基于 DNA 超分子水凝胶的保护性 NK 细胞储库用于增强三阴性乳腺癌治疗
Protective NK Cell Reservoir Based on DNA Supramolecular Hydrogel for Enhanced Triple-Negative Breast Cancer Therapy.
CELL INTELLIGENCE · 肿瘤细胞治疗研究
肿瘤细胞治疗研究
英文原题:3D Collagen Fiber Concentration Regulates Treg Cell Infiltration in Triple Negative Breast Cancer.
3D Collagen Fiber Concentration Regulates Treg Cell Infiltration in Triple Negative Breast Cancer.
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我们的结果支持 Treg 表达与乳腺癌进展以及 TNBC 亚型预后的关联。此外,增加胶原密度可能促进 Treg 浸润,从而诱导免疫抑制的 TME。
三阴性乳腺癌(TNBC)的特征是预后差,且由于缺乏生物标志物而缺少有效的治疗药物。肿瘤浸润性调节性T细胞(Tregs)的高丰度与恶性疾病的较差预后相关。探索Treg细胞浸润与TNBC之间的关联将为理解TNBC的免疫抑制提供新见解,并可能为开发新型免疫治疗方法铺平道路。
TCGA中的患者根据CIBERSORT分析得到的Treg丰度被分为Treg高(Treg-H)和Treg低(Treg-L)组。评估了Treg表达水平与乳腺癌临床特征及预后之间的关联。接下来,在生存依赖性单因素Cox和LASSO回归分析后建立了Treg相关预后模型,并伴随外部GEO队列验证。然后,在Treg-H和Treg-L组之间进行了GO、KEGG和GSEA分析。应用Masson和天狼星红/固绿染色进行ECM表征。相应地,将Jurkat T细胞包封在3D胶原中以模拟ECM微环境,并根据免疫荧光染色定量CD4、FOXP3和CD25的表达水平。
Tregs的表达水平与乳腺癌患者的临床特征显著相关,Treg细胞高表达提示TNBC预后不良。为进一步评估这一点,我们建立了一个Treg相关预后模型,该模型在TCGA训练队列和GEO验证队列的TNBC患者中均能准确预测结局。随后,我们在Treg-H组和Treg-L组之间识别出ECM相关信号通路,表明ECM在Treg浸润中的作用。由于我们发现伴有远处迁移的TNBC患者中胶原浓度升高,我们将Jurkat T细胞包裹在不同胶原浓度的3D基质中,并观察到胶原浓度升高促进了Treg生物标志物的表达,支持ECM对Treg浸润的调控作用。
Triple negative breast cancer (TNBC) is characterized by poor prognosis and a lack of effective therapeutic agents owing to the absence of biomarkers. A high abundance of tumor-infiltrating regulatory T cells (Tregs) was associated with worse prognosis in malignant disease. Exploring the association between Treg cell infiltration and TNBC will provide new insights for understanding TNBC immunosuppression and may pave the way for developing novel immune-based treatments.
Patients from TCGA were divided into Treg-high (Treg-H) and Treg-low (Treg-L) groups based on the abundance of Tregs according to CIBERSORT analysis. The association between expression level of Tregs and the clinical characteristics as well as prognosis of breast cancer were evaluated. Next, a Treg-related prognostic model was established after survival-dependent univariate Cox and LASSO regression analysis, companied with an external GEO cohort validation. Then, GO, KEGG and GSEA analyses were performed between the Treg-H and Treg-L groups. Masson and Sirius red/Fast Green staining were applied for ECM characterization. Accordingly, Jurkat T cells were encapsulated in 3D collagen to mimic the ECM microenvironment, and the expression levels of CD4, FOXP3 and CD25 were quantified according to immunofluorescence staining.
The expression level of Tregs is significantly associated with the clinical characteristics of breast cancer patients, and a high level of Treg cell expression indicates a poor prognosis in TNBC. To further evaluate this, a Treg-related prognostic model was established that accurately predicted outcomes in both TCGA training and GEO validation cohorts of TNBC patients. Subsequently, ECM-associated signaling pathways were identified between the Treg-H and Treg-L groups, indicating the role of ECM in Treg infiltration. Since we found increasing collagen concentrations in TNBC patients with distant migration, we encapsulated Jurkat T cells within a 3D matrix with different collagen concentrations and observed that increasing collagen concentrations promoted the expression of Treg biomarkers, supporting the regulatory role of ECM in Treg infiltration.
Our results support the association between Treg expression and breast cancer progression as well as prognosis in the TNBC subtype. Moreover, increasing collagen density may promote Treg infiltration, and thus induce an immunosuppressed TME.
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