{"title":"多组学和聚类分析揭示了肺腺癌患者未满足需求的内在机制,并确定了潜在的治疗靶点。","authors":"Ken Asada, Syuzo Kaneko, Ken Takasawa, Kouya Shiraishi, Norio Shinkai, Yoko Shimada, Satoshi Takahashi, Hidenori Machino, Kazuma Kobayashi, Amina Bolatkan, Masaaki Komatsu, Masayoshi Yamada, Mototaka Miyake, Hirokazu Watanabe, Akiko Tateishi, Takaaki Mizuno, Yu Okubo, Masami Mukai, Tatsuya Yoshida, Yukihiro Yoshida, Hidehito Horinouchi, Shun-Ichi Watanabe, Yuichiro Ohe, Yasushi Yatabe, Takashi Kohno, Ryuji Hamamoto","doi":"10.1186/s12943-024-02093-w","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The cancer genome contains several driver mutations. However, in some cases, no known drivers have been identified; these remaining areas of unmet needs, leading to limited progress in cancer therapy. Whole-genome sequencing (WGS) can identify non-coding alterations associated with the disease. Consequently, exploration of non-coding regions using WGS and other omics data such as ChIP-sequencing (ChIP-seq) to discern novel alterations and mechanisms related to tumorigenesis have been attractive these days.</p><p><strong>Methods: </strong>Integrated multi-omics analyses, including WGS, ChIP-seq, DNA methylation, and RNA-sequencing (RNA-seq), were conducted on samples from patients with non-clinically actionable genetic alterations (non-CAGAs) in lung adenocarcinoma (LUAD). Second-level cluster analysis was performed to reinforce the correlations associated with patient survival, as identified by RNA-seq. Subsequent differential gene expression analysis was performed to identify potential druggable targets.</p><p><strong>Results: </strong>Differences in H3K27ac marks in non-CAGAs LUAD were found and confirmed by analyzing RNA-seq data, in which mastermind-like transcriptional coactivator 2 (MAML2) was suppressed. The down-regulated genes whose expression was correlated to MAML2 expression were associated with patient prognosis. WGS analysis revealed somatic mutations associated with the H3K27ac marks in the MAML2 region and high levels of DNA methylation in MAML2 were observed in tumor samples. The second-level cluster analysis enabled patient stratification and subsequent analyses identified potential therapeutic target genes and treatment options.</p><p><strong>Conclusions: </strong>We overcome the persistent challenges of identifying alterations or driver mutations in coding regions related to tumorigenesis through a novel approach combining multi-omics data with clinical information to reveal the molecular mechanisms underlying non-CAGAs LUAD, stratify patients to improve patient prognosis, and identify potential therapeutic targets. This approach may be applicable to studies of other cancers with unmet needs.</p>","PeriodicalId":19000,"journal":{"name":"Molecular Cancer","volume":"23 1","pages":"182"},"PeriodicalIF":27.7000,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11367768/pdf/","citationCount":"0","resultStr":"{\"title\":\"Multi-omics and clustering analyses reveal the mechanisms underlying unmet needs for patients with lung adenocarcinoma and identify potential therapeutic targets.\",\"authors\":\"Ken Asada, Syuzo Kaneko, Ken Takasawa, Kouya Shiraishi, Norio Shinkai, Yoko Shimada, Satoshi Takahashi, Hidenori Machino, Kazuma Kobayashi, Amina Bolatkan, Masaaki Komatsu, Masayoshi Yamada, Mototaka Miyake, Hirokazu Watanabe, Akiko Tateishi, Takaaki Mizuno, Yu Okubo, Masami Mukai, Tatsuya Yoshida, Yukihiro Yoshida, Hidehito Horinouchi, Shun-Ichi Watanabe, Yuichiro Ohe, Yasushi Yatabe, Takashi Kohno, Ryuji Hamamoto\",\"doi\":\"10.1186/s12943-024-02093-w\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>The cancer genome contains several driver mutations. However, in some cases, no known drivers have been identified; these remaining areas of unmet needs, leading to limited progress in cancer therapy. Whole-genome sequencing (WGS) can identify non-coding alterations associated with the disease. Consequently, exploration of non-coding regions using WGS and other omics data such as ChIP-sequencing (ChIP-seq) to discern novel alterations and mechanisms related to tumorigenesis have been attractive these days.</p><p><strong>Methods: </strong>Integrated multi-omics analyses, including WGS, ChIP-seq, DNA methylation, and RNA-sequencing (RNA-seq), were conducted on samples from patients with non-clinically actionable genetic alterations (non-CAGAs) in lung adenocarcinoma (LUAD). Second-level cluster analysis was performed to reinforce the correlations associated with patient survival, as identified by RNA-seq. Subsequent differential gene expression analysis was performed to identify potential druggable targets.</p><p><strong>Results: </strong>Differences in H3K27ac marks in non-CAGAs LUAD were found and confirmed by analyzing RNA-seq data, in which mastermind-like transcriptional coactivator 2 (MAML2) was suppressed. The down-regulated genes whose expression was correlated to MAML2 expression were associated with patient prognosis. WGS analysis revealed somatic mutations associated with the H3K27ac marks in the MAML2 region and high levels of DNA methylation in MAML2 were observed in tumor samples. The second-level cluster analysis enabled patient stratification and subsequent analyses identified potential therapeutic target genes and treatment options.</p><p><strong>Conclusions: </strong>We overcome the persistent challenges of identifying alterations or driver mutations in coding regions related to tumorigenesis through a novel approach combining multi-omics data with clinical information to reveal the molecular mechanisms underlying non-CAGAs LUAD, stratify patients to improve patient prognosis, and identify potential therapeutic targets. This approach may be applicable to studies of other cancers with unmet needs.</p>\",\"PeriodicalId\":19000,\"journal\":{\"name\":\"Molecular Cancer\",\"volume\":\"23 1\",\"pages\":\"182\"},\"PeriodicalIF\":27.7000,\"publicationDate\":\"2024-09-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11367768/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Molecular Cancer\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1186/s12943-024-02093-w\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Molecular Cancer","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12943-024-02093-w","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
Multi-omics and clustering analyses reveal the mechanisms underlying unmet needs for patients with lung adenocarcinoma and identify potential therapeutic targets.
Background: The cancer genome contains several driver mutations. However, in some cases, no known drivers have been identified; these remaining areas of unmet needs, leading to limited progress in cancer therapy. Whole-genome sequencing (WGS) can identify non-coding alterations associated with the disease. Consequently, exploration of non-coding regions using WGS and other omics data such as ChIP-sequencing (ChIP-seq) to discern novel alterations and mechanisms related to tumorigenesis have been attractive these days.
Methods: Integrated multi-omics analyses, including WGS, ChIP-seq, DNA methylation, and RNA-sequencing (RNA-seq), were conducted on samples from patients with non-clinically actionable genetic alterations (non-CAGAs) in lung adenocarcinoma (LUAD). Second-level cluster analysis was performed to reinforce the correlations associated with patient survival, as identified by RNA-seq. Subsequent differential gene expression analysis was performed to identify potential druggable targets.
Results: Differences in H3K27ac marks in non-CAGAs LUAD were found and confirmed by analyzing RNA-seq data, in which mastermind-like transcriptional coactivator 2 (MAML2) was suppressed. The down-regulated genes whose expression was correlated to MAML2 expression were associated with patient prognosis. WGS analysis revealed somatic mutations associated with the H3K27ac marks in the MAML2 region and high levels of DNA methylation in MAML2 were observed in tumor samples. The second-level cluster analysis enabled patient stratification and subsequent analyses identified potential therapeutic target genes and treatment options.
Conclusions: We overcome the persistent challenges of identifying alterations or driver mutations in coding regions related to tumorigenesis through a novel approach combining multi-omics data with clinical information to reveal the molecular mechanisms underlying non-CAGAs LUAD, stratify patients to improve patient prognosis, and identify potential therapeutic targets. This approach may be applicable to studies of other cancers with unmet needs.
期刊介绍:
Molecular Cancer is a platform that encourages the exchange of ideas and discoveries in the field of cancer research, particularly focusing on the molecular aspects. Our goal is to facilitate discussions and provide insights into various areas of cancer and related biomedical science. We welcome articles from basic, translational, and clinical research that contribute to the advancement of understanding, prevention, diagnosis, and treatment of cancer.
The scope of topics covered in Molecular Cancer is diverse and inclusive. These include, but are not limited to, cell and tumor biology, angiogenesis, utilizing animal models, understanding metastasis, exploring cancer antigens and the immune response, investigating cellular signaling and molecular biology, examining epidemiology, genetic and molecular profiling of cancer, identifying molecular targets, studying cancer stem cells, exploring DNA damage and repair mechanisms, analyzing cell cycle regulation, investigating apoptosis, exploring molecular virology, and evaluating vaccine and antibody-based cancer therapies.
Molecular Cancer serves as an important platform for sharing exciting discoveries in cancer-related research. It offers an unparalleled opportunity to communicate information to both specialists and the general public. The online presence of Molecular Cancer enables immediate publication of accepted articles and facilitates the presentation of large datasets and supplementary information. This ensures that new research is efficiently and rapidly disseminated to the scientific community.