Graduate School, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, People's Republic of China; Department of Endocrinology & Rheumatology, Shanghai University of Medicine & Health Sciences Affiliated Zhoupu Hospital, Shanghai 201318, People's Republic of China.
Department of Endocrinology & Rheumatology, Shanghai University of Medicine & Health Sciences Affiliated Zhoupu Hospital, Shanghai 201318, People's Republic of China.
Immunobiology. 2023 Sep;228(5):152726. doi: 10.1016/j.imbio.2023.152726. Epub 2023 Aug 9.
With the recent advancement in omics and molecular techniques, a wealth of new molecular biomarkers have become available for the diagnosis and classification of primary Sjögren's syndrome (pSS) patients. However, whether these biomarkers are universal is of great interest to us. In this study, we used various methods to obtain shared biomarkers derived from multiple tissue in pSS patients and to explore their relationship with immune microenvironment alterations. First we identified differentially expressed genes (DEGs) between pSS and healthy controls utilizing nine mRNA microarray datasets obtained from the Gene Expression Omnibus (GEO). Then, shared biomarkers were filtered out using robust rank aggregation (RRA), data integration analysis, weighted gene co-expression network analysis (WGCNA), and least absolute selection and shrinkage operator (LASSO) regression; their roles in pSS and association with changes in the immune microenvironment were also analyzed. In addition, these biomarkers were further confirmed with both the testing set and immunohistochemistry (IHC). As a result, ten biomarkers, i.e., EPSTI1, IFI44, IFIT1, IFIT2, IFIT3, MX1, OAS1, PARP9, SAMD9L and TRIM22, were identified. Receiver operating characteristic (ROC) curves showed that the ten genes could discriminate pSS from controls. Gene set enrichment analysis (GSEA) showed that the enrichment of immune-related gene sets was significant in pSS patients with high expression of either biomarker. Furthermore, the association between some immunocytes and these biomarkers was identified. In the two distinct molecular patterns of pSS patients based on the expressions of these biomarkers, the proportions of immunocytes were significantly different. Our study identified shared biomarkers of multi-tissue origin and revealed their relationship with altered immune microenvironment in pSS patients. These markers not only have diagnostic implications but also provide potential immunotherapeutic targets for the clinical treatment of pSS patients.
随着组学和分子技术的最新进展,大量新的分子生物标志物可用于原发性干燥综合征 (pSS) 患者的诊断和分类。然而,这些生物标志物是否具有普遍性是我们非常关注的问题。在这项研究中,我们使用各种方法从 pSS 患者的多种组织中获得共享的生物标志物,并探索它们与免疫微环境改变的关系。首先,我们利用从基因表达综合数据库 (GEO) 获得的九个 mRNA 微阵列数据集,鉴定了 pSS 患者与健康对照之间差异表达的基因 (DEGs)。然后,使用稳健秩聚合 (RRA)、数据集成分析、加权基因共表达网络分析 (WGCNA) 和最小绝对收缩和选择算子 (LASSO) 回归筛选出共享的生物标志物;分析它们在 pSS 中的作用及其与免疫微环境变化的关系。此外,我们还通过测试集和免疫组织化学 (IHC) 进一步验证了这些生物标志物。结果,鉴定出 10 个生物标志物,即 EPSTI1、IFI44、IFIT1、IFIT2、IFIT3、MX1、OAS1、PARP9、SAMD9L 和 TRIM22。受试者工作特征 (ROC) 曲线表明,这 10 个基因可以区分 pSS 患者和对照组。基因集富集分析 (GSEA) 表明,在高表达任何生物标志物的 pSS 患者中,免疫相关基因集的富集是显著的。此外,还确定了一些免疫细胞与这些生物标志物之间的关联。在基于这些生物标志物表达的两种不同的 pSS 患者分子模式中,免疫细胞的比例有显著差异。我们的研究确定了多组织来源的共享生物标志物,并揭示了它们与 pSS 患者免疫微环境改变的关系。这些标志物不仅具有诊断意义,而且为 pSS 患者的临床治疗提供了潜在的免疫治疗靶点。