MAPK信号级联的网络和建模分析揭示了EGR1通过ERK2蛋白在乳腺癌中的调节

IF 6.3 2区 医学 Q1 BIOLOGY
Honey Pavithran , Preetam Ghosh , Ranjith Kumavath
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引用次数: 0

摘要

该研究利用网络药理学研究和生物信息学方法,探讨了心脏糖苷(CGs),包括lanatoside C (LC), peruvoside (PS)和strophanthidin (STR)在治疗乳腺癌中的治疗相关性。基于我们之前的体外研究和转录组分析,我们旨在探索本研究中所选化合物对蛋白质表达变化的影响。该方法旨在描述活性蛋白靶点及其在控制癌症进展中的分子作用机制。最初,我们使用SWISSTargetPrediction预测了单个化合物的蛋白靶点,并将结果与初步研究中获得的转录组数据中的差异表达基因进行了比较。通过使用UALCAN算法比较其在TCGA癌症和正常患者数据中的表达,进一步研究鉴定的蛋白靶点的网络相关性,并进行交叉验证。此外,我们的目标是通过使用GEPIA2数据库对关键蛋白进行生存分析,确定可能作为恶性乳腺癌预测或预后指标的候选生物标志物。总的来说,该分析使我们了解了MAPK1和EGR1蛋白之间的共依赖表达,进一步强调了它们在癌症诊断和可能的治疗结果中的临床意义。MD模拟研究进一步验证了最重要的蛋白靶点及其相互作用评分和化合物的结构稳定性,结果表明MAPK1和EGR1蛋白在300-ns轨迹附近具有较高的结构稳定性。最后,基于MAPK/ERK信号级联的途径模拟研究显示,该系统的生化参数和稳定性显著改变取决于关键蛋白ERK2(也称为MAPK1和EGR1蛋白)在该途径中的浓度。这些发现强调了CGs的治疗潜力,并进一步强调了已确定的蛋白质在靶向乳腺癌中的重要作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Network and modeling analysis of MAPK signaling cascade uncovers EGR1 regulation through ERK2 protein in breast cancer

Network and modeling analysis of MAPK signaling cascade uncovers EGR1 regulation through ERK2 protein in breast cancer
The study explores the therapeutic relevance of Cardiac glycosides (CGs), including lanatoside C (LC), peruvoside (PS), and strophanthidin (STR) in treating breast cancer, using network pharmacology studies and bioinformatics approaches. Building on our prior in vitro studies and transcriptome profiling, we aimed to explore protein expression alterations influenced by the selected compounds in the present study. The methodology was structured and directed to delineate the active protein targets and their molecular mechanism of action in controlling cancer progression. Initially, we predicted the protein targets of individual compounds using SWISSTargetPrediction, and the results were compared with the differentially expressed genes from the transcriptome data acquired in the preliminary studies. The identified protein targets were further studied for their network relatedness and cross-verified by comparing their expression in cancer and normal patient data from TCGA using the UALCAN algorithm. Additionally, we aimed to identify the candidate biomarkers that potentially served as predictive or prognostic indicators in malignant breast cancer by conducting survival analysis of the crucial proteins using the GEPIA2 database. Overall, the analysis allowed us to understand the co-dependence expression between MAPK1 and EGR1 proteins, further emphasizing their clinical significance in cancer diagnosis and probable therapeutic outcomes. MD simulation studies further verified the most significant protein targets with their interaction scores and structural stability of the compounds, which showed higher structural stability around 300-ns trajectories for MAPK1 and EGR1 proteins. Finally, the pathway simulation studies, modeling on the MAPK/ERK signaling cascade, showed significant alteration in the biochemical parameters and stability of the system depending on the concentration of crucial proteins ERK2, also known as MAPK1 and EGR1 proteins in the pathway. These findings underscore the therapeutic potential of CGs and further highlight the significant role of identified proteins in targeting breast cancer.
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来源期刊
Computers in biology and medicine
Computers in biology and medicine 工程技术-工程:生物医学
CiteScore
11.70
自引率
10.40%
发文量
1086
审稿时长
74 days
期刊介绍: Computers in Biology and Medicine is an international forum for sharing groundbreaking advancements in the use of computers in bioscience and medicine. This journal serves as a medium for communicating essential research, instruction, ideas, and information regarding the rapidly evolving field of computer applications in these domains. By encouraging the exchange of knowledge, we aim to facilitate progress and innovation in the utilization of computers in biology and medicine.
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