The emergence of immunotherapy has profoundly changed the treatment model for triple-negative breast cancer (TNBC). But the heterogeneity of this disease resulted in significant differences in immunotherapy efficacy, and only some patients are able to benefit from this therapeutic modality. With the recent explosion in studies on the mechanism of cancer immunotherapy drug resistance, this article will focus on the processes of the immune response; summarize the immune evasion mechanisms in TNBC into three categories: loss of tumor-specific antigen, antigen presentation deficiency, and failure to initiate an immune response; together with the aberrant activation of a series of immune-critical signaling pathways, we will discuss how these activities jointly shape the immunosuppressive landscape within the tumor microenvironment. This review will attempt to elucidate the molecular mechanism of drug resistance in TNBC, identify potential targets that may assist in reversing drug resistance, and lay a foundation for research on identifying biomarkers for predicting immune efficacy and selection of breast cancer populations that may benefit from immunotherapy.

Background: Angiogenesis strongly reflects poor breast cancer outcome and an important contributor to breast cancer (BC) metastasis; therefore, anti-angiogenic intervention is a potential tool for cancer treatment. However, currently used antibodies against vascular endothelial growth factor A (VEGFA) or inhibitors that target the VEGFA receptor are not effective due to weak penetration and low efficiency. Herein, we assessed the anti-BC angiogenic role of muscone, a natural bioactive musk constituent, and explored possible anti-cancer mechanisms of this compound. Methods: CCK-8, EdU, scratch and Transwell assessments were employed to detect the muscone-mediated regulation of breast cancer (BC) and human umbilical vein endothelial cells (HUVECs) proliferation and migration. Tube formation, matrigel plug assay and zebrafish assay were employed for assessment of regulation of tumor angiogenesis by muscone. In vivo xenograft mouse model was constructed to compare microvessel density (MVD), vascular leakage, vascular maturation and function in muscone-treated or untreated mice. RNA sequencing was performed for gene screening, and Western blot verified the effect of the VEGFA-VEGFR2 pathway on BC angiogenic inhibition by muscone. Results: Based on our findings, muscone suppressed BC progression via tumor angiogenic inhibition in cellular and animal models. Functionally, muscone inhibited BC cell proliferation and migration as well as tumor cell-conditioned medium-based endothelial cell proliferation and migration. Muscone exhibited a strong suppressive influence on tumor vasculature in cellular and animal models. It abrogated tumor cell growth in a xenograft BC mouse model and minimized tumor microvessel density and hypoxia, and increased vascular wall cell coverage and perfusion. Regarding the mechanism of action, we found that muscone suppressed phosphorylation of members of the VEGF/PI3K/Akt/MAPK axis, and it worked synergistically with a VEGFR2 inhibitor, an Akt inhibitor, and a MAPK inhibitor to further inhibit tube formation. Conclusion: Overall, our results demonstrate that muscone may proficiently suppress tumor angiogenesis via modulation of the VEGF/PI3K/Akt/MAPK axis, facilitating its candidacy as a natural small molecule drug for BC treatment.

Background: Disulfidptosis is a novel type of programmed cell death. However, the value of disulfidptosis-related genes (DRGs) in the prediction of breast cancer prognosis is unclear. Methods: RNA-seq data of 1231 patients, together with information on patient clinical characteristics and prognosis, were downloaded from TCGA. DRGs were identified between cancerous and non-cancerous tissues. The LASSO algorithm was used to assign half of the samples to the training set. Risk scores were used for construction of a prognostic model for risk stratification and prognosis prediction, and the clinical applicability was examined using a line diagram. The relationships between risk scores, immune cell infiltration, molecular subtypes, and responses to immunotherapy and chemotherapy were examined. Results: We identified and obtained four DRG-related prognostic lncRNAs (AC009097.2, AC133552.5, YTHDF3-AS1, and AC084824.5), which were used for establishing the risk model. Longer survival was associated with low risk. The DRG-associated lncRNAs were found to independently predict patient prognosis. The AUCs under the ROCs for one-, three-, and 5-year survival in the training cohort were 0.720, 0.687, and 0.692, respectively. The model showed that the high-risk patients had reduced overall survival as well as high tumor mutation burdens. Furthermore, high-risk patients showed increased sensitivity to therapeutic drugs, including docetaxel, paclitaxel, and oxaliplatin. Conclusion: The risk score model was effective for predicting both prognosis and sensitivity to therapeutic drugs, suggesting its possible usefulness for the management of patients with breast cancer.

The purpose of this study was to investigate the relationship between coagulation related genes (CRGs) and breast cancer (BC). First, we found that most CRGs are abnormally expressed in BC patients and correlated with their prognosis. Therefore, we explored the expression of CRGs in benign and malignant breast tissues in the Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx), extracted differentially expressed CRGs, and established an artificial neural network (ANN) diagnostic model to distinguish the nature of breast tissues, as well as a risk scoring model for prognostic assessment and risk stratification. The specimen transcriptomic data we provided confirmed the diagnostic performance of the ANN model described above. For the risk score model, we used internal and external validation, using ROC curves and C-index values to test its predictive value in the TCGA and Gene Expression Omnibus (GEO) cohorts, and further established a prognostic nomogram for clinical application. In addition, we evaluated the performance of diagnostic and prognostic models using 3 cross-validations methods. RABIF was further identified as a core gene. We performed a more detailed study of RABIF: RT-qPCR of BC cell lines and immunohistochemical staining (IHC) of breast tissue samples showed that RABIF is highly expressed in BC especially in advanced BC. Our study demonstrates the value of CRGs as diagnostic and prognostic targets and may contribute to clinical decision-making in BC.