Identifying Driver Genes Mutations with Clinical Significance in Thyroid Cancer
- 주제(키워드) Medical informatics , papillary thyroid carcinoma , cancer , gene mutation analysis , BRAF , clinical significance
- 주제(기타) Computer Science, Information Systems
- 주제(기타) Materials Science, Multidisciplinary
- 설명문(일반) [Yu, Hyeong Won; Choi, June Young] Seoul Natl Univ, Bundang Hosp, Dept Surg, Seongnam Si, South Korea; [Afzal, Muhammad; Hussain, Maqbool] Sejong Univ, Dept Software, Seoul, South Korea; [Kwon, Hyungju] Ewha Womans Univ, Coll Med, Dept Surg, Seoul, South Korea; [Park, Young Joo] Seoul Natl Univ Hosp, Dept Internal Med, Seoul, South Korea; [Park, Young Joo; Lee, Kyu Eun] Coll Med, Seoul, South Korea; [Lee, Kyu Eun] Seoul Natl Univ Hosp, Dept Surg, Seoul, South Korea
- 등재 SCIE, SCOPUS
- OA유형 gold
- 발행기관 TECH SCIENCE PRESS
- 발행년도 2021
- 총서유형 Journal
- URI http://www.dcollection.net/handler/ewha/000000175475
- 본문언어 영어
- Published As http://dx.doi.org/10.32604/cmc.2021.014910
초록/요약
Advances in technology are enabling gene mutations in papillary thyroid carcinoma (PTC) to be analyzed and clinical outcomes, such as recurrence, to be predicted. To date, the most common genetic mutation in PTC is in BRAF kinase (BRAF). However, whether mutations in other genes coincide with those in BRAF remains to be clarified. The aim of this study was to find mutations in other genes that co-exist with mutated BRAF, and to analyze their frequency and clinical relevance in PTC. Clinical and genetic data were collected from 213 PTC patients with a total of 36,572 mutation sites in 735 genes. After matching with genes from PTC entries in a global database (NCBI Gene), 69 genes with mutations in coding regions were chosen for further study. Through frequency-based analysis, we identified commonly mutated genes co-existing with mutated BRAF and, using the mutation count correlation matrix (MCCM) method, analyzed their incidence according to age and gender. We designed Chord diagrams to reveal gene relationships concerning age and gender, and found that mutations in ALK, ATM, COL1A1, MSTIR, PRKCA, and WNK1 most commonly coincide with mutated BRAF, followed by APC, AURKA, and AURKB. These findings provide further insight into the genetic profile of PTC.
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