian Davenport, Guangdi Wang, Elena Skripnikova, Xiao-Lin Li, Nathan J. Bowen, Leticia B McDaniels, Yuan-Xiang Meng, Paula Polk, Yong-Yu Liu, Qian-Jin Zhang |
| Abstract |
Patients with advanced epithelial ovarian cancer often experience disease recurrence after standard therapies, a critical factor in determining their five-year survival rate. Recent reports indicated that long-term or short-term survival is associated with varied gene expression of cancer cells. Thus, identification of novel prognostic biomarkers should be considered. Since the mouse genome is similar to the human genome, we explored potential prognostic biomarkers using two groups of mouse ovarian cancer cell lines (group 1: IG-10, IG-10pw, and IG-10pw/agar; group 2: IG-10 clones 2, 3, and 11) which display highly and moderately aggressive phenotypes in vivo. Mice injected with these cell lines have different survival time and rates, capacities of tumor, and ascites formations, reflecting different prognostic potentials. Using an Affymetrix Mouse Genome 430 2.0 Array, a total of 181 genes were differentially expressed (P < 0.01) by at least twofold between two groups of the cell lines. Of the 181 genes, 109 and 72 genes were overexpressed in highly and moderately aggressive cell lines, respectively. Analysis of the 109 and 72 genes using Ingenuity Pathway Analysis (IPA) tool revealed two cancer-related gene networks. One was associated with the highly aggressive cell lines and affiliated with MYC gene, and another was associated with the moderately aggressive cell lines and affiliated with the androgen receptor (AR). Finally, the gene enrichment analysis indicated that the overexpressed 89 genes (out of 109 genes) in highly aggressive cell lines had a function annotation in the David database. The cancer-relevant significant gene ontology (GO) terms included Cell cycle, DNA metabolic process, and Programmed cell death. None of the genes from a set of the 72 genes overexpressed in the moderately aggressive cell lines had a function annotation in the David database. Our results suggested that the overexpressed MYC and 109 gene set represented highly aggressive ovarian cancer potential biomarkers while overexpressed AR and 72 gene set represented moderately aggressive ovarian cancer potential biomarkers. Based on our knowledge, the current study is first time to report the potential biomarkers relevant to different aggressive ovarian cancer. These potential biomarkers provide important information for investigating human ovarian cancer prognosis. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 7% |
| Unknown | 13 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Other | 3 | 21% |
| Professor > Associate Professor | 3 | 21% |
| Student > Ph. D. Student | 3 | 21% |
| Student > Master | 2 | 14% |
| Researcher | 2 | 14% |
| Other | 3 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 5 | 36% |
| Medicine and Dentistry | 3 | 21% |
| Biochemistry, Genetics and Molecular Biology | 2 | 14% |
| Nursing and Health Professions | 1 | 7% |
| Environmental Science | 1 | 7% |
| Other | 2 | 14% |
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 12 March 2016.
All research outputs
#14,753,130
of 23,613,071 outputs
Outputs from Tumor Biology
#941
of 2,614 outputs
Outputs of similar age
#159,359
of 299,985 outputs
Outputs of similar age from Tumor Biology
#24
of 117 outputs
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