As a multifunctional extracellular protein, connective tissue growth factor (CTGF/CCN2) is significantly associated with the progression and prognosis of triple-negative breast cancer (TNBC). However, current blockade therapies targeting CTGF's multiple domains are limited, creating substantial challenges in treatment. Lysosome-targeting chimeras (LYTACs) have emerged as a promising approach for achieving complete protein degradation and inhibiting CTGF's various bioactivities. In this study, a self-assembling LYTAC nanoplatform, NanoCLY, designed to tumor microenvironment (TME)-responsively degrade CTGF is presented. The complete degradation of CTGF downregulates the TGF-β signaling pathway and disrupts the CTGF-IL-6 cell crosstalk within the TME, which further inhibits the activation of inflammatory cancer-associated fibroblasts (CAFs) and alleviates the inflammatory TME. Notably, the anti-TNBC effect of LYTAC-based CTGF degradation therapy surpasses that of antibody-based blockade therapy in both in vitro and in vivo models. The findings provide a proof of concept for CTGF degradation in TNBC and introduce the first CTGF-LYTAC nanoplatform aimed at TME-directed therapy.

Elderly breast cancer patients and survivors are at high risk of bone loss but experience obstacles to harness the known benefits of exercise due to aging, cancer, and cancer treatment. Previously, we and others showed that moderate mechanical loading suppressed breast cancer-induced osteolysis in young adult mice. To overcome the mechano-transduction deficits in aged skeletons, we recently tested a dual therapy combining mechanical and Yoda1 activation of mechanosensitive Piezo1 channels. We found that the dual therapy was more effective in mitigating bone loss due to aging and doxorubicin in mature mice than the individual interventions. In the present study, we further tested the hypothesis that dual therapy combining moderate tibial loading and Yoda1 protects aged skeleton from breast cancer-induced osteolysis better than individual treatments. Aged female C57BL/6 J mice (~74-week-old) receiving Py8119 breast cancer cells in both tibiae were assigned to the four experimental groups (n = 5-8 per group) to examine the effects of 4-week Yoda1 (dose 5 mg/kg, 5 times/week) and moderate tibial loading (4.5 N peak load, 4 Hz, 300 cycles per day, 5 days/week), individually or combined on bone structural integrity. At the end of 4 weeks' experiments, the dual therapy group had the lowest incidence of osteolytic perforation (56 %) compared to the non-treated group (80 %), loading only group (70 %), and Yoda1 only group (100 %). The relative drop of cortical polar moment of inertia (Ct.pMOI), calculated as [(Week 4- Week 0)/Week 0, %], were analyzed at the proximal end, mid-diaphysis, and tibial-fibular junction of the tibia. The average values over the three locations were - 12.7 %, -3.2 %, -24.0 %, -4.2 % for the non-treated, loading only, Yoda1 only, and dual therapy groups, respectively. Furthermore, the % of samples with decreased Ct.pMOI (indication of structural deterioration) was suppressed in the dual therapy group (33 %), compared with nontreated (100 %), loading only (80 %), and Yoda1 only (100 %) groups. Each treatment differentially affected the osteoclast activity, tumor proliferation, and apoptosis of osteocytes, marrow cells and tumor cells, revealing the complex interactions of bone, tumor, and mechanical stimulations. In summary, the dual therapy resulted in skeletal benefits comparable to or slightly better than loading only treatment. However, the exacerbated bone loss and cortical perforation associated with Yoda1 call for further investigation on safe and effective treatments of skeletal damages caused by metastatic breast cancers.

Breast cancer remains one of the leading causes of mortality worldwide. While advancements in chemotherapy, immunotherapy, radiotherapy, and targeted therapies have significantly improved breast cancer treatment, many patients are diagnosed at advanced stages, where tumor cells exhibit aggressive behavior and therapy resistance. Understanding the mechanisms driving breast cancer progression is therefore critical. Metastasis is a major factor that drastically reduces patient prognosis and survival, accounting for most breast cancer-related deaths. ZEB proteins have emerged as key regulators of cancer metastasis. Beyond their role in metastasis, ZEB proteins also influence drug resistance. This review focuses on the role of ZEB1 and ZEB2 in regulating breast cancer metastasis. These proteins interact with components of the tumor microenvironment (TME) to drive cancer progression and metastasis. Additionally, ZEB proteins regulate angiogenesis through interactions with VEGF. Targeting ZEB proteins offers potential therapeutic benefits, particularly for aggressive breast cancer subtypes such as triple-negative breast cancer (TNBC), which often show poor therapeutic response. ZEB proteins also influence the sensitivity of breast cancer cells to chemotherapy, making them promising targets for enhancing treatment efficacy. Given their upregulation in breast cancer, ZEB proteins can serve as valuable diagnostic and prognostic markers.

There is a need for advanced developments to battle aggressive breast cancer variations and to address treatment resistance. In cancer therapy, ZnO nanoparticles (NPs) possess the ability to selectively and effectively induce apoptosis in cancer cells. There is an urgent necessity to create novel anti-cancer therapies, and recent studies indicate that ZnO nanoparticles have significant promise. The purpose of our study based on developed a simple, green synthesis method for ZnO-NPs nanoparticles using Hammada scoparia (Pomel) Iljin extract. Characterization through XRD, SEM, and FTIR confirmed the successful synthesis and structural properties of the NPs, revealing an average crystallite size of 17.786 nm and a particle size of 36.12 ± 4.52 nm. EDX analysis detected significant amounts of zinc and oxygen, while FTIR spectra identified various functional groups. Antioxidant assays (ABTS, DPPH, FRAP) showed that ZnO-NPs exhibit notable free radical scavenging activities, albeit less effective than ascorbic acid. Additionally, cyclic voltammetry and electronic spectroscopy studies indicated strong electrostatic interactions between ZnO-NPs and biomolecules such as DNA and BSA, suggesting potential applications in drug delivery. Cytotoxicity tests on MCF-7 breast cancer cells demonstrated significant dose-dependent inhibition of cell viability, emphasizing the potential of ZnO-NPs as effective agents in cancer therapy. Overall, the findings underscore the promising biomedical applications of ZnO-NPs, particularly in antioxidant and anticancer therapies.

Bone metastasis from breast cancer significantly elevates patient morbidity and mortality, making early detection crucial for improving outcomes. This study utilizes radiomics to analyze changes in the thoracic vertebral bone marrow microenvironment from chest computerized tomography (CT) images prior to bone metastasis in breast cancer, and constructs a model to predict metastasis.

This study retrospectively gathered data from breast cancer patients who were diagnosed and continuously monitored for five years from January 2013 to September 2023. Radiomic features were extracted from the bone marrow of thoracic vertebrae on non-contrast chest CT scans. Multiple machine learning algorithms were utilized to construct various radiomics models for predicting the risk of bone metastasis, and the model with optimal performance was integrated with clinical features to develop a nomogram. The effectiveness of this combined model was assessed through receiver operating characteristic (ROC) analysis as well as decision curve analysis (DCA).

The study included a total of 106 patients diagnosed with breast cancer, among whom 37 developed bone metastases within five years. The radiomics model's area under the curve (AUC) for the test set, calculated using logistic regression, is 0.929, demonstrating superior predictive performance compared to alternative machine learning models. Furthermore, DCA demonstrated the potential of radiomics models in clinical application, with a greater clinical benefit in predicting bone metastasis than clinical model and nomogram.

CT-based radiomics can capture subtle changes in the thoracic vertebral bone marrow before breast cancer bone metastasis, offering a predictive tool for early detection of bone metastasis in breast cancer.

Recent studies about human epidermal growth factor receptor 2 (HER2)-low values have garnered great interest among oncologists. We aimed to investigate whether HER2-low impacts the prognosis of early-stage breast cancer overall and in specific subgroups, explore differences in clinicopathologic markers, and examine the role of age in HER2-low prognostic stratification.

We conducted a retrospective analysis of 6920 HER2-negative breast cancer patients from the First Affiliated Hospital of Wenzhou Medical University (2010-2022). The study focused on the impact of HER2-low status (immunohistochemistry +1 or +2, in situ hybridization not amplified) on overall survival (OS), considering the age at diagnosis.

Generally, HER2-low status correlated with less aggressive cancer indicators. No significant prognostic differences were observed between HER2-low and HER2-0 in the entire cohort, HR-positive, and HR-negative groups. However, in TNBC patients aged ≥ 65, HER2-low correlated with significantly better OS (HR = 0.45, 95% CI 0.24-0.83, p = 0.011), a finding consistent after multivariable adjustment (HR = 0.34, 95% CI 0.14-0.80, p = 0.014). In other subgroups, prognosis did not significantly correlate with HER2 status. The combination of HER2-low status and age plays a key role in prognostic stratification in TNBC. Patients aged ≥ 65 with HER2-0 had considerably poorer prognoses compared to other subgroups.

This extensive retrospective study demonstrates that HER2-low status cannot serve as an independent prognostic factor in the entire cohort, nor in the HR-positive and HR-negative groups individually. However, the combined factors of HER2-low status and age may indicate a potential contribution to the prognostic stratification of TNBC.

Improved survival due to advances in medical therapy has resulted in increasing numbers of cancer patients living with bone metastases; however, our understanding of the prognostic implications of bone metastases requires larger population-based studies outlining their incidence and prevalence in different primary cancer types, including those with lower incidence. This study aimed to evaluate the incidence and prevalence of bone metastases in solid organ tumors by analyzing reports of staging CT studies with natural language processing (NLP).

In this retrospective study, 639,470 reports representing 129,326 unique patients were analyzed; 6279 randomly selected reports were manually annotated and labeled for the presence or absence of bone metastases. From these data, a BERT-based NLP model was developed and applied to the patient database. The cumulative incidence at 5 years and prevalence of bone metastases in each cancer type were calculated.

The accuracy of the NLP model on a validation set was 97.1%, with a positive predictive value (precision) of 88.0% and a sensitivity (recall) of 86.3%. The 5-year incidence rate of bone metastases was highest in prostate, breast, head and neck, and lung cancer (52%, 41%, 36%, 33%). Incidence was lowest in central nervous system cancer and testicular cancer (8%, 5%). Prevalence was highest in prostate, breast, and lung cancer (32%, 25% and 23%), and lowest in central nervous system cancer and testicular cancer (4%, 4%).

NLP was utilized to demonstrate patterns of bone metastases in a broad range of cancer types and is a valuable tool in population-based assessment of bone metastases.

Breast cancer remains the leading cause of cancer-related death in women, with 5-year survival rates of as high as 90% for patients with early-stage breast cancer without metastasis, falling to 10% once bone metastases (BM) occur. Currently, there is no cure for breast cancer with BM. However, appropriate treatment can extend survival and improve patients' quality of life. Therefore, it is important to accurately evaluate the presence of BM in patients with breast cancer. The present meta-analysis evaluated the diagnostic performance of 18F-FDG and 18F-NaF as PET/CT tracers for breast cancer-associated BM. The present study aimed to compare the diagnostic performance of fluorine-18 fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomographs (PET/CT) and 18F-sodium fluoride (18F-NaF) PET/CT in patients with breast cancer and BM. The PubMed and Embase databases were searched for English literature on the diagnostic performance of 18F-FDG PET/CT and 18F-NaF PET/CT for breast cancer BM, and two authors independently extracted data. All included studies presented data that could be used to construct a 2×2 contingency table. The methodological quality of the selected studies was assessed using QUADAS-2, and forest plots were generated based on the sensitivity and specificity of 18F-FDG PET/CT and 18F-NaF PET/CT in the diagnosis of BM associated with breast cancer. A total of 14 articles were identified, including eight on the analysis of 18F-FDG PET/CT, five on 18F-NaF PET/CT and one on both. The studies on 18F-FDG PET/CT and 18F-NaF PET/CT included 530 and 270 patients, respectively. The pooled sensitivities were 0.88 [95% confidence interval (95% CI), 0.76-0.94] for 18F-FDG PET/CT and 0.98 (95% CI, 0.92-1.00) for 18F-NaF PET/CT, and the pooled specificities were 0.99 (95% CI, 0.97-1.00) and 0.91 (95% CI: 0.76-0.97), respectively. The area under the summary receiver operating characteristic curve for both 18F-FDG PET/CT and 18F-NaF PET/CT was 0.99 (95% CI, 0.98-1.00). Lesion-based analysis using 18F-FDG PET/CT was performed for 909 lesions, with a sensitivity of 0.84 (95% CI, 0.67-1.00) and specificity of 1.00 (95% CI, 0.98-1.00). Compared with 18F-FDG PET/CT, 18F-NaF PET/CT showed higher sensitivity (98 vs. 88%) but lower specificity (91 vs. 99%), although the difference between methods was not statistically significant. In conclusion, the results of the present study indicated that 18F-NaF PET/CT and 18F-FDG PET/CT are both accurate methods for the detection of BM in patients with breast cancer, and have comparable diagnostic accuracy.

Breast cancer stem cells (BCSCs) have been suggested to be responsible for the development of Breast cancer (BC). The aim of this study was to evaluate BCSCs and the target organs microenvironment immunophenotyping markers in common BC metastases, and therapeutic targets regarding to the mentioned criteria.

This narrative review involved searching international databases; PubMed, Google Scholar using predetermined keywords including breast cancer, breast cancer stem cells, breast cancer metastases, immunophenotyping, immunohistochemistry and metastases. The search results were assessed based on the title, abstract, and full text of the articles, and relevant findings were included in the review.

BCSCs express high amounts of aldehyde dehydrogenase 1 (ALDH1), Ganglioside 2 (GD2), CD44 and CD133 but are negative for CD24 marker. CXCR4 and OPN have high expression in the cells and may contribute in BC metastasis to the bone. Nestin, CK5, prominin-1 (CD133) markers in BCSCs have been reported to correlate with brain metastasis. High expression of CD44 in BCSCs and CXCL12 expression in the liver microenvironment may contribute to BC metastasis to the liver. Aberrantly expressed vascular cell adhesion molecule-1 (VCAM-1) that binds to collagen and elastin fibers on pulmonary parenchyma, and CXCR4 of BCSCs and CXCL12 in lung microenvironment may promote the cells homing and metastasis to lung.

As in various types of BC metastases different markers that expressed by the cells and target organ microenvironment are responsible, BCSCs immunophenotyping can be used as target markers to predict the disease prognosis and treatment.

Bone metastases occur in 50-70% of patients with breast cancer (BC) and result in high mortality. Platelet distribution width (PDW), a commonly used parameter of activated platelets, has been associated with a poor prognosis in BC. We aim to investigate the prognostic role of PDW for bone metastasis in BC patients.

515 patients who received BC surgery in the Harbin Medical University Cancer Hospital from July 1, 2016, to December 31, 2017, were reviewed. Patients' characteristics and platelet indices upon enrollment in this study were collected. The Kaplan-Meier method was used to estimate the 5-year bone metastasis incidence. The univariate and multivariate Cox regression analyses were utilized to identify risk factors associated with bone metastasis.

The patients with bone metastases exhibited lower PDW levels than the patients without bone metastases. Moreover, decreased PDW was significantly correlated with histologic type, multifocal disease, and lymph node status. In addition, the patients with reduced PDW levels were more likely to develop bone metastasis. Multivariate analysis showed that PDW was an independent predictor for bone metastasis.

PDW is an independent predictor of bone metastasis in BC. Further research is warranted.

Aim: Breast cancer and its metastases involve high mortality even with advances in chemotherapy. Solid lipid nanoparticles provide a platform for drug delivery, reducing side effects and treatment-induced bone loss. A solid nanoparticle containing doxorubicin was evaluated for its ability to prevent bone loss in a pre-clinical breast cancer model.Methods: We investigated the effects of SLNDox in an aggressive metastatic stage IV breast cancer model, which has some important features that are interesting for bone loss investigation. This study evaluates bone loss prevention potential from solid lipid nanoparticles containing doxorubicin breast cancer treatment, an evaluation of the attenuation of morphological changes in bone tissue caused by the treatment and the disease and an assessment of bone loss imaging using computed tomography and electron microscopy.Results: Chemotherapy-induced bone loss was also observed in tumor-free animals; a solid lipid nanoparticle containing doxorubicin prevented damage to the growth plate and to compact and cancellous bones in the femur of tumor-bearing and healthy animals.Conclusion: The association of solid lipid nanoparticles with chemotherapeutic drugs with proven efficacy promotes the prevention of serious consequences of chemotherapy, reducing tumor progression, increasing quality of life and improving prognosis and survival.

Breast cancer has become the most prevalent malignant tumor in women, and the occurrence of distant metastasis signifies a poor prognosis. Utilizing predictive models to forecast distant metastasis in breast cancer presents a novel approach. This study aims to utilize readily available clinical data and advanced machine learning algorithms to establish an accurate clinical prediction model. The overall objective is to provide effective decision support for clinicians.

Data from 239 patients from two centers were analyzed, focusing on clinical blood biomarkers (tumor markers, liver and kidney function, lipid profile, cardiovascular markers). Spearman correlation and the least absolute shrinkage and selection operator regression were employed for feature dimension reduction. A predictive model was built using LightGBM and validated in training, testing, and external validation cohorts. Feature importance correlation analysis was conducted on the clinical model and the comprehensive model, followed by univariate and multivariate regression analysis of these features.

Through internal and external validation, we constructed a LightGBM model to predict de novo bone metastasis in newly diagnosed breast cancer patients. The area under the receiver operating characteristic curve values of this model in the training, internal validation test, and external validation test1 cohorts were 0.945, 0.892, and 0.908, respectively. Our validation results indicate that the model exhibits high sensitivity, specificity, and accuracy, making it the most accurate model for predicting bone metastasis in breast cancer patients. Carcinoembryonic Antigen, creatine kinase, albumin-globulin ratio, Apolipoprotein B, and Cancer Antigen 153 (CA153) play crucial roles in the model's predictions. Lipoprotein a, CA153, gamma-glutamyl transferase, α-Hydroxybutyrate dehydrogenase, alkaline phosphatase, and creatine kinase are positively correlated with breast cancer bone metastasis, while white blood cell ratio and total cholesterol are negatively correlated.

This study successfully utilized clinical blood biomarkers to construct an artificial intelligence model for predicting distant metastasis in breast cancer, demonstrating high accuracy. This suggests potential clinical utility in predicting and identifying distant metastasis in breast cancer. These findings underscore the potential prospect of developing economically efficient and readily accessible predictive tools in clinical oncology.

Breast cancer has emerged as the most common cancer globally, with a significant reduction in overall survival rate after metastasis. Compared with other types of breast cancer, triple-negative breast cancer (TNBC) is more prone to metastasize, presenting substantial treatment challenges due to the lack of effective therapies. LGR4, which is highly expressed in breast cancer, has been shown to promote the proliferation and invasion of breast cancer cells. However, its specific role in TNBC remains unclear. In this study, we applied a multi-omics approach to explore the regulatory mechanism of LGR4 in TNBC metastasis. Our findings showed that LGR4 could regulate actin cytoskeletal through EGFR and curtail EGFR activation-induced TNBC metastasis by inhibiting MGP expression. These insights provide new perspectives on the role of LGR4 in breast cancer metastasis.

Breast cancer (BC) is a global health concern, and development of diagnostic tools and targeted treatments for BC remains challenging. Therapeutic approaches for BC often involve a combination of surgery, radiation therapy, chemotherapy, targeted therapy, and hormone therapy. In recent years, there has been a growing interest in the role of noncoding RNAs (ncRNAs), including long ncRNAs (lncRNAs) and microRNAs (miRNAs), in BC and their therapeutic implications. Various biological processes such as cell proliferation, migration, and apoptosis rely on the activities of these ncRNAs, and their dysregulation has been implicated in BC progression. The regulatory function of the competitive endogenous RNA (ceRNA) network, which comprises lncRNAs, miRNAs, and mRNAs, has been the subject of extensive pathophysiological research. Most lncRNAs serve as molecular sponges for miRNAs and sequester their activities, thereby regulating the expression of target mRNAs and contributing to the promotion or inhibition of BC progression. This review summarizes recent findings on the role of ceRNA networks in BC progression, metastasis, and therapeutic resistance, and highlights the association of ceRNA networks with transcription factors and signaling pathways. Understanding the ceRNA network can lead to the discovery of biomarkers and targeted treatment methods to prevent the spread and metastasis of BC.

Bone is a frequent site for metastatic development in various cancer types, including breast cancer, with a grim prognosis due to the distinct bone environment. Despite considerable advances, our understanding of the underlying processes leading to bone metastasis progression remains elusive. Here, we applied a bioactive three-dimensional (3D) model capable of mimicking the endosteal bone microenvironment. MDA-MB-231 and MCF7 breast cancer cells were cultured on the scaffolds, and their behaviors and the effects of the biomaterial on the cells were examined over time. We demonstrated that close interactions between the cells and the biomaterial affect their proliferation rates and the expression of c-Myc, cyclin D, and KI67, leading to cell cycle arrest. Moreover, invasion assays revealed increased invasiveness within this microenvironment. Our findings suggest a dual role for endosteal mimicking signals, influencing cell fate and potentially acting as a double-edged sword, shuttling between cell cycle arrest and more active, aggressive states.

Breast cancer (BC) is the second-leading factor of mortality for women globally and is brought on by a variety of genetic and environmental causes. The conventional treatments for this disease have limitations, making it difficult to improve the lifespan of breast cancer patients. As a result, extensive research has been conducted over the past decade to find innovative solutions to these challenges. Targeting of the antitumor immune response through the immunomodulatory checkpoint protein B7 family has revolutionized cancer treatment and led to intermittent patient responses. B7-H3 has recently received attention because of its significant demodulation and its immunomodulatory effects in many cancers. Uncontrolled B7-H3 expression and a bad outlook are strongly associated, according to a substantial body of cancer research. Numerous studies have shown that BC has significant B7-H3 expression, and B7-H3 induces an immune evasion phenotype, consequently enhancing the survival, proliferation, metastasis, and drug resistance of BC cells. Thus, an innovative target for immunotherapy against BC may be the B7-H3 checkpoint.In this review, we discuss the structure and regulation of B7-H3 and its double costimulatory/coinhibitory function within the framework of cancer and normal physiology. Then we expound the malignant behavior of B7-H3 in BC and its role in the tumor microenvironment (TME) and finally focus on targeted drugs against B7-H3 that have opened new therapeutic opportunities in BC.

Bone metastasis is considered as a considerable challenge for breast cancer patients. Various in vitro and in vivo models have been developed to examine this occurrence. In vitro models are employed to simulate the intricate tumor microenvironment, investigate the interplay between cells and their adjacent microenvironment, and evaluate the effectiveness of therapeutic interventions for tumors. The endeavor to replicate the latency period of bone metastasis in animal models has presented a challenge, primarily due to the necessity of primary tumor removal and the presence of multiple potential metastatic sites.The utilization of novel bone metastasis models, including three-dimensional (3D) models, has been proposed as a promising approach to overcome the constraints associated with conventional 2D and animal models. However, existing 3D models are limited by various factors, such as irregular cellular proliferation, autofluorescence, and changes in genetic and epigenetic expression. The imperative for the advancement of future applications of 3D models lies in their standardization and automation. The utilization of artificial intelligence exhibits the capability to predict cellular behavior through the examination of substrate materials' chemical composition, geometry, and mechanical performance. The implementation of these algorithms possesses the capability to predict the progression and proliferation of cancer. This paper reviewed the mechanisms of bone metastasis following primary breast cancer. Current models of breast cancer bone metastasis, along with their challenges, as well as the future perspectives of using these models for translational drug development, were discussed.

This study explores a deep learning (DL) approach to predicting bone metastases in breast cancer (BC) patients using clinical information, such as the fat index, and features like Computed Tomography (CT) images.

CT imaging data and clinical information were collected from 431 BC patients who underwent radical surgical resection at Harbin Medical University Cancer Hospital. The area of muscle and adipose tissue was obtained from CT images at the level of the eleventh thoracic vertebra. The corresponding histograms of oriented gradients (HOG) and local binary pattern (LBP) features were extracted from the CT images, and the network features were derived from the LBP and HOG features as well as the CT images through deep learning (DL). The combination of network features with clinical information was utilized to predict bone metastases in BC patients using the Gradient Boosting Decision Tree (GBDT) algorithm. Regularized Cox regression models were employed to identify independent prognostic factors for bone metastasis.

The combination of clinical information and network features extracted from LBP features, HOG features, and CT images using a convolutional neural network (CNN) yielded the best performance, achieving an AUC of 0.922 (95% confidence interval [CI]: 0.843-0.964, P< 0.01). Regularized Cox regression results indicated that the subcutaneous fat index was an independent prognostic factor for bone metastasis in breast cancer (BC).

Subcutaneous fat index could predict bone metastasis in BC patients. Deep learning multimodal algorithm demonstrates superior performance in assessing bone metastases in BC patients.

Breast cancer bone metastasis is closely associated with the bone microenvironment. Zuogui Pill (ZGP), a clinically approved formulation in China, effectively regulates the bone microenvironment for the prevention and treatment of osteoporosis.

Few reports have utilized the ZGP for bone metastasis models. This study investigated the intervention and bone-protective properties of ZGP against breast cancer bone metastasis, explored the potential mechanism, and screened for its active compositions by molecules fishing.

To investigate the intervention efficacy of ZGP and its protein-level mechanism of action, the mouse bone metastasis model and in vitro cell co-culture model were constructed. Affinity ultrafiltration, molecular docking, cellular thermal shift assay and physical scale detection were used to investigate the affinity components of the RANKL protein in ZGP.

The administration of ZGP combined with zoledronic acid inhibited the development of tumors and secondary lung metastasis in mice. This translated to a prolonged survival period and enhanced quality of life. ZGP could disrupt the malignant cycle by modulating the Piezo1-Notch-1-GPX4 signaling pathway in the "bone-cancer" communication in the cell co-culture model. Furthermore, 25 chemical components of ZGP were identified, with 10 active compounds exhibiting significant affinity for the RANKL protein.

The findings of this work highlighted ZGP's potential for intervening in the progression of breast cancer bone metastasis. Thus, this investigation served as an experimental foundation for expanding the application scope of ZGP and for advancing drug development efforts in bone metastasis treatment.

The goal of this study is to develop a risk prediction model for estimating overall survival (OS) in young females diagnosed with stage IV breast cancer.

The clinical information was retrieved from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015. To identify the dependent risk factors, we utilized the Cox proportional hazards regression model in both single and multivariate analyses. We then created a new nomogram to predict the 1-, 3-, and 5-year overall survival probability for these patients based on the identified risk factors.

Six hundred seventy-six patients who met the eligibility requirements were stochastically partitioned into training (n = 475) and validation (n = 201) groups in a 7:3 ratio. Histology, breast subtype, T classification, brain metastasis, bone metastasis, liver metastasis, and surgery were identified as independent prognostic factors for cancer. To predict the 1-, 3-, and 5-year overall survival (OS) probabilities, all of these independent factors were incorporated into nomograms. Our nomogram demonstrated a favorable discriminatory power, as evidenced by a C-index of 0.737 (95% CI: 0.708-0.766) and 0.717 (95% CI: 0.664-0.770) for the training and validation cohorts, respectively. The calibration curves showed satisfactory consistency in both cohorts. Using this nomogram, we developed a risk stratification model that categorized patients into low-, intermediate-, and high-risk groups.

The prediction model was more precisely to predict the OS of young females with stage IV breast cancer and could enable individualized risk estimation that could be conducive to physicians exploring therapeutic strategies for effectiveness.

Breast cancer constitutes about 28% of all new cancer diagnoses in women, making it the most frequently diagnosed cancer among them. Our objective was to assess the role of bone scans (BS) in preoperative investigations of breast cancer.

This study involved 105 patients with varying stages of breast cancer, ranging from T1 to T4. We categorized them into three groups: group 1 comprised 40 women with breast cancer who underwent retrospective BS, group 2 included 30 patients with breast cancer who prospectively did not require BS for all cases, and group 3 consisted of 35 women retrospectively diagnosed with breast cancer who did not necessitate BS for all cases. The diagnosis of bone metastasis was confirmed upon obtaining a positive result through bone scintigraphy, subsequently affirmed by another imaging technique such as CT, X-ray, or MRI.

The hospital costs were significantly lower in groups 2 and 3 compared to that of group 1, indicating that performing a BS for every case is unnecessary. It was observed that the time taken for surgery was notably shorter in groups 2 and 3 compared to that of group 1. BS in cases classified as M stage were deemed both costly and time-consuming.

Routine BS are not cost-effective and represent an unnecessary investment of time. They should not be deemed mandatory as preoperative investigations in breast cancer cases. Instead, they should be considered in conjunction with MRI, particularly in cases of T4 breast cancer.

Breast cancer (BC) has become the most common malignancy in women. The incidence and detection rates of BC brain metastasis (BCBM) have increased with the progress of imaging, multidisciplinary treatment techniques and the extension of survival time of BC patients. BM seriously affects the quality of life and sur-vival prognosis of BC patients. Therefore, clinical research on the clinicopathological features and prognostic factors of BCBM is valuable. By analyzing the clinicopathological parameters of BCBM patients, and assessing the risk factors and prognostic indicators, we can perform hierarchical diagnosis and treatment on the high-risk population of BCBM, and achieve clinical benefits of early diagnosis and treatment.

To explore the clinicopathological features and prognostic factors of BCBM, and provide references for diagnosis, treatment and management of BCBM.

The clinicopathological data of 68 BCBM patients admitted to the Air Force Medical Center, Chinese People's Liberation Army (formerly Air Force General Hospital) from 2000 to 2022 were collected. Another 136 BC patients without BM were matched at a ratio of 1:2 based on the age and site of onset for retrospective analysis. Categorical data were subjected to χ2 test or Fisher's exact probability test, and the variables with P < 0.05 in the univariate Cox proportional hazards model were incorporated into the multivariate model to identify high-risk factors and independent prognostic factors of BCBM, with a hazard ratio (HR) > 1 suggesting poor prognostic factors. The survival time of patients was estimated by the Kaplan-Meier method, and overall survival was compared between groups by log-rank test.

Multivariate Cox regression analysis showed that patients with stage III/IV tumor at initial diagnosis [HR: 5.58, 95% confidence interval (CI): 1.99-15.68], lung metastasis (HR: 24.18, 95%CI: 6.40-91.43), human epidermal growth factor receptor 2 (HER2)-overexpressing BC and triple-negative BC were more prone to BM. As can be seen from the prognostic data, 52 of the 68 BCBM patients had died by the end of follow-up, and the median time from diagnosis of BC to the occurrence of BM and from the occurrence of BM to death or last follow-up was 33.5 and 14 mo, respectively. It was confirmed by multivariate Cox regression analysis that patients with neurological symptoms (HR: 1.923, 95%CI: 1.005-3.680), with bone metastasis (HR: 2.011, 95%CI: 1.056-3.831), and BM of HER2-overexpressing and triple-negative BC had shorter survival time.

HER2-overexpressing, triple-negative BC, late tumor stage and lung metastasis are risk factors of BM. The presence of neurological symptoms, bone metastasis, and molecular type are influencing prognosis factors of BCBM.

Carnosine is an endogenous dipeptide composed of β-alanine and L-histidine, possessing a multimodal pharmacodynamic profile that includes anti-inflammatory and anti-oxidant activities. Carnosine has also shown its ability to modulate cell proliferation, cell cycle arrest, apoptosis, and even glycolytic energy metabolism, all processes playing a key role in the context of cancer. Cancer is one of the most dreaded diseases of the 20th and 21st centuries. Among the different types of cancer, breast cancer represents the most common non-skin cancer among women, accounting for an estimated 15% of all cancer-related deaths in women. The main aim of the present review was to provide an overview of studies on the anti-cancer activity of carnosine, and in particular its activity against breast cancer. We also highlighted the possible advantages and limitations involved in the use of this dipeptide. The first part of the review entailed a brief description of carnosine's biological activities and the pathophysiology of cancer, with a focus on breast cancer. The second part of the review described the anti-tumoral activity of carnosine, for which numerous studies have been carried out, especially at the preclinical level, showing promising results. However, only a few studies have investigated the therapeutic potential of this dipeptide for breast cancer prevention or treatment. In this context, carnosine has shown to be able to decrease the size of cancer cells and their viability. It also reduces the levels of vascular endothelial growth factor (VEGF), cyclin D1, NAD+, and ATP, as well as cytochrome c oxidase activity in vitro. When tested in mice with induced breast cancer, carnosine proved to be non-toxic to healthy cells and exhibited chemopreventive activity by reducing tumor growth. Some evidence has also been reported at the clinical level. A randomized phase III prospective placebo-controlled trial showed the ability of Zn-carnosine to prevent dysphagia in breast cancer patients undergoing adjuvant radiotherapy. Despite this evidence, more preclinical and clinical studies are needed to better understand carnosine's anti-tumoral activity, especially in the context of breast cancer.

Bone metastases represent about 70% of breast cancer metastases and are associated with worse prognosis as the tumor cells acquire more aggressive features. The selection and investigation of patients with a high risk of developing bone metastasis would have a significant impact on patients' management and survival. The patients were selected from the database of Carol Davila Clinical Nephrology Hospital of Bucharest. Their tumor specimens were pathologically processed, and a representative area was selected. This area was scanned using an Olympus VS200 slide scanner and further analyzed using QuPath software v0.4.4. A representative group of approximately 60-100 tumor cells was selected from each section, for which the following parameters were analyzed: nuclear area, nuclear perimeter, long axis and cell surface. Starting from these measurements, the following were calculated: the mean nuclear area and mean nuclear volume, the nucleus to cytoplasm ratio, the length of the two axes, the long axis to short axis ratio, the acyclicity and anellipticity grade and the mean internuclear distance. The tumor cells belonging to patients known to have bone metastasis seemed to have a lower nuclear area (<55 µm2, p = 0.0035), smaller long axis (<9 µm, p = 0.0015), smaller values for the small axis (<7 µm, p = 0.0008), smaller mean nuclear volume (<200 µm3, p = 0.0146) and lower mean internuclear distance (<10.5 µm, p = 0.0007) but a higher nucleus to cytoplasm ratio (>1.1, p = 0.0418), higher axis ratio (>1.2, p = 0.088), higher acyclicity grade (>1.145, p = 0.0857) and higher anellipticity grade (>1.14, p = 0.1362). These parameters can be used for the evaluation of risk category of developing bone metastases. These results can be useful for the evaluation of bone metastatic potential of breast cancer and for the selection of high-risk patients whose molecular profiles would require further investigations and evaluation.

Breast cancer (BC) remains one of the most common malignancies among women worldwide. Breast cancer shows metastatic heterogeneity with priority to different organs, which leads to differences in prognosis and response to therapy among patients. The main targets for metastasis in BC are the bone, lung, liver and brain. The molecular mechanism of BC organ-specificity is still under investigation. In recent years, the appearance of new genomic approaches has led to unprecedented changes in the understanding of breast cancer metastasis organ-specificity and has provided a new platform for the development of more effective therapeutic agents. This review summarises recent data on molecular organ-specific markers of metastasis as the basis of a possible therapeutic approach in order to improve the diagnosis and prognosis of patients with metastatically heterogeneous breast cancer.

This study aimed at establishing more accurate predictive models based on novel machine learning algorithms, with the overarching goal of providing clinicians with effective decision-making assistance. We retrospectively analyzed the breast cancer patients recorded in the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2016. Multivariable logistic regression analyses were used to identify risk factors for bone metastases in breast cancer, whereas Cox proportional hazards regression analyses were used to identify prognostic factors for breast cancer with bone metastasis (BCBM). Based on the identified risk and prognostic factors, we developed diagnostic and prognostic models that incorporate six machine learning classifiers. We then used the area under the receiver operating characteristic (ROC) curve (AUC), learning curve, precision curve, calibration plot, and decision curve analysis to evaluate performance of the machine learning models. Univariable and multivariable logistic regression analyses showed that bone metastases were significantly associated with age, race, sex, grade, T stage, N stage, surgery, radiotherapy, chemotherapy, tumor size, brain metastasis, liver metastasis, lung metastasis, breast subtype, and PR. Univariate and multivariate Cox regression analyses revealed that age, race, marital status, grade, surgery, radiotherapy, chemotherapy, brain metastasis, liver metastasis, lung metastasis, breast subtype, ER, and PR were closely associated with the prognosis of BCBM. Among the six machine learning models, the XGBoost algorithm predicted the most accurate results (Diagnostic model AUC = 0.98; Prognostic model AUC = 0.88). According to the Shapley additive explanations (SHAP), the most critical feature of the diagnostic model was surgery, followed by N stage. Interestingly, surgery was also the most critical feature of prognostic model, followed by liver metastasis. Based on the XGBoost algorithm, we could effectively predict the diagnosis and survival of bone metastasis in breast cancer and provide targeted references for the treatment of BCBM patients.

Bone metastasis of breast cancer considerably reduces not only overall survival but also health-related quality of life due to pain, fatigue, and skeletal-related events.

This study aims to analyze the research hotspots and trends of global research on bone metastasis of breast cancer in the past 20 years to provide a reference for relevant personnel in this field to carry out academic research.

The literature related to bone metastasis of breast cancer from 2002 to 2021 was retrieved from the Web of Science. The bibliometric research method and VOSviewer and CiteSpace were used to analyze the publications, and the research status and development direction in the last 20 years were visualized.

A total of 7381 articles were included. The number of global publications is increasing every year. The United States contributes the most to global research, with the most citations and the highest H-index. The journal Cancer Research published the most articles on this issue. "Macrophage" and "skeletal related event" will receive more attention and be the next popular hotspot in the future.

There will be an increasing number of publications on bone metastasis of breast cancer based on current global trends. The United States made the largest contribution to this field. More focus will be placed on the mechanisms of metastasis research, which may be the next popular topic in bone metastasis of breast cancer.

Breast cancer stands as the most prevalent form of cancer affecting women, with metastasis serving as a leading cause of mortality among patients with breast cancer. Gaining a comprehensive understanding of the metastatic mechanism in breast cancer is essential for early detection and precision treatment of the disease. Circulating tumor cells (CTCs) play a vital role in this context, representing cancer cells that detach from tumor tissues and enter the bloodstream of cancer patients. These cells travel in the blood circulation as single cells or clusters. Recent research has shed light on the enhanced metastatic potential of CTC clusters compared to single CTCs, despite their limited occurrence. The aim of the present review was to explore recent findings on CTCs with a particular focus on the clustering phenomenon of CTCs observed in breast cancer. Additionally, the present review delved into the comparison between single CTCs and CTC clusters regarding their implications for the treatment and prognosis of patients diagnosed with metastatic breast cancer. By examining the role and mechanisms of CTCs in breast cancer metastasis, the present review provided an improved understanding of CTCs and their significance in early detection of breast cancer metastasis through peripheral blood analysis. Moreover, it contributed to the comprehension of cancer prognosis and prediction by highlighting the implications of CTCs in these aspects. Ultimately, the present study seeks to advance knowledge in the field and pave the way for improved approaches to breast cancer management.

The prognostic outcomes of metastasis patterns in patients with de novo metastatic breast cancer (dnMBC) of different ages are unknown. Our study used a large-scale data to investigate the metastasis patterns and prognostic features in dnMBC of different ages.

Total 24,698 women with dnMBC in the Surveillance, Epidemiology and End Results database (2010-2018) were divided into three groups by age. Chi-squared test was used to compare metastasis patterns and logistic regression was performed to investigate the risk of age and specific organ metastases. Kaplan-Meier survival curves were used to compare the overall survival.

In three groups, young group had the largest proportion of liver metastases (35.2% vs. 28.2% vs. 21.1%, p < 0.001), and elderly group had the largest proportion of lung metastases (22.6% vs. 30.0% vs. 35.0%, p < 0.001) and the lowest proportion of bone metastases (65.7% vs. 67.6% vs. 64.4%, p < 0.001). In young group, patients with liver metastases had better prognosis than patients with lung metastases (MST: 34 months vs. 29 months, p = 0.041), but in middle-aged and elderly groups, the prognosis of lung metastases was better than that of liver metastases (MST in middle-aged group: 24 months vs. 20 months, p = 0.002; MST in elderly group: 12 months vs. 6 months, p < 0.001).

DnMBC patients at different age have distinct metastasis patterns and prognostic features. The findings lend support to consideration of tailored management and surveillance strategies for different age patients.

Human epidermal growth factor receptor 2 (HER2) is overexpressed in 15-30% of breast cancers but has low expression in normal tissue, making it attractive for targeted alpha therapy (TAT). HER2-positive breast cancer typically metastasizes to bone, resulting in incurable disease and significant morbidity and mortality. Therefore, new strategies for HER2-targeting therapy are needed. Here, we present the preclinical in vitro and in vivo characterization of the HER2-targeted thorium-227 conjugate (HER2-TTC) TAT in various HER2-positive cancer models. In vitro, HER2-TTC showed potent cytotoxicity in various HER2-expressing cancer cell lines and increased DNA double strand break formation and the induction of cell cycle arrest in BT-474 cells. In vivo, HER2-TTC demonstrated dose-dependent antitumor efficacy in subcutaneous xenograft models. Notably, HER2-TTC also inhibited intratibial tumor growth and tumor-induced abnormal bone formation in an intratibial BT-474 mouse model that mimics breast cancer metastasized to bone. Furthermore, a match in HER2 expression levels between primary breast tumor and matched bone metastases samples from breast cancer patients was observed. These results demonstrate proof-of-concept for TAT in the treatment of patients with HER2-positive breast cancer, including cases where the tumor has metastasized to bone.

Metastases of breast cancer (BC) are often referred to as stage IV breast cancer due to their severity and high rate of mortality. The median survival time of patients with metastatic BC is reduced to 3 years. Currently, the treatment regimens for metastatic BC are similar to the primary cancer therapeutics and are limited to conventional chemotherapy, immunotherapy, radiotherapy, and surgery. However, metastatic BC shows organ-specific complex tumor cell heterogeneity, plasticity, and a distinct tumor microenvironment, leading to therapeutic failure. This issue can be successfully addressed by combining current cancer therapies with nanotechnology. The applications of nanotherapeutics for both primary and metastatic BC treatments are developing rapidly, and new ideas and technologies are being discovered. Several recent reviews covered the advancement of nanotherapeutics for primary BC, while also discussing certain aspects of treatments for metastatic BC. This review provides comprehensive details on the recent advancement and future prospects of nanotherapeutics designed for metastatic BC treatment, in the context of the pathological state of the disease. Furthermore, possible combinations of current treatment with nanotechnology are discussed, and their potential for future transitions in clinical settings is explored.

Bone is the most common site of metastasis from breast cancer, which is the most prevalent cancer affecting women globally. Bone metastasis from breast cancer severely affects the quality of life of patients and increases mortality. The molecular mechanisms of metastasis, colonization, and proliferation of breast cancer cells in bone are complex and involve the interaction between breast cancer cells and the bone microenvironment. However, the precise mechanism is not clear at present. In recent years, the Hippo signaling pathway has attracted much attention due to its important role in regulating the expression of major effector molecules during tumor development. In particular, studies have found that the mutation and aberrant expression of the core components of the Hippo signaling pathway affect breast cancer cell migration and invasion, indicating that this pathway plays a role in bone metastasis, although the molecular mechanism of this pathway in breast cancer metastasis has not been fully elucidated. In this review, we discuss the function of the Hippo signaling pathway, introducing its role in breast cancer metastasis, especially bone metastasis of breast cancer, so as to lay a solid theoretical foundation for further research and for the development of effective targeted therapeutic agents.

ObjectiveTo assess use of bone-targeting agents (BTA) in patients with confirmed bone metastases (BM) from breast cancer (BC), non-small cell lung cancer (NSCLC) or prostate cancer (PC).

Retrospective cohort study.

Regional hospital-based oncology database of approximately 2 million patients in England.

Patients aged ≥18 years with a diagnosis of BC, NSCLC or PC as well as BM between 1 January 2007 and 31 December 2018, with follow-up to 30 June 2020 or death; BM diagnosis ascertained from recorded medical codes and unstructured data using natural language processing (NLP).

Initiation or non-initiation of BTA following BM diagnosis, time from BM diagnosis to BTA initiation, time from first to last BTA, time from last BTA to death.

This study included 559 BC, 894 NSCLC and 1013 PC with BM; median age (Q1-Q3) was 65 (52-76), 69 (62-77) and 75 (62-77) years, respectively. NLP identified BM diagnosis from unstructured data for 92% patients with BC, 92% patients with NSCLC and 95% patients with PC. Among patients with BC, NSCLC and PC with BM, 47%, 87% and 88% did not receive a BTA, and 53%, 13% and 12% received at least one BTA, starting a median 65 (27-167), 60 (28-162) and 610 (295-980) days after BM, respectively. Median (Q1-Q3) duration of BTA treatment was 481 (188-816), 89 (49-195) and 115 (53-193) days for patients with BC, NSCLC and PC. For those with a death record, median time from last BTA to death was 54 (26-109) for BC, 38 (17-98) for NSCLC and 112 (44-218) days for PC.

In this study identifying BM diagnosis from both structured and unstructured data, a high proportion of patients did not receive a BTA. Unstructured data provide new insights on the real-world use of BTA.

Bone marrow metastasis (BMM) is uncommon in breast cancer (BC), and early diagnosis is challenging. BMM lacks definitive treatment options and poses a great threat to the survival of patients. Herein, we investigated the clinical features, prognosis, and factors affecting the prognosis of BC patients with symptomatic BMM to help improve the understanding of this disease and provide effective diagnostic and treatment strategies.

Clinical data of 67 patients with BC and BMM were retrospectively analyzed for clinical characteristics, treatment, and prognosis of BMM. Univariate and multivariate analyses were performed to determine factors affecting overall survival following BMM (BMMOS).

Among patients with BMM, 86.6% were diagnosed after bone metastasis (BM), while 13.4% were diagnosed simultaneously with BM. A total of 73.1%, 13.4%, and 13.4% of the patients had hormone receptor-positive/human epidermal growth factor 2-negative (HR+/HER2-) tumors, HER2+ tumors, and triple-negative tumors, respectively. The most common symptoms of BMM were the coexistence of anemia and thrombocytopenia (26.9%), anemia (19.4%), and pancytopenia (17.9%). The median BMMOS was 7.6 months (95% CI, 3.9-11.3). Univariate and multivariate analyses showed that BMMOS was associated with platelet count <75 × 109 /L at the time of BMM diagnosis. The BMMOS of patients who underwent endocrine therapy, combined chemotherapy, and mono-chemotherapy after BMM was 15.7, 9.7, and 8.6 months, respectively, whereas that of untreated patients was 2.9 months, and the difference among the results was statistically significant (χ2  = 20.102, p < 0.0001). Changes in patient hemogram and/or body temperature during treatment were consistent with the overall effect of the disease (p < 0.0001).

BMM should be considered in BC patients with BM, an unexplained reduction in hemogram parameters, especially anemia and thrombocytopenia, and/or fever without chills. Active, effective, individualized treatment strategies can prolong BMMOS.

Distal metastases from breast cancer, especially bone metastases, are extremely common in the late stages of the disease and are associated with a poor prognosis. EMT is a biomarker of the early process of bone metastasis, and MMP-9 and MMP-13 are important osteoclastic activators. Previously, we found that meso-Hannokinol (HA) could significantly inhibit EMT and MMP-9 and MMP-13 expressions in breast cancer cells. On this basis, we further explored the role of HA in breast cancer bone metastasis. In vivo, we established a breast cancer bone metastasis model by intracardially injecting breast cancer cells. Intraperitoneal injections of HA significantly reduced breast cancer cell metastasis to the leg bone in mice and osteolytic lesions caused by breast cancer. In vitro, HA inhibited the migration and invasion of breast cancer cells and suppressed the expressions of EMT, MMP-9, MMP-13, and other osteoclastic activators. HA inhibited EMT and MMP-9 by activating the ROS/JNK pathway as demonstrated by siJNK and SP600125 inhibition of JNK phosphorylation and NAC scavenging of ROS accumulation. Moreover, HA promoted bone formation and inhibited bone resorption in vitro. In conclusion, our findings suggest that HA may be an excellent candidate for treating breast cancer bone metastasis.

Patients with oligometastatic breast cancer (BC) are candidates of choice for metastasis-directed therapy (MDT). This paper summarizes the opinions of an expert committee about the management of oligometastatic BC. The experts could complete the questionnaire from 13 September 2021, to 10 October 2021, followed by a discussion. The experts were physicians working in the Province of Quebec (Canada) and specialized in BC care, including surgical oncologists, medical oncologists, and radiation oncologists. The experts provided their opinions about the context of the disease and therapeutic approach, local and systemic therapies, and the prognosis of oligometastatic BC. In addition to the expert panel's opinions about the management of oligometastatic disease per se, the experts stated that a prospective data registry should be implemented to collect data about oligometastatic BC to improve knowledge about oligometastatic BC and implement data-driven MDT. These data could also allow for the design of treatment algorithms. In conclusion, this paper presents the expert panel's opinions about the management of oligometastatic BC and highlights the needs to be met to improve the care of this condition.

Introduction: Bone metastasis of breast cancer (BC) is a process in which the disruption of the bone homeostatic microenvironment leads to an increase in osteoclast differentiation. Ailanthus altissima shows an inhibitory effect on osteoclast differentiation. Ailanthone (AIL) refers to a natural compound isolated from Ailanthus altissima, a Chinese herbal medicine, and has effective anti-tumor activity in numerous cell lines. Its impact on bone metastases for BC is yet unclear. Methods: We measured the effect of AIL on MDA-MB-231 cells by wound healing experiments, Transwell and colony formation experiment. Using the Tartrate-resistant Acid Phosphatase (TRAP) staining tests, filamentous (F-actin) staining and bone resorption test to detect the effect of AIL on the osteoclast cell differentiation of the Bone Marrow-derived Macrophages (BMMs), activated by the MDA-MB-231 cell Conditioned Medium (MDA-MB-231 CM) and the Receptor Activator of Nuclear factor-κB Ligand (RANKL),and to explore its possibility Mechanisms. In vivo experiments verified the effect of AIL on bone destruction in breast cancer bone metastasis model mice. Results: In vitro, AIL significantly decrease the proliferation, migration and infiltration abilities of MDA-MB-231 cells at a safe concentration, and also reduced the expression of genes and proteins involved in osteoclast formation in MDA-MB-231 cells. Osteoclast cell differentiation of the BMMs, activated by MDA-MB-231 CM and RANKL, were suppressed by AIL in the concentration-dependent manner. Additionally, it inhibits osteoclast-specific gene and protein expression. It was noted that AIL inhibited the expression of the osteoclast differentiation-related cytokines RANKL and interleukin-1β (IL-1β) that were secreted by the MDA-MB-231 cells after upregulating the Forkhead box protein 3 (FOXP3) expression. Furthermore, AIL also inhibits the expression of the Mitogen-Activated Protein Kinase (MAPK), Phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT), and Nuclear factor-κB Ligand (NF-κB) signaling pathways, which then suppresses the MDA-MB-231CM-induced development of Osteoclasts. Conclusion: Our study shows that AIL blocks osteoclast differentiation in the bone metastasis microenvironment by inhibiting cytokines secreted by BC cells, which may be a potential agent for the treatment of BC and its secondary bone metastasis.

Bone metastases affect 50% to 70% of breast cancer (BC) patients and have a high mortality rate. Adipose tissue loss plays a pivotal role in the progression of cancer.

This study aims to evaluate the prognostic value of adipose tissue for bone metastasis in BC patients.

517 BC patients were studied retrospectively. Patients' characteristics before the surgery were collected. Quantitative measurements of the subcutaneous fat index (SFI) were performed at the level of the eleventh thoracic vertebra. In order to adjust for the heterogeneity between the low SFI and high SFI groups, propensity score matching (PSM) was used. The Kaplan-Meier method was used to estimate the 5-year bone metastatic incidence. The prognostic analysis was performed with the Cox regression models.

Compared with the patients without bone metastasis, the patients with bone metastasis had reduced SFI levels. In addition, Kaplan-Meier analysis revealed that patients with low SFI were more likely to develop bone metastases. The independent predictive value of SFI for bone metastases was confirmed by Cox regression analysis. The survival analysis was repeated after PSM with a 1:1 ratio, yielding similar results (P< 0.05).

SFI is an independent predictor of bone metastasis in BC patients.

Ezrin, known as a crosslinker between the plasma membrane and actin cytoskeleton, is closely associated with breast cancer (BC) progression. Here, we explored a novel role of ezrin in breast cancer liver metastasis (BCLM).

The clinical relevance of ezrin was evaluated using in silico tools and confirmed in BC specimens. The effect of ezrin on proliferation, migration and invasion was examined in vitro and in vivo using murine primary liver-metastatic breast cancer cells (mLM). The molecular mechanism involved in ezrin-mediated activation of the Notch1 signaling pathway was elucidated using in vitro models.

Data-mining demonstrated that ezrin mRNA and protein expression is up-regulated in breast cancer cohorts and has prognostic significance. Ezrin overexpression promotes cell proliferation, migration and invasion in vitro and in vivo. Hairy and enhancer of split-1 (Hes1) is one of the most significantly enriched candidates of differentially expressed genes in ezrin overexpression and control mLM cells. Ezrin can positively regulate Hes1 mRNA and protein expression, and their coexpression was associated with poor prognosis in BC patients. Ezrin promoted BC cell proliferation in a Hes1-dependent manner without directly interacting with Hes1. The functional link between ezrin and Hes1 is dependent on Notch1 activation through promotion of furin-like convertase cleavage.

Our results demonstrated that ezrin drives BCLM through activation of the Notch signaling pathway via furin-like convertase. These findings provide a better understanding of the mechanism of ezrin in breast cancer progression, with the goal of discovering a novel target for the treatment of BCLM in the future.

Bone metastasis is a common complication of many types of advanced cancer, including breast cancer. Bone metastasis may cause severe pain, fractures, and hypercalcemia, rendering clinical management challenging and substantially reducing the quality of life and overall survival (OS) time of breast cancer patients. Studies have revealed that bone metastasis is related to interactions between tumor cells and the bone microenvironment, and involves complex molecular biological mechanisms, including colonization, osteolytic destruction, and an immunosuppressive bone microenvironment. Agents inhibiting bone metastasis (such as bisphosphate and denosumab) alleviate bone destruction and improve the quality of life of breast cancer patients with bone metastasis. However, the prognosis of these patients remains poor, and the specific biological mechanism of bone metastasis is incompletely understood. Additional basic and clinical studies are urgently needed, to further explore the mechanism of bone metastasis and develop new therapeutic drugs. This review presents a summary of the molecular mechanisms and therapeutic strategies of bone metastasis of breast cancer, aiming to improve the quality of life and prognosis of breast cancer patients and provide a reference for future research directions.

Breast cancer has a high mortality rate among malignant tumors, with metastases identified as the main cause of the high mortality. Dysbiosis of the gut microbiota has become a key factor in the development, treatment, and prognosis of breast cancer. The many microorganisms that make up the gut flora have a symbiotic relationship with their host and, through the regulation of host immune responses and metabolic pathways, are involved in important physiologic activities in the human body, posing a significant risk to health. In this review, we build on the interactions between breast tissue (including tumor tissue, tissue adjacent to the tumor, and samples from healthy women) and the microbiota, then explore factors associated with metastatic breast cancer and dysbiosis of the gut flora from multiple perspectives, including enterotoxigenic Bacteroides fragilis, antibiotic use, changes in gut microbial metabolites, changes in the balance of the probiotic environment and diet. These factors highlight the existence of a complex relationship between host-breast cancer progression-gut flora. Suggesting that gut flora dysbiosis may be a host-intrinsic factor affecting breast cancer metastasis and progression not only informs our understanding of the role of microbiota dysbiosis in breast cancer development and metastasis, but also the importance of balancing gut flora dysbiosis and clinical practice.