Molecular characterization of lung adenocarcinoma from Korean patients using next generation sequencing

Korean Lung Cancer Consortium (KLCC)

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10 Citations (Scopus)


The treatment of Lung adenocarcinoma (LUAD) could benefit from the incorporation of precision medicine. This study was to identify cancer-related genetic alterations by next generation sequencing (NGS) in resected LUAD samples from Korean patients and to determine their associations with clinical features. A total of 201 tumors and their matched peripheral blood samples were analyzed using targeted sequencing via the Illumina HiSeq 2500 platform of 242 genes with a median depth of coverage greater than 500X. One hundred ninety-two tumors were amenable to data analysis. EGFR was the most frequently mutated gene, occurring in 106 (55%) patients, followed by TP53 (n = 67, 35%) and KRAS (n = 11, 6%). EGFR mutations were strongly increased in patients that were female and never-smokers. Smokers had a significantly higher tumor mutational burden (TMB) than never-smokers (average 4.84 non-synonymous mutations/megabase [mt/Mb] vs. 2.84 mt/Mb, p = 0.019). Somatic mutations of APC, CTNNB1, and AMER1 in the WNT signaling pathway were highly associated with shortened disease-free survival (DFS) compared to others (median DFS of 89 vs. 27 months, p = 0.018). Patients with low TMB, annotated as less than 2 mt/ Mb, had longer DFS than those with high TMB (p = 0.041). A higher frequency of EGFR mutations and a lower of KRAS mutations were observed in Korean LUAD patients. Profiles of 242 genes mapped in this study were compared with whole exome sequencing genetic profiles generated in The Cancer Genome Atlas Lung Adenocarcinoma. NGS-based diagnostics can provide clinically relevant information such as mutations or TMB from readily available formalin-fixed paraffin-embedded tissue.

Original languageEnglish
Article numbere0224379
JournalPloS one
Issue number11
Publication statusPublished - 2019 Nov 1

Bibliographical note

Publisher Copyright:
© 2019 Chun et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

All Science Journal Classification (ASJC) codes

  • General


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