Multi-omics and clustering analyses reveal the mechanisms underlying unmet needs for patients with lung adenocarcinoma and identify potential therapeutic targets.

IF 27.7 1区 医学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY
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
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引用次数: 0

Abstract

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.

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。
背景:癌症基因组包含多种驱动突变。然而,在某些情况下,尚未发现已知的驱动基因;这些领域的需求仍未得到满足,导致癌症治疗进展有限。全基因组测序(WGS)可以确定与疾病相关的非编码改变。因此,利用 WGS 和其他组学数据(如 ChIP-测序(ChIP-seq))对非编码区进行探索,以发现与肿瘤发生有关的新的改变和机制,如今已具有吸引力:方法:对肺腺癌(LUAD)中存在非临床可操作基因改变(non-CAGAs)的患者样本进行了多组学综合分析,包括WGS、ChIP-seq、DNA甲基化和RNA测序(RNA-seq)。进行了二级聚类分析,以加强 RNA-seq 确定的与患者生存相关的关联性。随后进行了差异基因表达分析,以确定潜在的药物靶点:结果:通过分析RNA-seq数据,发现并证实了非CAGAs LUAD中H3K27ac标记的差异,其中mastermind样转录辅激活子2(MAML2)受到抑制。与MAML2表达相关的下调基因与患者的预后有关。WGS分析揭示了与MAML2区域H3K27ac标记相关的体细胞突变,并在肿瘤样本中观察到MAML2的高水平DNA甲基化。二级聚类分析实现了患者分层,随后的分析确定了潜在的治疗靶基因和治疗方案:我们通过一种将多组学数据与临床信息相结合的新方法,克服了识别与肿瘤发生相关的编码区改变或驱动突变的长期挑战,揭示了非CAGAs LUAD的分子机制,对患者进行分层以改善患者预后,并确定了潜在的治疗靶点。这种方法可能适用于其他未满足需求的癌症研究。
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来源期刊
Molecular Cancer
Molecular Cancer 医学-生化与分子生物学
CiteScore
54.90
自引率
2.70%
发文量
224
审稿时长
2 months
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.
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