| Title |
Rare frequency of gene variation and survival analysis in thymic epithelial tumors
|
|---|---|
| Published in |
OncoTargets and therapy, October 2016
|
| DOI | 10.2147/ott.s108749 |
| Pubmed ID | |
| Authors |
Zhengbo Song, Xinmin Yu, Yiping Zhang |
| Abstract |
Thymic epithelial tumor (TET) is a rare mediastinal neoplasm and little is known about its genetic variability and prognostic factors. This study investigated the genetic variability and prognostic factors of TET. We sequenced 22 cancer-related hotspot genes in TET tissues and matched normal tissues using Ampliseq Ion Torrent next-generation technology. Overall survival was evaluated using Kaplan-Meier methods and compared with log-rank tests. A histological analysis of 52 patients with a median age of 52 years showed 15 patients (28.8%) with thymic carcinoma, five with type A thymoma (9.6%), eight with type AB (15.4%), six with type B1 (11.5%), nine with type B2 (17.3%), and nine with type B3 thymoma (17.3%). Three gene mutations were identified, including two with PIK3CA mutation and one with EGFR mutation. The three patients with mutant genes included two cases of thymoma (one with EGFR and the other with PIK3CA mutation) in addition to a case of thymic carcinoma (PIK3CA mutation). The 5-year survival rates were 77.7% in all patients. The 5-year survival rates were 93.3%, 90.0%, 76.9%, and 22.9% corresponding to Masaoka stages I, II, III, and IV (P<0.001). The 5-year survival rates were 100%, 100%, 83.3%, 88.9%, 65.6%, and 60.9% in the histological subtypes of A, AB, B1, B2, and B3 thymomas, and thymic carcinoma, respectively (P=0.012). Hotspot gene mutations are rare in TET. PIK3CA and EGFR mutations represent candidate driver genes and treatment targets in TET. Masaoka stage and histological subtypes predict the survival of TET. |
X Demographics
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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 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 11 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 2 | 18% |
| Student > Bachelor | 1 | 9% |
| Student > Master | 1 | 9% |
| Researcher | 1 | 9% |
| Professor > Associate Professor | 1 | 9% |
| Other | 1 | 9% |
| Unknown | 4 | 36% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 3 | 27% |
| Medicine and Dentistry | 3 | 27% |
| Immunology and Microbiology | 1 | 9% |
| Earth and Planetary Sciences | 1 | 9% |
| Unknown | 3 | 27% |
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 17 October 2016.
All research outputs
#17,286,379
of 25,374,647 outputs
Outputs from OncoTargets and therapy
#1,146
of 3,016 outputs
Outputs of similar age
#216,525
of 332,576 outputs
Outputs of similar age from OncoTargets and therapy
#39
of 74 outputs
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