Identification of Novel Hub Genes and Potential Signaling Pathways with the Pathogenesis of Oral Cavity Squamous Cell Carcinoma Based on Bioinformatics Analysis.

IF 2.5 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Cancer Informatics Pub Date : 2026-02-13 eCollection Date: 2026-01-01 DOI:10.1177/11769351261417703
Mohammad Reza Eskandarion, Mojtaba Vand Rajabpour, Shahroo Etemad-Moghadam, Farrokh Heidari, Seyede FatemeMahmoudi Hashemi, Hadiseh Mohammadpour, Amir Mohammad Karimi, Ebrahim Karimi, Mojgan Alaeddini
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引用次数: 0

Abstract

Background & aim: Oral squamous cell carcinoma (OSCC) is a devastating disease with poor prognosis and low survival rates, despite advancements in diagnosis and treatment. Early detection and identification of molecular targets are crucial for improving patient outcomes. This study aims to identify differentially expressed genes (DEGs) and key molecular pathways involved in the OSCC. This study's findings will contribute to the development of effective targeted therapies, ultimately improving the prognosis and survival rates of OSCC patients.

Materials & methods: Three gene expression profiles (GSE37991, GSE30784, and GSE107591) from the GEO database were analyzed for differentially expressed genes using EnrichR. Subsequent downstream analyses of the selected module genes were conducted using various bioinformatics tools including STRING, Cytoscape, GEPIA, cBioPortal, NetworkAnalyst, MirWalk, and a bipartite miRNA-mRNA correlation network.

Result: The reanalysis indicated that the Toll-like receptor (TLR) signaling pathway plays a significant role in the development of oral SCC and CXCL8, CCL5, CXCL10, STAT1, IL1B, and TLR2 genes were up-regulated and enriched significantly in the signaling pathways' interactions in oral SCC. Genetic mutation analysis of hub genes in OSCC revealed that STAT1 have 2.5% mutation rate and 0% for other genes. It was revealed that the development and prediction of OSCC may be affected by hsa-mir-146a-5 and hsa-mir-155-5p.

Conclusion: Novel potential biomarkers and signaling pathways associated with OSCC have been identified, which may be important in the transformation of OSCC adenocarcinoma and may serve as therapeutic targets for OSCC.

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基于生物信息学分析的口腔鳞状细胞癌新枢纽基因及其潜在信号通路的鉴定
背景与目的:口腔鳞状细胞癌(OSCC)是一种预后差、生存率低的毁灭性疾病,尽管在诊断和治疗方面取得了进展。早期发现和识别分子靶点对改善患者预后至关重要。本研究旨在确定与OSCC相关的差异表达基因(DEGs)和关键分子通路。本研究结果将有助于开发有效的靶向治疗方法,最终改善OSCC患者的预后和生存率。材料与方法:使用富集软件对GEO数据库中的三个基因表达谱(GSE37991、GSE30784和GSE107591)进行差异表达基因分析。随后对所选模块基因进行下游分析,使用各种生物信息学工具,包括STRING、Cytoscape、GEPIA、cbiopportal、NetworkAnalyst、MirWalk和一个双端miRNA-mRNA相关网络。结果:再分析表明toll样受体(TLR)信号通路在口腔SCC的发生发展中起重要作用,且在这些信号通路的相互作用中,CXCL8、CCL5、CXCL10、STAT1、IL1B和TLR2基因显著上调和富集。对OSCC中心基因的基因突变分析显示,STAT1的突变率为2.5%,其他基因的突变率为0%。结果显示,OSCC的发展和预测可能受到hsa-mir-146a-5和hsa-mir-155-5p的影响。结论:已经发现了与OSCC相关的新的潜在生物标志物和信号通路,它们可能在OSCC腺癌的转化过程中发挥重要作用,并可能成为OSCC的治疗靶点。
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
Cancer Informatics
Cancer Informatics Medicine-Oncology
CiteScore
3.00
自引率
5.00%
发文量
30
审稿时长
8 weeks
期刊介绍: The field of cancer research relies on advances in many other disciplines, including omics technology, mass spectrometry, radio imaging, computer science, and biostatistics. Cancer Informatics provides open access to peer-reviewed high-quality manuscripts reporting bioinformatics analysis of molecular genetics and/or clinical data pertaining to cancer, emphasizing the use of machine learning, artificial intelligence, statistical algorithms, advanced imaging techniques, data visualization, and high-throughput technologies. As the leading journal dedicated exclusively to the report of the use of computational methods in cancer research and practice, Cancer Informatics leverages methodological improvements in systems biology, genomics, proteomics, metabolomics, and molecular biochemistry into the fields of cancer detection, treatment, classification, risk-prediction, prevention, outcome, and modeling.
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