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槟榔碱诱导口腔癌的分子机制:网络毒理学与分子对接技术的综合分析

Molecular mechanisms of arecoline-induced oral cancer: a network toxicology and molecular docking techniques integrated analysis.

作者信息

Leng Linghan, Wang Xin, Wang Hao, Hu Yingchun, Deng Yaxing, Wang Chenglin

机构信息

Department of Intensive Care Unit, Chengdu Fifth People's Hospital (The Second Clinical Medical College, Affiliated Fifth People's Hospital of Chengdu University of Traditional Chinese Medicine), Chengdu, Sichuan, China.

School of Stomatology, Southwest Medical University, Luzhou, Sichuan, China.

出版信息

Discov Oncol. 2025 May 21;16(1):842. doi: 10.1007/s12672-025-02659-0.

Abstract

The IARC classified betel nut as Group 1 carcinogen (2004) and arecoline as Group 2B carcinogen (2020), with approximately one-third of global oral cancer cases attributed to smokeless tobacco or betel nut consumption. While current evidence establishes an association between arecoline and oral cancer, the underlying molecular mechanisms remain complex and poorly elucidated. This study employs network toxicology integrated with molecular docking techniques to systematically investigate the potential molecular pathogenesis of arecoline-induced oral cancer, aiming to provide novel insights for targeted therapeutic strategies. The SMILES structure of arecoline was retrieved from PubChem for foundational data preparation. Toxicity profiling was conducted using ProTox-3.0 and ADMETlab databases. Potential targets of arecoline were identified via STITCH and SwissTargetPrediction. Oral cancer-related targets were collated from GeneCards, OMIM, and TTD. Intersection analysis between arecoline targets and oral cancer-associated targets was performed to identify shared targets, which were further utilized to construct compound-target regulatory network and subjected to PPI, GO, and KEGG analyses. Core targets driving oral cancer were screened using the cytoHubba plugin. Then, the correlation between core targets and immune cell infiltration in oral cancer was explored, and molecular docking validated the binding affinity of arecoline to core targets. Finally, Gromacs 2022.3 software was used to simulate the molecular dynamics of the complexes obtained by molecular docking for 100 ns. Using the STITCH and SwissTargetPrediction databases, a total of 46 potential targets of arecoline were identified. Concurrently, 2,375 oral cancer-related targets were retrieved from GeneCards, OMIM, and TTD. Intersection analysis of these two target sets yielded 26 overlapping targets. PPI analysis revealed that TP53, IL6, SNAI1, and CASP3 occupied central positions in the network, exhibiting extensive interactions with other target proteins. Enrichment analysis comprehensively elucidated the molecular functions, biological processes, cellular components, and associated pathways of these overlapping targets. Further screening using Cytoscape software identified four core targets: TP53, TNF, IL6, and CASP3. Immune infiltration analysis indicated that the expression levels of TP53, TNF, IL6, and CASP3 in oral cancer tissues were positively correlated with the infiltration levels of immune cells, including CD8 + T cells, Th1 cells, NK cells, and macrophages. Molecular docking experiments demonstrated strong binding activities between arecoline and TP53, IL6, and CASP3, while TNF also exhibited moderate binding affinity. Dynamic simulation further verified the stable binding of arecoline to TP53, TNF, IL6 and CASP3. Arecoline may induce oral cancer by acting on core targets including TP53, TNF, IL6, and CASP3, which interfere with normal cellular growth regulation, inflammatory responses, and apoptotic mechanisms. Therapeutic strategies targeting TP53, TNF, IL6, and CASP3 may represent novel research directions for clinical diagnosis and treatment of oral cancer.

摘要

国际癌症研究机构(IARC)在2004年将槟榔果列为1类致癌物,2020年将槟榔碱列为2B类致癌物,全球约三分之一的口腔癌病例归因于无烟烟草或槟榔果的消费。虽然目前的证据证实了槟榔碱与口腔癌之间存在关联,但其潜在的分子机制仍然复杂且尚未完全阐明。本研究采用网络毒理学结合分子对接技术,系统地研究槟榔碱诱导口腔癌的潜在分子发病机制,旨在为靶向治疗策略提供新的见解。从PubChem检索槟榔碱的SMILES结构以进行基础数据准备。使用ProTox-3.0和ADMETlab数据库进行毒性分析。通过STITCH和SwissTargetPrediction识别槟榔碱的潜在靶点。从GeneCards、OMIM和TTD整理口腔癌相关靶点。对槟榔碱靶点和口腔癌相关靶点进行交集分析以识别共同靶点,进一步利用这些靶点构建化合物-靶点调控网络,并进行蛋白质-蛋白质相互作用(PPI)、基因本体(GO)和京都基因与基因组百科全书(KEGG)分析。使用cytoHubba插件筛选驱动口腔癌的核心靶点。然后,探讨核心靶点与口腔癌中免疫细胞浸润的相关性,分子对接验证槟榔碱与核心靶点的结合亲和力。最后,使用Gromacs 2022.3软件对分子对接获得的复合物进行100纳秒的分子动力学模拟。利用STITCH和SwissTargetPrediction数据库,共识别出46个槟榔碱的潜在靶点。同时,从GeneCards、OMIM和TTD检索到2375个口腔癌相关靶点。这两个靶点集的交集分析产生了26个重叠靶点。PPI分析表明,TP53、IL6、SNAI1和CASP3在网络中占据中心位置,与其他靶蛋白表现出广泛的相互作用。富集分析全面阐明了这些重叠靶点的分子功能、生物学过程、细胞成分和相关途径。使用Cytoscape软件进一步筛选确定了四个核心靶点:TP53、TNF、IL6和CASP3。免疫浸润分析表明,口腔癌组织中TP53、TNF、IL6和CASP3的表达水平与免疫细胞(包括CD8 + T细胞、Th1细胞、NK细胞和巨噬细胞)的浸润水平呈正相关。分子对接实验表明槟榔碱与TP53、IL6和CASP3之间具有强结合活性,而TNF也表现出中等结合亲和力。动态模拟进一步验证了槟榔碱与TP53、TNF、IL6和CASP3的稳定结合。槟榔碱可能通过作用于包括TP53、TNF、IL6和CASP3在内的核心靶点诱导口腔癌,这些靶点会干扰正常的细胞生长调节、炎症反应和凋亡机制。针对TP53、TNF、IL6和CASP3的治疗策略可能代表口腔癌临床诊断和治疗的新研究方向。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c3a5/12095829/4723c4e5d289/12672_2025_2659_Fig1_HTML.jpg

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