3D Collagen Fiber Concentration Regulates Treg Cell Infiltration in Triple Negative Breast Cancer

Frontiers in Immunology

Bo Wang¹  Lizhe Zhu²  Yan Zhou³  Jinteng Feng³  Huan Gao³  Yingying Ma³  Yina Jiang⁴  Yinliang Lu⁵  Qi Tian⁶ 

[1] Center for Translational Medicine, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China;Department of Breast Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China;Department of Medical Oncology, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China;Department of Pathology, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China;Department of Radiation Oncology, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China;Department of Radiology, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China;

关键词: triple negative breast cancer;    tumor microenvironment;    regulatory T cells;    extracellular matrix;    tumor-infiltrating lymphocytes;    prognostic model;   

DOI  :  10.3389/fimmu.2022.904418

来源: DOAJ

【 摘 要 】

BackgroundTriple 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.Materials and MethodsPatients 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.ResultsThe 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.ConclusionOur 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.

【 授权许可】

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