利用深度学习破解端粒酶启动子突变对动态转移形态组的影响。

IF 3.8 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS PLoS Computational Biology Pub Date : 2024-07-30 eCollection Date: 2024-07-01 DOI:10.1371/journal.pcbi.1012271
Andres J Nevarez, Anusorn Mudla, Sabrina A Diaz, Nan Hao
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引用次数: 0

摘要

在转移转化过程中,黑色素瘤的基因改变与细胞内和细胞间的形态学变化呈现出复杂的相互作用。特定突变在这些变化中的作用虽然至关重要,但仍有待全面阐明。端粒酶启动子突变(TERTp突变)对黑色素瘤的进展、侵袭性和对各种新兴疗法(包括化学抑制剂、端粒酶抑制剂、靶向疗法和免疫疗法)的耐药性有显著影响。我们的目的是了解在黑色素瘤转移中富集的两种显性单复性 TERTp 突变(C228T 和 C250T)的形态和表型影响。我们开发了含有TERTp突变的同源克隆细胞系,并利用由内源性端粒酶启动子引导的双色表达报告,从而获得了等位基因分辨率。这种方法使我们能够监测这些突变诱导的形态变化。TERTp突变细胞的形态组与野生型细胞有显著差异,等位基因表达模式增加,伤口愈合率提高,时空动态独特。值得注意的是,与 C228T 相比,C250T 突变在形态组中产生了更明显的变化,这表明它在转移潜能中起着不同的作用。我们的发现强调了TERTp突变对黑色素瘤细胞结构和行为的不同影响。C250T 突变可能为转移提供了独特的形态组和系统驱动优势。这些见解为我们理解黑色素瘤转移中的非编码突变如何影响系统并表现为细胞形态组提供了基础。
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Using deep learning to decipher the impact of telomerase promoter mutations on the dynamic metastatic morpholome.

Melanoma showcases a complex interplay of genetic alterations and intra- and inter-cellular morphological changes during metastatic transformation. While pivotal, the role of specific mutations in dictating these changes still needs to be fully elucidated. Telomerase promoter mutations (TERTp mutations) significantly influence melanoma's progression, invasiveness, and resistance to various emerging treatments, including chemical inhibitors, telomerase inhibitors, targeted therapy, and immunotherapies. We aim to understand the morphological and phenotypic implications of the two dominant monoallelic TERTp mutations, C228T and C250T, enriched in melanoma metastasis. We developed isogenic clonal cell lines containing the TERTp mutations and utilized dual-color expression reporters steered by the endogenous Telomerase promoter, giving us allelic resolution. This approach allowed us to monitor morpholomic variations induced by these mutations. TERTp mutation-bearing cells exhibited significant morpholome differences from their wild-type counterparts, with increased allele expression patterns, augmented wound-healing rates, and unique spatiotemporal dynamics. Notably, the C250T mutation exerted more pronounced changes in the morpholome than C228T, suggesting a differential role in metastatic potential. Our findings underscore the distinct influence of TERTp mutations on melanoma's cellular architecture and behavior. The C250T mutation may offer a unique morpholomic and systems-driven advantage for metastasis. These insights provide a foundational understanding of how a non-coding mutation in melanoma metastasis affects the system, manifesting in cellular morpholome.

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来源期刊
PLoS Computational Biology
PLoS Computational Biology BIOCHEMICAL RESEARCH METHODS-MATHEMATICAL & COMPUTATIONAL BIOLOGY
CiteScore
7.10
自引率
4.70%
发文量
820
审稿时长
2.5 months
期刊介绍: PLOS Computational Biology features works of exceptional significance that further our understanding of living systems at all scales—from molecules and cells, to patient populations and ecosystems—through the application of computational methods. Readers include life and computational scientists, who can take the important findings presented here to the next level of discovery. Research articles must be declared as belonging to a relevant section. More information about the sections can be found in the submission guidelines. Research articles should model aspects of biological systems, demonstrate both methodological and scientific novelty, and provide profound new biological insights. Generally, reliability and significance of biological discovery through computation should be validated and enriched by experimental studies. Inclusion of experimental validation is not required for publication, but should be referenced where possible. Inclusion of experimental validation of a modest biological discovery through computation does not render a manuscript suitable for PLOS Computational Biology. Research articles specifically designated as Methods papers should describe outstanding methods of exceptional importance that have been shown, or have the promise to provide new biological insights. The method must already be widely adopted, or have the promise of wide adoption by a broad community of users. Enhancements to existing published methods will only be considered if those enhancements bring exceptional new capabilities.
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