Studies on the Role of S100A9-RAGE/TLR4 Signaling Axis in Regulating Brain Metastasis and Endothelial Adhesion of Non-Small Cell Lung Cancer
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摘要:
目的 探究非小细胞肺癌（non-small cell lung cancer，NSCLC）来源S100A9调控侵袭转移及激活转移土壤脑微血管内皮的机制。 方法 使用R语言提取TCGA数据库RNAseq数据，采用配对样本T检验，分析S100A9在NSCLC组织和正常肺组织中的表达，用ggplot2包进行可视化；用survival包进行比例风险假设检验和拟合生存回归，比较S100A9高/低表达组之间的预后情况，用survminer包和ggplot2包进行可视化。RT-qPCR、Western Blot检测S100A9在NSCLC细胞系（A549、NCI-H1299）和正常肺上皮细胞（BEAS-2B）中的表达差异，利用A549细胞与人脑微血管内皮细胞（HCMEC/D3）共培养构建血瘤屏障BTB模型，并构建siS100A9敲低的A549细胞株，划痕愈合、Transwell实验检测不同处理组A549细胞的迁移、侵袭能力变化情况，CCK-8、流式细胞术检测不同浓度S100A9处理HCMEC/D3细胞后的增殖活性和对细胞周期的影响，RT-qPCR、Western Blot检测不同浓度S100A9处理hCMEC/D3细胞后对土壤传感器受体RAGE、TLR4和肿瘤跨内皮迁移相关黏附分子ICAM-1、VCAM-1、ALCAM的表达变化，并通过CCK-8、RT-qPCR、Western Blot检测FPS-ZM1、TAK242预阻滞RAGE、TLR4通路后，对不同浓度S100A9刺激下hCMEC/D3细胞的增殖活性和黏附分子表达的回复情况。 结果 TCGA数据库RNAseq数据挖掘与分析显示，肺癌组织样本中S100A9表达显著高于正常肺组织样本（P = 0.03）Kaplan-Meier生存曲线图显示，S100A9高表达组的生存概率低于S100A9低表达组，提示S100A9高表达与患者更差的总体生存期显著相关[HR = 1.46 （1.10～1.95），P = 0.01]。在细胞实验中，S100A9在NSCLC细胞系中高表达（P < 0.05），敲低S100A9能抑制A549细胞的迁移和侵袭（P < 0.05），敲低组在6、12、24、36、48 h的平均迁移抑制率为80.61%、75.70%、73.78%、69.54%、56.96%，平均侵袭抑制率为57.38%（48 h），同时S100A9靶向正调控BTB模型中hCMEC/D3细胞的增殖活性和细胞周期（P < 0.05）。在机制上，S100A9通过土壤传感器受体RAGE、TLR4促进A549与hCMEC/D3交互通讯，上调hCMEC/D3细胞的ICAM-1、VCAM-1、ALCAM表达（P < 0.05），回复实验证实S100A9-RAGE/TLR4调控轴能够影响肺癌脑转移的内皮黏附过程（P < 0.05）。 结论 S100A9-RAGE/TLR4与肺癌脑转移进展有关，敲低S100A9能抑制肺癌细胞的侵袭转移，阻滞下游土壤传感器受体RAGE、TLR4能减弱脑微血管内皮的增殖生长，并抑制肺癌细胞与脑微血管内皮之间形成预转移黏附微环境，对开发肺癌脑转移的早期诊断和治疗靶点具有潜在意义。 -
关键词:
- S100A9 /
- 非小细胞肺癌 /
- 脑转移 /
- 脑微血管内皮细胞BMECs
Abstract:Objective To explore the mechanism of S100A9 derived from non-small cell lung cancer （NSCLC） in regulating invasion, metastasis and activating the brain microvascular endothelium of the metastatic niche. Methods R language was used to extract RNAseq data from the TCGA database and a paired-sample T-test was employed to analyze the expression of S100A9 in NSCLC tissues and normal lung tissues. Visualization was conducted using the ggplot2 package; the proportional hazards assumption test and survival regression were performed using the survival package to compare the prognosis between the high/low expression groups of S100A9, and visualization was carried out using the survminer package and ggplot2 package. RT-qPCR and Western Blot were used to detect the expression differences of S100A9 in NSCLC cell lines （A549, NCI-H1299） and normal lung epithelial cells （BEAS-2B）. An in vitro co-culture of A549 cells and human brain microvascular endothelial cells （HCMEC/D3） was established to construct a blood-tumor barrier （BTB） model. Additionally, siS100A9 knockdown A549 cell strains were constructed. Scratch healing and Transwell assays were performed to assess the changes in the migration and invasion abilities of A549 cells in different treatment groups. CCK-8 and flow cytometry were used to examine the proliferative activity and cell cycle effects of HCMEC/D3 cells treated with varying concentrations of S100A9. RT-qPCR and Western Blot were employed to investigate the expression changes of receptors for advanced glycation endproducts （RAGE）, Toll-like receptor 4 （TLR4）, and tumor transendothelial migration-related adhesion molecules （ICAM-1, VCAM-1, ALCAM） in hCMEC/D3 cells treated with different concentrations of S100A9. Furthermore, CCK-8, RT-qPCR, and Western Blot were utilized to assess the recovery of proliferative activity and adhesion molecule expression in hCMEC/D3 cells stimulated with different concentrations of S100A9 after pretreatment with FPS-ZM1 and TAK242 to block RAGE and TLR4 pathways, respectively. Results The RNAseq data mining and analysis from the TCGA database revealed that the expression of S100A9 in lung cancer tissue samples was significantly higher than that in normal lung tissue samples （P = 0.03）. The Kaplan-Meier survival curve graph showed that the survival probability of the S100A9 high-expression group was lower than that of the S100A9 low-expression group, suggesting that the high expression of S100A9 was significantly associated with a poorer overall survival period for patients （HR = 1.46 （1.10 - 1.95）, P = 0.01）. In the cell experiments, S100A9 was highly expressed in NSCLC （P < 0.05）. Knockdown of S100A9 inhibited the migration and invasion of A549 cells （P < 0.05）. The average migration inhibition rate of the knockdown group at 6, 12, 24, 36, and 48 hours was 80.61%, 75.70%, 73.78%, 69.54%, and 56.96% respectively, and the average invasion inhibition rate was 57.38% （at 48 hours）. Meanwhile, the proliferative activity and cell cycle of hCMEC/D3 cells in the BTB model were regulated positively （P < 0.05）. Mechanistically, S100A9 promoted the crosstalk between A549 and hCMEC/D3 cells through RAGE and TLR4, upregulating the expression of ICAM-1, VCAM-1, and ALCAM in hCMEC/D3 cells （P < 0.05）. Recovery experiments confirmed that the S100A9-RAGE/TLR4 regulatory axis could affect the endothelial adhesion process during lung cancer brain metastasis （P < 0.05）. Conclusion The S100A9-RAGE/TLR4 axis is associated with the progression of lung cancer brain metastasis. Knockdown of S100A9 can inhibit the invasion and metastasis of lung cancer cells. Blocking downstream RAGE and TLR4 receptors can attenuate the proliferative growth of brain microvascular endothelium and inhibit the formation of a pre-metastatic adhesive microenvironment between lung cancer cells and brain microvascular endothelium. This has potential implications for exploring early diagnosis and therapeutic targets for lung cancer brain metastasis. -
图 1 TCGA公共数据库分析S100A9表达差异及S100A9高/低表达组的预后情况
A：S100A9在正常肺组织（Normal）和肿瘤组织（Tumor）配对样本之间的表达差异图；B：Kaplan-Meier生存曲线图示S100A9高/低表达组之间的预后情况；*P < 0.05。
Figure 1. Analysis of the expression difference of S100A9 and the prognosis of S100A9 high/low expression groups in the TCGA public database
图 2 NSCLC肺癌细胞和正常肺上皮细胞之间S100A9的表达差异
A：RT-qPCR检测肺癌细胞和正常肺上皮细胞的S100A9 mRNA表达；B：S100A9免疫印迹代表图。C：WB检测肺癌细胞和正常肺上皮细胞的S100A9蛋白定量分析图；*P < 0.05，**P < 0.01，***P < 0.001。
Figure 2. The expression difference of S100A9 between NSCLC lung cancer cells and normal lung epithelial cells
图 3 NSCLC肺癌细胞与人脑血管内皮细胞共培养模型中S100A9随时间的表达变化
A：RT-qPCR检测共培养0/4/8/12/24 h组S100A9 mRNA表达；B：S100A9免疫印迹代表图；C：WB检测共培养0/4/8/12/24 h组S100A9蛋白定量分析图；*P < 0.05，**P < 0.01，***P < 0.001，****P <
0.0001 。Figure 3. The expression changes of S100A9 over time in the co-culture model of NSCLC lung cancer cells and human brain vascular endothelial cells
图 4 RT-qPCR、WB验证siRNA-S100A9（si-1、si-2、si-3）的敲低效率
A：RT-qPCR验证siRNA-S100A9的敲低效率；B：S100A9免疫印迹代表图；C：WB验证siRNA-S100A9敲低效率的蛋白定量分析图；*P < 0.05，**P < 0.01，***P < 0.001，****P <
0.0001 。Figure 4. RT-qPCR and WB assays to verify the knockdown efficiency of siRNA-S100A9 （si-1，si-2，si-3）
图 5 RT-qPCR、WB验证si-S100A9#3的敲低效率
A：RT-qPCR验证si-S100A9#3的敲低效率；B：S100A9免疫印迹代表图；C：WB验证si-S100A9#3敲低效率的蛋白定量分析图；***P < 0.001。
Figure 5. RT-qPCR and WB assays to verify the knockdown efficiency of si-S100A9#3
图 6 划痕实验检测敲低S100A9对肺癌细胞A549迁移能力的影响（40×）
A：划痕实验检测S100A9不同处理后的A549细胞迁移能力；B：划痕试验统计图；*P < 0.05，**P < 0.01，***P < 0.001。
Figure 6. Scoring experiment to detect the effect of knockdown of S100A9 on the migration ability of lung cancer cell line A549 （40×）
图 7 Transwell实验检测敲低S100A9对肺癌细胞A549侵袭能力的影响（100×）
A：Transwell实验检测S100A9不同处理后的A549细胞侵袭能力；B：侵袭实验统计图；****P <
0.0001 。Figure 7. Transwell assay to investigate the effect of S100A9 knockdown on the invasion ability of lung cancer cell line A549 （100×）
图 8 人重组S100A9对人脑微血管内皮hCMEC/D3增殖活力的影响
*P < 0.05，**P < 0.01，***P < 0.001，****P <
0.0001 。Figure 8. The effect of human recombinant S100A9 on the proliferation activity of human brain microvascular endothelial cells hCMEC/D3
图 9 人重组S100A9对人脑微血管内皮hCMEC/D3细胞周期的影响
A：人重组S100A9不同处理后的hCMEC/D3细胞周期；B：流式细胞周期分析图；**P < 0.01，***P < 0.001。
Figure 9. The effect of human recombinant S100A9 on the cell cycle of human brain microvascular endothelial cells hCMEC/D3
图 10 CCK-8法检测使用FPS-ZM1和TAK242阻滞处理后，500 nM S100A9对脑微血管内皮hCMEC/D3的促增殖作用是否可逆
*P < 0.05，**P < 0.01，***P < 0.001。
Figure 10. The CCK-8 method was used to detect whether the proliferative effect of 500 nM S100A9 on human brain microvascular endothelial hCMEC/D3 cells，induced by FPS-ZM1 and TAK242 blocking treatments，was reversible
图 11 RT-qPCR、WB检测S100A9-RAGE/TLR4对脑微血管内皮hCMEC/D3细胞间黏附分子（ICAM-1）、血管间黏附分子（VCAM-1）、白细胞活化黏附因子（ALCAM）表达的影响
A：RT-qPCR检测RAGE、TLR4和3种黏附分子的mRNA表达；B：RGAE、TLR4和3种黏附分子的免疫印迹代表图；C：WB检测RGAE、TLR4和3种黏附分子的蛋白定量分析图；*P < 0.05，**P < 0.01，***P < 0.001，****P <
0.0001 。Figure 11. RT-qPCR and WB assays were used to investigate the effects of S100A9-RAGE/TLR4 on the expression of intercellular adhesion molecules （ICAM-1），vascular adhesion molecule （VCAM-1），and leukocyte-activating adhesion factor （ALCAM） in brain microvascular endothelial cells （hCMEC/D3）
表 1 siRNA-S100A9三靶点合成序列
Table 1. siRNA-S100A9 three-target synthetic sequences
名称 序列（5′-3′） si-S100A9（h）-1 S：CCUCCCACGAGAAGAUGCA（dT）（dT）
A：UGCAUCUUCUCGUGGGAGG（dT）（dT）si-S100A9（h）-2 S：GCAACAUAGAGACCAUCAU（dT）（dT）
A：AUGAUGGUCUCUAUGUUGC（dT）（dT）si-S100A9（h）-3 S：GCUGAGCUUCGAGGAGUUCAU
A：AUGAACUCCUCGAAGCUCAGC
下载: 导出CSV
表 2 引物序列
Table 2. Primer sequences
名称 序列（5′-3′） S100A9 F：CTTCCACCAATACTCTGT
R：TCATTCTTATTCTCCTTCTTGRAGE F：CAATGAACAGGAATGGAA
R：AGAGGCAGAATCTACAATTLR4 F：TCAGTGTGCTTGTAGTAT
R：CCTGGCTTGAGTAGATAAICAM-1 F：CAAGAAGATAGCCAACCAATG
R：CAGTACACGGTGAGGAAGVCAM-1 F：GGAGTATATGAATGTGAATCTAA
R：ATGGCAGGTATTATTAAGGAALCAM F：AATAGTCAAGGTGTTCAAG
R：CATCTGGATAACTGTCTTCGAPDH F：AAAGGGTCATCATCTCTG
R：GCTGTTGTCATACTTCTC
下载: 导出CSV
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