使用COFE的节律分析揭示了体内人类癌症的多组昼夜节律。

IF 9.8 1区 生物学 Q1 Agricultural and Biological Sciences
Bharath Ananthasubramaniam, Ramji Venkataramanan
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引用次数: 0

摘要

对人类生理中普遍存在的昼夜节律的研究需要定期测量时间。对装有生物钟的不同内部组织进行重复采样在实践和伦理上都是不可行的。在这里,我们提出了一种新的无监督机器学习方法(COFE),该方法可以使用来自个体的单个高通量组学样本(没有时间标签)来重建整个队列的昼夜节律。COFE可以同时为样本分配时间标签,并识别用于时间重建的节奏数据特征,同时还可以检测无效顺序。利用COFE,我们利用来自癌症基因组图谱(TCGA)数据库的数据,在11种不同的人类腺癌中发现了广泛的新生昼夜节律基因表达节律。核心时钟基因表达高峰时间的排列在癌症中是保守的,除了几个关键基因的错误时间外,类似于健康的功能时钟。此外,转录组中的节律与癌症相关的蛋白质组密切相关。所有癌症共有的节律性基因和蛋白质都参与了新陈代谢和细胞周期。尽管这些节律在许多癌症中与细胞周期同步,但它们与健康匹配组织中的时钟不耦合。大多数fda批准的和潜在的抗癌药物的靶点在肿瘤组织中具有节律性,具有不同的振幅和峰值时间。这些发现强调了在癌症治疗中考虑“时间”的效用,并建议关注健康组织中的时钟,而不是癌症组织中自由运行的时钟。因此,我们的方法创造了新的机会,可以重新利用没有时间标签的数据来研究昼夜节律。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Rhythm profiling using COFE reveals multi-omic circadian rhythms in human cancers in vivo.

The study of ubiquitous circadian rhythms in human physiology requires regular measurements across time. Repeated sampling of the different internal tissues that house circadian clocks is both practically and ethically infeasible. Here, we present a novel unsupervised machine learning approach (COFE) that can use single high-throughput omics samples (without time labels) from individuals to reconstruct circadian rhythms across cohorts. COFE can simultaneously assign time labels to samples and identify rhythmic data features used for temporal reconstruction, while also detecting invalid orderings. With COFE, we discovered widespread de novo circadian gene expression rhythms in 11 different human adenocarcinomas using data from The Cancer Genome Atlas (TCGA) database. The arrangement of peak times of core clock gene expression was conserved across cancers and resembled a healthy functional clock except for the mistiming of a few key genes. Moreover, rhythms in the transcriptome were strongly associated with the cancer-relevant proteome. The rhythmic genes and proteins common to all cancers were involved in metabolism and the cell cycle. Although these rhythms were synchronized with the cell cycle in many cancers, they were uncoupled with clocks in healthy matched tissue. The targets of most of FDA-approved and potential anti-cancer drugs were rhythmic in tumor tissue with different amplitudes and peak times. These findings emphasize the utility of considering "time" in cancer therapy, and suggest a focus on clocks in healthy tissue rather than free-running clocks in cancer tissue. Our approach thus creates new opportunities to repurpose data without time labels to study circadian rhythms.

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来源期刊
PLoS Biology
PLoS Biology BIOCHEMISTRY & MOLECULAR BIOLOGY-BIOLOGY
CiteScore
15.40
自引率
2.00%
发文量
359
审稿时长
3-8 weeks
期刊介绍: PLOS Biology is the flagship journal of the Public Library of Science (PLOS) and focuses on publishing groundbreaking and relevant research in all areas of biological science. The journal features works at various scales, ranging from molecules to ecosystems, and also encourages interdisciplinary studies. PLOS Biology publishes articles that demonstrate exceptional significance, originality, and relevance, with a high standard of scientific rigor in methodology, reporting, and conclusions. The journal aims to advance science and serve the research community by transforming research communication to align with the research process. It offers evolving article types and policies that empower authors to share the complete story behind their scientific findings with a diverse global audience of researchers, educators, policymakers, patient advocacy groups, and the general public. PLOS Biology, along with other PLOS journals, is widely indexed by major services such as Crossref, Dimensions, DOAJ, Google Scholar, PubMed, PubMed Central, Scopus, and Web of Science. Additionally, PLOS Biology is indexed by various other services including AGRICOLA, Biological Abstracts, BIOSYS Previews, CABI CAB Abstracts, CABI Global Health, CAPES, CAS, CNKI, Embase, Journal Guide, MEDLINE, and Zoological Record, ensuring that the research content is easily accessible and discoverable by a wide range of audiences.
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