The regulatory roles of T helper cells in distinct extracellular matrix characterization in breast cancer.

Tumors are characterized by extracellular matrix (ECM) remodeling and stiffening. The ECM has been recognized as an important determinant of breast cancer progression and prognosis. Recent studies have revealed a strong link between ECM remodeling and immune cell infiltration in a variety of tumor types. However, the landscape and specific regulatory mechanisms between ECM and immune microenvironment in breast cancer have not been fully understood. Using genomic data and clinical information of breast cancer patients obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, we conducted an extensive multi-omics analysis to explore the heterogeneity and prognostic significance of the ECM microenvironment. Masson and Sirius red staining were applied to quantify the contents of collagen in the ECM microenvironment. Tissue immunofluorescence (IF) staining was applied to identify T helper (Th) cells. We classified breast cancer patients into two ECM-clusters and three gene-clusters by consensus clustering. Significant heterogeneity in prognosis and immune cell infiltration have been found in these distinct clusters. Specifically, in the ECM-cluster with better prognosis, the expression levels of Th2 and regulatory T (Treg) cells were reduced, while the Th1, Th17 and T follicular helper (Tfh) cells-associated activities were significantly enhanced. The correlations between ECM characteristics and Th cells infiltration were then validated by clinical tissue samples from our hospital. The ECM-associated prognostic model was then constructed by 10 core prognostic genes and stratified breast cancer patients into two risk groups. Kaplan-Meier analysis showed that the overall survival (OS) of breast cancer patients in the high-risk group was significantly worse than that of the low-risk group. The risk scores for breast cancer patients obtained from our prognostic model were further confirmed to be associated with immune cell infiltration, tumor mutation burden (TMB) and stem cell indexes. Finally, the half-maximal inhibitory concentration (IC50) values of antitumor agents for patients in different risk groups were calculated to provide references for therapy targeting distinct ECM characteristics. Our findings identify a novel strategy for breast cancer subtyping based on the ECM characterization and reveal the regulatory roles of Th cells in ECM remodeling. Targeting ECM remodeling and Th cells hold potential to be a therapeutic alternative for breast cancer in the future.

Tian Q ，Gao H ，Ma Y ，Zhu L ，Zhou Y ，Shen Y ，Wang B ... -  《Frontiers in Immunology》

Immunity and Extracellular Matrix Characteristics of Breast Cancer Subtypes Based on Identification by T Helper Cells Profiling.

The therapeutic effect of immune checkpoint inhibitors on tumors is not only related to CD8+ effector T cells but also sufficiently related to CD4+ helper T (TH) cells. The immune characteristics of breast cancer, including gene characteristics and tumor-infiltrating lymphocytes, have become significant biomarkers for predicting prognosis and immunotherapy response in recent years. Breast cancer samples from The Cancer Genome Atlas (TCGA) database and triple-negative breast cancer (TNBC) samples from GSE31519 in the Gene Expression Omnibus (GEO) database were extracted and clustered based on gene sets representing TH cell signatures. CIBERSORT simulations of immune cell components in the tumor microenvironment and gene set enrichment analyses (GSEAs) were performed in the different clusters to verify the classification of the subtypes. The acquisition of differentially expressed genes (DEGs) in the different clusters was further used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. The clinical information from different clusters was used for survival analysis. Finally, the surgical tissues of TNBC samples were stained by immunofluorescence staining and Masson's trichrome staining to explore the correlation of TH cell subtypes with extracellular matrix (ECM). The breast cancer samples from the datasets in TCGA database and GEO database were classified into TH-activated and TH-silenced clusters, which was verified by the immune cell components and enriched immune-related pathways. The DEGs of TH-activated and TH-silenced clusters were obtained. In addition to TH cells and other immune-related pathways, ECM-related pathways were found to be enriched by DEGs. Furthermore, the survival data of TCGA samples and GSE31519 samples showed that the 10-year overall survival (p-value < 0.001) and 10-year event-free survival (p-value = 0.162) of the TH-activated cluster were better, respectively. Fluorescent labeling of TH cell subtypes and staining of the collagen area of surgical specimens further illustrated the relationship between TH cell subtypes and ECM in breast cancer, among which high TH1 infiltration was related to low collagen content (p-value < 0.001), while high TH2 and Treg infiltration contained more abundant collagen (p-value < 0.05) in TNBC. With regard to the relationship of TH cell subtypes, TH2 was positively correlated with Treg (p-value < 0.05), while TH1 was negatively correlated with both of them. The immune and ECM characteristics of breast cancer subtypes based on TH cell characteristics were revealed, and the relationship between different TH cell subsets and ECM and prognosis was explored in this study. The crosstalk between ECM and TH cell subtypes formed a balanced TME influencing the prognosis and treatment response in breast cancer, which suggests that the correlation between TH cells and ECM needs to be further emphasized in future breast cancer studies.

Zhou Y ，Tian Q ，Gao H ，Zhu L ，Zhang Y ，Zhang C ，Yang J ，Wang B ... -  《Frontiers in Immunology》

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

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.

Gao H ，Tian Q ，Zhou Y ，Zhu L ，Lu Y ，Ma Y ，Feng J ，Jiang Y ，Wang B ... -  《Frontiers in Immunology》

Follistatin-Like 3 Correlates With Lymph Node Metastasis and Serves as a Biomarker of Extracellular Matrix Remodeling in Colorectal Cancer.

As a heterogeneous disease, colorectal cancer (CRC) presents a great challenge to individualized treatment due to its lymph node metastasis (LNM). Existing studies have shown that immune and stromal components in extracellular matrix (ECM) act as important part in tumorigenicity and progression, while their roles in LNM have not been fully elucidated. Here, crucial ECM-related genes responsible for LNM in CRC were selected by multi-omics analysis. Firstly, we characterized the immune infiltration landscape of CRC samples from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases by using ssGSEA algorithm. The CRC patients were divided into several immune subgroups by hierarchical clustering analyses. Then, differential genes were identified among immune subgroups and CRC vs. normal tissues in TCGA and GEO GSE39582 cohorts, respectively. Next, weighted correlation network analysis (WGCNA) was employed to construct a co-expression network to find LNM-related modules and hub genes. Subsequently, we evaluated the clinical value of hub gene in prognostic prediction and chemotherapy/immunotherapy. Besides, the protein level of key gene was verified in an external cohort from our center. Finally, we explored the underlying mechanism of FSTL3-mediated LNM by Gene function annotation and correlation analysis. Two immune subgroups, namely Immunity_High and Immunity_Low, were defined among the two CRC cohorts using ssGSEA algorithm, respectively. Based on the two immune subgroups, 2,635 overlapping differentially expressed genes were obtained from two cohorts, which were sequentially subjected to WGCNA and univariate Cox regression analysis. Ultimately, FSTL3 was selected as the key gene. Here, we first confirmed that overexpression of FSTL3 correlated with LNM and worse prognosis in CRC and was verified at the protein level in the external validation cohort. Moreover, FSTL3 expression showed strongly positive correlation with immune and stromal components in ECM. We furthermore found that FSTL3 may accelerate LNM through the formation of inhibitory immune microenvironment via promoting macrophage and fibroblast polarization and T cell exhaustion. Interestingly, high FSTL3 expression is linked to chemoresistance, but immunotherapy-sensitive. FSTL3 is identified as a biomarker for ECM remodeling and worse clinical outcomes for the first time in CRC and is also a potential immunotherapeutic target to block LNM for CRC.

Yang C ，Cao F ，Huang S ，Zheng Y ... -  《-》

Identification of a pyroptosis-related prognostic signature in breast cancer.

The relationship between pyroptosis and cancer is complex. It is controversial that whether pyroptosis represses or promotes tumor development. This study aimed to explore prognostic molecular characteristics to predict the prognosis of breast cancer (BRCA) based on a comprehensive analysis of pyroptosis-related gene expression data. RNA-sequcing data of BRCA were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Ominibus (GEO) datasets. First, pyroptosis-related differentially expressed genes (DEGs) between normal and tumor tissues were identified from the TCGA database. Based on the DEGs, 1053 BRCA patients were divided into two clusters. Second, DEGs between the two clusters were used to construct a signature by a least absolute shrinkage and selection operator (LASSO) Cox regression model, and the GEO cohort was used to validate the signature. Various statistical methods were applied to assess this gene signature. Finally, Single-sample gene set enrichment analysis (ssGSEA) was employed to compare the enrichment scores of 16 types of immune cells and 13 immune-related pathways between the low- and high-risk groups. We calculated the tumor mutational burden (TMB) of TCGA cohort and evaluated the correlations between the TMB and riskscores of the TCGA cohort. We also compared the TMB between the low- and high-risk groups. A total of 39 pyroptosis-related DEGs were identified from the TCGA-breast cancer dataset. A prognostic signature comprising 16 genes in the two clusters of DEGs was developed to divide patients into high-risk and low-risk groups, and its prognostic performance was excellent in two independent patient cohorts. The high-risk group generally had lower levels of immune cell infiltration and lower activity of immune pathway activity than did the low-risk group, and different risk groups revealed different proportions of immune subtypes. The TMB is higher in high-risk group compared with low-risk group. OS of low-TMB group is better than that of high-TMB group. A 16-gene signature comprising pyroptosis-related genes was constructed to assess the prognosis of breast cancer patients and its prognostic performance was excellent in two independent patient cohorts. The signature was found closely associated with the tumor immune microenvironment and the potential correlation could provide some clues for further studies. The signature was also correlated with TMB and the mechanisms are still warranted.

Chen H ，Luo H ，Wang J ，Li J ，Jiang Y ... -  《BMC CANCER》