Hosseinpour Zahra, Zamanian Azodi Mona, Jahani Sherafat Somayeh, Rezaei Tavirani Mostafa
Cancer Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Proteomics Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Gastroenterol Hepatol Bed Bench. 2023;16(4):415-420. doi: 10.22037/ghfbb.v16i4.2695.
This study aims to investigate the anticancer molecular mechanism of RT2 through protein-protein interaction (PPI) network analysis. For this aim, a bioinformatics evaluation of the proteome profile of colon cancer is carried out.
Antimicrobial peptides such as RT2 showed anticancer properties against various tumors. The molecular mechanism of the anticancer effect of RT2 is a challenging subject.
By applying Cytoscape V.3.9.1 and integrated apps, the profile of the interaction network and related centrality is analyzed. An enrichment analysis of hub bottlenecks was also performed, and highlighted biological processes were visualized and determined.
Several 207 differentially expressed proteins were retrieved by PPI network analysis, and 10 hub bottlenecks were introduced. Among these differentially expressed proteins (DEPs), only AKT1 is from the queried DEPs. Key biological processes contributing to RT2 targeting mechanism include "Regulation of fibroblast proliferation", "Positive regulation of cyclin-dependent protein serine/threonine kinase activity", "positive regulation of miRNA transcription", and "fungiform papilla formation".
In conclusion, central proteins Tp53, MYC, EGFR, AKT1, HDAC1, and SRC can be introduced as a targeted biomarker panel of bioactive peptide treatments. However, extensive research is required to establish this claim before clinical application.
本研究旨在通过蛋白质-蛋白质相互作用(PPI)网络分析来探究RT2的抗癌分子机制。为此,对结肠癌蛋白质组图谱进行了生物信息学评估。
诸如RT2之类的抗菌肽对多种肿瘤显示出抗癌特性。RT2抗癌作用的分子机制是一个具有挑战性的课题。
通过应用Cytoscape V.3.9.1及集成应用程序,分析了相互作用网络图谱及相关中心性。还进行了枢纽瓶颈的富集分析,并对突出的生物学过程进行了可视化和确定。
通过PPI网络分析检索到207种差异表达蛋白,并引入了10个枢纽瓶颈。在这些差异表达蛋白(DEP)中,只有AKT1来自查询的DEP。促成RT2靶向机制的关键生物学过程包括“成纤维细胞增殖的调节”、“细胞周期蛋白依赖性蛋白丝氨酸/苏氨酸激酶活性的正调节”、“miRNA转录的正调节”以及“菌状乳头形成”。
总之,核心蛋白Tp53、MYC、EGFR、AKT1、HDAC1和SRC可作为生物活性肽治疗的靶向生物标志物组引入。然而,在临床应用之前,需要进行广泛的研究来证实这一说法。