| Title |
Evaluation of p53 gene expression and prognosis characteristics in uveal melanoma cases
|
|---|---|
| Published in |
OncoTargets and therapy, July 2017
|
| DOI | 10.2147/ott.s136785 |
| Pubmed ID | |
| Authors |
Haojie Liu, Ming Zhou |
| Abstract |
The objective of this study was to evaluate the correlation between the expression of p53 gene and the prognosis after local excision in uveal melanoma. Real-time polymerase chain reaction (RT-PCR) test and Western blot were used to detect the expression of p53 in C918, MUM-2B, and D78 cell lines at the levels of messenger RNA (mRNA) and protein. Immunohistochemistry staining was done in the tissues of 68 patients, which were diagnosed with uveal melanoma. Furthermore, the effects of p53 protein on the invasion abilities of both the cell lines were studied by transinfection of p53 small interfering RNA. The clinical and prognostic data regarding the effect of p53 protein on the patient's prognosis were calculated and further analyzed by Kaplan-Meier univariate analysis method. The results of RT-PCR and Western blot revealed that p53 mRNAs were highly expressed in C918 and MUM-2B cells. The high expression rate of p53 among the 88 uveal melanoma tissues was 77.27%. Transinfection of p53 serine could inhibit the expression of p53 in uveal melanoma and the invasion ability of the cells. This study found that the high expression of p53 and the prognosis of uveal melanoma patients were statistically correlated. The expression of p53 protein in uveal melanoma was unusual and was associated with the invasion ability of uveal melanoma. This indicates that the highest expression of p53 protein indicates worse prognosis of uveal melanoma patients. |
Mendeley readers
The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 31 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 8 | 26% |
| Researcher | 5 | 16% |
| Student > Doctoral Student | 2 | 6% |
| Student > Postgraduate | 2 | 6% |
| Student > Bachelor | 2 | 6% |
| Other | 5 | 16% |
| Unknown | 7 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 10 | 32% |
| Medicine and Dentistry | 6 | 19% |
| Veterinary Science and Veterinary Medicine | 2 | 6% |
| Computer Science | 1 | 3% |
| Unspecified | 1 | 3% |
| Other | 2 | 6% |
| Unknown | 9 | 29% |
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 13 July 2017.
All research outputs
#22,764,772
of 25,382,440 outputs
Outputs from OncoTargets and therapy
#2,078
of 3,016 outputs
Outputs of similar age
#286,158
of 326,871 outputs
Outputs of similar age from OncoTargets and therapy
#60
of 72 outputs
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