| Title |
Next-generation sequence detects ARAP3 as a novel oncogene in papillary thyroid carcinoma
|
|---|---|
| Published in |
OncoTargets and therapy, November 2016
|
| DOI | 10.2147/ott.s115668 |
| Pubmed ID | |
| Authors |
Qing-Xuan Wang, En-Dong Chen, Ye-Feng Cai, Yi-Li Zhou, Zhou-Ci Zheng, Ying-Hao Wang, Yi-Xiang Jin, Wen-Xu Jin, Xiao-Hua Zhang, Ou-Chen Wang |
| Abstract |
Thyroid cancer is the most frequent malignancies of the endocrine system, and it has became the fastest growing type of cancer worldwide. Much still remains unknown about the molecular mechanisms of thyroid cancer. Studies have found that some certain relationship between ARAP3 and human cancer. However, the role of ARAP3 in thyroid cancer has not been well explained. This study aimed to investigate the role of ARAP3 gene in papillary thyroid carcinoma. Whole exon sequence and whole genome sequence of primary papillary thyroid carcinoma (PTC) samples and matched adjacent normal thyroid tissue samples were performed and then bioinformatics analysis was carried out. PTC cell lines (TPC1, BCPAP, and KTC-1) with transfection of small interfering RNA were used to investigate the functions of ARAP3 gene, including cell proliferation assay, colony formation assay, migration assay, and invasion assay. Using next-generation sequence and bioinformatics analysis, we found ARAP3 genes may play an important role in thyroid cancer. Downregulation of ARAP3 significantly suppressed PTC cell lines (TPC1, BCPAP, and KTC-1), cell proliferation, colony formation, migration, and invasion. This study indicated that ARAP3 genes have important biological implications and may act as a potentially drugable target in PTC. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| China | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 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% |
| Student > Master | 2 | 18% |
| Researcher | 2 | 18% |
| Student > Ph. D. Student | 1 | 9% |
| Professor | 1 | 9% |
| Other | 1 | 9% |
| Unknown | 2 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 3 | 27% |
| Medicine and Dentistry | 2 | 18% |
| Nursing and Health Professions | 1 | 9% |
| Computer Science | 1 | 9% |
| Agricultural and Biological Sciences | 1 | 9% |
| Other | 0 | 0% |
| 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 24 November 2016.
All research outputs
#19,944,994
of 25,374,647 outputs
Outputs from OncoTargets and therapy
#1,447
of 3,016 outputs
Outputs of similar age
#231,759
of 317,808 outputs
Outputs of similar age from OncoTargets and therapy
#56
of 74 outputs
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