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Mechanism of ERBB2 gene overexpression by the formation of super-enhancer with genomic structural abnormalities in lung adenocarcinoma without clinically actionable genetic alterations.
Kaneko, Syuzo; Takasawa, Ken; Asada, Ken; Shiraishi, Kouya; Ikawa, Noriko; Machino, Hidenori; Shinkai, Norio; Matsuda, Maiko; Masuda, Mari; Adachi, Shungo; Takahashi, Satoshi; Kobayashi, Kazuma; Kouno, Nobuji; Bolatkan, Amina; Komatsu, Masaaki; Yamada, Masayoshi; Miyake, Mototaka; Watanabe, Hirokazu; Tateishi, Akiko; Mizuno, Takaaki; Okubo, Yu; Mukai, Masami; Yoshida, Tatsuya; Yoshida, Yukihiro; Horinouchi, Hidehito; Watanabe, Shun-Ichi; Ohe, Yuichiro; Yatabe, Yasushi; Saloura, Vassiliki; Kohno, Takashi; Hamamoto, Ryuji.
Affiliation
  • Kaneko S; Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan. sykaneko@ncc.go.jp.
  • Takasawa K; Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, 103-0027, Japan. sykaneko@ncc.go.jp.
  • Asada K; Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan.
  • Shiraishi K; Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, 103-0027, Japan.
  • Ikawa N; Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan.
  • Machino H; Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, 103-0027, Japan.
  • Shinkai N; Division of Genome Biology, National Cancer Center Research Institute, Tokyo, 104-0045, Japan.
  • Matsuda M; Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan.
  • Masuda M; Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan.
  • Adachi S; Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, 103-0027, Japan.
  • Takahashi S; Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan.
  • Kobayashi K; Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, 103-0027, Japan.
  • Kouno N; Division of Genome Biology, National Cancer Center Research Institute, Tokyo, 104-0045, Japan.
  • Bolatkan A; Department of Proteomics, National Cancer Center Research Institute, Tokyo, 104-0045, Japan.
  • Komatsu M; Department of Proteomics, National Cancer Center Research Institute, Tokyo, 104-0045, Japan.
  • Yamada M; Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan.
  • Miyake M; Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, 103-0027, Japan.
  • Watanabe H; Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan.
  • Tateishi A; Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, 103-0027, Japan.
  • Mizuno T; Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan.
  • Okubo Y; Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, 103-0027, Japan.
  • Mukai M; Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan.
  • Yoshida T; Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, 103-0027, Japan.
  • Yoshida Y; Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan.
  • Horinouchi H; Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, 103-0027, Japan.
  • Watanabe SI; Endoscopy Division, National Cancer Center Hospital, Tokyo, 104-0045, Japan.
  • Ohe Y; Department of Diagnostic Radiology, National Cancer Center Hospital, Tokyo, 104-0045, Japan.
  • Yatabe Y; Department of Diagnostic Radiology, National Cancer Center Hospital, Tokyo, 104-0045, Japan.
  • Saloura V; Department of Thoracic Oncology, National Cancer Center Hospital, Tokyo, 104-0045, Japan.
  • Kohno T; Division of Genome Biology, National Cancer Center Research Institute, Tokyo, 104-0045, Japan.
  • Hamamoto R; Department of Thoracic Oncology, National Cancer Center Hospital, Tokyo, 104-0045, Japan.
Mol Cancer ; 23(1): 126, 2024 Jun 11.
Article in En | MEDLINE | ID: mdl-38862995
ABSTRACT

BACKGROUND:

In an extensive genomic analysis of lung adenocarcinomas (LUADs), driver mutations have been recognized as potential targets for molecular therapy. However, there remain cases where target genes are not identified. Super-enhancers and structural variants are frequently identified in several hundred loci per case. Despite this, most cancer research has approached the analysis of these data sets separately, without merging and comparing the data, and there are no examples of integrated analysis in LUAD.

METHODS:

We performed an integrated analysis of super-enhancers and structural variants in a cohort of 174 LUAD cases that lacked clinically actionable genetic alterations. To achieve this, we conducted both WGS and H3K27Ac ChIP-seq analyses using samples with driver gene mutations and those without, allowing for a comprehensive investigation of the potential roles of super-enhancer in LUAD cases.

RESULTS:

We demonstrate that most genes situated in these overlapped regions were associated with known and previously unknown driver genes and aberrant expression resulting from the formation of super-enhancers accompanied by genomic structural abnormalities. Hi-C and long-read sequencing data further corroborated this insight. When we employed CRISPR-Cas9 to induce structural abnormalities that mimicked cases with outlier ERBB2 gene expression, we observed an elevation in ERBB2 expression. These abnormalities are associated with a higher risk of recurrence after surgery, irrespective of the presence or absence of driver mutations.

CONCLUSIONS:

Our findings suggest that aberrant gene expression linked to structural polymorphisms can significantly impact personalized cancer treatment by facilitating the identification of driver mutations and prognostic factors, contributing to a more comprehensive understanding of LUAD pathogenesis.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Gene Expression Regulation, Neoplastic / Enhancer Elements, Genetic / Receptor, ErbB-2 / Adenocarcinoma of Lung / Lung Neoplasms Limits: Aged / Female / Humans / Male / Middle aged Language: En Journal: Mol Cancer Journal subject: NEOPLASIAS Year: 2024 Document type: Article Affiliation country: Japan

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Gene Expression Regulation, Neoplastic / Enhancer Elements, Genetic / Receptor, ErbB-2 / Adenocarcinoma of Lung / Lung Neoplasms Limits: Aged / Female / Humans / Male / Middle aged Language: En Journal: Mol Cancer Journal subject: NEOPLASIAS Year: 2024 Document type: Article Affiliation country: Japan