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Kaneko S, Takasawa K, Asada K, Shiraishi K, Ikawa N, Machino H, Shinkai N, Matsuda M, Masuda M, Adachi S, Takahashi S, Kobayashi K, Kouno N, Bolatkan A, Komatsu M, Yamada M, Miyake M, Watanabe H, Tateishi A, Mizuno T, Okubo Y, Mukai M, Yoshida T, Yoshida Y, Horinouchi H, Watanabe SI, Ohe Y, Yatabe Y, Saloura V, Kohno T, Hamamoto R. Mechanism of ERBB2 gene overexpression by the formation of super-enhancer with genomic structural abnormalities in lung adenocarcinoma without clinically actionable genetic alterations. Mol Cancer 2024; 23:126. [PMID: 38862995 PMCID: PMC11165761 DOI: 10.1186/s12943-024-02035-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Accepted: 05/30/2024] [Indexed: 06/13/2024] Open
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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Affiliation(s)
- Syuzo Kaneko
- Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan.
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, 103-0027, Japan.
| | - Ken Takasawa
- Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, 103-0027, Japan
| | - Ken Asada
- Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, 103-0027, Japan
| | - Kouya Shiraishi
- Division of Genome Biology, National Cancer Center Research Institute, Tokyo, 104-0045, Japan
| | - Noriko Ikawa
- Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan
| | - Hidenori Machino
- Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, 103-0027, Japan
| | - Norio Shinkai
- Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, 103-0027, Japan
| | - Maiko Matsuda
- Division of Genome Biology, National Cancer Center Research Institute, Tokyo, 104-0045, Japan
| | - Mari Masuda
- Department of Proteomics, National Cancer Center Research Institute, Tokyo, 104-0045, Japan
| | - Shungo Adachi
- Department of Proteomics, National Cancer Center Research Institute, Tokyo, 104-0045, Japan
| | - Satoshi Takahashi
- Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, 103-0027, Japan
| | - Kazuma Kobayashi
- Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, 103-0027, Japan
| | - Nobuji Kouno
- Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, 103-0027, Japan
| | - Amina Bolatkan
- Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, 103-0027, Japan
| | - Masaaki Komatsu
- Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, 103-0027, Japan
| | - Masayoshi Yamada
- Endoscopy Division, National Cancer Center Hospital, Tokyo, 104-0045, Japan
| | - Mototaka Miyake
- Department of Diagnostic Radiology, National Cancer Center Hospital, Tokyo, 104-0045, Japan
| | - Hirokazu Watanabe
- Department of Diagnostic Radiology, National Cancer Center Hospital, Tokyo, 104-0045, Japan
| | - Akiko Tateishi
- Department of Thoracic Oncology, National Cancer Center Hospital, Tokyo, 104-0045, Japan
| | - Takaaki Mizuno
- Division of Genome Biology, National Cancer Center Research Institute, Tokyo, 104-0045, Japan
- Department of Thoracic Oncology, National Cancer Center Hospital, Tokyo, 104-0045, Japan
- Department of Experimental Therapeutics, National Cancer Center Hospital, Tokyo, 104-0045, Japan
| | - Yu Okubo
- Department of Thoracic Surgery, National Cancer Center Hospital, Tokyo, 104-0045, Japan
| | - Masami Mukai
- Division of Medical Informatics, National Cancer Center Hospital, Tokyo, 104-0045, Japan
| | - Tatsuya Yoshida
- Department of Thoracic Oncology, National Cancer Center Hospital, Tokyo, 104-0045, Japan
| | - Yukihiro Yoshida
- Department of Thoracic Surgery, National Cancer Center Hospital, Tokyo, 104-0045, Japan
| | - Hidehito Horinouchi
- Department of Thoracic Oncology, National Cancer Center Hospital, Tokyo, 104-0045, Japan
| | - Shun-Ichi Watanabe
- Department of Thoracic Surgery, National Cancer Center Hospital, Tokyo, 104-0045, Japan
| | - Yuichiro Ohe
- Department of Thoracic Oncology, National Cancer Center Hospital, Tokyo, 104-0045, Japan
| | - Yasushi Yatabe
- Department of Diagnostic Pathology, National Cancer Center Hospital, Tokyo, 104-0045, Japan
| | - Vassiliki Saloura
- Center for Cancer Research, National Cancer Institute, Bethesda, MD, 20892, USA
| | - Takashi Kohno
- Division of Genome Biology, National Cancer Center Research Institute, Tokyo, 104-0045, Japan
| | - Ryuji Hamamoto
- Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan.
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo, 103-0027, Japan.
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Roy D, Calaf GM. Allelic loss at chromosome 11q13 alters FGF3 gene expression in a human breast cancer progression model. Oncol Rep 2014; 32:2445-52. [PMID: 25333703 DOI: 10.3892/or.2014.3502] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2014] [Accepted: 08/26/2014] [Indexed: 11/06/2022] Open
Abstract
Identification of markers with the potential to predict tumorigenic behavior is important in breast cancer, due to the variability in clinical disease progression. Genetic alterations during neoplastic progression may appear as changes in total DNA content, single genes, or gene expression. Oncogenic alterations are thought to be prognostic indices for patients with breast cancer. Breast cancer deregulation can occur in the normal cellular process and can be measured by microsatellite instability (MSI)/loss of heterozygosity (LOH). Chromosome 11 is unique in this respect, as three regions of MSI/LOH have been identified (11p15-p15.5, 11q13-q13.3 and 11q23-q24). There are many important families of genes, such as FGF, CCND1, FADD, BAD and GAD2, that are located on chromosome 11 and these play a crucial role in breast cancer progression. Among them, different members of the fibroblast growth factor (FGF) family of genes are clustered around human chromosome 11q13 amplicon, which are constantly altering during breast cancer progression. Therefore, in this study, locus 11q13 and FGF3 gene (11q13) function were investigated in a radiation and estrogen breast cancer model induced by high-LET (α-particle) radiation and estrogen exposure. To assess the effect of ionizing radiation and estrogen at chromosome 11q13 loci and the subsequent role of FGF3 gene expression, various microsatellite markers were chosen in this region, and allelic loses (~20-45%) were identified by PCR-SSCP analysis. Results showed an increase in FGF3 protein expression and a 6- to 8-fold change in gene expression of FGF3 and associated genes. These deregulations could be utilized as an appropriate target for therapeutic intervention in breast cancer.
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Affiliation(s)
- Debasish Roy
- Department of Natural Sciences, Hostos College of the City University of New York, Bronx, NY, USA
| | - Gloria M Calaf
- Instituto de Alta Investigación, Universidad de Tarapacá, Arica, Chile
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Bachleitner-Hofmann T, Sun MY, Chen CT, Liska D, Zeng Z, Viale A, Olshen AB, Mittlboeck M, Christensen JG, Rosen N, Solit DB, Weiser MR. Antitumor activity of SNX-2112, a synthetic heat shock protein-90 inhibitor, in MET-amplified tumor cells with or without resistance to selective MET Inhibition. Clin Cancer Res 2011; 17:122-33. [PMID: 21208906 DOI: 10.1158/1078-0432.ccr-10-0253] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
PURPOSE Heat shock protein-90 (HSP-90), a molecular chaperone required by numerous oncogenic kinases [e.g., HER-2, epidermal growth factor receptor (EGFR), Raf-1, v-Src, and AKT] for conformational stability, has attracted wide interest as a novel target for cancer therapy. HSP-90 inhibition induces degradation of HSP-90 client proteins, leading to a combinatorial inhibition of multiple oncogenic signaling pathways with consecutive growth arrest and apoptosis. MET, a tyrosine kinase that is constitutively active in tumor cells with MET oncogene amplification, has recently been identified as another HSP-90 client. EXPERIMENTAL DESIGN The aim of our study was to assess the efficacy of SNX-2112, a synthetic HSP-90 inhibitor, in 3 different MET-amplified tumor cell lines (GTL-16, MKN-45, and EBC-1) as well as PR-GTL-16 cells, a GTL-16 subline selected for resistance to the highly selective MET kinase inhibitor PHA-665752. RESULTS In all cell lines, SNX-2112 led to degradation of MET, HER-2, EGFR, and AKT, as well as abrogation of Ras/Raf/MEK/MAPK and PI3K/AKT signaling, followed by complete cell cycle arrest. SNX-5542, an orally bioavailable prodrug of SNX-2112, displayed significant antitumor efficacy in vivo in nude mice bearing MET-amplified tumor xenografts. Importantly, HSP-90 inhibition maintained its antitumor efficacy in PR-GTL-16 cells both in vitro and in vivo, suggesting that HSP-90 inhibition could be a particularly valuable strategy in MET-amplified tumors that have acquired resistance to MET kinase inhibition. CONCLUSIONS Our study provides evidence for the efficacy of HSP-90 inhibition in MET-amplified cancer cells, particularly when MET kinase inhibitor resistance has emerged.
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