Department of Nephrology, Hangzhou TCM Hospital of Zhejiang Chinese Medical University (Hangzhou Hospital of Traditional Chinese Medicine), Hangzhou 310007, Zhejiang, China.
Department of Nephrology, Hangzhou TCM Hospital of Zhejiang Chinese Medical University (Hangzhou Hospital of Traditional Chinese Medicine), Hangzhou 310007, Zhejiang, China.
Int Immunopharmacol. 2024 Dec 25;143(Pt 1):113236. doi: 10.1016/j.intimp.2024.113236. Epub 2024 Oct 7.
Immunogenic cell death (ICD) is a unique cell death triggered by chemotherapy. However, studies elucidating the potential therapeutic role of ICD and the underlying mechanism in diabetic nephropathy (DN) are limited.
WGCNA was conducted on the human kidney biopsy data linked to DN, analyzing gene sets associated with ICD. Gene Set Enrichment Analysis and Gene Set Variation Analysis were utilized to examine the discrepancy in biological function. We used Gene Ontology, the Kyoto Encyclopedia of Genes and Genomes, and the GeneMANIA database to investigate the function of the signature genes. An analysis using the receiver operating characteristic (ROC) was conducted to validate the diagnostic value of hub genes. Additionally, immune infiltration-related analyses were also performed. In conclusion, we examined the association between the glomerular filtration rate, serum creatinine, and hub genes. Hub genes were validated by immunohistochemistry using db/db mice kidneys.
WGCNA revealed that the targets in the turquoise unit (1674 genes) exhibited the highest positive correlation with ICD. Furthermore, 4222 statistically significant DEGs were identified when comparing the DN and healthy control groups. Significantly, the KEGG pathway enrichment analysis indicated a connection between ICD and the nuclear factor-kappa B signaling pathway and the synthesis of cytokines (tumor necrosis factor superfamily). ROC analysis revealed that 16 hub genes exhibited strong discriminatory potential as biomarkers for DN. Therefore, immunohistochemical validation, with the potential involvement of chemokines (CCL11, CCR2, CCR7, CX3CR1, CXCL10, CXCL12, and CXCR5) and immune cells (CD3G, CD5, and CD247) may be crucial for the diagnosis and therapy of DN.
DKK3, NR4A1, NR4A2, VEGFA, and DUSP1 may be associated with the development of DN. The pathogenesis of DN may specifically involve chemokines (CCL11, CCR2, CCR7, CX3CR1, CXCL10, CXCL12, and CXCR5) and immune cells (CD3G, CD5, and CD247), with LCP2 playing a significant role.
免疫原性细胞死亡（ICD）是一种由化疗引发的独特细胞死亡方式。然而，关于 ICD 在糖尿病肾病（DN）中的潜在治疗作用及其潜在机制的研究仍有限。
对与 DN 相关的人类肾活检数据进行 WGCNA 分析，分析与 ICD 相关的基因集。使用基因集富集分析和基因集变异分析来检测生物学功能的差异。我们使用基因本体论、京都基因与基因组百科全书和基因 MANIA 数据库来研究特征基因的功能。使用接收器操作特征（ROC）分析来验证关键基因的诊断价值。此外，还进行了免疫浸润相关分析。总之，我们研究了肾小球滤过率、血清肌酐与关键基因之间的关系。使用 db/db 小鼠肾脏的免疫组织化学验证了关键基因。
WGCNA 显示，绿松石单元（1674 个基因）中的靶标与 ICD 呈最强的正相关。此外，DN 组与健康对照组比较，发现了 4222 个具有统计学意义的差异表达基因。更重要的是，KEGG 通路富集分析表明 ICD 与核因子-κB 信号通路和细胞因子（肿瘤坏死因子超家族）的合成有关。ROC 分析表明，16 个关键基因作为 DN 的生物标志物具有较强的鉴别潜力。因此，免疫组织化学验证，可能涉及趋化因子（CCL11、CCR2、CCR7、CX3CR1、CXCL10、CXCL12 和 CXCR5）和免疫细胞（CD3G、CD5 和 CD247），对 DN 的诊断和治疗可能至关重要。
DKK3、NR4A1、NR4A2、VEGFA 和 DUSP1 可能与 DN 的发生发展有关。DN 的发病机制可能具体涉及趋化因子（CCL11、CCR2、CCR7、CX3CR1、CXCL10、CXCL12 和 CXCR5）和免疫细胞（CD3G、CD5 和 CD247），LCP2 起关键作用。
