Identifying Driver Genes Mutations with Clinical Significance in Thyroid Cancer

Hyeong Won Yu, Muhammad Afzal, Maqbool Hussain, Hyungju Kwon, Young Joo Park, June Young Choi, Kyu Eun Lee

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)1241-1251
Number of pages11
JournalComputers, Materials and Continua
Volume67
Issue number1
DOIs
StatePublished - 2021

Bibliographical note

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Keywords

  • BRAF
  • cancer
  • clinical significance
  • gene mutation analysis
  • Medical informatics
  • papillary thyroid carcinoma

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