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基于机器学习分析揭示与肾纤维化患者免疫浸润相关的潜在诊断基因生物标志物。

Revealing Potential Diagnostic Gene Biomarkers Associated with Immune Infiltration in Patients with Renal Fibrosis Based on Machine Learning Analysis.

机构信息

Department of Clinical Medicine Research Center, The Fourth Affiliated Hospital, International Institutes of Medicine, Zhejiang University School of Medicine, Yiwu 322000, China.

Department of Physical Education, Minjiang University, Fuzhou 350108, China.

出版信息

J Immunol Res. 2022 Apr 20;2022:3027200. doi: 10.1155/2022/3027200. eCollection 2022.

Abstract

Chronic kidney disease is characterized by the development of renal fibrosis. The basic mechanisms of renal fibrosis have not yet been fully investigated despite significant progress in understanding the etiology of the disease. In this work, the researchers sought to identify potential diagnostic indicators for renal fibrosis. From the GEO database, we were able to acquire two gene expression profiles with publically available data (GSE22459 and GSE76882, respectively) from human renal fibrosis and control samples. 215 renal fibrosis specimens and 124 normal specimens were examined for differentially expressed genes (DEGs). The SVM-RFE and LASSO regression models were used to discover potential markers. CIBERSORT was applied to estimate the combined cohorts' immune cell fraction compositional trends in renal fibrosis. RT-PCR was used to examine the expression of ISG20 in renal fibrosis and healthy samples. In vitro experiments were applied to examine the function of ISG20 knockdown on the progression of renal fibrosis. In this study, we identified 24 DEGs. The result of LASSO and SVM-RFE identified nine critical genes. ROC assays confirmed the diagnostic value of the above nine genes for renal fibrosis. Immune cell infiltration analysis revealed that ISG20 and SERPINA3 were both found to be correlated with T cell follicular helper, neutrophils, T cell CD4 memory activated, eosinophils, T cell CD8, dendritic cell activated, B cell memory, monocytes, macrophage M2, plasma cells, T cell CD4 naïve, mast cell resting, B cell naïve, T cell regulatory, and NK cell activated. Finally, we observed that the expression of ISG20 and SERPINA3 was distinctly increased in renal fibrosis samples compared with normal samples. ISG20 siRNA significantly suppressed the progression of renal fibrosis in vitro. Overall, this study identified nine diagnostic biomarkers for renal fibrosis. ISG20 may be a novel therapeutic target of renal fibrosis.

摘要

慢性肾脏病的特征是肾纤维化的发展。尽管在了解疾病病因方面取得了重大进展,但肾纤维化的基本机制仍未得到充分研究。在这项工作中,研究人员试图确定肾纤维化的潜在诊断指标。我们从 GEO 数据库中获取了两个具有公开数据的基因表达谱(分别为 GSE22459 和 GSE76882),来自人类肾纤维化和对照样本。检查了 215 个肾纤维化标本和 124 个正常标本的差异表达基因(DEGs)。使用 SVM-RFE 和 LASSO 回归模型发现潜在标记物。应用 CIBERSORT 估计肾纤维化合并队列中免疫细胞分数组成趋势。使用 RT-PCR 检查 ISG20 在肾纤维化和健康样本中的表达。进行体外实验以检查 ISG20 敲低对肾纤维化进展的影响。在这项研究中,我们鉴定了 24 个 DEGs。LASSO 和 SVM-RFE 的结果确定了 9 个关键基因。ROC 检测证实了上述 9 个基因对肾纤维化的诊断价值。免疫细胞浸润分析表明,ISG20 和 SERPINA3 均与滤泡辅助性 T 细胞、中性粒细胞、T 细胞 CD4 记忆激活、嗜酸性粒细胞、T 细胞 CD8、树突状细胞激活、B 细胞记忆、单核细胞、M2 巨噬细胞、浆细胞、T 细胞 CD4 幼稚、静止肥大细胞、B 细胞幼稚、T 细胞调节和 NK 细胞激活相关。最后,我们观察到 ISG20 和 SERPINA3 在肾纤维化样本中的表达明显高于正常样本。ISG20 siRNA 显著抑制体外肾纤维化的进展。总的来说,这项研究确定了九个诊断肾纤维化的生物标志物。ISG20 可能是肾纤维化的一个新的治疗靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2901/9045970/3b5d9bf739ee/JIR2022-3027200.001.jpg

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