RHOJ is a small G protein characterized by its abundant expression in endothelial cells. Existing research has documented a link between abnormal RHOJ expression and carcinogenesis. This research aims to investigate the protective role of RHOJ in nonsmall cell lung cancer (NSCLC). In this study, Cancer Genome Atlas database and Gene Expression Omnibus were collected to analyze RHOJ expression and gene regulation networks in NSCLC. Oncomine^™ and Gene Expression Profiling Interactive Analysis tools were first utilized to analyze RHOJ expression, and then cBioPortal was employed for identification of RHOJ alterations and associated functional networks. To identify differential RHOJ expression, LinkedOmics was used, which also served to analyze Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways. Besides, the target networks of kinases factors were explored using gene enrichment analysis. Our results suggested that lower expression of RHOJ was observed in patients with NSCLC compared with normal people. Low expression of this gene is linked to functional networks involving cytoskeleton, adhesion, infection, and Ras signaling pathways. Functional network analysis suggested that RHOJ regulates the Staphylococcus aureus infection, AGE-RAGE signaling pathway, and DNA and RNA damage. In conclusion, the results in this study demonstrated that data mining is an effective approach that can uncover information about RHOJ expression and potential regulatory networks in NSCLC, thus laying the groundwork for future studies of a similar kind.

中文翻译：

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基于综合生物信息学分析的 RHOJ 在非小细胞肺癌中的保护作用。

RHOJ 是一种小 G 蛋白，其特点是在内皮细胞中大量表达。现有研究已经证明 RHOJ 表达异常与致癌作用之间存在联系。本研究旨在探讨 RHOJ 在非小细胞肺癌 (NSCLC) 中的保护作用。本研究收集了癌症基因组图谱数据库和基因表达综合数据库，分析了 NSCLC 中 RHOJ 的表达和基因调控网络。安康^™和基因表达谱交互式分析工具首先用于分析 RHOJ 表达，然后使用 cBioPortal 来识别 RHOJ 改变和相关的功能网络。为了识别差异 RHOJ 表达，使用了 LinkedOmics，它也用于分析基因本体论和京都基因和基因组途径百科全书。此外，使用基因富集分析探索激酶因子的目标网络。我们的结果表明，与正常人相比，NSCLC 患者中观察到 RHOJ 的表达较低。该基因的低表达与涉及细胞骨架、粘附、感染和 Ras 信号通路的功能网络有关。功能网络分析表明RHOJ调节金黄色葡萄球菌感染、AGE-RAGE 信号通路以及 DNA 和 RNA 损伤。总之，本研究的结果表明，数据挖掘是一种有效的方法，可以揭示 NSCLC 中 RHOJ 表达和潜在调控网络的信息，从而为未来类似的研究奠定基础。