Huang Shan, Yin Hang
Department of Urology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.
Institute of Urology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.
Medicine (Baltimore). 2024 Nov 22;103(47):e40270. doi: 10.1097/MD.0000000000040270.
Acute rejection (AR) is a common complication in the early stage after kidney transplantation. Some studies have shown that the occurrence of AR after kidney transplantation may further affect the development of tumors, and both AR and tumor development are related to immune cells and immune genes, so it is particularly important to diagnose the occurrence of AR at an early stage and to analyze the correlation between AR and tumors. In this study, we applied bioinformatics techniques for differential expression analysis and weighted gene co-expression network analysis analysis of AR patients to obtain differentially expressed genes and modular genes significantly associated with AR, respectively, so as to obtain their intersecting genes with immune-related genes; 21 intersecting genes were screened by lasso regression and Boruta algorithm to obtain the genes, and finally, the feature genes that were significantly associated with the dependent variable were further obtained by single-factor and multi-factor logistic regression. Then the best diagnostic model for AR was screened by 10 machine learning methods, and we evaluated the model in various aspects, such as receiver operator characteristic curve, decision curve analysis. We then focused on the role of FAM3C in renal cancer. We finally screened 4 feature genes (CD1D, FPR2, FAM3C, and HMOX1) to construct the AR diagnostic model; through comparative evaluation, we believe that logistic regression shows a better advantage in the construction of diagnostic models for AR. FAM3C may become a potential biological marker for AR diagnosis and plays an important role in the development of renal cancer. In summary, immune-related genes play an important role in the diagnosis of AR after kidney transplantation, and the gene FAM3C may be a potential therapeutic target for AR and renal cancer.
急性排斥反应（AR）是肾移植术后早期常见的并发症。一些研究表明，肾移植术后AR的发生可能会进一步影响肿瘤的发展，且AR和肿瘤发展均与免疫细胞及免疫基因有关，因此早期诊断AR的发生并分析AR与肿瘤之间的相关性尤为重要。在本研究中，我们应用生物信息学技术对AR患者进行差异表达分析和加权基因共表达网络分析，分别获得与AR显著相关的差异表达基因和模块基因，从而得到它们与免疫相关基因的交集基因；通过套索回归和Boruta算法筛选出21个交集基因，最终通过单因素和多因素逻辑回归进一步获得与因变量显著相关的特征基因。然后通过10种机器学习方法筛选出AR的最佳诊断模型，并从受试者工作特征曲线、决策曲线分析等多个方面对该模型进行评估。随后我们重点研究了FAM3C在肾癌中的作用。我们最终筛选出4个特征基因（CD1D、FPR2、FAM3C和HMOX1）构建AR诊断模型；通过比较评估，我们认为逻辑回归在构建AR诊断模型方面表现出更好的优势。FAM3C可能成为AR诊断的潜在生物标志物，并在肾癌发展中发挥重要作用。综上所述，免疫相关基因在肾移植术后AR的诊断中发挥重要作用，基因FAM3C可能是AR和肾癌的潜在治疗靶点。
