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Attention Score in Context
| Title |
TP53 and PIK3CA gene mutations in adenocarcinoma, squamous cell carcinoma and high-grade intraepithelial neoplasia of the cervix
|
|---|---|
| Published in |
Journal of Translational Medicine, September 2014
|
| DOI | 10.1186/s12967-014-0255-5 |
| Pubmed ID | |
| Authors |
Maria Lina Tornesello, Clorinda Annunziata, Luigi Buonaguro, Simona Losito, Stefano Greggi, Franco M Buonaguro |
| Abstract |
BackgroundMutations in the tumor suppressor gene TP53 and proto-oncogene PIK3CA and alterations of p53 and PIK3CA AKT mTOR pathways are common events in several human cancers. We focused on the analysis of TP53 and PIK3CA gene variations in adenocarcinoma, squamous cell carcinoma as well as in intraepithelial neoplasia grade 3 of the cervix.MethodsDNA samples from 28 cervical adenocarcinoma, 55 squamous cell carcinoma and 31 intraepithelial neoplasia grade 3 (CIN3), previously characterized in terms of human papillomavirus (HPV) prevalence and genotype distribution, were analyzed for TP53 and PIK3CA mutations in the exons 4¿9 and exon 9, respectively.ResultsSingle nucleotide substitutions in TP53 and PIK3CA genes were detected in 36% and 11% of adenocarcinoma, in 16% and in 5% of squamous cell carcinoma, and in 13% and none of CIN 3, respectively. Nucleotide changes in TP53 were significantly more frequent in adenocarcinoma cases than in squamous cell carcinoma and CIN3 (P¿=¿0.035) and were independent from HPV infection status.ConclusionsMutations in the TP53 gene and to lesser extent in the PIK3CA gene seem more frequent in cervical adenocarcinoma than in squamous cell carcinoma and CIN3. Whether TP53 and PIK3CA gene mutations have an impact on prognosis and response to molecularly targeted therapies as well as in cytotoxic drugs in different cervical cancer histotypes needs to be analyzed in investigative clinical trials. |
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 % |
|---|---|---|
| Unknown | 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 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 1 | 2% |
| Unknown | 49 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 20% |
| Student > Master | 7 | 14% |
| Researcher | 6 | 12% |
| Student > Postgraduate | 5 | 10% |
| Other | 4 | 8% |
| Other | 8 | 16% |
| Unknown | 10 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 15 | 30% |
| Biochemistry, Genetics and Molecular Biology | 8 | 16% |
| Agricultural and Biological Sciences | 8 | 16% |
| Immunology and Microbiology | 2 | 4% |
| Engineering | 2 | 4% |
| Other | 2 | 4% |
| Unknown | 13 | 26% |
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 16 September 2014.
All research outputs
#20,236,620
of 22,763,032 outputs
Outputs from Journal of Translational Medicine
#3,305
of 3,980 outputs
Outputs of similar age
#188,345
of 225,899 outputs
Outputs of similar age from Journal of Translational Medicine
#62
of 82 outputs
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We're also able to compare this research output to 82 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.