Breast Cancer with Brain Metastasis: Molecular Insights and Clinical Management

Magnetic Particle Imaging Reveals that Iron-Labeled Extracellular Vesicles Accumulate in Brains of Mice with Metastases

The incidence of breast cancer remains high worldwide and is associated with a significant risk of metastasis to the brain that can be fatal; this is due, in part, to the inability of therapeutics to cross the blood-brain barrier (BBB). Extracellular vesicles (EVs) have been found to cross the BBB and further have been used to deliver drugs to tumors. EVs from different cell types appear to have different patterns of accumulation and retention as well as the efficiency of bioactive cargo delivery to recipient cells in the body. Engineering EVs as delivery tools to treat brain metastases, therefore, will require an understanding of the timing of EV accumulation and their localization relative to metastatic sites. Magnetic particle imaging (MPI) is a sensitive and quantitative imaging method that directly detects superparamagnetic iron. Here, we demonstrate MPI as a novel tool to characterize EV biodistribution in metastatic disease after labeling EVs with superparamagnetic iron oxide (SPIO) nanoparticles. Iron-labeled EVs (FeEVs) were collected from iron-labeled parental primary 4T1 tumor cells and brain-seeking 4T1BR5 cells, followed by injection into the mice with orthotopic tumors or brain metastases. MPI quantification revealed that FeEVs were retained for longer in orthotopic mammary carcinomas compared to SPIOs. MPI signal due to iron could only be detected in brains of mice bearing brain metastases after injection of FeEVs, but not SPIOs, or FeEVs when mice did not have brain metastases. These findings indicate the potential use of EVs as a therapeutic delivery tool in primary and metastatic tumors.

In vitro study on anti-proliferative and anti-cancer activity of picrosides in triple-negative breast cancer

Picrorhiza kurroa, an "Indian gentian," a known Himalayan medicinal herb with rich source of phytochemicals like picrosides I, II, and other glycosides, has been traditionally used for the treatment of liver and respiratory ailments. Picrosides anti-proliferative, anti-oxidant, anti-inflammatory and other pharmacological properties were evaluated in treating triple-negative breast cancer (TNBC). Picroside I and II were procured from Sigma-Aldrich and were analyzed for anti-cancer activity in triple-negative breast cancer (MDA-MB-231) cells. Cell viability was analyzed using MTT and trypan blue assays. Apoptosis was analyzed through DNA fragmentation and Annexin V/PI flow cytometric analysis. Wound healing and cell survival assays were employed to determine the inhibition of invasion capacity and anti-proliferative activity of picrosides in MDA-MB-231 cells. Measurement of intracellular ROS was studied through mitochondrial membrane potential assessment using DiOC6 staining for anti-oxidant activity of picrosides in MDA-MB-231 cells. Both Picroside I and II have shown decreased cell viability of MDA-MB-231 cells with increasing concentrations. IC50 values of 95.3 µM and 130.8 µM have been obtained for Picroside I and II in MDA-MB-231 cells. Early apoptotic phase have shown an increase of 20% (p < 0.05) with increasing concentrations (0, 50, 75, and 100 µM) of Picroside I and 15% (p < 0.05) increase with Picroside II. Decrease in mitochondrial membrane potential of 2-2.5-fold (p < 0.05) was observed which indicated decreased reactive oxygen species (ROS) generation with increasing concentrations of Picroside I and II. An increasing percentage of 70-80% (p < 0.05) cell population was arrested in G0/G1 phase of cell cycle after Picroside I and II treatment in cancer cells. Our results suggest that Picroside I and II possess significant anti-proliferative and anti-cancer activity which is mediated by inhibition of cell growth, decreased mitochondrial membrane potential, DNA damage, apoptosis, and cell cycle arrest. Therefore, Picroside I and II can be developed as a potential anti-cancer drug of future and further mechanistic studies are underway to identify the mechanism of anti-cancer potential.

Clinico-pathologic factors and survival of patients with breast cancer diagnosed with de novo brain metastasis: a national cancer database analysis

PURPOSE

Patients with Breast Cancer (BC) with Brain Metastasis (BCBM) have poor survival outcomes. We aimed to explore the clinico-pathologic and therapeutic factors predicting the survival in patients with de novo BCBM using the National Cancer Database (NCDB).

PATIENTS AND METHODS

The NCDB was queried for patients with BC between 2010 and 2020. Survival analysis with Kaplan-Meier curves and log rank tests were used to find median overall survival (OS) in months (95% CI) across the different variables. A multivariate cox regression model was computed to identify significant predictors of survival.

RESULTS

Out of n = 2,610,598 patients, n = 9005 (0.34%) had de novo BCBM. A trend of decreasing OS was observed with increasing age, Charlson-Deyo score (CDS), and number of extracranial metastatic sites. The highest median OS was observed in the Triple Positive and the lowest OS in the Triple Negative subgroup. Based on treatment regimen, combination of systemic therapy and local therapy achieved the highest OS. A positive trend in OS was observed in the BC subgroup analysis with targeted therapy demonstrating a survival benefit when added to systemic therapy. The multivariate cox regression model showed that age, race, ethnicity, insurance, median income, facility type, CDS, BC subtype, metastatic location sites, and treatment combinations received were significantly associated with risk of death. Receiving only local treatment for BM without systemic therapy more than doubled the risk of death compared to combining it with systemic therapy.

CONCLUSIONS

This analysis suggests that treatment of systemic disease is the major factor influencing survival in patients with BCBM. Moreover, targeted therapy with anti-HER2 increased survival when added to systemic therapy explaining the highest median OS noted in the Triple Positive subgroup.

Integrated Bioinformatics Analysis to Identify a Novel Four-Gene Prognostic Model of Breast Cancer and Reveal Its Association with Immune Infiltration

Liquid-liquid phase separation (LLPS) impact immune signaling in cancer and related genes have shown prognostic value in breast cancer (BRCA). However, the crosstalk between LLPS and immune infiltration in BRCA remain unclear. Therefore, we aimed to develop a novel prognostic model of BRCA related to LLPS and immune infiltration. BRCA-related, liquid-liquid phase separation (LLPS)-related genes, and differentially expressed genes (DEGs) were identified using public databases. Mutation and drug sensitivity analyses were performed using Gene Set Cancer Analysis database. Univariate cox regression and LASSO Cox regression were used for the construction and verification of prognostic model. Kaplan-Meier analysis was performed to evaluate overall survival (OS). Gene set variation analysis was conducted to analyze key pathways. CIBERSORT was used to assess immune infiltration and its correlation with prognostic genes was determined through Pearson analysis. A total of 6056 BRCA-associated genes, 3775 LLPS-associated genes, and 4049 DEGs, resulting in 314 overlapping genes. Twenty-eight prognostic genes were screened, and some of them were mutational and related to drug sensitivity Subsequently, a prognostic model comprising L1CAM, EVL, FABP7, and CST1 was built. Patients in high-risk group had shorter OS than those in low-risk group. The infiltrating levels of CD8+ T cells, macrophages M0, macrophages M2, dendritic cells activated, and mast cells resting was altered in high-risk group of breast cancer patients compared to low-risk group. L1CAM, EVL, FABP7, and CST1 were related to these infiltrating immune cells. L1CAM, EVL, FABP7, and CST1 were potential diagnostic biomarkers and therapeutic targets for BRCA.