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德瓦纳: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。

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

机构信息

Department of General Surgery and Liver Transplant Center, Proteomics-Metabolomics Analysis Platform, NHC Key Lab of Transplant Engineering and Immunology, West China Hospital, Sichuan University, Chengdu, China.

Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, China.

出版信息

Brief Bioinform. 2024 Sep 23;25(6). doi: 10.1093/bib/bbae564.

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.

摘要

顺铂是治疗实体瘤最常用的化疗药物之一。作为一种遗传毒性药物,顺铂与 DNA 结合形成铂-DNA 加合物,导致 DNA 损伤,并激活各种 DNA 结合蛋白 (DBP) 介导的一系列信号通路,最终导致细胞死亡。因此,DBP 在细胞对顺铂的反应和决定细胞命运中起着至关重要的作用。然而,系统研究 DBP 对顺铂损伤的反应及其时间动态变化仍然缺乏。为了解决这个问题,我们开发了一种新颖的、用户友好的独立软件,DEWNA,用于动态熵权网络分析,以揭示 DBP 的动态变化及其功能。DEWNA 利用熵权法、多尺度嵌入基因共表达网络分析和广义报道基因评分分析来处理时间过程蛋白质组表达数据,帮助科学家在疾病进展过程中识别蛋白质枢纽和途径熵谱。我们将 DEWNA 应用于一个来自 A549 细胞的 DBP 数据集,该数据集对 8 个时间点的顺铂诱导损伤做出反应,数据由独立数据采集质谱 (DIA-MS) 生成。结果表明,DEWNA 可以有效地识别对顺铂诱导的 DNA 损伤有显著改变的蛋白质枢纽和相关途径,并提供了一个全面的视角,了解不同途径如何随时间动态相互作用和响应顺铂治疗。值得注意的是,我们观察到在药物治疗过程中不同的 DNA 修复途径和细胞死亡机制的动态激活,为细胞对 DNA 损伤的反应的分子机制提供了新的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37eb/11530294/1a409328eae9/bbae564f1.jpg

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