Application of amplicon-based targeted sequencing with the molecular barcoding system to detect uncommon minor EGFR mutations in patients with treatment-naïve lung adenocarcinoma

Kei Namba, Shuta Tomida, Takehiro Matsubara, Yuta Takahashi, Eisuke Kurihara, Yusuke Ogoshi, Takahiro Yoshioka, Tatsuaki Takeda, Hidejiro Torigoe, Hiroki Sato, Kazuhiko Shien, Hiromasa Yamamoto, Junichi Sou, Kazunori Tsukuda, Shinichi Toyooka

Research output: Contribution to journalArticle

Abstract

Background: In lung cancer, epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor sensitizing mutations co-existing with rare minor EGFR mutations are known as compound mutations. These minor EGFR mutations can lead to acquired resistance after EGFR tyrosine kinase inhibitor treatment, so determining the mutation status of patients is important. However, using amplicon-based targeted deep sequencing based on next-generation sequencing to characterize mutations is prone to sequencing error. We therefore assessed the benefit of incorporating molecular barcoding with high-throughput sequencing to investigate genomic heterogeneity in treatment-naïve patients who have undergone resection of their non-small cell lung cancer (NSCLC) EGFR mutations. Methods: We performed amplicon-based targeted sequencing with the molecular barcoding system (MBS) to detect major common EGFR mutations and uncommon minor mutations at a 0.5% allele frequency in fresh-frozen lung cancer samples. Results: Profiles of the common mutations of EGFR identified by MBS corresponded with the results of clinical testing in 63 (98.4%) out of 64 cases. Uncommon mutations of EGFR were detected in seven cases (10.9%). Among the three types of major EGFR mutations, patients with the G719X mutation had a significantly higher incidence of compound mutations than those with the L858R mutation or exon 19 deletion (p = 0.0052). This was validated in an independent cohort from the Cancer Genome Atlas dataset (p = 0.018). Conclusions: Our findings demonstrate the feasibility of using the MBS to establish an accurate NSCLC patient genotype. This work will help understand the molecular basis of EGFR compound mutations in NSCLC, and could aid the development of new treatment modalities.

Original languageEnglish
Article number175
JournalBMC Cancer
Volume19
Issue number1
DOIs
Publication statusPublished - Feb 26 2019

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Epidermal Growth Factor Receptor
Mutation
Therapeutics
Non-Small Cell Lung Carcinoma
Adenocarcinoma of lung
Protein-Tyrosine Kinases
Lung Neoplasms
High-Throughput Nucleotide Sequencing
Atlases
Gene Frequency
Exons

Keywords

  • Clinical sequencing
  • Compound mutations
  • EGFR
  • Epidermal growth factor receptor
  • Genomic heterogeneity
  • Molecular barcoding
  • Molecular barcoding
  • Mutation detection
  • Next-generation sequencing
  • Non-small cell lung cancer
  • Non-small cell lung cancer
  • Patient genotype
  • Sequence artifact
  • Treatment-naïve
  • Uncommon mutation

ASJC Scopus subject areas

  • Oncology
  • Genetics
  • Cancer Research

Cite this

Application of amplicon-based targeted sequencing with the molecular barcoding system to detect uncommon minor EGFR mutations in patients with treatment-naïve lung adenocarcinoma. / Namba, Kei; Tomida, Shuta; Matsubara, Takehiro; Takahashi, Yuta; Kurihara, Eisuke; Ogoshi, Yusuke; Yoshioka, Takahiro; Takeda, Tatsuaki; Torigoe, Hidejiro; Sato, Hiroki; Shien, Kazuhiko; Yamamoto, Hiromasa; Sou, Junichi; Tsukuda, Kazunori; Toyooka, Shinichi.

In: BMC Cancer, Vol. 19, No. 1, 175, 26.02.2019.

Research output: Contribution to journalArticle

Namba, Kei ; Tomida, Shuta ; Matsubara, Takehiro ; Takahashi, Yuta ; Kurihara, Eisuke ; Ogoshi, Yusuke ; Yoshioka, Takahiro ; Takeda, Tatsuaki ; Torigoe, Hidejiro ; Sato, Hiroki ; Shien, Kazuhiko ; Yamamoto, Hiromasa ; Sou, Junichi ; Tsukuda, Kazunori ; Toyooka, Shinichi. / Application of amplicon-based targeted sequencing with the molecular barcoding system to detect uncommon minor EGFR mutations in patients with treatment-naïve lung adenocarcinoma. In: BMC Cancer. 2019 ; Vol. 19, No. 1.
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AU - Namba, Kei

AU - Tomida, Shuta

AU - Matsubara, Takehiro

AU - Takahashi, Yuta

AU - Kurihara, Eisuke

AU - Ogoshi, Yusuke

AU - Yoshioka, Takahiro

AU - Takeda, Tatsuaki

AU - Torigoe, Hidejiro

AU - Sato, Hiroki

AU - Shien, Kazuhiko

AU - Yamamoto, Hiromasa

AU - Sou, Junichi

AU - Tsukuda, Kazunori

AU - Toyooka, Shinichi

PY - 2019/2/26

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N2 - Background: In lung cancer, epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor sensitizing mutations co-existing with rare minor EGFR mutations are known as compound mutations. These minor EGFR mutations can lead to acquired resistance after EGFR tyrosine kinase inhibitor treatment, so determining the mutation status of patients is important. However, using amplicon-based targeted deep sequencing based on next-generation sequencing to characterize mutations is prone to sequencing error. We therefore assessed the benefit of incorporating molecular barcoding with high-throughput sequencing to investigate genomic heterogeneity in treatment-naïve patients who have undergone resection of their non-small cell lung cancer (NSCLC) EGFR mutations. Methods: We performed amplicon-based targeted sequencing with the molecular barcoding system (MBS) to detect major common EGFR mutations and uncommon minor mutations at a 0.5% allele frequency in fresh-frozen lung cancer samples. Results: Profiles of the common mutations of EGFR identified by MBS corresponded with the results of clinical testing in 63 (98.4%) out of 64 cases. Uncommon mutations of EGFR were detected in seven cases (10.9%). Among the three types of major EGFR mutations, patients with the G719X mutation had a significantly higher incidence of compound mutations than those with the L858R mutation or exon 19 deletion (p = 0.0052). This was validated in an independent cohort from the Cancer Genome Atlas dataset (p = 0.018). Conclusions: Our findings demonstrate the feasibility of using the MBS to establish an accurate NSCLC patient genotype. This work will help understand the molecular basis of EGFR compound mutations in NSCLC, and could aid the development of new treatment modalities.

AB - Background: In lung cancer, epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor sensitizing mutations co-existing with rare minor EGFR mutations are known as compound mutations. These minor EGFR mutations can lead to acquired resistance after EGFR tyrosine kinase inhibitor treatment, so determining the mutation status of patients is important. However, using amplicon-based targeted deep sequencing based on next-generation sequencing to characterize mutations is prone to sequencing error. We therefore assessed the benefit of incorporating molecular barcoding with high-throughput sequencing to investigate genomic heterogeneity in treatment-naïve patients who have undergone resection of their non-small cell lung cancer (NSCLC) EGFR mutations. Methods: We performed amplicon-based targeted sequencing with the molecular barcoding system (MBS) to detect major common EGFR mutations and uncommon minor mutations at a 0.5% allele frequency in fresh-frozen lung cancer samples. Results: Profiles of the common mutations of EGFR identified by MBS corresponded with the results of clinical testing in 63 (98.4%) out of 64 cases. Uncommon mutations of EGFR were detected in seven cases (10.9%). Among the three types of major EGFR mutations, patients with the G719X mutation had a significantly higher incidence of compound mutations than those with the L858R mutation or exon 19 deletion (p = 0.0052). This was validated in an independent cohort from the Cancer Genome Atlas dataset (p = 0.018). Conclusions: Our findings demonstrate the feasibility of using the MBS to establish an accurate NSCLC patient genotype. This work will help understand the molecular basis of EGFR compound mutations in NSCLC, and could aid the development of new treatment modalities.

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KW - Next-generation sequencing

KW - Non-small cell lung cancer

KW - Non-small cell lung cancer

KW - Patient genotype

KW - Sequence artifact

KW - Treatment-naïve

KW - Uncommon mutation

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