Background: In this study, we aimed to explore the tumour associated immune signature of breast cancer (BC) and conduct integrative analyses with immune infiltrates in BC.Methods: We downloaded the transcriptome profiling and clinical data of BC from The Cancer Genome Atlas (TCGA) database. The list of immune-related signatures was from the Innate database. The limma package was utilized to conduct the normalization, and we screened the differential immune signatures in BC.A univariate Cox regression model and the LASSO method were used to find the hub prognostic immune genes. The TAIG risk model was calculated based on the multivariate Cox regression results, and a receiver operating characteristic (ROC) curve was generated to assess the predictive power of TAIG. Moreover, we also conducted a correlation analysis between TAIG and the clinical characteristics. Additionally, we utilized the METABRIC cohort as the validation data set. The TIMER database is a comprehensive resource for performing systematic analyses of immune infiltrates across various malignancies. We evaluated the associations of immune signatures with several immune cells based on TIMER. Furthermore, we used the CIBERSORT algorithm to determine the fractions of immune cells in each sample and compared the differential distributions of immune infiltrates between two TAIG groups using the Wilcoxon rank-sum test.Results: A total of 1,178 samples were obtained from the TCGA-BRCA database, but only 1,045 breast tumour samples were matched with complete transcriptome expression data. Meanwhile, we collected a total of 1,094 BC patients from the METABRIC cohort. We found a list of 1,399 differential immune signatures associated with survival, and functional analysis revealed that these genes participated in cytokine-cytokine receptor interactions, Th1 and Th2 cell differentiation and the JAK-STAT signalling pathway. The TAIG risk model was established from the multivariate Cox analysis, and we observed that high TAIG levels correlated with poor survival outcomes based on Kaplan-Meier analysis. The Kruskal-Wallis test suggested that high TAIG levels correlated with high AJCC-TNM stages and advanced pathological stages (P<0.01). We validated the well robustness of TAIG in METABRIC cohort and 5-year AUC reached up to 0.829. Moreover, we further uncovered the associations of hub immune signatures with immune cells and calculated the immune cell fractions in specific tumour samples based on gene signature expression. Last, we used the Wilcoxon ranksum test to compare the differential immune density in the two groups and found that several immune cells had a significantly lower infiltrating density in the high TAIG groups, including CD8 + T cells (P=0.031), memory resting CD4 + T cells (P=0.026), M0 macrophages (P=0.023), and M2 macrophages (P=0.048). Conclusions:In summary, we explored the immune signature of BC and constructed a TAIG risk model to predict prognosis. Moreover, we integrated the identified immune signature with tumour-infiltrating immune cell...

Myeloid‐derived suppressor cells (MDSCs) are responsible for antitumor immunodeficiency in tumor‐bearing hosts. Primarily, MDSCs are classified into 2 groups: monocytic (M)‐MDSCs and polymorphonuclear (PMN)‐MDSCs. In most cancers, PMN‐MDSCs (CD11b+Ly6ClowLy6G+ cells) represent the most abundant MDSC subpopulation. However, the functional and phenotypic heterogeneities of PMN‐MDSC remain elusive, which delays clinical therapeutic targeting decisions. In the 4T1 murine tumor model, CD11b+Ly6Glow PMN‐MDSCs were sensitive to surgical and pharmacological interventions. By comprehensively analyzing 64 myeloid cell‐related surface molecule expression profiles, cell density, nuclear morphology, and immunosuppressive activity, the PMN‐MDSC population was further classified as CD11b+Ly6GlowCD205+ and CD11b+Ly6GhighTLR2+ subpopulations. The dichotomy of PMN‐MDSCs based on CD205 and TLR2 is observed in 4T07 murine tumor models (but not in EMT6). Furthermore, CD11b+Ly6GlowCD205+ cells massively accumulated at the spleen and liver of tumor‐bearing mice, and their abundance correlated with in situ tumor burdens (with or without intervention). Moreover, we demonstrated that CD11b+Ly6GlowCD205+ cells were sensitive to glucose deficiency and 2‐deoxy‐d‐glucose (2DG) treatment. Glucose transporter 3 (GLUT3) knockdown by siRNA significantly triggered apoptosis and reduced glucose uptake in CD11b+Ly6GlowCD205+ cells, demonstrating the dependence of CD205+ PMN‐MDSCs survival on both glucose uptake and GLUT3 overexpression. As GLUT3 has been recognized as a target for the rescue of host antitumor immunity, our results further directed the PMN‐MDSC subsets into the CD205+GLUT3+ subpopulation as future targeting therapy.

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This study aims to isolate the potential antiproliferative and cytotoxic compounds from ginkgo biloba sarcotestas and investigates the underlying mechanism in human MDA-MB-231 and mouse 4T-1 triplenegative breast cancer cells. Our results showed that 2-Hydroxy-6-tridecylbenzoic acid was isolated by cytotoxicity-guided fractionation where different fractions were assessed using MTT assay against MDA-MB-231 and 4T-1 cells. Colony formation assay showed that 2-Hydroxy-6-tridecylbenzoic acid significantly inhibited cell proliferation. The inhibition was associated with the enhancement of cytochrome P450 (CYP) 1B1 expression in a dose-and time-dependent manner and no significant change of CYP1A1 expression by qPCR and Western blot assays in MDA-MB-231 and 4T-1 cells. The molecular mechanism was further demonstrated by the activation of aryl hydrocarbon receptor (AhR) pathway with the upregulation of AhR, AhR nuclear translocator (ARNT) and AhR-dependent xenobiotic response elements (XRE) activity. These findings may have implications for development of anticancer agents containing 2-Hydroxy-6-tridecylbenzoic acid as functional additives.

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