Introduction We have previously reported that Toll-like receptor 3 (TLR3) acts as a suppressor gene for breast cancer initiation and progression. In this study, we evaluated the role of TLR3 in breast cancer using our original Fudan University Shanghai Cancer Center (FUSCC) datasets and breast cancer tissue microarrays. Methods Using FUSCC multiomics datasets on triple- negative breast cancer (TNBC), we compared the mRNA expression of TLR3 in TNBC tissue and the adjacent normal tissue. A Kaplan–Meier plotter was performed to investigate the expression of TLR3 on prognosis in the FUSCC TNBC cohort. We performed immunohistochemical staining to analyze TLR3 protein expression in the TNBC tissue microarrays. Furthermore, bioinformatics analysis was performed using the Cancer Genome Atlas (TCGA) data to verify the results of our FUSCC study. The relationship between TLR3 and clinicopathological features was analyzed with logistic regression and the Wilcoxon signed-rank test. The association between clinical characteristics and overall survival in TCGA patients was assessed using the Kaplan–Meier method and Cox regression analysis. Gene set enrichment analysis (GSEA) was performed to identify signaling pathways that are differentially activated in breast cancer. Results The mRNA expression of TLR3 was lower in TNBC tissue than in the adjacent normal tissue in the FUSCC datasets. The TLR3 had high expression in immunomodulatory (IM) and mesenchymal-like (MES) subtypes and low expression in luminal androgen receptor (LAR) and basal-like immune-suppressed (BLIS) subtypes. High expression of TLR3 in TNBC predicted better prognosis in the FUSCC TNBC cohort. Immunohistochemical staining of the tissue microarrays showed that TLR3 had lower expression in breast cancer tissues than in the adject normal tissues. Furthermore, the TLR3 expression was positively associated with B cell, CD4 + T cells, CD8 + T cells, neutrophils, macrophages, and myeloid dendritic cells. Bioinformatic analysis using high-throughput RNA-sequencing data from the TCGA demonstrated that the reduced expression of TLR3 in breast cancer was associated with advanced clinicopathological characteristics, survival time, and poor prognosis. Conclusions TLR3 has low expression in TNBC tissue. High expression of TLR3 in triple-negative breast cancer predicts better prognosis. TLR3 expression may be a potential prognostic molecular marker of poor survival in breast cancer.
Background Tumour tissue contains not only tumour cells but also some stromal cells and immune cells. This is one composition of the immune microenvironment of the tumour and causes a significant effect on the prognostic factors and recurrence of malignant tumor. Methods In this research, single-cell RNA data from triple-negative breast cancers (TNBCs) were comprehensively analyzed and 1,527 marker genes expressed in immune cells were identified. Subsequently, RNA sequencing and clinical data from 360 patients in the Triple Negative Breast Cancer database at the Fudan University Shanghai Cancer Center (FUSCC) were divided into two groups in a 1:1 ratio, the training group and the validation group. An eight-gene Immune Cell-Associated Predictive Gene (ICAPG) model for predicting breast cancer (BC) recurrence was developed using mRNA data from the training group combined with immune cell marker genes. Based on this model, subjects were divided into two different risk level groups. The predictive power of the model was fully validated using the validation group and The Cancer Genome Atlas (TCGA) database. The localization and expression of these eight genes were then confirmed in a single-cell database. ssGSEA and CIBERSORT algorithms were used to characterize the differences in immune cell infiltration between the two different risk groups. Results The eight-gene ICAPG model was proven to be effective in the validation group. The low-risk group patients presented higher criterion of infiltration of CD8 + T cells and higher levels of tumour-infiltrating lymphocytes (TILs). In addition, the relationship between predictive models and homologous recombination deficiency (HRD) was explored and it was revealed that subjects from the high-risk group tended to have higher HRD values. Conclusions This research established a new predictive model on the basis of immune cell marker genes that might effectively predict relapse in TNBC patients.
Introduction: Normalization cancer immunotherapy is a new strategy to treat breast cancer. Sialic acid binding Ig-like lectin 15 (Siglec-15) is a new potential target for normalization cancer immunotherapy. In this study, we evaluated the role of Siglec-15 in breast cancer and investigated the influence of Siglec-15 on the microenvironment of infiltrating immune cells in cancer. Methods We performed immunohistochemical staining to analyse Siglec-15 expression in primary invasive breast cancer tissue microarrays. The tissue specimens were from 90 patients. Furthermore, the relationship between Siglec-15 and clinicopathological features was analysed with logistic regression and the Wilcoxon signed-rank test. The association between clinical characteristics and overall survival in The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) patients was assessed. Results Immunohistochemical staining of tissue microarrays showed that Siglec-15 had higher expression in breast cancer tissues than in adjacent normal tissues. Breast cancer tissues had higher Siglec-15 expression than normal tissues did. Kaplan–Meier survival analysis suggested that triple-negative breast cancer with high Siglec-15 expression had poorer survival than those with lower Siglec-15 expression (p = 0.042). Furthermore, the high Siglec-15 expression group had low activated dendritic cells, follicular helper T cells, and M1 macrophages. Conclusions Siglec-15 had a high expression in breast cancer tissues. High Siglec-15 expression is associated with low activated dendritic cell, follicular helper T cell, and M1 macrophage proportions in breast cancer tissue and predicts poor prognosis in triple-negative breast cancer. Siglec-15 expression may be a potential prognostic molecular marker of poor survival in breast cancer.
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