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Circulating tumor cells (CTCs) are some of the key culprits that cause cancer metastasis and metastasis-related deaths. These cells exist in a dynamic microenvironment where they experience fluid shear stress (FSS), and the CTCs that survive FSS are considered to be highly metastatic and stem cell-like. Biophysical stresses such as FSS are also known to cause the production of extracellular vesicles (EVs) that can facilitate cell–cell communication by carrying biomolecular cargos such as microRNAs. Here, we hypothesized that physiological FSS will impact the yield of EV production, and that these EVs will have biomolecules that transform the recipient cells. The EVs were isolated using direct flow filtration with and without FSS from the MDA-MB-231 cancer cell line, and the expression of key stemness-related genes and microRNAs was characterized. There was a significantly increased yield of EVs under FSS. These EVs also contained significantly increased levels of miR-21, which was previously implicated to promote metastatic progression and chemotherapeutic resistance. When these EVs from FSS were introduced to MCF-7 cancer cells, the recipient cells had a significant increase in their stem-like gene expression and CD44+/CD24− cancer stem cell-like subpopulation. There was also a correlated increased proliferation along with an increased ATP production. Together, these findings indicate that the presence of physiological FSS can directly influence the EVs' production and their contents, and that the EV-mediated transfer of miR-21 can have an important role in FSS-existing contexts, such as in cancer metastasis. [ABSTRACT FROM AUTHOR]

Ectonucleotide pyrophosphatase/phosphodiesterase 1 (ENPP1) expression correlates with poor prognosis in many cancers, and we previously discovered that ENPP1 is the dominant hydrolase of extracellular cGAMP: a cancer-cell-produced immunotransmitter that activates the anticancer stimulator of interferon genes (STING) pathway. However, ENPP1 has other catalytic activities and the molecular and cellular mechanisms contributing to its tumorigenic effects remain unclear. Here, using single-cell RNA-seq, we show that ENPP1 in both cancer and normal tissues drives primary breast tumor growth and metastasis by dampening extracellular 23-cyclic-GMP-AMP (cGAMP)-STING-mediated antitumoral immunity. ENPP1 loss-of-function in both cancer cells and normal tissues slowed primary tumor growth and abolished metastasis. Selectively abolishing the cGAMP hydrolysis activity of ENPP1 phenocopied ENPP1 knockout in a STING-dependent manner, demonstrating that restoration of paracrine cGAMP-STING signaling is the dominant anti-cancer mechanism of ENPP1 inhibition. Finally, ENPP1 expression in breast tumors deterministically predicated whether patients would remain free of distant metastasis after pembrolizumab (anti-PD-1) treatment followed by surgery. Altogether, ENPP1 blockade represents a strategy to exploit cancer-produced extracellular cGAMP for controlled local activation of STING and is therefore a promising therapeutic approach against breast cancer.

Recent studies have shown that stress can substantially facilitate breast cancer metastasis, which can be reduced by nonselective β1/β2-adrenergic receptor (β1/β2-AR) blocker. However, several side effects were identified. Thus, it is extremely warranted to explore more effective and better-tolerated β2-AR blocker. Currently, we demonstrated that baicalin (BA), a major bioactive component of Scutellaria baicalensis Georgi, could significantly attenuate stress hormones especially epinephrine (Epi)-induced breast cancer cell migration and invasion in vitro. Mechanistically, we identified that β2-AR was a direct target of BA via the drug affinity responsive target stability (DARTS) combined with mass spectrum assay, and BA photoaffinity probe with pull-down assay, which was further confirmed by a couple of biophysical and biochemical assays. Furthermore, we demonstrated that BA could directly bind to the Phe-193 and Phe-289 of β2-AR, subsequently inhibit cyclic adenosine monophosphate-protein kinase A-focal adhesion kinase (cAMP-PKA-FAK) pathway, and thus impede epithelial-mesenchymal transition (EMT), thereby hindering the metastatic progression of the chronic stress coupled with syngeneic and xenograft in vivo orthotopic and tail vein mouse model. These findings firstly identify BA as a potential β2-AR inhibitor in the treatment of stress-induced breast cancer metastasis.

Breast cancer (BCa) is a highly heterogeneous disease, with hormone receptor status being a key factor in patient prognostication and treatment decision‐making. The majority of primary tumours are positive for oestrogen receptor alpha (ERα), which plays a key role in tumorigenesis and disease progression, and represents the major target for treatment of BCa. However, around one‐third of patients with ERα‐positive BCa relapse and progress into the metastatic stage, with 20% of metastatic cases characterised by loss of ERα expression after endocrine treatment, known as ERα‐conversion. It remains unclear whether ERα‐converted cancers are biologically similar to bona fide ERα‐negative disease and which signalling cascades compensate for ERα loss and drive tumour progression. To better understand the biological changes that occur in metastatic BCa upon ERα loss, we performed (phospho)proteomics analysis of 47 malignant pleural effusions derived from 37 BCa patients, comparing ERα‐positive, ERα‐converted and ERα‐negative cases. Our data revealed that the loss of ERα‐dependency in this metastatic site leads to only a partial switch to an ERα‐negative molecular phenotype, with preservation of a luminal‐like proteomic landscape. Furthermore, we found evidence for decreased activity of several key kinases, including serum/glucocorticoid regulated kinase 1 (SGK1), in ERα‐converted metastases. Loss of SGK1 substrate phosphorylation may compensate for the loss of ERα‐dependency in advanced disease and exposes a potential therapeutic vulnerability that may be exploited in treating these patients.

Breast cancer is the lead cause of cancer-related deaths among women globally. Breast cancer metastasis is a complex and still inadequately understood process and a key dimension of mortality attendant to breast cancer. This study reports dysregulated genes across metastatic stages and tissues, shedding light on their molecular interplay in disease pathogenesis and new possibilities for drug discovery. Comprehensive analyses of gene expression data from primary breast tumor, circulating tumor cells, and distant metastatic sites in the brain, lung, liver, and bone were conducted. Genes dysregulated across multiple stages and tissues were identified as metastatic cascade genes, and are further classified based on functional associations with metastasis-related mechanisms. Their interactions with HUB genes in interactome networks were scrutinized, followed by pathway enrichment analysis. Validation for their potential as targets included assessments for survival, druggability, prognostic marker status, secretome annotation, protein expression, and cell type marker association. Results displayed critical genes in the metastatic cascade and those specific to metastatic sites, revealing the involvement of the collagen degradation and assembly of collagen fibrils and other multimeric structure pathways in driving metastasis. Notably, pivotal cascade genes FABP4, CXCL12, APOD, and IGF1 emerged with high metastatic potential, linked to significant druggability and survival scores, establishing them as potential molecular targets. The significance of this research lies in its potential to uncover novel biomarkers for early detection, therapeutic targets, and a deeper understanding of the molecular mechanisms underpinning the metastatic cascade in breast cancer, and with an eye to precision/personalized medicine. [ABSTRACT FROM AUTHOR]

Breast cancer (BCa) is a highly heterogeneous disease, with hormone receptor status being a key factor in patient prognostication and treatment decision‐making. The majority of primary tumours are positive for oestrogen receptor alpha (ERα), which plays a key role in tumorigenesis and disease progression, and represents the major target for treatment of BCa. However, around one‐third of patients with ERα‐positive BCa relapse and progress into the metastatic stage, with 20% of metastatic cases characterised by loss of ERα expression after endocrine treatment, known as ERα‐conversion. It remains unclear whether ERα‐converted cancers are biologically similar to bona fide ERα‐negative disease and which signalling cascades compensate for ERα loss and drive tumour progression. To better understand the biological changes that occur in metastatic BCa upon ERα loss, we performed (phospho)proteomics analysis of 47 malignant pleural effusions derived from 37 BCa patients, comparing ERα‐positive, ERα‐converted and ERα‐negative cases. Our data revealed that the loss of ERα‐dependency in this metastatic site leads to only a partial switch to an ERα‐negative molecular phenotype, with preservation of a luminal‐like proteomic landscape. Furthermore, we found evidence for decreased activity of several key kinases, including serum/glucocorticoid regulated kinase 1 (SGK1), in ERα‐converted metastases. Loss of SGK1 substrate phosphorylation may compensate for the loss of ERα‐dependency in advanced disease and exposes a potential therapeutic vulnerability that may be exploited in treating these patients. [ABSTRACT FROM AUTHOR]

Breast cancer (BrC) is the most frequently diagnosed malignancy in woman and most BrC related deaths are due to metastasis. BrC frequently metastasizes to the lymph nodes, liver, lung, bone and brain while the urinary bladder is considered as an unusual site for breast metastasis. We report a case of bladder metastasis identified in a patient with past BrC history, presenting with hematuria, low urinary tract symptoms, and hydronephrosis.

Ectonucleotide pyrophosphatase/phosphodiesterase 1 (ENPP1) expression correlates with poor prognosis in many cancers, and we previously discovered that ENPP1 is the dominant hydrolase of extracellular cGAMP: a cancer-cell-produced immunotransmitter that activates the anticancer stimulator of interferon genes (STING) pathway. However, ENPP1 has other catalytic activities and the molecular and cellular mechanisms contributing to its tumorigenic effects remain unclear. Here, using single-cell RNA-seq, we show that ENPP1 in both cancer and normal tissues drives primary breast tumor growth and metastasis by dampening extracellular 2'3'-cyclic-GMP-AMP (cGAMP)-STING-mediated antitumoral immunity. ENPP1 loss-of-function in both cancer cells and normal tissues slowed primary tumor growth and abolished metastasis. Selectively abolishing the cGAMP hydrolysis activity of ENPP1 phenocopied ENPP1 knockout in a STING-dependent manner, demonstrating that restoration of paracrine cGAMP-STING signaling is the dominant anti-cancer mechanism of ENPP1 inhibition. Finally, ENPP1 expression in breast tumors deterministically predicated whether patients would remain free of distant metastasis after pembrolizumab (anti-PD-1) treatment followed by surgery. Altogether, ENPP1 blockade represents a strategy to exploit cancer-produced extracellular cGAMP for controlled local activation of STING and is therefore a promising therapeutic approach against breast cancer. [ABSTRACT FROM AUTHOR]

Aim: Method: This research presents a model combining machine learning (ML) techniques and eXplainable artificial intelligence (XAI) to predict breast cancer (BC) metastasis and reveal important genomic biomarkers in metastasis patients. Method: A total of 98 primary BC samples was analyzed, comprising 34 samples from patients who developed distant metastases within a 5-year follow-up period and 44 samples from patients who remained disease-free for at least 5 years after diagnosis. Genomic data were then subjected to biostatistical analysis, followed by the application of the elastic net feature selection method. This technique identified a restricted number of genomic biomarkers associated with BC metastasis. A light gradient boosting machine (LightGBM), categorical boosting (CatBoost), Extreme Gradient Boosting (XGBoost), Gradient Boosting Trees (GBT), and Ada boosting (AdaBoost) algorithms were utilized for prediction. To assess the models' predictive abilities, the accuracy, F1 score, precision, recall, area under the ROC curve (AUC), and Brier score were calculated as performance evaluation metrics. To promote interpretability and overcome the "black box" problem of ML models, a SHapley Additive exPlanations (SHAP) method was employed. Results: The LightGBM model outperformed other models, yielding remarkable accuracy of 96% and an AUC of 99.3%. In addition to biostatistical evaluation, in XAI-based SHAP results, increased expression levels of TSPYL5, ATP5E, CA9, NUP210, SLC37A1, ARIH1, PSMD7, UBQLN1, PRAME, and UBE2T (p ≤ 0.05) were found to be associated with an increased incidence of BC metastasis. Finally, decreased levels of expression of CACTIN, TGFB3, SCUBE2, ARL4D, OR1F1, ALDH4A1, PHF1, and CROCC (p ≤ 0.05) genes were also determined to increase the risk of metastasis in BC. Conclusion: The findings of this study may prevent disease progression and metastases and potentially improve clinical outcomes by recommending customized treatment approaches for BC patients. [ABSTRACT FROM AUTHOR]

Abstract Background Nitric oxide is produced by different nitric oxide synthases isoforms. NO activates two signaling pathways, one dependent on soluble guanylate cyclase and protein kinase G, and other where NO post-translationally modifies proteins through S-nitrosylation, which is the modification induced by NO in free-thiol cysteines in proteins to form S-nitrosothiols. High levels of NO have been detected in blood of breast cancer patients and increased NOS activity has been detected in invasive breast tumors compared to benign or normal breast tissue, suggesting a positive correlation between NO biosynthesis, degree of malignancy and metastasis. During metastasis, the endothelium plays a key role allowing the adhesion of tumor cells, which is the first step in the extravasation process leading to metastasis. This step shares similarities with leukocyte adhesion to the endothelium, and it is plausible that it may also share some regulatory elements. The vascular cell adhesion molecule-1 (VCAM-1) expressed on the endothelial cell surface promotes interactions between the endothelium and tumor cells, as well as leukocytes. Data show that breast tumor cells adhere to areas in the vasculature where NO production is increased, however, the mechanisms involved are unknown. Results We report that the stimulation of endothelial cells with interleukin-8, and conditioned medium from breast tumor cells activates the S-nitrosylation pathway in the endothelium to induce leukocyte adhesion and tumor cell extravasation by a mechanism that involves an increased VCAM-1 cell surface expression in endothelial cells. We identified VCAM-1 as an S-nitrosylation target during this process. The inhibition of NO signaling and S-nitrosylation blocked the transmigration of tumor cells through endothelial monolayers. Using an in vivo model, the number of lung metastases was inhibited in the presence of the S-nitrosylation inhibitor N-acetylcysteine (NAC), which was correlated with lower levels of S-nitrosylated VCAM-1 in the metastases. Conclusions S-Nitrosylation in the endothelium activates pathways that enhance VCAM-1 surface localization to promote binding of leukocytes and extravasation of tumor cells leading to metastasis. NAC is positioned as an important tool that might be tested as a co-therapy against breast cancer metastasis.

Circulating tumor cells (CTCs) are some of the key culprits that cause cancer metastasis and metastasis-related deaths. These cells exist in a dynamic microenvironment where they experience fluid shear stress (FSS), and the CTCs that survive FSS are considered to be highly metastatic and stem cell-like. Biophysical stresses such as FSS are also known to cause the production of extracellular vesicles (EVs) that can facilitate cell–cell communication by carrying biomolecular cargos such as microRNAs. Here, we hypothesized that physiological FSS will impact the yield of EV production, and that these EVs will have biomolecules that transform the recipient cells. The EVs were isolated using direct flow filtration with and without FSS from the MDA-MB-231 cancer cell line, and the expression of key stemness-related genes and microRNAs was characterized. There was a significantly increased yield of EVs under FSS. These EVs also contained significantly increased levels of miR-21, which was previously implicated to promote metastatic progression and chemotherapeutic resistance. When these EVs from FSS were introduced to MCF-7 cancer cells, the recipient cells had a significant increase in their stem-like gene expression and CD44+/CD24− cancer stem cell-like subpopulation. There was also a correlated increased proliferation along with an increased ATP production. Together, these findings indicate that the presence of physiological FSS can directly influence the EVs’ production and their contents, and that the EV-mediated transfer of miR-21 can have an important role in FSS-existing contexts, such as in cancer metastasis.

Wenli Dang,1– 3 Bin Xing,1– 3 Xintao Jia,1– 3 Ying Zhang,1– 3 Bei Jia,1– 3 Changxiang Yu,1– 3 Jiachen He,1– 3 Ziwei Li,1– 3 Huihui Li,1– 3 Zhidong Liu1– 3 1State Key Laboratory of Component-Based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, People’s Republic of China; 2Engineering Research Center of Modern Chinese Medicine Discovery and Preparation Technique, Ministry of Education, Tianjin University of Traditional Chinese Medicine, Tianjin, People’s Republic of China; 3Haihe Laboratory of Modern Chinese Medicine, Tianjin, People’s Republic of ChinaCorrespondence: Zhidong Liu, Tianjin University of Traditional Chinese Medicine, No. 10 Poyang Lake Road, 301617, Tuanbo New Town, Jinghai District, Tianjin, People’s Republic of China, Tel +86 22-59596170, Email lonerliuzd@163.comBackground: Subcellular organelle targeted nano-formulations for cancer treatment are receiving increasing attention owing to their benefits of precise drug delivery, maximized therapeutic index, and reduced off-target side effects. The nucleus and mitochondria, as the main subcellular organelles, are the significant organelles responsible for maintaining cell operation and metabolism. They can be involved in many essential physiological and pathological processes such as cell proliferation, organism metabolism, intracellular transportation, and play a critical role in regulating cell biology. Meanwhile, breast cancer metastasis is one of the leading causes of death in breast cancer patients. With the development of nanotechnology, nanomaterials have been widely used in tumor therapy.Methods: We designed a subcellular organelle targeted nanostructured lipid carriers (NLC) to deliver paclitaxel (PTX) and gambogic acid (GA) to tumor tissues.Results: Due to the surface of NLC being modified by subcellular organelle targeted peptide, the PTX and GA co-loaded NLC can accurately release PTX and GA in tumor cells. This property makes NLC able to easy to enter tumor site and target the specific subcellular organelle. The modified NLC can efficiently inhibit the growth of 4T1 primary tumor and lung metastasis, which may be related to the down-regulation of matrix metalloproteinase-9 (MMP-9) and BCL-2 levels, up-regulation of E-cadherin level, and antagonized PTX-induced increase of C-C chemokine ligand 2 (CCL-2) levels by GA. Meanwhile, the synergistic anti-tumor effect of GA and PTX has also been verified in vitro and in vivo experiments.Conclusion: The subcellular organelle targeted peptide modified PTX+GA multifunctional nano-drug delivery system has a good therapeutic effect on tumors, and this study provides significant insights into the role of different subcellular organelles in inhibiting tumor growth and metastasis and inspires researchers to develop highly effective cancer therapeutic strategies through subcellular organelle targeted drugs.Graphical Abstract: Keywords: breast cancer metastasis, gambogic acid, paclitaxel, mitochondria, nucleus

ABSTRACTThe clinical successes of immune checkpoint blockade (ICB) in advanced cancer patients have recently spurred the clinical implementation of ICB in the neoadjuvant and perioperative setting. However, how neoadjuvant ICB therapy affects the systemic immune landscape and metastatic spread remains to be established. Tumors promote both local and systemic expansion of regulatory T cells (Tregs), which are key orchestrators of tumor-induced immunosuppression, contributing to immune evasion, tumor progression and metastasis. Tregs express inhibitory immune checkpoint molecules and thus may be unintended targets for ICB therapy counteracting its efficacy. Using ICB-refractory models of spontaneous primary and metastatic breast cancer that recapitulate the poor ICB response of breast cancer patients, we observed that combined anti-PD-1 and anti-CTLA-4 therapy inadvertently promotes proliferation and activation of Tregs in the tumor, tumor-draining lymph node and circulation. Also in breast cancer patients, Treg levels were elevated upon ICB. Depletion of Tregs during neoadjuvant ICB in tumor-bearing mice not only reshaped the intratumoral immune landscape into a state favorable for ICB response but also induced profound and persistent alterations in systemic immunity, characterized by elevated CD8+ T cells and NK cells and durable T cell activation that was maintained after treatment cessation. While depletion of Tregs in combination with neoadjuvant ICB did not inhibit primary tumor growth, it prolonged metastasis-related survival driven predominantly by CD8+ T cells. This study demonstrates that neoadjuvant ICB therapy of breast cancer can be empowered by simultaneous targeting of Tregs, extending metastasis-related survival, independent of a primary tumor response.

Background: Nitric oxide is produced by different nitric oxide synthases isoforms. NO activates two signaling pathways, one dependent on soluble guanylate cyclase and protein kinase G, and other where NO post-translationally modifies proteins through S-nitrosylation, which is the modification induced by NO in free-thiol cysteines in proteins to form S-nitrosothiols. High levels of NO have been detected in blood of breast cancer patients and increased NOS activity has been detected in invasive breast tumors compared to benign or normal breast tissue, suggesting a positive correlation between NO biosynthesis, degree of malignancy and metastasis. During metastasis, the endothelium plays a key role allowing the adhesion of tumor cells, which is the first step in the extravasation process leading to metastasis. This step shares similarities with leukocyte adhesion to the endothelium, and it is plausible that it may also share some regulatory elements. The vascular cell adhesion molecule-1 (VCAM-1) expressed on the endothelial cell surface promotes interactions between the endothelium and tumor cells, as well as leukocytes. Data show that breast tumor cells adhere to areas in the vasculature where NO production is increased, however, the mechanisms involved are unknown. Results: We report that the stimulation of endothelial cells with interleukin-8, and conditioned medium from breast tumor cells activates the S-nitrosylation pathway in the endothelium to induce leukocyte adhesion and tumor cell extravasation by a mechanism that involves an increased VCAM-1 cell surface expression in endothelial cells. We identified VCAM-1 as an S-nitrosylation target during this process. The inhibition of NO signaling and S-nitrosylation blocked the transmigration of tumor cells through endothelial monolayers. Using an in vivo model, the number of lung metastases was inhibited in the presence of the S-nitrosylation inhibitor N-acetylcysteine (NAC), which was correlated with lower levels of S-nitrosylated VCAM-1 in the metastases. Conclusions: S-Nitrosylation in the endothelium activates pathways that enhance VCAM-1 surface localization to promote binding of leukocytes and extravasation of tumor cells leading to metastasis. NAC is positioned as an important tool that might be tested as a co-therapy against breast cancer metastasis. [ABSTRACT FROM AUTHOR]

Despite the advancements in breast cancer (BrC) diagnosis and treatment, a considerable proportion of patients with early-stage disease still experience local recurrence or metastasis. This study aimed to assess the levels of specific angiogenic parameters in the EDTA plasma of BrC patients before and after treatment and to explore their clinical and prognostic significance. The levels of vascular endothelial growth factor A (VEGF-A), soluble form of vascular endothelial growth factor receptor type 1 (sVEGFR1), and soluble form of vascular endothelial growth factor receptor type 2 (sVEGFR2) were measured in 84 early BrC patients, both prior to surgery and within a median time of nine months post-treatment. Prognostic significance was evaluated using Kaplan-Meier survival and Cox regression analyses. Linear regression models were employed to examine the independent impact of selected angiogenic factors on DFS in breast cancer patients. The results of uni- and multivariate analyses indicated that a pre-treatment concentration of sVEGFR1 above 30.99 pg/mL was associated with improved disease-free survival (DFS) (p < 0.0001 for both analyses), while a pre-treatment concentration of sVEGFR2 above 9475.67 pg/mL was associated with an increased risk of BrC relapse (p < 0.0001 for both analyses). Additionally, a post-treatment concentration of sVEGFR2 above 7361.71 pg/mL was associated with better overall survival (OS) based on the Kaplan-Meier survival analysis (p = 0.0141). Furthermore, linear regression models revealed a significant inverse association between pre-treatment levels of sVEGFR1 and the risk of relapse (standardized β −0.2578, p = 0.0499) and a significant positive association of VEGF-A levels with the risk of recurrence (standardized β 0.2958, p = 0.0308). In conclusion, the findings suggest that both pre- and post-treatment levels of sVEGFR1 and sVEGFR2 may hold promise as potential prognostic markers for BrC patients. [ABSTRACT FROM AUTHOR]

Up to 30% of breast cancer (BC) patients will develop distant metastases (DM), for which there is no cure. Here, statistical and machine learning (ML) models were developed to estimate the risk of site-specific DM following local-regional therapy. This retrospective study cohort included 175 patients diagnosed with invasive BC who later developed DM. Clinicopathological information was collected for analysis. Outcome variables were the first site of metastasis (brain, bone or visceral) and the time interval (months) to developing DM. Multivariate statistical analysis and ML-based multivariable gradient boosting machines identified factors associated with these outcomes. Machine learning models predicted the site of DM, demonstrating an area under the curve of 0.74, 0.75, and 0.73 for brain, bone and visceral sites, respectively. Overall, most patients (57%) developed bone metastases, with increased odds associated with estrogen receptor (ER) positivity. Human epidermal growth factor receptor-2 (HER2) positivity and non-anthracycline chemotherapy regimens were associated with a decreased risk of bone DM, while brain metastasis was associated with ER-negativity. Furthermore, non-anthracycline chemotherapy alone was a significant predictor of visceral metastasis. Here, clinicopathologic and treatment variables used in ML prediction models predict the first site of metastasis in BC. Further validation may guide focused patient-specific surveillance practices. [ABSTRACT FROM AUTHOR]

Tumor metastasis depends on the dynamic balance of the actomyosin cytoskeleton. As a key component of actomyosin filaments, non-muscle myosin-IIA disassembly contributes to tumor cell spreading and migration. However, its regulatory mechanism in tumor migration and invasion is poorly understood. Here, we found that oncoprotein hepatitis B X-interacting protein (HBXIP) blocked the myosin-IIA assemble state promoting breast cancer cell migration. Mechanistically, mass spectrometry analysis, co-immunoprecipitation assay and GST-pull down assay proved that HBXIP directly interacted with the assembly-competent domain (ACD) of non-muscle heavy chain myosin-IIA (NMHC-IIA). The interaction was enhanced by NMHC-IIA S1916 phosphorylation via HBXIP-recruited protein kinase PKCβII. Moreover, HBXIP induced the transcription of PRKCB, encoding PKCβII, by coactivating Sp1, and triggered PKCβII kinase activity. Interestingly, RNA sequencing and mouse metastasis model indicated that the anti-hyperlipidemic drug bezafibrate (BZF) suppressed breast cancer metastasis via inhibiting PKCβII-mediated NMHC-IIA phosphorylation in vitro and in vivo. We reveal a novel mechanism by which HBXIP promotes myosin-IIA disassembly via interacting and phosphorylating NMHC-IIA, and BZF can serve as an effective anti-metastatic drug in breast cancer.

Metastasis is a multi-step process that leads to the dissemination of tumor cells to new sites and, consequently, to multi-organ neoplasia. Although most lethal breast cancer cases are related to metastasis occurrence, little is known about the dysregulation of each step, and clinicians still lack reliable therapeutic targets for metastasis impairment. To fill these gaps, we constructed and analyzed gene regulatory networks for each metastasis step (cell adhesion loss, epithelial-to-mesenchymal transition, and angiogenesis). Through topological analysis, we identified E2F1, EGR1, EZH2, JUN, TP63, and miR-200c-3p as general hub-regulators, FLI1 for cell-adhesion loss specifically, and TRIM28, TCF3, and miR-429 for angiogenesis. Applying the FANMOD algorithm, we identified 60 coherent feed-forward loops regulating metastasis-related genes associated with distant metastasis-free survival prediction. miR-139-5p, miR-200c-3p, miR-454-3p, and miR-1301-3p, among others, were the FFL’s mediators. The expression of the regulators and mediators was observed to impact overall survival and to go along with metastasis occurrence. Lastly, we selected 12 key regulators and observed that they are potential therapeutic targets for canonical and candidate antineoplastics and immunomodulatory drugs, like trastuzumab, goserelin, and calcitriol. Our results highlight the relevance of miRNAs in mediating feed-forward loops and regulating the expression of metastasis-related genes. Altogether, our results contribute to understanding the multi-step metastasis complexity and identifying novel therapeutic targets and drugs for breast cancer management. [ABSTRACT FROM AUTHOR]

Recent studies have demonstrated that cancer-associated adipocytes (CAAs) in the tumor microenvironment are involved in the malignant progression of breast cancer. However, the underlying mechanism of CAA formation and its effects on the development of breast cancer are still unknown. Here, we show that CSF2 is highly expressed in both CAAs and breast cancer cells. CSF2 promotes inflammatory phenotypic changes of adipocytes through the Stat3 signaling pathway, leading to the secretion of multiple cytokines and proteases, particularly C–X–C motif chemokine ligand 3 (CXCL3). Adipocyte-derived CXCL3 binds to its specific receptor CXCR2 on breast cancer cells and activates the FAK pathway, enhancing the mesenchymal phenotype, migration, and invasion of breast cancer cells. In addition, a combination treatment targeting CSF2 and CXCR2 shows a synergistic inhibitory effect on adipocyte-induced lung metastasis of mouse 4T1 cells in vivo. These findings elucidate a novel mechanism of breast cancer metastasis and provide a potential therapeutic strategy for breast cancer metastasis. [ABSTRACT FROM AUTHOR]

Tumor metastasis depends on the dynamic balance of the actomyosin cytoskeleton. As a key component of actomyosin filaments, non-muscle myosin-IIA disassembly contributes to tumor cell spreading and migration. However, its regulatory mechanism in tumor migration and invasion is poorly understood. Here, we found that oncoprotein hepatitis B X-interacting protein (HBXIP) blocked the myosin-IIA assemble state promoting breast cancer cell migration. Mechanistically, mass spectrometry analysis, co-immunoprecipitation assay and GST-pull down assay proved that HBXIP directly interacted with the assembly-competent domain (ACD) of non-muscle heavy chain myosin-IIA (NMHC-IIA). The interaction was enhanced by NMHC-IIA S1916 phosphorylation via HBXIP-recruited protein kinase PKC β II. Moreover, HBXIP induced the transcription of PRKCB , encoding PKC β II, by coactivating Sp1, and triggered PKC β II kinase activity. Interestingly, RNA sequencing and mouse metastasis model indicated that the anti-hyperlipidemic drug bezafibrate (BZF) suppressed breast cancer metastasis via inhibiting PKC β II-mediated NMHC-IIA phosphorylation in vitro and in vivo. We reveal a novel mechanism by which HBXIP promotes myosin-IIA disassembly via interacting and phosphorylating NMHC-IIA, and BZF can serve as an effective anti-metastatic drug in breast cancer. This study reveals a novel mechanism by which HBXIP promotes myosin-IIA disassembly via interacting and phosphorylating NMHC-IIA, and the anti-hyperlipidemic drug bezafibrate can serve as an effective anti-metastatic drug in breast cancer. [Display omitted] [ABSTRACT FROM AUTHOR]

The clinical successes of immune checkpoint blockade (ICB) in advanced cancer patients have recently spurred the clinical implementation of ICB in the neoadjuvant and perioperative setting. However, how neoadjuvant ICB therapy affects the systemic immune landscape and metastatic spread remains to be established. Tumors promote both local and systemic expansion of regulatory T cells (Tregs), which are key orchestrators of tumor-induced immunosuppression, contributing to immune evasion, tumor progression and metastasis. Tregs express inhibitory immune checkpoint molecules and thus may be unintended targets for ICB therapy counteracting its efficacy. Using ICB-refractory models of spontaneous primary and metastatic breast cancer that recapitulate the poor ICB response of breast cancer patients, we observed that combined anti-PD-1 and anti-CTLA-4 therapy inadvertently promotes proliferation and activation of Tregs in the tumor, tumor-draining lymph node and circulation. Also in breast cancer patients, Treg levels were elevated upon ICB. Depletion of Tregs during neoadjuvant ICB in tumor-bearing mice not only reshaped the intratumoral immune landscape into a state favorable for ICB response but also induced profound and persistent alterations in systemic immunity, characterized by elevated CD8+ T cells and NK cells and durable T cell activation that was maintained after treatment cessation. While depletion of Tregs in combination with neoadjuvant ICB did not inhibit primary tumor growth, it prolonged metastasis-related survival driven predominantly by CD8+ T cells. This study demonstrates that neoadjuvant ICB therapy of breast cancer can be empowered by simultaneous targeting of Tregs, extending metastasis-related survival, independent of a primary tumor response. [ABSTRACT FROM AUTHOR]

Aim: Method: This research presents a model combining machine learning (ML) techniques and eXplainable artificial intelligence (XAI) to predict breast cancer (BC) metastasis and reveal important genomic biomarkers in metastasis patients. Method: A total of 98 primary BC samples was analyzed, comprising 34 samples from patients who developed distant metastases within a 5-year follow-up period and 44 samples from patients who remained disease-free for at least 5 years after diagnosis. Genomic data were then subjected to biostatistical analysis, followed by the application of the elastic net feature selection method. This technique identified a restricted number of genomic biomarkers associated with BC metastasis. A light gradient boosting machine (LightGBM), categorical boosting (CatBoost), Extreme Gradient Boosting (XGBoost), Gradient Boosting Trees (GBT), and Ada boosting (AdaBoost) algorithms were utilized for prediction. To assess the models’ predictive abilities, the accuracy, F1 score, precision, recall, area under the ROC curve (AUC), and Brier score were calculated as performance evaluation metrics. To promote interpretability and overcome the “black box” problem of ML models, a SHapley Additive exPlanations (SHAP) method was employed. Results: The LightGBM model outperformed other models, yielding remarkable accuracy of 96% and an AUC of 99.3%. In addition to biostatistical evaluation, in XAI-based SHAP results, increased expression levels of TSPYL5, ATP5E, CA9, NUP210, SLC37A1, ARIH1, PSMD7, UBQLN1, PRAME, and UBE2T (p ≤ 0.05) were found to be associated with an increased incidence of BC metastasis. Finally, decreased levels of expression of CACTIN, TGFB3, SCUBE2, ARL4D, OR1F1, ALDH4A1, PHF1, and CROCC (p ≤ 0.05) genes were also determined to increase the risk of metastasis in BC. Conclusion: The findings of this study may prevent disease progression and metastases and potentially improve clinical outcomes by recommending customized treatment approaches for BC patients.

Human homolog of mouse double minute 2 (HDM2) is an oncogene frequently overexpressed in cancers with poor prognosis, but mechanisms of controlling its abundance remain elusive. In an unbiased biochemical search, we discovered Skp1-Cullin 1-FBXO22-ROC1 (SCFFBXO22) as the most dominating HDM2 E3 ubiquitin ligase from human proteome. The results of protein decay rate analysis, ubiquitination, siRNA-mediated silencing, and coimmunoprecipitation experiments support a hypothesis that FBXO22 targets cellular HDM2 for ubiquitin-dependent degradation. In human breast cancer cells, FBXO22 knockdown (KD) increased cell invasiveness, which was driven by elevated levels of HDM2. Moreover, mouse 4T1 breast tumor model studies revealed that FBXO22 KD led to a significant increase of breast tumor cell metastasis to the lung. Finally, low FBXO22 expression is correlated with worse survival and high HDM2 expression in human breast cancer. Altogether, these findings suggest that SCFFBXO22 targets HDM2 for degradation and possesses inhibitory effects against breast cancer tumor cell invasion and metastasis.

Background: As per the WHO, more than 2 million new cases are diagnosed with breast cancer and more than 685,000 deaths have been reported in 2020. Incidence of recurrence and metastasis has also risen and poses a challenge for developing new therapies with the identification of newer targets. Methods: The objective of this study is to analyze and integrate various data across genomic, transcriptomic, and proteomic levels to find promising markers linked with tumor progression and metastasis development in breast cancer. This study begins with the extraction of data of differentially expressed proteins and subsequently analyzes their gene expression changes and genomic alterations to integrate all three omics data. We used curated breast cancer datasets of different proteomic experiments from dbDEPC3.0 and TCGA datasets of the Metastatic Breast Cancer Project to compare gene expressions and genomic alterations. We further used cBioportal, GeneMania, GEPIA2, Reactome, and canSAR computational tools for identifying the most significant genes associated with tumor progression and metastasis. Results: Based on false discovery rate, 14 genes were subjected to pathway analysis in Reactome and the top 25 significant pathways were analyzed out of a total of 170 pathways. Our study found fibrinogen gamma (FGG) and fibrinogen beta (FGB) linked to pathways connecting RAS-MAPK, its downstream mutants, integrin signaling, and extracellular matrix remodeling pathways. Conclusion: Survival analysis suggested that FGG (P = 0.0065) and FGB (P = 0.013) have a significant positive correlation along with their stage-wise changes in copy number variations and genomic alterations play a pivotal role in controlling tumor progression and metastasis.

Recent studies have shown that stress can substantially facilitate breast cancer metastasis, which can be reduced by nonselective β1/β2-adrenergic receptor (β1/β2-AR) blocker. However, several side effects were identified. Thus, it is extremely warranted to explore more effective and better-tolerated β2-AR blocker. Currently, we demonstrated that baicalin (BA), a major bioactive component of Scutellaria baicalensis Georgi, could significantly attenuate stress hormones especially epinephrine (Epi)-induced breast cancer cell migration and invasion in vitro. Mechanistically, we identified that β2-AR was a direct target of BA via the drug affinity responsive target stability (DARTS) combined with mass spectrum assay, and BA photoaffinity probe with pull-down assay, which was further confirmed by a couple of biophysical and biochemical assays. Furthermore, we demonstrated that BA could directly bind to the Phe-193 and Phe-289 of β2-AR, subsequently inhibit cyclic adenosine monophosphate-protein kinase A-focal adhesion kinase (cAMP-PKA-FAK) pathway, and thus impede epithelial-mesenchymal transition (EMT), thereby hindering the metastatic progression of the chronic stress coupled with syngeneic and xenograft in vivo orthotopic and tail vein mouse model. These findings firstly identify BA as a potential β2-AR inhibitor in the treatment of stress-induced breast cancer metastasis. Our data suggest that baicalin reduces chronic stress-induced breast cancer metastasis by directly binding to and consequentially blocking the activation of β2-AR. [Display omitted] • Baicalin reduces chronic stress-induced breast cancer metastasis. • Baicalin directly binds to and consequentially blocks the activation of β2-AR. • Baicalin acts as β2-AR inhibitor to treat stress-induced breast cancer metastasis. [ABSTRACT FROM AUTHOR]

Up to 30% of breast cancer (BC) patients will develop distant metastases (DM), for which there is no cure. Here, statistical and machine learning (ML) models were developed to estimate the risk of site-specific DM following local-regional therapy. This retrospective study cohort included 175 patients diagnosed with invasive BC who later developed DM. Clinicopathological information was collected for analysis. Outcome variables were the first site of metastasis (brain, bone or visceral) and the time interval (months) to developing DM. Multivariate statistical analysis and ML-based multivariable gradient boosting machines identified factors associated with these outcomes. Machine learning models predicted the site of DM, demonstrating an area under the curve of 0.74, 0.75, and 0.73 for brain, bone and visceral sites, respectively. Overall, most patients (57%) developed bone metastases, with increased odds associated with estrogen receptor (ER) positivity. Human epidermal growth factor receptor-2 (HER2) positivity and non-anthracycline chemotherapy regimens were associated with a decreased risk of bone DM, while brain metastasis was associated with ER-negativity. Furthermore, non-anthracycline chemotherapy alone was a significant predictor of visceral metastasis. Here, clinicopathologic and treatment variables used in ML prediction models predict the first site of metastasis in BC. Further validation may guide focused patient-specific surveillance practices.

Despite the advancements in breast cancer (BrC) diagnosis and treatment, a considerable proportion of patients with early-stage disease still experience local recurrence or metastasis. This study aimed to assess the levels of specific angiogenic parameters in the EDTA plasma of BrC patients before and after treatment and to explore their clinical and prognostic significance. The levels of vascular endothelial growth factor A (VEGF-A), soluble form of vascular endothelial growth factor receptor type 1 (sVEGFR1), and soluble form of vascular endothelial growth factor receptor type 2 (sVEGFR2) were measured in 84 early BrC patients, both prior to surgery and within a median time of nine months post-treatment. Prognostic significance was evaluated using Kaplan-Meier survival and Cox regression analyses. Linear regression models were employed to examine the independent impact of selected angiogenic factors on DFS in breast cancer patients. The results of uni- and multivariate analyses indicated that a pre-treatment concentration of sVEGFR1 above 30.99 pg/mL was associated with improved disease-free survival (DFS) (p < 0.0001 for both analyses), while a pre-treatment concentration of sVEGFR2 above 9475.67 pg/mL was associated with an increased risk of BrC relapse (p < 0.0001 for both analyses). Additionally, a post-treatment concentration of sVEGFR2 above 7361.71 pg/mL was associated with better overall survival (OS) based on the Kaplan-Meier survival analysis (p = 0.0141). Furthermore, linear regression models revealed a significant inverse association between pre-treatment levels of sVEGFR1 and the risk of relapse (standardized β −0.2578, p = 0.0499) and a significant positive association of VEGF-A levels with the risk of recurrence (standardized β 0.2958, p = 0.0308). In conclusion, the findings suggest that both pre- and post-treatment levels of sVEGFR1 and sVEGFR2 may hold promise as potential prognostic markers for BrC patients.

Breast cancer is the most commonly diagnosed cancer in the world, and metastasis is often the main cause of death in breast cancer patients. Salvia miltiorrhiza -Ginseng (SG) herb pair is clinically used for the treatment of cardiovascular diseases and cancers. However, the pharmacological action of this pair on breast cancer is yet unclear. In this study, a spontaneous metastasis model of breast cancer was constructed to assess the therapeutic value of SG. After administration of different doses of SG, the results showed that although it did not significantly inhibit tumor growth, high-dose SG administration could inhibit tumor metastasis. Then, based on systematic pharmacology combined with Gene Expression Omnibus (GEO) database, potential targets of drugs were identified such as vascular endothelial growth factor A (VEGFA), matrix metalloproteinase (MMP9), prostaglandin endoperoxide synthase2 (PTGS2), etc. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) analysis revealed that these targets were related to cytokine-mediated signaling pathway, cell migration and other biological processes and signaling pathways such as PI3K/Akt, etc. The systematic pharmacology analysis showed that SG effectively inhibited the VEGFA and MMP9-mediated biological events such as angiogenesis, epithelial-mesenchymal transition (EMT) and impaired tumor metastasis. Overall, our research aimed to provide new ideas for the treatment of breast cancer lung metastasis in traditional Chinese medicine.

Ageing is a major risk factor for cancer metastasis but the underlying mechanisms remain unclear. Here, we characterised ageing effects on cancer-induced endothelial-mesenchymal transition (EndMT) in the pulmonary circulation of female BALB/c mice in a metastatic 4T1 breast cancer model. The effect of intravenously injected 4T1 cells on pulmonary endothelium, pulmonary metastasis, lung tissue architecture, and systemic endothelium was compared between 40-week-old and 20-week-old mice. The 40-week-old mice showed features of ongoing EndMT in their lungs before 4T1 breast cancer cell injection. Moreover, they had preexisting endothelial dysfunction in the aorta detected by in vivo magnetic resonance imaging (MRI) compared to 20-week-old mice. The injection of 4T1 breast cancer cells into 40-week-old mice resulted in rapid EndMT progression in their lungs. In contrast, injection of 4T1 breast cancer cells into 20-week-old mice resulted in initiation and less pronounced EndMT progression. Although the number of metastases did not differ significantly between 20-week-old and 40-week-old mice, the lungs of older mice displayed altered lung tissue architecture and biochemical content, reflected in higher Amide II/Amide I ratio, higher fibronectin levels, and hypoxia-inducible factor 1 subunit alpha (HIF1α) levels as well as lower nitric oxide (NO) production. Our results indicate that age-dependent pre-existing endothelial dysfunction in the pulmonary endothelium of 40-week-old mice predisposed them to rapid EndMT progression in the presence of circulating 4T1 breast cancer cells what might contribute to a more severe metastatic breast cancer phenotype in these ageing mice compared to younger mice.

Tumor-initiating cells with reprogramming plasticity or stem-progenitor cell properties (stemness) are thought to be essential for cancer development and metastatic regeneration in many cancers; however, elucidation of the underlying molecular network and pathways remains demanding. Combining machine learning and experimental investigation, here we report CD81, a tetraspanin transmembrane protein known to be enriched in extracellular vesicles (EVs), as a newly identified driver of breast cancer stemness and metastasis. Using protein structure modeling and interface prediction-guided mutagenesis, we demonstrate that membrane CD81 interacts with CD44 through their extracellular regions in promoting tumor cell cluster formation and lung metastasis of triple negative breast cancer (TNBC) in human and mouse models. In-depth global and phosphoproteomic analyses of tumor cells deficient with CD81 or CD44 unveils endocytosis-related pathway alterations, leading to further identification of a quality-keeping role of CD44 and CD81 in EV secretion as well as in EV-associated stemness-promoting function. CD81 is coexpressed along with CD44 in human circulating tumor cells (CTCs) and enriched in clustered CTCs that promote cancer stemness and metastasis, supporting the clinical significance of CD81 in association with patient outcomes. Our study highlights machine learning as a powerful tool in facilitating the molecular understanding of new molecular targets in regulating stemness and metastasis of TNBC.

The extracellular matrix (ECM) is a complex meshwork comprising over 100 proteins. It serves as an adhesive substrate for cells and, hence, plays critical roles in health and disease. We have recently identified a novel ECM protein, SNED1, and have found that it is required for neural crest cell migration and craniofacial morphogenesis during development and in breast cancer, where it is necessary for the metastatic dissemination of tumor cells. Interestingly, both processes involve the dynamic remodeling of cell-ECM adhesions via cell surface receptors. Sequence analysis revealed that SNED1 contains two amino acid motifs, RGD and LDV, known to bind integrins, the largest class of ECM receptors. We thus sought to investigate the role of SNED1 in cell adhesion. Here, we report that SNED1 mediates breast cancer and neural crest cell adhesion via its RGD motif. We further demonstrate that cell adhesion to SNED1 is mediated by α5β1integrin. These findings are a first step toward identifying the signaling pathways activated downstream of the SNED1-integrin interactions guiding craniofacial morphogenesis and breast cancer metastasis., Competing Interests: COMPETING INTERESTS The Naba laboratory holds a sponsored research agreement with Boehringer-Ingelheim for work not related to the content of this manuscript. AN holds consulting agreements with AbbVie, XM Therapeutics, and RA Capital.

Abstract Background Metastasis represents the leading cause of death in patients with breast cancer. Traditional Chinese medicine is particularly appreciated for metastatic diseases in Asian countries due to its benefits for survival period prolongation and immune balance modulation. However, the underlying molecular mechanisms remain largely unknown. This study aimed to explore the antimetastatic effect and immunomodulatory function of a clinical formula Aiduqing (ADQ). Methods Naive CD4+ T cells, regulatory T cells (Tregs), and CD8+ T cells were sorted by flow cytometry. Then, breast cancer cells and these immune cells were co-cultured in vitro or co-injected into mice in vivo to simulate their coexistence. Flow cytometry, ELISA, qPCR, double luciferase reporter gene assay, and chromatin immunoprecipitation assay were conducted to investigate the immunomodulatory and antimetastatic mechanisms of ADQ. Results ADQ treatment by oral gavage significantly suppressed 4T1-Luc xenograft growth and lung metastasis in the orthotopic breast cancer mouse model, without noticeable hepatotoxicity, nephrotoxicity, or hematotoxicity. Meanwhile, ADQ remodeled the immunosuppressive tumor microenvironment (TME) by increasing the infiltration of tumor-infiltrating lymphocytes (TILs) and cytotoxic CD8+ T cells, and decreasing the infiltration of Tregs, naive CD4+ T cells, and tumor-associated macrophages (TAMs). Molecular mechanism studies revealed that ADQ remarkably inhibited CXCL1 expression and secretion from TAMs and thus suppressed the chemotaxis and differentiation of naive CD4+ T cells into Tregs, leading to the enhanced cytotoxic effects of CD8+ T cells. Mechanistically, TAM-derived CXCL1 promoted the differentiation of naive CD4+ T cells into Tregs by transcriptionally activating the NF-κB/FOXP3 signaling. Lastly, mouse 4T1-Luc xenograft experiments validated that ADQ formula inhibited breast cancer immune escape and lung metastasis by suppressing the TAM/CXCL1/Treg pathway. Conclusions This study not only provides preclinical evidence supporting the application of ADQ in inhibiting breast cancer metastasis but also sheds novel insights into TAM/CXCL1/NF-κB/FOXP3 signaling as a promising therapeutic target for Treg modulation and breast cancer immunotherapy. Video Abstract

Breast cancer (BC) is the most common cancer affecting women worldwide, with over 2 million women diagnosed every year, and close to 8 million women currently alive following a diagnosis of BC in the last 5-years. The side effects such as chemodrug toxicity to healthy tissues and drug resistance severely affect the quality of life of BC patients. To overcome these limitations, many efforts have been made to develop nanomaterial-based drug delivery systems. Among these nanocarriers, lipid-based delivery platforms represented one of the most successful candidates for cancer therapy, improving the safety profile and therapeutic efficacy of encapsulated drugs. In this review we will mainly discuss and summarize the recent advances in such delivery systems for BC metastasis treatment, with a particular focus on targeting the common metastatic sites in bone, brain and lung. We will also provide our perspectives on lipid-based nanocarrier development for future clinical translation.

Background: As per the WHO, more than 2 million new cases are diagnosed with breast cancer and more than 685,000 deaths have been reported in 2020. Incidence of recurrence and metastasis has also risen and poses a challenge for developing new therapies with the identification of newer targets. Methods: The objective of this study is to analyze and integrate various data across genomic, transcriptomic, and proteomic levels to find promising markers linked with tumor progression and metastasis development in breast cancer. This study begins with the extraction of data of differentially expressed proteins and subsequently analyzes their gene expression changes and genomic alterations to integrate all three omics data. We used curated breast cancer datasets of different proteomic experiments from dbDEPC3.0 and TCGA datasets of the Metastatic Breast Cancer Project to compare gene expressions and genomic alterations. We further used cBioportal, GeneMania, GEPIA2, Reactome, and canSAR computational tools for identifying the most significant genes associated with tumor progression and metastasis. Results: Based on false discovery rate, 14 genes were subjected to pathway analysis in Reactome and the top 25 significant pathways were analyzed out of a total of 170 pathways. Our study found fibrinogen gamma (FGG) and fibrinogen beta (FGB) linked to pathways connecting RAS-MAPK, its downstream mutants, integrin signaling, and extracellular matrix remodeling pathways. Conclusion: Survival analysis suggested that FGG (P = 0.0065) and FGB (P = 0.013) have a significant positive correlation along with their stage-wise changes in copy number variations and genomic alterations play a pivotal role in controlling tumor progression and metastasis. [ABSTRACT FROM AUTHOR]

Metastatic disease to the liver is a known and common site of breast cancer spread, classically presenting as either hypovascular or hypervascular masses. Rarely, hepatic metastatic disease may have an atypical diffuse and intrasinusoidal pattern of involvement, which may be radiographically occult or extremely challenging to diagnose even with multiphase contrast enhanced techniques. We report a case of a 28-year-old female with stage III invasive ductal carcinoma of the breast, who recently discontinued treatment due to pregnancy, presenting with progressive signs and symptoms of rapidly decompensating liver failure due to sinusoidal obstruction. Multimodality imaging was performed without evidence for focal hepatic metastatic disease; however, intrahepatic vein (IVC) compression was noted. Hepatic sinusoidal tumor infiltration was confirmed by liver biopsy. After palliative chemotherapy the disease became less infiltrative and more conspicuous on imaging, revealing itself as hepatic metastases, with decreased compression of the intrahepatic IVC and resolution of signs and symptoms of sinusoidal obstruction syndrome.

[Display omitted] • A series of pyrazolo[1,5- a ]pyrimidine analogs were designed as selective ROCK2 inhibitors. • 7u exerted optimum ROCK2 inhibitory activity and excellent selectivity over the isoform protein. • 7u inhibited MDA-MB-231 cell migration and invasion in a dose dependent manner. • The binding model of 7u with ROCK2 well accounted for its superior activities. Rho-associated coiled-coil kinase (ROCK) is involved in multiple cellular activities regulating the actin cytoskeleton, such as cell morphology, adhesion, and migration. The inhibition of ROCK is a feasible strategy to suppress breast cancer metastasis. Herein, based on Belumosudil, a series of pyrazolo[1,5- a ]pyrimidine derivatives as selective ROCK2 inhibitors were designed and synthesized. Through systematic investigation of SARs, the piperazine analog 7u was identified with optimum ROCK2 inhibitory activity (IC 50 = 36.8 nM) and excellent selectivity over the isoform protein ROCK1 (>250-fold). Intriguingly, upon treatment with 7u , the arrangement of the MDA-MB-231 cytoskeleton was affected accompanied by the alteration of morphology. Furthermore, cell scratch and transwell assays indicated that 7u inhibited MDA-MB-231 cell migration and invasion in a dose-dependent manner. Ultimately, the binding model of 7u with ROCK2 well accounted for the superior activities of 7u as a promising ROCK2 inhibitor with the potential application in breast cancer metastasis treatment. [ABSTRACT FROM AUTHOR]

Breast cancer bone metastasis poses significant challenge for therapeutic strategies. Inside the metastatic environment, osteoclasts and tumor cells interact synergistically to promote cancer progression. In this study, the proprotein convertase furin is targeted due to its critical roles in both tumor cell invasion and osteoclast function. Importantly, the furin inhibitor is specifically delivered by bone targeting superparamagnetic iron oxide (SPIO) nanoparticles. Our in vitro and in vivo data demonstrate that this system can effectively inhibit both osteoclastic bone resorption and breast cancer invastion, leading to alleviated osteolysis. Therefore, the bone targeting & furin inhibition nanoparticle system is a promising therapeutic and diagnostic strategy for breast cancer bone metastasis.

Breast cancer lung metastases (BCLM) are a major cause of high mortality in patients. The shortage of therapeutic targets and rapid drug screening tools for BCLM is a major challenge at present. Mitochondrial autophagy, which involves the degradation of proteins associated with cancer cell aggressiveness, represents a possible therapeutic approach for the treatment of BCLM. Herein, four fluorescent biosensors with different alkyl chains were designed and synthesized to monitor mitochondrial autophagy. Among them, PMV-12 demonstrated the highest sensitivity to viscosity variance, the least impact on polarity, and the longest imaging time. The introduction of the C 12 -chain made PMV-12 anchored in the mitochondrial membrane without being disturbed by changes of the mitochondrial membrane potential (MMP), thereby achieving the long-term monitor in situ for mitochondrial autophagy. Mitochondria stained with PMV-12 induced swelling and viscosity increase after treating with apigenin, which indicated that apigenin is a potential mitochondrial autophagy inducer. Apigenin was subsequently verified to inhibit cancer cell invasion by 92%. Furthermore, PMV-12 could monitor the process of BCLM in vivo and evaluate the therapeutic effects of apigenin. This work provides a fluorescent tool for elucidating the role of mitochondrial autophagy in the BCLM process and for anti-metastatic drug development. [Display omitted] [ABSTRACT FROM AUTHOR]

Breast cancer has the highest incidence and death rate among women; moreover, its metastasis to other organs increases the mortality rate. Since several studies have reported gene expression and cancer prognosis to be related, the study of breast cancer metastasis using gene expression is crucial. To this end, a novel deep neural network architecture, deep learning-based cancer metastasis estimator (DeepCME), is proposed in this paper for predicting breast cancer metastasis. However, the problem of overfitting occurs frequently while training deep learning models using gene expression data because they contain a large number of genes and the sample size is rather small. To address overfitting, several regularization methods are implemented, such as L1 penalty, batch normalization, and dropout. To demonstrate the superior performance of our model, area under curve (AUC) scores are evaluated and then compared with five baseline models: logistic regression, support vector classifier (SVC), random forest, decision tree, and k -nearest neighbor. Considering results, DeepCME demonstrates the highest average AUC scores in most cross-validation cases, and the average AUC score of DeepCME is 0.754, which is approximately 12.9% higher than SVC, the second-best model. In addition, the 30 most significant genes related to breast cancer metastasis are identified based on DeepCME results and some are discussed in further detail considering the reports from some previous medical studies. Considering the high expense involved in measuring the expression of a single gene, the ability to develop the cost-effective and time-efficient tests using only a few key genes is valuable. Based on this study, we expect DeepCME to be utilized clinically for predicting breast cancer metastasis and be applied to other types of cancer as well after further research.

Several machine learning algorithms have demonstrated high predictive capability in the identification of cancer within digitized pathology slides. The Augmented Reality Microscope (ARM) has allowed these algorithms to be seamlessly integrated within the pathology workflow by overlaying their inferences onto its microscopic field of view in real time. We present an independent assessment of the LYmph Node Assistant (LYNA) models, state-of-the-art algorithms for the identification of breast cancer metastases in lymph node biopsies, optimized for usage on the ARM. We assessed the models on 40 whole slide images at the commonly used objective magnifications of 10×, 20×, and 40×. We analyzed their performance across clinically relevant subclasses of tissue, including breast cancer, lymphocytes, histiocytes, blood, and fat. Each model obtained overall AUC values of approximately 0.98, accuracy values of approximately 0.94, and sensitivity values above 0.88 at classifying small regions of a field of view as benign or cancerous. Across tissue subclasses, the models performed most accurately on fat and blood, and least accurately on histiocytes, germinal centers, and sinus. The models also struggled with the identification of isolated tumor cells, especially at lower magnifications. After testing, we reviewed the discrepancies between model predictions and ground truth to understand the causes of error. We introduce a distinction between proper and improper ground truth for analysis in cases of uncertain annotations. Taken together, these methods comprise a novel approach for exploratory model analysis over complex anatomic pathology data in which precise ground truth is difficult to establish.

Background: Metastasis represents the leading cause of death in patients with breast cancer. Traditional Chinese medicine is particularly appreciated for metastatic diseases in Asian countries due to its benefits for survival period prolongation and immune balance modulation. However, the underlying molecular mechanisms remain largely unknown. This study aimed to explore the antimetastatic effect and immunomodulatory function of a clinical formula Aiduqing (ADQ). Methods: Naive CD4+ T cells, regulatory T cells (Tregs), and CD8+ T cells were sorted by flow cytometry. Then, breast cancer cells and these immune cells were co-cultured in vitro or co-injected into mice in vivo to simulate their coexistence. Flow cytometry, ELISA, qPCR, double luciferase reporter gene assay, and chromatin immunoprecipitation assay were conducted to investigate the immunomodulatory and antimetastatic mechanisms of ADQ. Results: ADQ treatment by oral gavage significantly suppressed 4T1-Luc xenograft growth and lung metastasis in the orthotopic breast cancer mouse model, without noticeable hepatotoxicity, nephrotoxicity, or hematotoxicity. Meanwhile, ADQ remodeled the immunosuppressive tumor microenvironment (TME) by increasing the infiltration of tumor-infiltrating lymphocytes (TILs) and cytotoxic CD8+ T cells, and decreasing the infiltration of Tregs, naive CD4+ T cells, and tumor-associated macrophages (TAMs). Molecular mechanism studies revealed that ADQ remarkably inhibited CXCL1 expression and secretion from TAMs and thus suppressed the chemotaxis and differentiation of naive CD4+ T cells into Tregs, leading to the enhanced cytotoxic effects of CD8+ T cells. Mechanistically, TAM-derived CXCL1 promoted the differentiation of naive CD4+ T cells into Tregs by transcriptionally activating the NF-κB/FOXP3 signaling. Lastly, mouse 4T1-Luc xenograft experiments validated that ADQ formula inhibited breast cancer immune escape and lung metastasis by suppressing the TAM/CXCL1/Treg pathway. Conclusions: This study not only provides preclinical evidence supporting the application of ADQ in inhibiting breast cancer metastasis but also sheds novel insights into TAM/CXCL1/NF-κB/FOXP3 signaling as a promising therapeutic target for Treg modulation and breast cancer immunotherapy. 5spcww6AwskguE5dGnjCJQ Video Abstract [ABSTRACT FROM AUTHOR]

Breast cancer is an aggressive silent disease, representing 11.7% of the diagnosed cancer worldwide, and it is also a leading cause of death in Saudi Arabia. Consequently, microRNAs have emerged recently as potential biomarkers to diagnose and monitor such cases at the molecular level, which tends to be problematic during diagnosis. MicroRNAs are highly conserved non- coding oligonucleotide RNA. Over the last two decades, studies have determined the functional significance of these small RNAs and their impact on cellular development and the interaction between microRNAs and messenger RNAs, which affect numerous molecular pathways and physiological functions. Moreover, many disorders, including breast cancer, are associated with the dysregulation of microRNA. Sparingly, many microRNAs can suppress cancer cell proliferation, apoptosis, angiogenesis, invasion, metastasis, and vice versa. Remarkably, microRNAs can be harvested from patients' biofluids to predict disease progression that considered a non-invasive method. Nevertheless, MicroRNAs are currently utilized as anti- cancer therapies combined with other drug therapies or even as a single agents' treatment. Therefore, this review will focus on microRNAs' role in breast cancer as an indicator of disease progression. In addition, this review summarizes the current knowledge of drug sensitivity and methods in detecting microRNA and their application to improve patient care and identifies the current gaps in this field. [ABSTRACT FROM AUTHOR]

Abstract Background The abundance of molecular profiling of breast cancer tissues entailed active research on molecular marker-based early diagnosis of metastasis. Recently there is a surging interest in combining gene expression with gene networks such as protein-protein interaction (PPI) network, gene co-expression (CE) network and pathway information to identify robust and accurate biomarkers for metastasis prediction, reflecting the common belief that cancer is a systems biology disease. However, controversy exists in the literature regarding whether network markers are indeed better features than genes alone for predicting as well as understanding metastasis. We believe much of the existing results may have been biased by the overly complicated prediction algorithms, unfair evaluation, and lack of rigorous statistics. In this study, we propose a simple approach to use network edges as features, based on two types of networks respectively, and compared their prediction power using three classification algorithms and rigorous statistical procedure on one of the largest datasets available. To detect biomarkers that are significant for the prediction and to compare the robustness of different feature types, we propose an unbiased and novel procedure to measure feature importance that eliminates the potential bias from factors such as different sample size, number of features, as well as class distribution. Results Experimental results reveal that edge-based feature types consistently outperformed gene-based feature type in random forest and logistic regression models under all performance evaluation metrics, while the prediction accuracy of edge-based support vector machine (SVM) model was poorer, due to the larger number of edge features compared to gene features and the lack of feature selection in SVM model. Experimental results also show that edge features are much more robust than gene features and the top biomarkers from edge feature types are statistically more significantly enriched in the biological processes that are well known to be related to breast cancer metastasis. Conclusions Overall, this study validates the utility of edge features as biomarkers but also highlights the importance of carefully designed experimental procedures in order to achieve statistically reliable comparison results.

Abstract Background Discovering a highly accurate and robust gene signature for the prediction of breast cancer metastasis from gene expression profiling of primary tumors is one of the most challenging tasks to reduce the number of deaths in women. Due to the limited success of gene-based features in achieving satisfactory prediction accuracy, many methodologies have been proposed in recent years to develop network-based features by integrating network information with gene expression. However, evaluation results are inconsistent to confirm the effectiveness of network-based features, because of many confounding factors involved in classification model learning process, such as data normalization, dimension reduction, and feature selection. An unbiased comparative evaluation is essential for uncovering the strength of network-based features. Methods In this study, we compared several types of network-based features obtained using different mathematical operators (Mean, Maximum, Minimum, Median, Variance) on geneset (i.e., a gene and its’ neighbors in the network) in protein-protein interaction network and gene co-expression network for their ability in predicting breast cancer metastasis using gene expression data from more than 10 patient cohorts. Results While network-based features are usually statistically more significant than gene-based feature, a consistent improvement of prediction performance using network-based features requires a substantial number of patients in the dataset. In contrary to many previous reports, no evidence was found to support the robustness of network-based features and we argue some of the robustness may be due to the inherent bias associated with node degree in the network. In addition, different types of network features seem to cover different pathways and are complementary to each other. Consequently, an ensemble classifier combining different network features was proposed and was found to significantly outperform classifiers based on gene-based feature or any single type of network-based features. Conclusions Network-based features and their combination show promise for improving the prediction of breast cancer metastasis but may require a large amount of training data. Robustness claim of network-based features needs to be re-examined with network node degree and other confounding factors in consideration.

An 80-year-old woman with a history of breast cancer 16 years ago presented with malnutrition, swelling, and paresthesia of the right cheek. Computed tomography revealed diffuse osteosclerosis without lysis and adjacent soft tissue swelling on the right mandible. These radiological findings were more compatible with primary chronic osteomyelitis than metastasis from breast cancer, and biopsy was necessary for diagnosis. This report describes breast cancer metastasis mimicking primary chronic osteomyelitis 16 years after diagnosis and its differential diagnosis in the mandible.

Brain metastases affect one-third of patients with HER2-positive breast cancer. However, solitary pituitary metastases are rare and are often difficult to diagnose. A better understanding of its clinical and radiological manifestations may lead to earlier diagnosis and treatment. Therefore, we present this case report of a patient with a solitary pituitary metastasis, focusing on her diagnosis and treatment.