DEWNA: dynamic entropy weight network analysis and its application to the DNA-binding proteome in A549 cells with cisplatin-induced damage.

IF 6.8 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Shisheng Wang, Wenjuan Zeng, Yin Yang, Jingqiu Cheng, Dan Liu, Hao Yang
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引用次数: 0

Abstract

Cisplatin is one of the most commonly used chemotherapy drugs for treating solid tumors. As a genotoxic agent, cisplatin binds to DNA and forms platinum-DNA adducts that cause DNA damage and activate a series of signaling pathways mediated by various DNA-binding proteins (DBPs), ultimately leading to cell death. Therefore, DBPs play crucial roles in the cellular response to cisplatin and in determining cell fate. However, systematic studies of DBPs responding to cisplatin damage and their temporal dynamics are still lacking. To address this, we developed a novel and user-friendly stand-alone software, DEWNA, designed for dynamic entropy weight network analysis to reveal the dynamic changes of DBPs and their functions. DEWNA utilizes the entropy weight method, multiscale embedded gene co-expression network analysis and generalized reporter score-based analysis to process time-course proteome expression data, helping scientists identify protein hubs and pathway entropy profiles during disease progression. We applied DEWNA to a dataset of DBPs from A549 cells responding to cisplatin-induced damage across 8 time points, with data generated by data-independent acquisition mass spectrometry (DIA-MS). The results demonstrate that DEWNA can effectively identify protein hubs and associated pathways that are significantly altered in response to cisplatin-induced DNA damage, and offer a comprehensive view of how different pathways interact and respond dynamically over time to cisplatin treatment. Notably, we observed the dynamic activation of distinct DNA repair pathways and cell death mechanisms during the drug treatment time course, providing new insights into the molecular mechanisms underlying the cellular response to DNA damage.

DEWNA:动态熵权网络分析及其在顺铂诱导损伤的 A549 细胞 DNA 结合蛋白质组中的应用。
顺铂是治疗实体瘤最常用的化疗药物之一。作为一种基因毒性药物,顺铂与 DNA 结合,形成铂-DNA 加合物,造成 DNA 损伤,并激活由各种 DNA 结合蛋白(DBPs)介导的一系列信号通路,最终导致细胞死亡。因此,DBPs 在细胞对顺铂的反应和决定细胞命运方面起着至关重要的作用。然而,有关 DBPs 对顺铂损伤的反应及其时间动态的系统研究仍然缺乏。为了解决这个问题,我们开发了一种新颖且用户友好的单机软件 DEWNA,用于动态熵权网络分析,以揭示 DBPs 的动态变化及其功能。DEWNA 利用熵权法、多尺度嵌入式基因共表达网络分析和基于广义报告得分的分析来处理时序蛋白质组表达数据,帮助科学家识别疾病进展过程中的蛋白质枢纽和通路熵谱。我们将 DEWNA 应用于 A549 细胞对顺铂诱导的损伤做出反应的 DBPs 数据集,该数据集跨越 8 个时间点,由数据无关采集质谱(DIA-MS)生成。结果表明,DEWNA 能有效识别顺铂诱导 DNA 损伤时发生显著改变的蛋白质枢纽和相关通路,并能全面了解不同通路如何相互作用并随时间动态响应顺铂处理。值得注意的是,我们观察到在药物治疗过程中,不同的DNA修复通路和细胞死亡机制被动态激活,这为我们深入了解细胞对DNA损伤反应的分子机制提供了新的视角。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Briefings in bioinformatics
Briefings in bioinformatics 生物-生化研究方法
CiteScore
13.20
自引率
13.70%
发文量
549
审稿时长
6 months
期刊介绍: Briefings in Bioinformatics is an international journal serving as a platform for researchers and educators in the life sciences. It also appeals to mathematicians, statisticians, and computer scientists applying their expertise to biological challenges. The journal focuses on reviews tailored for users of databases and analytical tools in contemporary genetics, molecular and systems biology. It stands out by offering practical assistance and guidance to non-specialists in computerized methodologies. Covering a wide range from introductory concepts to specific protocols and analyses, the papers address bacterial, plant, fungal, animal, and human data. The journal's detailed subject areas include genetic studies of phenotypes and genotypes, mapping, DNA sequencing, expression profiling, gene expression studies, microarrays, alignment methods, protein profiles and HMMs, lipids, metabolic and signaling pathways, structure determination and function prediction, phylogenetic studies, and education and training.
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