| Title |
High-resolution genome-wide analysis identified recurrent genetic alterations in NK/T-cell lymphoma, nasal type, which are associated with disease progression
|
|---|---|
| Published in |
Medical Oncology, June 2014
|
| DOI | 10.1007/s12032-014-0071-z |
| Pubmed ID | |
| Authors |
Lin Sun, Min Li, Xin Huang, Jiaosheng Xu, Zifen Gao, Cuiling Liu |
| Abstract |
Extranodal NK/T-cell lymphoma, nasal type, is an aggressive mature NK-cell/T-cell lymphoma. Using array-based comparative genomic hybridization (array CGH) assays, we screened genomic alterations and potential candidate genes implicated in pathogenesis, progression, and prognosis. Our array CGH analysis detected an average of 83 chromosomal aberrations in 13 cases, ranging from 0 to 387. There were 177 recurrent chromosomal gains and 35 recurrent losses. Eleven gains and 14 losses were detected in more than 30 % of the cases, including gains of 3q26.1, 7q34, and 8q24.3 and losses of 15q24.2, 19q13.32, 5p13.2, and 14q21.1. The most common losses were observed in the 15q24.2 and 19q13.32 regions (9 cases, 69.2 %, respectively). Loss of 8p11.23 was associated with significant poor survival (P = 0.024). Five out of six patients with the loss of 8p11.23 died within 8 months after initial diagnosis with a median survival of 6 months. Several candidate genes were identified in the regions with frequent chromosomal aberrations, including ADAM3A (8p11.23) and GSTT1 (22q11.23). In summary, our studies detected recurrent genetic alterations in NK/T-cell lymphoma, some of which are associated with adverse prognosis. Some candidate genes in these regions may be involved in the pathogenesis and disease progression. |
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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 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 > Bachelor | 2 | 18% |
| Other | 1 | 9% |
| Student > Doctoral Student | 1 | 9% |
| Student > Ph. D. Student | 1 | 9% |
| Researcher | 1 | 9% |
| Other | 1 | 9% |
| Unknown | 4 | 36% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 4 | 36% |
| Biochemistry, Genetics and Molecular Biology | 1 | 9% |
| Computer Science | 1 | 9% |
| Nursing and Health Professions | 1 | 9% |
| Unknown | 4 | 36% |
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 02 July 2014.
All research outputs
#20,232,430
of 22,758,248 outputs
Outputs from Medical Oncology
#955
of 1,286 outputs
Outputs of similar age
#192,641
of 228,053 outputs
Outputs of similar age from Medical Oncology
#13
of 27 outputs
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