Breast cancer is the leading cause of cancer deaths worldwide in women. This aggressive tumour can be categorized into two main groups: in situ and infiltrative, with the latter being the most common malignant lesions. The current use of Magnetic Resonance Imaging (MRI) was shown to provide highest sensitivity in the detection and discrimination between benign vs. malignant lesions, when interpreted by expert radiologists. In this article, we present the prototype of a Computer-Aided Detection/Diagnosis (CAD) system that could provide valuable assistance to the radiologist for the discrimination between in situ and infiltrating tumours. The system consists of two main processing levels: 1) Localization of possibly tumoral regions of interest (ROIs) through an iterative procedure based on intensity values (ROI Hunter) followed by a deep-feature extraction and classification method for false-positive rejection; 2) Characterization of the selected ROIs and discrimination between in situ and invasive tumour, consisting of Radiomics feature extraction and classification through a machine-learning algorithm. The CAD system was developed and evaluated using a DCE-MRI image database, containing at least one confirmed mass per image, as diagnosed by an expert radiologist. When evaluating the accuracy of the ROI Hunter procedure with respect to the radiologist-drawn boundaries, sensitivity to mass detection was found to be 75%. The AUC of the ROC curve for discrimination between in situ and infiltrative tumors was 0.70.

We previously described a model of deep intrinsic resistance of breast cancer wherein we used a function-based approach to selection of cancer cells that can survive a variety of challenges in prolonged but reversible quiescence. Our experimental results suggested that resistant cancer cells possess a variety of mechanisms, including modifications of the epigenome and transcriptome, for generating a high degree of cellular heterogeneity. In the present study, we evaluated JIB-04, a small-molecule epigenetic inhibitor initially discovered to inhibit cancer growth, to determine its ability to affect deep intrinsic resistance in our breast cancer model. We found that long pretreatment with JIB-04 sensitized resistant triple-negative inflammatory breast cancer cells and their parental cell line SUM149 to the chemotherapeutic drugs doxorubicin and paclitaxel. Resistant cancer cells derived from another inflammatory breast cancer cell line, FC-IBC02, were considerably more sensitive to JIB-04 than was the parental cell line. Investigating a mechanism of sensitization, we found that JIB-04 exposure increased the expression of PD-L1 in resistant cells, suggesting that JIB-04 may also sensitize resistant breast cancer cells to anti-PD-L1 immune therapy. Finally, these results support the usefulness of our experimental strategy for evaluating anticancer agents such as JIB-04 that may halt cancer evolution and prevent development of cancer resistance to currently used therapies.

Breast cancer is a complex and heterogeneous disease that displays diverse molecular subtypes and clinical outcomes. Although it is known that the location of tumors can affect their biological behavior, the underlying mechanisms are not fully understood. In our previous study, we found a differential methylation profile and membrane potential between left (L) and right (R)-sided breast tumors. In this current study, we aimed to identify the ion channels responsible for this phenomenon and determine any associated phenotypic features. To achieve this, experiments were conducted in mammary tumors in mice, human patient samples, and with data from public datasets. The results revealed that L-sided tumors have a more depolarized state than R-ones. We identified a 6-ion channel-gene signature (CACNA1C, CACNA2D2, CACNB2, KCNJ11, SCN3A, and SCN3B) associated with side: L-tumors exhibit lower expression levels than R-ones. Additionally, in silico analyses show that the signature correlates inversely with DNA methylation writers and with key biological processes involved in cancer progression, such as proliferation and stemness. The signature also correlates inversely with patients’ survival rates. In an in vivo mouse model, we confirmed that KI67 and CD44 markers were increased in L-sided tumors and similar tendency for KI67 was found in patient L-tumors. Overall, this study provides new insights into the potential impact of anatomical location on breast cancer biology and highlights the need for further investigation into possible differential treatment options.

PIK3CA is a gene usually mutated in breast cancer and has an important role in tumor progression and treatment. Therefore, there is required a technique to detect low-rate PIK3CA mutations improving the clinical conduct. This study aimed to compare chip-based dPCR and Sanger sequencing to detect PIK3CA mutations in breast cancer patients. Fifty-seven tumor samples from breast cancer patients were collected and analyzed by Sanger sequencing and dPCR for PIK3CA mutations (E545K, H1047R, and H1047L). Digital PCR sensitivity, specificity, and overall performance were estimated by contingency tables, receptor operator characteristic (ROC), and area under the curve (AUC). Sanger sequencing identified PIK3CA mutations in six patients (10.5%), two with H1047R, and four with E545K. Digital PCR confirmed those mutations and identified 19 additional patients with at least one mutation. Comparison between dPCR and Sanger sequencing showed a sensitivity of 100% (95% CI 53-100%), and a specificity of 84.2% (95% CI 83 - 84.2%). Besides, H1047R mutation showed a significant association with breast cancer phenotype (p =0.019) and lymphatic node infiltration (p =0.046). Digital PCR showed a high sensitivity to detect mutations in tumor samples and it might be capable to detect low-rate mutations and tumor subpopulations not detected by Sanger sequencing.

Aims: To assess the occurrence of Chemotherapy-induced nausea and vomiting (CINV) after standard antiemetic therapy in the acute (24 h post-chemotherapy) and delayed (2–5 days post-chemotherapy) phases, as well as to identify risk factors for CINV in the acute and delayed phases. Methods: This prospective longitudinal and observational study analyzed the data of 400 breast cancer patients scheduled for chemotherapy over two cycles in two hospitals. The self-report survey was developed to assess the occurrence of CINV and their associated factors. CINV was evaluated with a Multinational Association of Supportive Care in Cancer Antiemetic Tool (MAT) on days 2 and 6 of chemotherapy. The incidence of acute and delayed CINV were presented by frequency and percentage. Generalized equation estimates (GEE) was used to identify risk factors of acute and delayed CINV. Results: There were 400 evaluable patients with complete Round 1 data, 334 for Round 2 data. Among 400 patients, 29.8% and 23.5% experienced acute and delayed CINV, respectively. Risk factors associated with for acute CINV were pain/insomnia, history of CINV, history of motion sickness (MS), and highly emetogenic chemotherapy regimen, while history of MS, CINV history, number of completed chemotherapy cycle number < 3, and the incidence of acute CINV were risk factors of delayed CINV (all p < 0.05). Conclusions: The findings may help nurses working for Chinese population in identifying patients at risk for CINV and in planning effective program to reduce the occurrence of CINV.

Chemotherapy-related deaths, the result of treatment with faulty medications, account for nearly 10% of all breast cancer deaths (Rashbass, 2016). Patient-specific, personalized medicine is evidently required to administer optimized therapeutics and prevent treatment-related mortality. In order to develop a predictive model for breast cancer therapy, the following study analyzed the mRNA data of 4,704 genes derived from 20 breast cancer patients before and after doxorubicin treatment for 16 weeks (O’brien et al., 2006; Perou et al., 2000). The genomic data of each patient was first stratified into 9 groups (corresponding to the 9 Mechanisms defined in Figure 4) based on mRNA expression in response to the tumor and to the doxorubicin treatment. The study then employed the Planckian Distribution Equation (PDE) discovered at Rutgers University to model the stratified samples by transforming each mechanism into a single long-tailed histogram fitted by the PDE. Our PDE model is based on 3 parameters - A, B, and C - of which 2 were extracted from each model to generate the plots seen in figures 5e and 5f. The drug-induced slopes of the A vs C plots were then determined for all 9 mechanisms of each patient. The study observed an increase in post-treatment mRNA levels for longer surviving patients in 6 mechanisms. Further analysis displayed how the drug treatment uniquely altered each of the mechanisms based on the length of patient survival. These results indicate that the PDE-based procedures described herein may provide a novel tool for discovering potential anti-breast cancer pharmaceuticals.

Breast cancer pathogenesis, treatment, and patient outcomes are shaped by tumor-intrinsic genomic alterations that divide breast tumors into molecular subtypes. These molecular subtypes often dictate viable therapeutic interventions, and ultimately, patient outcomes. However, heterogeneity of therapeutic response may be a result of underlying epigenetic features that may further stratify breast cancer patient outcomes. In this review we examine non-genetic mechanisms that drive functional changes to chromatin in breast cancer to contribute to cell and tumor fitness, and highlight how epigenetic activity may inform therapeutic response. We conclude by providing perspectives on the future of therapeutic targeting of epigenetic enzymes, an approach which holds untapped potential to improve breast cancer patient outcomes.

Breast cancer (BC) is the most common malignancy and second only to lung cancer in terms of mortality in women. Despite the incredible progress made in this field, the metastatic breast cancer leaves a poor prognosis. In an era of personalized medicine, there is an urgent need for a better knowledge of the biology leading to the disease, which can lead to the design of always more accurate drugs against patients’ specific molecular aberrations. Among one of the actionable targets is the Fibroblast Growth Factor Receptor (FGFR) pathway, triggered by specific ligands. The FGFRs/FGFs axis offers interesting molecular targets to be pursued in clinical development. This mini-review will focus on the current knowledge of the FGFRs mutations leading to tumour formation and summarizes the state-of-the-art of therapeutic strategies for targeted treatments against the FGFRs/FGFs axis in the context of BC.

Deep convolutional neural networks (CNNs) have been widely used in various medical imaging tasks. However, due to the intrinsic locality of convolution operation, CNNs generally cannot model long-range dependencies well, which are important for accurately identifying breast cancer from unregistered multi-view mammograms. This motivates us to leverage the architecture of Vision Transformers to capture long-range relationships of multiple mammograms from the same patient. For this purpose, we employ local Transformer blocks to separately learn patch relationships within a specific view (CC/MLO) of one side (right/left) of mammogram. The outputs from different views and sides are concatenated and fed into global Transformer blocks, to jointly learn patch relationships between two different views of the left and right breasts. To evaluate the proposed model, we retrospectively assembled a dataset involving 949 sets of CC and MLO view mammograms, which include 470 malignant cases and 479 normal or benign cases. We trained and evaluated the model using a five-fold cross-validation method. Without any arduous preprocessing steps (e.g., optimal window cropping, chest wall or pectoral muscle removal, two-view image registration, etc.), our two-view Transformer-based model achieves lesion classification accuracy of 77.0% and area under ROC curve (AUC = 0.814), outperforming state-of-the-art multi-view CNNs by 3.1% and 3%, respectively. Meanwhile, the new two-view model improves mammographic case classification accuracies of two single-view models by 7.4% (CC) and 4.5% (MLO), respectively. The promising results unveil the great potential of using Transformers to develop high-performing computer-aided diagnosis (CADx) schemes of mammography.

Breast cancer (BC) is the second leading cause of death in the United States in women. 1 in 8 women in their lifetime has a risk of developing breast cancer. With advances in omics technology, more data is available for diagnosis, treatment, and prognosis. The help of Machine Learning algorithms, a subdomain of Artificial Intelligence, would allow for a better clinical support tool. Machine Learning could be the key to answering a complex problem in BC. The methodology of this research question involves collecting and finding data such as RNA-Seq datasets, selecting and training appropriate machine learning algorithms, and evaluating the performance of the algorithms in predicting BC prognosis. Also, the study explores and tries to identify the most relevant genes and pathways through feature selection extraction and dimensionality reduction techniques. After applying feature extraction, the top 10 genes were extracted using the Univariate Feature Selection (UFS) method, precisely the SelectKBest technique. After employing different machine learning algorithms, such as Networks, Random Forest, Linear SVM, Logistic Regression, and Quadratic Discriminant Analysis (QDA), we found QDA was the best model in classifying the RNA-seq dataset with a 96% accuracy rate and 94% ROC AUC. This study suggests that AK2 and CD68 have a positive correlation with each other, and it could potentially be a biomarker and therapeutic target for BC.

Rutin has been reported as a potential anti-cancer agent for several decades. This study evaluated the effects of rutin on the proliferation, metastasis, and angiogenesis of MDA-MB-231 and MCF-7 breast cancer cell lines. Increasing concentrations of rutin significantly stimulated the proliferation of MDA-MB-231 and MCF-7 cells compared to controls. Wound scratch assay demonstrated that rutin had an inducing effect on the migration of the cells. In MDA-MB-231 and MCF-7 cells, rutin upregulated MKI67, VIM, CDH2, FN1, and VEGFA and downregulated CDH1 and THBS1 genes. It also increased N-cadherin and VEGFA and decreased E-cadherin and thrombospondin 1 protein expression. Our data indicated that rutin could stimulate proliferation, migration, and pro-angiogenic activity in two different breast cancer cell lines. This phytoestrogen induced invasion and migration of both cell lines by a mechanism involving the EMT process. This suggests that rutin may act as a breast cancer-promoting phytoestrogen.

Close to half (45.4%) of 2.3 million breast cancers (BC) diagnosed in 2020 were from Asia. While the burden of breast cancer has been examined on the level of broad geographic regions, literature on more in-depth coverage of the individual countries and subregions of the Asian continent is lacking. This review examines the breast cancer burden in 47 Asian countries. Breast cancer screening guidelines and risk-based screening initiatives are discussed.

This narrative review aims to clarify the role of tertiary lymphoid structures in breast cancer. We examine their development, composition, prognostic value and current ways of recognising them. A comprehensive literature review was performed using PubMed/Medline, Scopus and EMBASE databases. A significant area of interest in breast cancer research involves targeting immune checkpoint molecules, particularly in the triple-negative subtype, where treatment options remain limited. However, existing biomarkers have limitations in accurately predicting treatment response.  In this context, tertiary lymphoid structures (TLS) emerge as a prognostic biomarker and also as a promising predictive marker for response. TLS are ectopic lymphoid formations or neo-organogenesis that can develop after prolonged exposure to inflammatory signals mediated by chemokines and cytokines. Their presence is inversely correlated with estrogen receptor (ER) and/or progesterone receptor (PR) expression, but positively associated with a higher pathologic complete response rate and improved overall  survival. In certain scenarios, TLS-positive tumors were associated with improved outcomes regardless of the presence of PDL-1 (programmed cell death ligand 1) expression or and TILs (tumor-infiltrating lymphocytes).

Background: Metastatic triple-negative breast cancer (TNBC) is aggressive with a poor median overall survival (OS), ranging from 8 to 13 months. There exists considerable heterogeneity in the survival at the individual patient level. To better understand the survival heterogeneity and improve risk stratification, our study aims to identify the factors influencing survival utilizing a large patient sample in the National Cancer Database (NCDB). Methods: Women diagnosed with metastatic TNBC from 2010 to 2020 in the NCDB were included. Demographic, clinic-pathological, treatment data, and overall survival (OS) outcomes were collected. Kaplan-Meier curves were used to estimate OS. The log-rank test was used to identify OS differences between groups for each variable in the univariate analysis. For the multivariate analysis, the Cox proportional hazard model with backward elimination was used to identify factors affecting OS. Adjusted hazard ratios and 95% confidence intervals are presented. Results: 2,273 women had a median overall survival of 13.6 months. Factors associated with statistically significantly worse OS included older age, higher comorbidity scores, specific histologies, higher number of metastatic sites, presence of liver or other site metastases in those with only one metastatic site (excluding brain metastases), presence of cranial and extra-cranial metastases, lack of chemotherapy, lack of immunotherapy, lack of surgery to distant sites, lack of radiation to distant sites, and receipt of palliative treatment to alleviate symptoms. In the multivariate analysis, comorbidity score, histology, number of metastatic sites, immunotherapy, and chemotherapy had a statistically significant effect on the OS. Conclusions: Through NCDB analysis, we have identified prognostic factors for metastatic TNBC. These findings will help improve prognostication at diagnosis, optimize treatment strategies, and facilitate patient stratification in future clinical trials.

Abstract Objectives: The purpose of this study was to determine whether breast cancer and diabetes status are related in adult Americans. Methods: We conducted a cross-sectional study of 7,599 individuals from the National Health and Nutrition Examination Survey (NHANES). Diabetes was classified as type 2 diabetes and pre-diabetes. Both prediabetes and diabetes were diagnosed according to ADA 2014 guidelines. Multiple logistic regression analysis was used to explore the relationship between diabetes status and breast cancer. Results: We found that prediabetes (OR = 0. 60, 95% CI:(0. 40, 0. 88), P= 0. 009613) and non-diabetes (OR = 0.05.3,95% CI: (0.34, 0.83), P = 0. 006014) were associated with a reduced risk of breast cancer in comparison to Type 2 diabetes (literature). Prediabetes in non-Hispanic blacks was associated with a reduced risk of breast cancer (OR=0. 55,95%CI:0. 40-0. 75, P<0. 001). Using two segmented linear regression models to fit the relationship between BMI and breast cancer, we found that the relationship between BMI and breast cancer was nonlinear, but there was a threshold effect. The threshold effect analysis found that BMI affcted breast cancer at an inflection point 26. 3 Kg/m2. Adjusted OR (95% CI) on both sides of the turning point was 1. 0799 ( 1. 0029, 1. 1629 ) and 0. 9873 ( 0. 9638, 1. 0115 ), respectively. Conclusions: Diabetes status is associated with the risk of breast cancer development. Moreover, the risk of developing breast cancer steadily increased from nondiabetes to prediabetes and type 2 diabetes. In addition, the prevalence of breast cancer showed a gradual increase withincreasing BMI up to 26. 3 Kg/m2 with the highest prevalence of breast cancer. There was an inverse U-shaped relationship between BMI and the breast cancer prevalence.

Triple-negative breast cancer (TNBC) is a subtype of breast cancer that disproportionally accounts for the majority of breast cancer-related deaths due to the lack of specific targets for effective treatments. In this review, we highlight the complexity of the transforming growth factor-beta family (TGF-β) pathway and discuss how the dysregulation of the TGF-β pathway promotes oncogenic attributes in TNBC which negatively affects patient prognosis. Moreover, we discuss recent findings highlighting TGF-β inhibition as a potent method to target mesenchymal (CD44⁺/CD24^-) and epithelial (ALDH^high) cancer stem cell (CSC) populations. CSCs are associated with tumorigenesis, metastasis, relapse, resistance, and diminished patient prognosis; however, due to differential signal pathway enrichment and plasticity, these populations remain difficult to target and persist as a major barrier barring successful therapy. This review highlights the importance of TGF-β as a driver of chemoresistance, radioresistance and reduced patient prognosis in breast cancer and highlights novel treatment strategies which modulate TGF-β, impede cancer progression and reduce the rate of resistance generation via targeting the CSC populations in TNBC and thus reducing tumorigenicity. Potential TGF-β inhibitors targeting based on clinical trials are summarized for further investigation which may lead to the development of novel therapies to improve TNBC patient prognosis.

Breast cancer is the most commonly diagnosed cancer in women worldwide. Approximately, 70 % of breast cancer patients express hormone receptors (HR) (Luminal subtype). Adjuvant endocrine treatments are the standard of care in HR+/HER2- breast cancer. Over time, about 50% of those patients develop endocrine resistance and metastatic breast cancer. Cyclin-dependent kinase inhibitors (CDKi) in combination with an aromatase inhibitor or fulvestrant have demonstrated superior efficacy increasing progression-free survival, with a safe toxicity profile, in HR+/HER2- metastatic breast cancer patients. CDKi blocks kinases 4/6 ATP-binding domain preventing G1/S cell cycle transition. Despite this, not all patients respond to CDKi and those who respond, finally develop resistance to combination therapy. Different studies, in tumour tissue or cell lines, have tried to elucidate the mechanisms underlying this progression, but there are still no conclusive data. In the last few years, liquid biopsy has contributed relevant information to this knowledge. Liquid biopsy can be performed in real-time, non-invasively and be repeated whenever needed. Circulating tumour material are potential prognostic markers in metastatic luminal breast cancer to determine patient prognosis, monitor disease and treatment selection. The objective of this review is to outline the different studies carried out in HR+ metastatic breast cancer patients treated with CDKi plus endocrine therapy using liquid biopsy approaches looking for possible resistance mechanisms.

This study analyzes oral supplement of molecular iodine (I2) alone and in combination with the neoadjuvant therapy 5-fluorouracil/epirubicin/cyclophosphamide or taxotere/epirubicin (FEC/TE) in women with Early (stage II) and Advanced (stage III) breast cancer. In the Early group, 30 women were treated with I2 (5 mg/day) or placebo (colored water) for 7–35 days before surgery. For the Advanced group, 30 patients received I2 or placebo along with FEC/TE treatment. After surgery, all patients received FEC/TE + I2 for 170 days. I2 supplementation showed a significant attenuation of the side effects and absence of tumor chemoresistance. Control, I2, FEC/TE, and FEC/TE+I2 groups exhibit response rate of 0, 33%, 73%, and 100%, respectively, and a pathologic complete response of 18%, and 36% in the last two groups. Five-year disease-free survival rate was significantly higher in patients with I2 supplement before and after surgery compared to those receiving the supplement only after surgery (82% vs. 46%). I2-treated tumors exhibit less invasive potential, and significant increases in apoptosis, estrogen receptor expression, and immune cell infiltration. Transcriptomic analysis indicated activation of the antitumoral immune response. The results led us to register a phase III clinical trial analyzing chemotherapy + I2 treatment for advanced breast cancer.

Background: Cancer stem cells (CSCs) exhibit self-renewal activity and give rise to other cell types in tumors. Due to the infinite proliferative potential of CSCs, drugs targeting these cells are necessary to completely inhibit cancer development. beta-lapachone (bL) has been widely used to treat cancer development, but its effect on cancer stem cells remain elusive. Thus, we investigated the effect of bL on mammosphere formation using breast cancer stem cell (BCSC) marker positive cells, MDA-MB-231. Methods: MDA-MB-231 Cells, which is negative for NQO1 expression, was constructed to stably express NQO1(NQO1 stable cells) to see the effect of bL. The effect of bL on cells were evaluated by wound healing and Transwell cell culture chambers, and ALDEFLUOR assay. Results: Here, we show that bL inhibited the proliferative ability of mammosphere derived from BCSC marker-positive cells, MDA-MB-231, in an NQO1-dependent manner. bL treatment efficiently downregulated expression level of BCSC markers CD44, ALDH1A1, and DLGAP5 that recently identified as a stem cell proliferation marker in both cultured cells and mammosphered cells. Moreover, bL efficiently downregulates cell proliferation and migration activities. Conclusions: These results strongly suggest that bL could be a therapeutic agent targeting breast cancer stem cells with proper NQO1 expression.

BRCA1 and 2 pathogenic variants increase lifetime risks of breast (50-75%) and ovarian cancer (15-20%). Guidelines recommend breast screening (MRI and mammogram) or risk-reducing mastectomy with salpingo-oophorectomy for ovarian cancer prevention. We sought to 1) characterize the population of BRCA1/2 carriers in Newfoundland and Labrador (NL) 2) evaluate risk-reducing interventions 3) identify factors influencing screening and prevention adherence. Methods: This is a retrospective study from a population-based provincial cohort of BRCA1/2 carriers. Eligibility criteria for risk-reducing interventions were defined for each case and patients were categorized based on their level of adherence with recommended screening or prevention. Chi-squared and regression analyses were used to determine which factors influenced uptake and level of adherence. Results: 276 BRCA1/2 carriers were identified; 156 living NL females composed the study population. Unaffected females were younger at testing than those with a cancer diagnosis (44.4 y versus 51.7 y; p=0.002). Categorized by eligibility, 61.0%, 61.6%, 39.0% and 75.7% of patients underwent MRI, mammogram, risk-reducing mastectomy, and risk-reducing salpingo-oophorectomy, respectively. Individuals with breast cancer were more likely to have risk-reducing mastectomy (64.7% versus 35.3%; p<0.001), and those who attended specialty hereditary cancer clinic were more likely to be adherent with breast/ovarian cancer recommendations (73.2% versus 13.4%; p<0.001) and to undergo risk-reducing salpingo-oophorectomy(84.1% versus 15.9%; p<0.001). Conclusions: Nearly 40% of female BRCA1/2 carriers were not receiving breast surveillance according to evidence-based recommendations. Cancer risk reduction and uptake of breast imaging and prophylactic breast and pelvic surgeries are significantly higher in patients who receive dedicated specialty care. Organized hereditary cancer prevention programs will be a valuable component of Canadian health care systems and have the potential to reduce the burden of disease country-wide.

Introduction: Antitumor host immune response is an important factor, but its role is not fully established. The role of tumor infiltrating lymphocytes (TIL) in breast cancer as an immunological biomarker has been significantly explored over the past years. The number of patients treated with neoadjuvant chemotherapy (NAC) increased and identification of a biomarker to predict the probability of pCR (pathological complete response) is a high priority. Materials and methods: We evaluated 334 cases of BC treated with NAC followed by surgical resection from 2020-2022 in Ist Clinic of Oncological Surgery, Oncological Institute "Prof Dr I Chiricuta" Cluj Napoca. Of the above, 122 cases were available for histological evaluation both in pre-NAC biopsy and post-NAC resection tissue. Evaluation of biopsy fragments and resection parts using hematoxylin eosin (H&amp;E). The TIL evaluation took place according to the recommendations of the International TIL Working Group (ITILWG). Results: There was a strong association between elevated levels of pre-NAC TIL. At the same time, there is a statistically significant correlation between stromal TIL and tumor grade, the number of lymph node metastases, the molecular subtype, and the number of mitoses (p &lt;0.005). Intratumoral TIL showed a significant correlation with tumor size, distant metastasis, molecular subtype, number of mitosis, stage and lymph node metastasis (p&lt;0.005). We also demonstrated that high pre-NAC TILs represent a strong predictive marker for pCR. Conclusion: This study reveals the role of TIL as a predictive biomarker in breast cancer not only for the well-established TNBC (triple negative breast cancer) and HER2+ (Her2 overexpressed) subtypes but also in Luminal A and B molecular subtypes. In this scenario, the evaluation of TILs as novel predictive and therapy-predicting factors should become a routinely performed analysis that could guide clinicians into the choice of the most appropriate therapy.

Wnt pathway is involved in breast cancer (BC) progression. Our aim was to evaluate the expression of some components of the Wnt pathway (β-catenin, FZD4, LRP5, LRP6 and TCF1) in order to detect potential associations with NHERF1 protein. In addition, we assessed their impact on patients’clinical outcome. We evaluated 220 primary BC samples by immunohistochemistry (IHC) and protein localization by immunofluorescence. We found a significant correlation between NHERF1 and FZD4, LRP5, LRP6 and TCF1. Univariate analysis showed that β-catenin (p<0.0001), FZD4 (p=0.0001), LRP5, LRP6 and TCF1 over-expression (p<0.0001 respectively) was related to poor disease free survival (DFS). A Kaplan-Meier analysis confirmed univariate data and showed a poor DFS for cNHERF1+/FZD4+ (p=0.0007), cNHERF1+/LRP5+ (p=0.0002), cNHERF1+/LRP6+ (p<0.0001) and cNHERF1+/TCF1+ phenotypes (p=0.0034). In multivariate analysis, TCF1 and β-catenin expression were independent prognostic variable of worse DFS (p=0.009 and p=0.027, respectively). In conclusion, we found that β-catenin, FZD4, LRP5, LRP6 and TCF1 overexpression was associated to poor prognosis. Furthermore, we first identified TCF1 as independent prognostic factor of poor outcome, indicating it as a new potential biomarker for BC patients management. In addition, Wnt pathway proteins expression, both alone and in association with NHERF1, suggests original associations of biological significance for new studies.

The HER2-targeted antibody-drug conjugates (ADCs) trastuzumab emtansine (T-DM1) and Trastuzumab deruxtecan (T-DXd) improved outcomes in breast cancer. Novel combinations and sequential approaches are under investigation to overcome resistance to T-DM1 and T-DXd. Furthermore, the landscape of HER2-targeted therapy is rapidly advancing with the development of ADCs designed to attack cancer cells with greater precision and reduced toxicity. Disitamab Vedotin (RC48) incorporates a HER2 antibody with unique binding epitope and a potent microtubule inhibitor as its cytotoxic moiety. ARX-788 comprises a non-cleavable linker and a novel maytansinoid derivative as the cytotoxic drug, engineered for increased stability and a higher drug-to-antibody ratio. SYD985, a duocarmycin-based ADC, is designed to be activated only in the acidic environment of the tumor, thus reducing off-target effects. BL-M0701 targets a different epitope on the HER2 protein, which might be beneficial in circumventing resistance that affects the binding of other ADCs and incorporate a camptothecin derivative as its payload. Zanidatamab zovodotin (ZW25) is an ADC that binds to two different HER2 epitopes simultaneously, enhancing the internalization and delivery of its cytotoxic payload. These and other ADCs in phase I trials hold the potential to improve outcomes for HER2-positive and HER2-Low breast cancer and possibly other solid tumors.

A brand-new approach to the understanding of breast cancer (BC) is urgently needed. In this contribution, the etiology, pathogenesis, and treatment of this disease is approached from the new pH-centric anticancer paradigm. Only this Unitarian perspective based upon that the hydrogen ion (H+) dynamics of cancer, allows understanding and integrating the many dualisms, confusions, and paradoxes of the disease. The new H+-related wide range model can embrace under a unique frame of mind the many aspects of the disease and at the same time therapeutically interfere with most, if not with all, the hallmarks of cancer known to date. The pH-related armamentarium available for the treatment of BC here reviewed may be beneficial for all types and stages of the disease. In this vein, we have attempted a mega synthesis of traditional and new knowledge in the different areas of breast cancer research and treatment based upon the wide range approach afforded by the hydrogen ion dynamics of cancer. The concerted utilization of a pH-related drugs nowadays available for the treatment of breast cancer is advanced.

Up to 25% of early human epidermal growth factor receptor 2-positive (HER2+) breast cancer (BC) patients will relapse despite the improvement achieved by the introduction of HER2-targeted therapy. Beyond trastuzumab, other agents approved for early HER2+ BC include the monoclonal antibody pertuzumab, the antibody-drug conjugate (ADC) trastuzumab-emtansine (T-DM1) and the reversible HER2 inhibitor lapatinib. New agents, such as trastuzumab-deruxtecan or tucatinib in combination with capecitabine and trastuzumab, have also shown an improvement in the metastatic setting. Other therapeutic strategies to overcome treatment resistance have been explored in HER2+ BC, mainly in HER2+ that also overexpress estrogen receptors (ER+). One strategy has been to target the cyclin-dependent kinases 4/6 (CDK4/6) as they are downstream of HER2 and many of the cellular pathways associated with resistance to HER2-targeted therapies play a key role in cell cycle and proliferation. Different trials have explored these strategies with encouraging results, but definitive results are needed. In addition, HER2+ BC is known to be more immunogenic than other BC subgroups, with high variability between tumors. Different immunotherapeutic agents have been investigated in this setting, with promising but controversial results obtained to date.

One in eight women will be diagnosed with breast cancer (BC) in their lifetime, resulting in over 2 million cases annually. BC is the most common cancer among women. Unfortunately, the etiology of majority of cases remains unknown. Recently, evidence has shown that the human microbiota plays an important role in health and disease. Intriguingly, studies have revealed the presence of microorganisms in human breast tissue, which was previously presumed to be sterile. Next-generation sequencing technologies have paved way for the investigation of breast microbiota, uncovering bacterial signatures that are associated with BC. Some of the bacterial species were found to possess pro-carcinogenic and/or anti-carcinogenic properties, suggesting that the breast microbiota has potentially crucial roles in maintenance of breast health. In this review, we summarize the recent findings on breast tissue microbiota and its interplay with BC. Bacterial signatures identified via next-generation sequencing as well as their impact on breast carcinogenesis and cancer therapies are reviewed. Correlation of breast tissue microbiota and other factors, such as geographical and racial differences, in BC is discussed. Additionally, we discuss the future directions of research on breast microbiota as well as its potential role in prevention, diagnosis and treatment of BC.

Background: Radiotherapy plays an important role in the management and survival of patients with breast cancer. The aim of this study was to examine the association between age, comorbidities and use of radiotherapy in this population. Methods: Patients diagnosed with breast cancer from 2004–2013 were identified from the American College of Surgeons National Cancer Database (NCDB). Follow-up time was measured from the date of diagnosis (baseline) to the date of death or censoring. Adjusted hazard ratios (aHR) and 95% confidence intervals (95%CI) were used as the measure of association. Results: Independently of comorbidities and other important outcome-related factors, patients >65 years of age who received radiotherapy survived significantly longer than those who did not receive radiotherapy (aHR = 0.53, 95%CI = 0.52–0.54). However, as women aged, those with comorbidities were less likely to receive RT (adjusted P-trend by age <0.0001). Conclusions: The development of decision-making tools to assist clinicians, and older women with breast cancer and comorbidities, are needed to facilitate personalized treatment plans regarding RT. This is particularly relevant as the population ages and the number of women with breast cancer is expected to increase in the near future.

Background: Triple negative breast cancer (TNBC) is the most aggressive form of breast cancer with poor outcomes. The molecular basis of TNBC remains poorly understood. The objective of this study was to explore the relationship between obesity and TNBC in premenopausal and postmenopausal Caucasian women using whole genome transcription profiling. Methods: We compared gene expression levels of tumor samples drawn from normal weight, overweight and obese in pre and postmenopausal women diagnosed with TNBC. We performed hierarchical clustering to assess similarity in patterns of gene expression profiles, and conducted network and pathway analysis to identify molecular networks and biological pathways. Results: We discovered gene signatures distinguishing normal weight from obese, normal weight from overweight and overweight from obese individuals in both premenopausal and postmenopausal women. The analysis revealed molecular networks and biological pathways dysregulated in response to obesity. Among the discovered pathways included the unfolded protein response, endoplasmatic reticulum stress, B cell receptor and the autophagy signaling pathways in obese premenopausal women and the integrin, axonal guidance, ERK/MAPK and Glutathione biosynthesis signaling pathways obese postmenopausal women. Conclusions: The results suggest that both overweight and obesity are associated with TNBC, highlighting the need for conformation of these results in independent studies.

In breast cancer, epithelial-mesenchymal transition (EMT) is positively associated with programmed death ligand 1 (PD-L1) expression and immune escape, and TWIST1 induces EMT and cancer metastasis. However, how TWIST1 regulates PD-L1 and immune evasion is unknown. This study analyzed TWIST1 and PD-L1 expression in breast cancers, investigated the mechanism for TWIST1 to regulate PD-L1 transcription, and assessed the effects of TWIST1 and PD-L1 in cancer cells on the cytotoxicity of CD8+ effector T cells. Interestingly, TWIST1 expression is associated with high-level PD-L1 in triple negative breast cancers (TNBCs). Overexpression and knockdown of TWIST1 robustly upregulates and downregulate PD-L1 expression, respectively. TWIST1 binds to the PD-L1 promoter and recruits the TIP60 acetyltransferase complex in a BRD8-dependent manner to promote PD-L1 expression, which drives immune escape of breast cancer cells by accelerating the exhaustion of CD8+ T cells. Accordingly, knockdown of TWIST1 or BRD8 or blockade of PD-L1 with a PD-L1 antibody significantly enhances CD8+ T cells to inhibit breast cancer cell growth. These results demonstrate that TWIST1 directly induces PD-L1 expression in breast cancer cells to drive immune evasion. Targeting TWIST1, BRD8 or PD-L1 in TNBC should facilitate CD8+ T cell-mediated immune therapy. TWIST1 may also serve as a biomarker for anti-PD-L1 immunotherapy.

Chromosomal instability (CIN), defined by variations in the number or structure of chromosomes from cell to cell, is recognized as a distinctive characteristic of cancer, associated with the ability of tumors to adapt to challenging environments. CIN has been recognized as a source of genetic variation that leads to clonal heterogeneity (CH). Recent findings suggest a potential association between CIN and CH with the prognosis of BC patients, particularly in tumors expressing the epidermal growth factor receptor 2 (HER2+). In fact, information on the role of CIN in other BC subtypes, including luminal B BC, is limited. Additionally, it remains unknown whether CIN in luminal B BC tumors, above a specific threshold, could have a detrimental effect on the growth of human tumors, or if low or intermediate CIN levels could be linked to a more favorable BC patient prognosis when contrasted with elevated levels. Clarifying these relationships could have a substantial impact on risk stratification and the development of future therapeutic strategies aimed at targeting CIN in BC. This study aimed to assess CIN and CH in tumor tissue samples from ten patients with luminal B BC, and compared them with established clinicopathological parameters. The results of our study show that luminal B BC patients exhibit intermediate CIN and stable aneuploidy, both of which correlated with lymphovascular invasion. These findings suggest that evaluating CIN, CH and aneuploidy could improve risk stratification, the prediction of clinical outcomes and future therapeutic approaches in luminal B BC patients.

Breast cancer is the most common cancer among women worldwide, and estrogen receptor-positive (ER+) breast cancer accounts for a significant proportion of cases. While various treatments are available, endocrine therapies are often the first-line treatment for this type of breast cancer. However, the development of drug resistance poses a significant challenge in managing this disease. ESR1 mutations have been identified as a common mechanism of endocrine therapy resistance in ER+ breast cancer. The first-generation selective estrogen receptor degrader (SERD) fulvestrant has shown some activity against ESR1 mutant tumors. However, due to its poor bioavailability and need for intramuscular injection, it may not be the optimal therapy for patients. Second-generation SERDs have been developed to overcome these limitations. These newer drugs have improved oral bioavailability and pharmacokinetics, making them more convenient and effective for patients. Several oral SERDs are now in phase III trials for early and advanced ER+ breast cancer. This review summarizes the background of oral SERD development, the current status, and future perspectives.

Background: Risk of metastatic recurrence of breast cancer after initial diagnosis and treatment depends on the presence of a number of risk factors. Although most univariate risk factors have been identified using classical methods, machine-learning methods are also being conducted to tease out non-obvious contributors to a patient’s individual risk of developing late distant metastasis. Bayesian-network algorithms may predict not only risk factors but also interactions among these risks, which consequently lead to metastatic breast cancer. We proposed to apply a previously developed machine-learning method to predict risk factors of 5-, 10- and 15-year metastasis. Methods: We applied a previously validated algorithm named the Markov Blanket and Interactive risk factor Learner (MBIL) on the electronic health record (EHR)-based Lynn Sage database (LSDB) from the Lynn Sage Comprehensive Breast Cancer at Northwestern Memorial Hospital. This algorithm provided an output of both single and interactive risk factors of 5-, 10-, and 15-year metastasis from LSDB. We individually examined and interpreted the clinical relevance of these interactions based on years to metastasis and the reliance on interactivity between risk factors. Results: We found that with lower alpha values (low interactivity score), the prevalence of variables with an independent influence on long term metastasis was higher (i.e., HER2, TNEG). As the value of alpha increased to 480, stronger interactions were needed to define clusters of factors that increased the risk of metastasis (i.e., ER, smoking, race, alcohol usage). Conclusion: MBIL identified single and interacting risk factors of metastatic breast cancer, many of which were supported by clinical evidence. These results strongly recommend the development of further large data studies with different databases to validate the degree to which some of these variables impact metastatic breast cancer in the long term.

(1) Background: Breast cancer (BC) is the second largest cause of mortality in female worldwide. Besides from basic risk factors, there are several hereditary variables that contribute to BC. Breast cancer has been linked to a variety of nuclear DNA changes as well as mitochondrial DNA alterations. The aim of this study was to analysis the association of mitochondrial tRNA leucine2 gene with BC. (2) Material and methods: In the current study, 24 samples have been collected from various families in Peshawar. DNA was extracted from Blood. PCR was used to amplify the mitochondrial tRNA MT-TL2 gene, and 22 samples were sequenced. The sequence was compared with accession #NC-012920.1 of the revised Cambridge Reference Sequence (rCRS). (3) Results: The results (Chromatograph, nucleotide sequence and rCRS alignment) shows mutations in mitochondrial tRNA MT-TL2 gene in our participants is not the cause of Breast cancer. (4) Conclusion: Yet, a significant number of BC patients must be studied, and their full mitochondrial DNA must be analyzed. This will provide an indication of the potential DNA marker that might be used to prevent BC deaths at the earliest stages.

Accurate assessment of the breast cancer deterioration degree plays a crucial role in making medical plan, and the important basis for degree assessment is the number of mitoses in a given area of the pathological image. We utilized deep multi-scale fused fully convolutional neural network (MFF-CNN) combing with conditional random felid (CRF) to detect mitoses in hematoxylin and eosin stained histology image. Analyze the characteristics of mitotic detection ----scale invariance and sparsity, as well as the difficulties ---- small amount of data , inconsistent image staining and sample class unbalanced. Based on this, mitotic detection model is designed. In this paper, a tissue-based staining equalization method is used, and to establish an effective training sample set, we select training samples by using CNN. A mitotic detection model fusing multi-level and multi-scale features and context information was designed, and the corresponding training strategy was made to reduce over-fitting. As preliminarily validated on the public 2014 ICPR MITOSIS data, our method achieves a better performance in term of detection accuracy than ever recorded for this dataset.

Matrix metalloproteases (MMPS) are a family of well-known enzymes which operate prevalently in the extracellular domain, where they fulfil the function of remodeling the extracellular matrix. Within the about 26 family members, encoded by 24 genes in humans, MMP-2 and MMP-9, have been regarded as the primary responsibility for the basement membrane and pericellular ECM rearrangement. In cases of infiltrating carcinomas, which arise from the epithelial tissues of a gland or of an internal organ, a marked alteration of the expression and the activity levels of both MMPs is known to occur. Present investigation represents the continuation and upgrading of our previous studies, now focusing on the occurrence and intensity levels of MMP-2 and -9, and their proteomic correlations, in a cohort of 80 breast cancer surgical tissues

Breast cancer (BC) is a heterogeneous disease representing a substantial economic burden. In order to develop policies that successfully decrease this burden, the factors affecting costs need to be fully understood. Evidence suggests that early detection in Stage I has a lower cost than late detection. We aim to provide conservative estimates of BC's stage-wise medical costs from German healthcare and the payer's perspective. To this end, we conducted a literature review of articles evaluating stage-wise costs of BC in Germany through PubMed, Web of Science, and Econ Lit databases supplemented by Google Scholar. We developed a decision tree model to estimate BC related medical costs in Germany using available treatment and cost information. The review generated seven studies; none estimated the stage-wise costs of BC. The studies were classified into two groups: (1) case scenarios (five studies) and two studies based on administrative data. The first sickness funds data study (Gruber, Stock, et al. 2012) used 1999 information to approach BC attributable cost; their results suggest a range between €3,929 and €11,787 depending on age. The second study (Kreis, Plöthner, et al. 2020) used 2011-2014 data and suggested an initial phase incremental cost of €21,499, an intermediate phase cost of €2,620, and a terminal phase cost of €34,513 per incident case. Our decision tree model based BC stage-wise cost estimates were €21,523 for Stage I, €25,679 for Stage II, €30,156 for Stage III, €42,086 for Stage IV. Alternatively, the modeled cost estimates are €20,284 for the initial phase of care, €851 for the intermediate phase of care, and €34,963 for the terminal phase of care. Our estimates for phases of care are consistent with recent German estimates provided by Kreis and Plöthner et al. Furthermore, the data collected by sickness funds are collected primarily for reimbursement purposes, where the German ICD-10 classification system defines a cancer diagnosis. As a result, claims data lack the clinical information necessary to understand stage-wise BC costs. Our model-based estimates fill the gap and inform future economic evaluations of BC interventions.

Breast cancer (BC) is the most common cancer diagnosed in women worldwide. Approximately 70% of BC patients have the luminal subtype, which expresses hormone receptors (HR+). Adjuvant endocrine treatments are the standard of care for HR+/HER2- BC patients. Over time, approximately 30% of those patients develop endocrine resistance and metastatic disease. Cyclin-dependent kinase inhibitors (CDKi) in combination with an aromatase inhibitor or fulvestrant have demonstrated superior efficacies in increasing progression-free survival, with a safe toxicity profile, in HR+/HER2- metastatic BC patients. CDKi blocks kinases 4/6, preventing G1/S cell cycle transition. However, not all patients respond to CDKi, and those who do respond ultimately develop resistance to the combined therapy. Studies in tumour tissues and cell lines have tried to elucidate the mechanisms underlying this progression, but there are still no conclusive data. Over the last few years, liquid biopsy has contributed relevant information. Circulating tumour materials are potential prognostic markers for determining patient prognosis in metastatic luminal BC, for monitoring disease and for treatment selection. This review outlines the different studies performed using liquid biopsy in patients with HR+ metastatic BC treated with CDKi plus endocrine therapy. We focus mainly on those studies that describe possible resistance mechanisms in circulating tumour-derived material.

Endoplasmic reticulum (ER) stress perturbs cell homeostasis and induces the unfolded protein response (UPR). In breast cancer, this process is activated by oestrogen deprivation and is associated with tamoxifen resistance. We present evidence that the transcription factor SOX2 and the long noncoding RNA SOX2 overlapping transcript (SOX2OT) are up-regulated in oestrogen receptor-positive (ER+) breast cancer and in response to oestrogen deprivation. We examined the effect of the UPR on SOX2 and SOX2OT expression, and the effect of SOX2OT on UPR pathways in breast cancer cell lines. The induction of the UPR by thapsigargin or glucose deprivation up-regulates SOX2OT expression. This up-regulation is also shown with the anti-oestrogen 4OH-tamoxifen and mTOR inhibitor everolimus in ER + breast cancer cells that are sensitive to oestrogen deprivation or everolimus treatment. SOX2OT overexpression decreased BiP and PERK expression. This effect of SOX2OT overexpression was confirmed on BiP and PERK pathway by q-PCR. Our results show that a long noncoding RNA regulates the UPR and evince a new function of SOX2OT as a participant of ER stress reprogramming of breast cancer cells.

(1) Background: Inflammatory breast cancer (IBC) is a rare and aggressive form of breast cancer that poses unique management challenges. This review aims to synthesize the current literature on IBC, focusing on diagnosis, treatment, and prognosis, while highlighting recent advances and ongoing issues in patient management.; (2) Methods: We outline the typical clinical presentation and diagnostic criteria of IBC. Additionally, we detail the main therapeutic strategies, including neoadjuvant chemotherapy, surgery, radiation therapy, targeted therapies, hormonal therapies, and emerging treatments such as immunotherapy. The review is based on a comprehensive analysis of the existing literature.; (3) Results: Despite advancements in systemic therapy and a better understanding of IBC biology, the prognosis for patients with IBC remains poor. The overall survival rate has shown only marginal improvement over the past few decades. Future research directions, including the identification of novel biomarkers for early detection and personalized medicine strategies, are identified. The need for more high-quality clinical trials to address the challenges in IBC management is emphasized.; (4) Conclusions: Managing IBC is a complex task that necessitates multidisciplinary care and patient-centered communication. This review provides clinicians and researchers with a comprehensive overview of the current challenges and future directions in IBC management. The goal is to guide treatment decisions and inform further research, ultimately improving patient outcomes and prognosis.

The antibody Trastuzumab (Tz) targeting ERBB2 has improved the prognosis of patients with breast cancer (BCa) that overexpress this receptor. Resistance to Tz negatively impacts prognosis. Several mechanisms have been reported to cause Tz resistance. The objective of this study was to identify common mechanisms in in vitro models of acquired BCa Tz resistance. In particular, we used three widely available ERBB2+ BCa cell lines adapted to grow in Tz. We performed several analyses to address possible changes in phenotype, proliferation, and ERBB2 membrane expres-sion common to the three Tz-R cell lines compared to wt, but none was found. High-resolution mass spectrometry analysis identified, instead, a common set of differentially expressed proteins (DEPs) in Tz-R vs. wt cells. Furthermore, bioinformatic tools revealed that all three Tz-R cell models shared a modulation of proteins involved in the metabolism of lipids, organophosphate biosynthetic process, and macromolecule methylation. Ultrastructural analysis confirmed altera-tion of lipid droplets in resistant cells. Our data strongly support the hypothesis that complex metabolic adaptation, including lipid metabolism, protein phosphorylation, and possibly chro-matin remodeling, may fuel Tz resistance. The identification of a common set of 10 DEPs in all three TZ-resistant cell lines may provide novel targets for therapeutic intervention.

Lifestyle has been associated with breast cancer risk through different pathways, including oxidative stress. Antioxidant enzymes are endogenous defense mechanisms against oxidative stress damage, and this response might be modulated by the genetic variation in these enzyme-codifying genes. This study aimed to analyze the synergistic effect of an antioxidant Healthy Lifestyle Index (HeLiX) composed of principal components of Western dietary pattern, alcohol consumption, smoking and physical activity, and genetic polymorphisms in the first-line antioxidant response family genes SOD, GPX, and CAT on breast cancer risk. We included 176 SNPs, and only CAT rs554576 remained significant after correction for multiple comparisons. Breast cancer odds were reduced at the highest (T3) and medium (T2) tertiles of the HeLiX. When stratified by HeLiX, we observed a reduced risk of breast cancer with at least one T-allele, and the effect increased in a dose-dependent manner. Compared to the reference category (HeLiX T1 and AA genotype), women at the HeLiX T3 with AT and TT genotypes in postmenopausal women showed an OR = 0.15 (95% CI 0.07–0.32). For HeLiX T2 and AT genotype OR = 0.26 (95% CI 0.13–0.54); for TT genotype OR = 0.24 (95% CI 0.12–0.45). For premenopausal women, at the HeLiX T3 and AT genotype OR = 0.29 (95% CI 0.13–0.62); for the TT genotype OR = 0.21 (95% CI 0.08–0.51). We also observed an inverse association for HeLiX T2 and TT genotype (OR 0.39 95% CI 0.17–0.87). Our study shows a significant synergistic gene-environment interaction on an additive scale, contributing to understanding pathways involved in breast cancer etiology and prevention.

Next Generation Sequencing based cancer risk screening with multigene panels has become the most successful method for programming cancer prevention strategies. ATM germ-line heterozygosity has been described as able to increase tumor susceptibility. In particular, families that carry heterozygous germ-line variants of ATM gene show a 5- to 9-fold risk of developing breast cancer. Recent studies identified ATM as the second most mutated gene after CHEK2 in BRCA-negative patients. Nowadays, more than 170 potential missense variants and several truncating mutations have been identified in ATM gene. Here we present the molecular characterization a new ATM deletion, identified thanks to the CNV algorithm implemented in the NGS analysis pipeline. An automated workflow implementing the SOPHiA Genetics’ Hereditary Cancer Solution (HCS) protocol was used to generate NGS libraries that were sequenced on Illumina MiSeq Platform. NGS data analysis allowed to identify a new inactivating deletion of exons 19-27 of ATM gene. DNA breakpoint was characterized both at DNA and RNA level

Intrinsic subtype of triple-negative breast cancer (TNBC) is based on genomic evaluation. In this study, we report the survival and pathological complete response (pCR) rates of TNBC patients subtyped by IHC and treated with neoadjuvant chemotherapy (NACT). A retrospective cohort of 187 TNBC patients who received NACT between 2008 and 2017 was used, and IHC subtyping was performed on biopsy specimens before chemotherapy. The subtyping revealed predominant basal-like tumors (IHC-BL, 61%), followed by basal-like immune-suppressed (IHC-BLIS, 31%), mesenchymal tumors (12.5%), luminal androgen receptor tumors (IHC-LAR, 12%) and basal-like immune-activated (IHC-BLIA, 10.9%). The pathological complete response (pCR) rate varied among subtypes, with IHC-BLIA showing the highest (30.0%) and IHC-LAR showing the lowest (4.5%). IHC-BLIS led in recurrence sites. Overall and disease-free survival analyses did not show significant differences among subtypes. Although, IHC-BLIA demonstrated a trend toward better survival and IHC-mesenchymal worse. Patients who achieved pCR exhibited significantly better disease-free survival and overall survival than non-responders. This study underscores the potential of IHC-based subtyping in TNBC management, highlighting distinct response patterns to neoadjuvant chemotherapy and potential implications for treatment strategies. Further research is warranted to validate these findings and explore tailored therapeutic approaches for specific TNBC subtypes.

Breast cancer is the most widespread malignancy in women from corner to corner of the world. Nanostructured lipid carrier (NLC) proved its efficacy in the treatment of cancer. NLC loaded with Imatinib (IMA) (NANIMA) was prepared and evaluated for in vitro efficacy in MCF-7 breast cancer cells. Hot homogenization method was used for the preparation of NANIMAs. Aqueous solution of surfactants (hot) was mixed with molten mixture of stearic acid and sesame oil (hot) under homogenization. The prepared NANIMAs were characterized and evaluated for size, polydispersity index, zeta potential, encapsulation efficiency, release studies, stability studies and MTT assay (cytotoxicity studies). The optimized NANIMA revealed particle size of 104.63 ± 9.55 d.nm, PdI of 0.227 ± 0.06 and EE of 99.79 ± 0.03. All NANIMAs revealed slow and sustained release behaviour. The surfactants used in the preparation of NANIMAs exhibited their effects on particle size, zeta potential, encapsulation efficiency, stability studies and release studies. The cytotoxicity studies unveiled 8.75 times increase in cytotoxicity for optimized NANIMA (IC50 = 6 µM) when compared with IMA alone (IC50 = 52.5 µM) on MCF-7 breast cancer cells. After this, NLC containing IMA possibly will be employed for the cure of breast cancer. A lesser amount of IMA loaded NLC will be sufficient than IMA alone for the treatment of breast cancer. Moreover, the patient will exhibit not as much of adverse effects as in case of IMA alone. Consequently, NANIMA could prove to be useful for effective therapeutic outcome in breast cancer treatment.

The purpose of this study was to identify subgroups of quality of life (QOL) changes in breast cancer survivors (BCS) and to determine factors associated with subgroups of consistently low or deteriorated QOL. We enrolled 101 women recently diagnosed with breast cancer in South Korea and asked them to complete a questionnaire at baseline (within 1 month of diagnosis), 1 year later (Year 1), 2 years later (Year 2), and 3 years later (Year 3). We assessed QOL using the global QOL subscale from the EORTC QLQ-C30. We defined low QOL as a global QOL score 10 points below the mean score of the general population. Based on low QOL as defined in this study, we identified subgroups of QOL changes over 3 years. We identified four subgroups of QOL changes: improved (47.4%), stable (30%), continuously low (8.8%), and deteriorated (13.8%) and considered the last two categories (22.6%) as poor QOL. Logistic regression analyses demonstrated that significant determinants of poor QOL were insomnia at Year 1, fatigue and anxiety at Year 2, and fatigue, depression, and comorbidity at Year 3. In conclusion, persistent symptoms of insomnia, fatigue, anxiety, depression, and comorbidity are potential risk factors for poor QOL in BCS.

Breast cancer, although the most frequently diagnosed malignant tumour in humans, has a less clear aetiology compared to other frequent cancer types. Mouse-mammary tumour virus (MMTV) is involved in breast cancer in mice and dogs and might play a role in the aetiology of some breast cancers in humans, since it has been identified in 20-40% of breast cancer samples in Western Europe, USA, Australia and some other parts of the world population. The purpose of our study was to identify MMTV DNA sequences in breast tissue samples from breast cancer patients operated in our regional centre from Romania. We have selected 75 patients with non-metastatic breast cancer treated with curative intent and searched with PCR the MMTV-like DNA sequence in the breast cancer tissue and normal breast tissue obtained from the same patients. Since none of the examined samples was positive for MMTV-like target sequences on PCR we could not prove that MMTV plays a role in the aetiology of breast cancer in our patient group. This finding is similar to publications of other geographically related research groups and might be due to the fact that only the Mus musculus domesticus mouse species was proven to carry infectious MMTV, but not the Mus musculus musculus species, which is specific to South-Eastern Europe (including Romania) and some parts of Asia.

Galectins have been shown to have roles in cancer progression via contributions to angiogenesis, metastasis, cell division, and evasion of immune destruction. This study analyses galectin-1, -3, and -9 serum concentrations in breast cancer patients by enzyme-linked immunosorbent assay (ELISA) against the characteristics of the patient and tumor such as stage, molecular subtype, and receptor expression. Galectin-9 was found to be statistically significantly increased in HER2 enriched tumors as well as being reduced in patients with hormone receptor positive tumors and increased in patients with HER2 amplified tissues. Galectin-1 was found to be statistically significantly increased in the serum of patients who had undergone hormonal, immunotherapy, or chemotherapy. These findings provide insight as to the changes in galectin levels during cancer progress, response to treatment and molecular phenotype. These findings are valuable in the further understanding of the relationships of galectin and tumor biology and can inform future research on therapeutic targets for galectin inhibitors and the utility of galectin biomarkers.

Breast cancer and cardiovascular diseases (CVD) represent significant global health challenges, with CVD being the leading cause of mortality and breast cancer showing a complex pattern of incidence and mortality. We explore the intricate interplay between these two seemingly distinct medical conditions, shedding light on their shared risk factors and potential pathophysiological connections. A specific connection between hypertension (HTN), atrial fibrillation (AF), myocardial infarction (MI), and breast cancer was evaluated. HTN is explored in detail, emphasizing the role of aging, menopause, insulin resistance, and obesity as common factors linking HTN and breast cancer. Moreover, an attempt is made to identify the potential impact of antihypertensive medications and highlight the increased risk of breast cancer among those women, with a focus on potential mechanisms. A summary of key findings underscores the need for a multisystemic approach to understanding the relationship between CVD and breast cancer is also explored with a highlight for all the gaps in current research, such as the lack of clinical observational data on MI and breast cancer in humans and the need for studies specifically designed for breast cancer. This paper concludes that there should be a focus on potential clinical applications of further investigation in this field, including personalized prevention and screening strategies for women at risk. Overall, the authors attempt to provide a comprehensive overview of the intricate connections between breast cancer and cardiovascular diseases, emphasizing the importance of further research in this evolving field of cardio-oncology.

Breast and Cervical cancer are significant causes of morbidity and mortality among women worldwide. Usually, conventional therapies and early detection has shown success in metastasis and relapse rates and improved overall survival of the patients. The elimination of the efficacy of chemotherapies and target therapies because cancer stem cells create resistance against chemotherapy, metastasis, and relapse. Studies reveal that cancer stem cell markers are important for improving efficiencies of targeted therapies. Our study aims to analyze the stem cell markers and target the most significant stem cell marker by phytochemicals and their derivates. Through the analysis, it was observed that CXCR4 and SOX-2, mir-1, mir-125, and mir-429 may have a crucial role in stemness of breast and cervical cancer respectively, while BPMD & MD simulations revealed Di-valinoyl curcumin as a potential compound for CXCR4 targeting.

Cancer metastasis accounts for approximately 90% of cancer deaths, and elucidating markers in metastasis is the first step in its prevention. To characterize metastasis marker genes of breast cancer (MGs), XGBoost models that classify metastasis status were trained with gene expression profiles from TCGA. Then, a metastasis score (MS) was assigned to each gene by calculating the inner product between the feature importance and AUC performance of the models. As a result, the 54, 202, and 357 genes with the highest MS were characterized as MGs by empirical P-value cutoffs of 0.001, 0.005, and 0.01, respectively. The three sets of MGs were compared with those from existing metastasis marker databases, which provided significant results in most comparisons. We noticed that the set of MGs with the median EP cutoff showed better performance than the other two sets, suggesting the importance of the cutoff used in determining MGs. They were also significantly enriched in biological processes associated to breast cancer metastasis. The MGs that could not be identified by statistical analysis (e.g., GOLM1, ELAVL1, UBP1, and AZGP1) as well as the MGs with the highest MS (e.g., ZNF676, FAM163B, LDOC2, IRF1, and STK40) were verified via the literature. Additionally, we checked how close the MGs are located to each other in the protein–protein interaction networks. We expect that the characterized markers will help understand and prevent breast cancer metastasis.

(1) Background: Breast cancer is the second leading cause of cancer death among women. The accurate prediction of survival intervals will help physicians make informed decisions on treatment strategies or the use of palliative care for patients; (2) Methods: The gene expression is predictive and correlates to patient prognosis. To establish a reliable prediction tool, we collected the RNA-seq data of breast cancer patients, a total of 1187 RNA-seq data (median age 58 years), in FPKM format from the TCGA database. Among them, 144 RNA-seq data with date of death information was selected to establish the SaBrcada-AD dataset. We first normalized the SaBrcada-AD dataset to transcripts per million (TPM) to build survival prediction model SaBrcada. After normalization and dimension raising, the differential gene expression data were used for testing eight different deep learning architectures. Among them, GoogLeNet performed the best. Considering the effect of age on prognosis, we examined all ages between the lower and upper quartiles of patient age for a stratified random sampling test; (3) Results: Stratifying by age based on a cut-off of 61 years of age improved the accuracy of SaBrcada compared to previous findings, resulting in an accuracy of 0.798. We also built a free website tool to provide 5 kinds of predicted survival period information for clinician reference; (4) Conclusions: We established a breast cancer survival analysis prediction model, SaBrcada, and a website tool with the same name. Through this highly reliable survival analysis model and website tool, information on survival intervals will be provided for clinicians as part of precision medicine.

This study aimed to determine the feasibility of the development of an over-the-counter (OTC) screening model using machine learning for breast cancer screening in the Asian women population. Data were retrospectively collected from women who came to the Hospital Universiti Sains Malaysia, Malaysia. Five screening models were developed based on machine learning methods; random forest, artificial neural network (ANN), support vector machine (SVM), elastic-net logistic regression and extreme gradient boosting (XGBoost). Features used for the development of the screening models were limited to information from the patients’ registration form. The model performance was assessed across the dense and non-dense groups. SVM had the best sensitivity while elastic-net logistic regression had the best specificity. In terms of precision, both random forest elastic-net logistic regression had the best performance, while, in terms of PR-AUC, XGBoost had the best performance. Additionally, SVM had a more balanced performance in terms of sensitivity and specificity across the mammographic density groups. The three most important features were age at examination, weight and number of children. In conclusion, OTC models developed from machine learning methods can improve the prognostic process of breast cancer in Asian women.

Curcumin (CUR) is a phytochemical with potent anticancer activities as demonstrated by both preclinical and clinical studies. CUR bioformulations, including loading in biodegradable polymers, have been explored to increase CUR’s solubility and chemical stability, control its release, and improve its delivery to cancer cells. In this study, copolymers comprising poly (L-lactide)-poly (ethylene glycol)-poly (L-lactide) (PLA-PEG-PLA) and poly (ethylene glycol)-poly (L-lactide)-poly (ethylene glycol) (PEG-PLA-PEG) were designed and synthesized to assess and compare their curcumin delivery capacity and inhibitory potency on MCF-7 breast cancer cells. Molecular dynamics simulations indicated that PLA-PEG-PLA has a higher propensity to interact with the cell membrane and more negative free energy, suggesting it is the better carrier for cell membrane penetration. Our characterization indicated that the microsphere copolymers were synthesized successfully. Of the two formulations, PLA-PEG-PLA experimentally exhibited better results, with an initial burst release of 17.5%, followed by a slow, constant release of the encapsulated drug up to 80%. PLA-PEG-PLA-curcumin showed a significant increase in cell death in MCF-7 cancer cells (IC50 = 23.01 ± 0.85 µM) based on the MTT assay. These data were consistent with gene expression studies of Bax, Bcl2, and hTERT which showed that PLA-PEG-PLA-CUR induced apoptosis more efficiently in these cells. Our study integrates in vitro and in silico approaches to identify an optimal co-polymer for the delivery of CUR to cancer cells.

This study delves into the realm of potential therapeutics for breast cancer by conducting a comprehensive docking simulation and virtual screening analysis using Autodock Vina Algorithm. The focus based on the human epidermal growth factor receptor 2 (HER2), a key protein associated with various cancers, particularly in the context of breast cancer.The results reveal compelling insights into the binding interactions of several natural compounds and drugs with HER2. Notably, Acebilustat, Bemcentinib, and Amentoflavone exhibit outstanding binding energies, averaging around -10 kcal/mol, suggesting strong and favorable interactions with the HER2 target.These encouraging findings not only emphasize the potential biological significance of these compounds but also hint at their potential usefulness in fighting breast cancer.Their promising binding affinities with HER2 position them as potential candidates for further investigation and development as therapeutic agents against breast cancer.

Breast Cancer (BC) is the second most common type of cancer worldwide and displays the highest cancer-related mortality among women worldwide. Targeted therapies have revolutionized the way BC has been treated in the last decades improving life expectancies of millions of women. Among the different molecular pathways that have been of interest for the development of targeted therapies are the Cyclin-Dependent Kinases (CDK). CDK inhibitors are a class of molecules that already exist in nature and those belonging to the INK4 protein family specifically inhibit the CDK4/6 proteins. CDK4/6 inhibitors specifically block the transition from the G1 to the S phase of the cell cycle by dephosphorylation of the retinoblastoma tumor suppressor protein. In the past four years CDK4/6 inhibitors palbociclib, ribociclib, and abemaciclib received their first FDA approval for the treatment of Hormone Receptor (HR)-positive and Human Epidermal growth factor Receptor 2 (HER2)-negative breast cancer after showing significant improvements in progression-free survival in the PALOMA-1, MONALEESA-2 and the MONARCH-2 randomized clinical trials, respectively. After the encouraging results from these clinical trials, CDK4/6 inhibitors have also been investigated in the other BC subtypes. In HER2-positive BC, combination of CDK4/6 inhibitors with HER2-targeted therapies showed promise in preclinical studies and their clinical evaluation is ongoing. Moreover, in triple-negative BC, CDK4/6 inhibitors efficacy has been investigated in combination with other targeted therapies or immunotherapies. This review summarizes the molecular background and clinical efficacy of CDK4/6 inhibitors as single agents or in combination with other targeted therapies for the treatment of BC. Future directions of ongoing clinical trials and predictive biomarkers will be further debated.

Doxorubicin (DOX) is a frequently used chemotherapeutic drug for breast cancer, but its site specificity and local internalization into tumor cells is rather low. In this paper we conjugated magnetic nanoparticles (MNPs) with DOX and/or a pseudopeptide NucAnt (N6L) as modality to enhance DOX-induced antitumor effects in breast cancer cells (BT474). In this context, we determined cellular uptake of MNP formulations, analyzed cell viability and expression of apoptotic and cell cycle proteins after magnetic hyperthermia (43°C, 1 h) in vivo and in vitro. We have shown that i) the presence of N6L on the surface of DOX-functionalized MNPs increases their internalization into a target cells and potentiates the cytotoxic potential of the anticancer drug, ii) in combination with hyperthermia, DOX functionalized MNPs influence the expression of apoptotic and cell cycle proteins, and also favors tumor regression in vivo. Our data show that intratumoral application of DOX coupled MNPs is able to overcome biological barriers to chemotherapeutic drugs, enabling them to penetrate into the target cells. Combined with hyperthermia these MNPs can be an effective method in enhancing the localised delivery and penetration of DOX into breast cancer cells.

Background: KDM5 enzymes are H3K4 specific histone demethylases involved in transcriptional regulation and DNA repair. These proteins are over-expressed in different kinds of cancer, including breast, prostate and bladder carcinoma, with positive effects on cancer proliferation and chemo-resistance. For these reasons, these enzymes are potential therapeutic cancer targets. Methods: In the present study, we analyzed the effects of three different inhibitors of KDM5 enzymes in MCF-7 breast cancer cells over-expressing JARID1B. In particular we tested H3K4 demethylation (western blot); target gene transcription (RNAseq and real time PCR); radio-sensitivity (citoxicity and clonogenic assays) and damage accumulation (kinetics of H2AX phosphorylation). Results: we show that two compounds with completely different chemical structure can selectively inhibit KDM5 enzymes and that both compounds are capable of increasing sensitivity of breast cancer cells to ionizing radiation and H2AX phosphorylation. Conclusions: These findings confirm the involvement of H3K4 specific demethylases in DNA damage signaling and repair and suggest new strategies for the therapeutic use of their inhibitors.

Breast cancer (BC) affects millions of women; it is the leading cause of death by neoplasia in wom-en worldwide, with at least 500 thousand deaths each year, 70% of which occur in developing countries. Elastography evaluates tissue stiffness, making this a promising non-invasive real-time technique. BI-RADS is recognized as a standard and helpful technique for establishing BC risk. This study aimed to determine, by strain elastography (SE), the fat-to-lesion index (F/L index), sen-sitivity, specificity, and optimal cut-off to diagnose BC. This prospective study included 216 wom-en who underwent SE, ultrasound, mammography, and breast biopsy; according to mammogra-phy, we recruited BI-RADS category 2 (n= 5), category 3 (n=29), category 4 (n= 94), category 5 (n= 71) and category 6 (n=17); after biopsy, 108 women were classified as negative, and 108 were pos-itive for BC. Three expert BC radiologists performed all imaging interpretations and biopsies. Our results show mean values of the F/L index for negative biopsies of 3.70±2.57 and positive biopsies of 18.10±17.01; we developed two models for the prediction of BC, a logistic regression model with an AUC of 0.893 and a neural network with an AUC of 0.902. The Youden index yielded a F/L index cut-off >5.76, with a sensitivity and specificity of 84.26%. Positive Spearman's Rho cor-relation coefficient was observed between the F/L index and BI-RADS, r=.073 (p< 0.001). ANOVA test showed a difference between F/L index vs. molecular subtypes (p=0.002). SE is helpful as a di-agnostic complement to mammography, or in cases where the latter is contraindicated, elas-tography has an adequate predictive capacity and is a fast and minimally invasive procedure.

Sulfotransferases (SULTs) family plays a significant role in the biotransformation of a variety of xenobiotics and endogenous compounds by which carcinogenesis and mutagenicity of different malignancies are increasingly affected. Recent data identified various genetically polymorphic SULTs enzymes with significant variations in the enzyme activity. This study aimed to investigate the impact of SULT1A1 gene polymorphism and and its potential risk on females with breast cancer in Jordan using a PCR-RFLP and Sanger Sequencing methods. The analysis showed that 24.7% of the patients and 25.3% of the controls were homozygous for the SULT1A1*1 allele (SULT1A1*1/SULT1A1*1) compared to 8.8% and 5.7% homozygous for the SULT1A1*2 allele (SULT1A1*2/SULT1A1*2) for patients and controls respectively. Most of the patients and controls were heterozygous for SULT1A1*1 allele (SULT1A1*1/SULT1A1*2) with rates of 66.5% and 69.0% in patients and controls respectively. In addition, the frequencies of the mutant SULT1A1*2 allele were 0.42 and 0.4 in the patient and control groups respectively. No significant difference in genotype and allele distribution was noted between the breast cancer and control groups. The risk of breast cancer in individuals carrying the SULT1A1*2 allele was determined by combining the SULT1A1*1/SULT1A1*2 and ULT1A1*2/SULT1A1*2 genotypes. No association was observed between SULT1A1 polymorphism and breast cancer incidence (P = 0.63; OR, 0.93; 95% CI, 0.68–1.26). However, SULT1A1*2 allele was found to increase the risk of breast cancer by 1.26-fold.

PIEZO1 plays a crucial role in the human body as a mechanosensory ion channel. It has been demonstrated that PIEZO1 is important in tissue development and regulating many essential physiological processes. Studies have suggested that the PIEZO1 ion channel plays a role in invasion and progression in cancer; elevated levels of PIEZO1 have been correlated with increased migration in breast cancer cells, chemo-resistance and invasion in gastric cancer cells, and increased invasion of osteosarcoma cells. In addition, high PIEZO1 expression levels were correlated with a worse prognosis in glioma patients. On the other hand, studies in lung cancer have attributed high PIEZO1 levels to better patient outcomes. However, the clinical impact of PIEZO1 in breast cancer is not well characterized. Therefore, our goal was to determine the clinical relevance of PIEZO1 in breast cancer. Analysis of breast cancer data from The Cancer Genome Atlas (TCGA) was conducted to investigate PIEZO1 expression levels and correlation to survival, followed by validation in an independent dataset, GSE3494. We also performed gene set enrichment analysis (GSEA) and analyzed immune cell levels in breast tumors from TCGA through a CIBERSORT algorithm. Our results demonstrated that PIEZO1 expression levels are higher in hormone receptor (HR) negative than HR positive cohorts. High PIEZO1 expression is correlated with a significant decrease in survival in HR negative cohorts, suggesting that PIEZO1 could be utilized as a prognostic biomarker in HR negative breast cancer. GSEA showed that various signaling pathways associated with more invasive phenotypes and resistance to treatments, including epithelial-mesenchymal transition (EMT), hypoxia, and multiple signaling pathways, are enriched in high PIEZO1 HR negative tumors. Our results also demonstrated a decrease in CD8+ and CD4+ T cell infiltration in high PIEZO1 HR negative tumors. Further investigations are necessary to elucidate the mechanistic roles of PIEZO1 in HR negative breast cancer.

Breast cancer-related lymphedema (BCRL) affects approximately 20% of women after breast cancer therapy. Advances in treatment have increased life expectancy, thus the prevalence of BCRL will continue to rise with the number of cancer survivors. Hence the need to develop strategies to prevent this condition. We provide a systematic review of the literature on primary prevention of BCRL by prophylactic lymphatic surgery (PLS). Between June and August 2022, we conducted a search of PubMed, Google Scholar and Cochrane. In the end a total of eighteen papers were selected. The eleven studies without a control group reported only 15 of 342 patients who developed lymphedema at least six months after PLS (4.59%). The seven studies with a control group included 569 patients, 328 cases and 241 controls. Among the cases, 36 (10%) developed lymphedema. In contrast, the incidence of lymphedema in controls was 40% (98 of 241 patients). Formulation of definite recommendations in favour of PLS is hindered by low-quality studies. There is no consensus on which technique should be preferred, nor on whether adjuvant radiotherapy might affect the efficacy of PLS. Randomized controlled trials are mandatory to conceive evidence-based recommendations.

Translational medicine requires facile experimental systems to replicate the dynamic biological systems of diseases. Drug approval continues to lag, partly due to incongruencies in the research pipeline that traditionally involve 2D models, which could be improved with 3D models. The bone marrow (BM) poses challenges to harvest as an intact organ making it difficult to study disease processes such as breast cancer (BC) survival in BM, and to effective evaluation of drug response in BM. Furthermore, it is a challenge to develop 3D BM structures due to its weak physical properties, and complex hierarchical structure and cellular landscape. To address this, we leveraged 3D bioprinting to create a BM structure with varied methylcellulose (M):alginate (A) ratios. We selected hydrogels containing 4% (w/v) M and 2% (w/v) A, which recapitulates rheological and ultrastructural features of the BM while maintaining stability in culture. This hydrogel sustained the culture of two key primary BM microenvironmental cells found at the perivascular region, mesenchymal stem cells and endothelial cells. More importantly, the scaffold showed evidence of cell autonomous dedifferentiation of BC cells to cancer stem cell properties. This scaffold could be the platform to create BM models for various disease and also for drug screening.

Primary systemic treatment (PST) downsizes the tumor and improves pathological response. The aim of this study is to analyze the feasibility and tolerance of primary concurrent radio-chemotherapy (PCRT) in breast cancer patients. Patients with localized TN/HER2+ tumors were enrolled in this prospective study. Radiation is delivered concomitantly during the first 3 weeks of chemotherapy, and it is based on a 15 fractions scheme (40.5Gy/2.7Gy per fraction to whole breast and nodal levels I-IV. Chemotherapy is based on Pertuzumab-Trastuzumab-Paclitaxel followed by anthracyclines in HER2+ and CBDCA-Paclitaxel followed by anthracyclines in TN breast cancers patients. 58 patients were enrolled, 25 patients (43%) were TN and 33 patients HER2+ (57%). With a median follow-up of 24.2 months, 56 patients completed PCRT and surgery. A total of 35 patients (87.5%) achieved &gt;90% loss of invasive carcinoma cell in the surgical specimen. The 70.8% and the 53.1% of patients with TN and HER-2+ subtype respectively achieved complete pathological response (pCR). This is the first study of concurrent neoadjuvant treatment in breast cancer in which three strategies are applied simultaneously: fractionation of RT in 15 sessions, adjustment of CT to tumor phenotype and local planning by PET. The pCR rates are encouraging.

The National Breast and Cervical Cancer Early Detection Program (NBCCEDP) of Minnesota, “Sage”, provides breast cancer screening to uninsured women. We introduce a novel mapping technique, spatially adaptive filters (SAFs), to estimate utilization of Sage screening in Minnesota. Sage screenings (N = 74,712) were geocoded. The eligible population was modeled with the RTI synthetic population dataset. Between 2011 and 2015, 36,979 women a year were Sage eligible. Utilization was highly variable across Minnesota (M = 37.2%, range 0% - 131%, SD = 18.7%). This replicable approach modeled utilization rates to the neighborhood-level, allowing Sage to prioritize locations and engage communities.

(1) Background: This case report focuses on a 46-year-old female patient diagnosed with a rare and aggressive form of breast cancer known as rapidly growing, ulcerated breast cancer. The patient exhibited rapid progression of the disease, experiencing discomfort and noticeable changes in the size and texture of the affected breast over a short period of time; (2) Methods: An intensive neoadjuvant chemotherapy regimen was employed as the primary treatment approach. The patient's response to this treatment was closely monitored and assessed. Various diagnostic tests and imaging techniques were utilized to evaluate the extent of the disease and track its response to the chemotherapy; (3) Results: The patient's response to the neoadjuvant chemotherapy regimen was remarkable, resulting in a complete pathologic response. This outcome, although unusual in rapidly growing, ulcerated breast cancers, highlights the effectiveness of neoadjuvant chemotherapy in managing large, locally advanced breast cancers; (4) Conclusions: The multidisciplinary approach employed in managing this complex breast cancer case proved to be crucial to the patient's favorable outcome. Despite the aggressive nature of the disease and the challenges posed by the rapid growth and ulceration, the patient achieved a positive result. This case contributes to the limited clinical literature on such unusual and aggressive breast cancer cases, providing valuable insights for future clinical practice.8

Genome-wide association studies have revealed a locus at 8p12 that is associated with breast cancer risk. Fine-mapping of this locus identified 16 candidate causal variants (CCVs). However, as these variants are intergenic, their function is unclear. To map chromatin looping from this risk locus to a previously identified candidate target gene, DUSP4, we performed chromatin conformation capture analyses in normal and tumoral breast cell lines. We identified putative regulatory elements, containing CCVs, that loop to the DUSP4 promoter region. Using reporter gene assays, we found that the risk allele of CCV rs7461885 reduced the activity of a DUSP4 enhancer element, consistent with the function of DUSP4 as a tumor suppressor gene. Furthermore, the risk allele of CCV rs12155535, located in another DUSP4 enhancer element, was negatively correlated with looping of this element to the DUSP4 promoter region, suggesting that this allele would be associated with reduced expression. These findings provide the first evidence that CCV risk alleles downregulate DUSP4 expression, suggesting that this gene is a regulatory target of the 8p12 breast cancer risk locus.

Triple negative breast cancer (TNBC) has a higher mRNA expression of programmed cell death ligand 1 (PD-L1) which is a ligand to programmed cell death protein 1 (PD-1). The binding of the ligand leads to suppressed activity of T-cell-mediated immune response against cancer cells. The approval of anti-PD-L1 drugs including pembrolizumab and atezolizumab in subgroups of TNBC offer potential improvement to the current treatment regimens available for TNBC. We conducted a meta-analysis to review the efficacy of pembrolizumab and atezolizumab for the treatment of TNBC in both adjuvant and neo-adjuvant settings. A systematic strategy was used as per the PRISMA 2020 statement. All statistical analyses were conducted using Review Manager 5.4. Outcome measures included objective response rate, progression free survival, overall survival in adjuvant therapy groups, and pathological complete response rates in neoadjuvant groups. Six clinical trials were included. For adjuvant therapies, the ORR (OR=1.26, P = 0.04) of Atezolizumab/Pembrolizumab plus chemotherapy was higher in intention to treat (ITT) arms than the placebo groups in TNBC. A positive effect size was found for PFS in the ITT arms (Cohen’s d = 1.55, P<0.001). The Atezolizumab plus chemotherapy group had a positive effect size for OS compared to the control groups (Cohen’s d = 0.52, P<0.001). In the neo-adjuvant setting, patients in ITT arms had higher pCR rates as compared to the control groups (OR= 1.61, P = 0.001). Our findings collate evidence of pembrolizumab and atezolizumab as a viable treatment option among patients with TNBC with PDL1+ subgroups deriving benefits.

Background: The present retrospective study was designed to evaluate the relative diagnostic utility of breast-specific gamma imaging (BSGI) and breast magnetic resonance imaging (MRI) as means of evaluating female breast cancer patients in China. Methods: A total of 229 malignant breast cancer patients underwent ultrasound, mammography, BSGI, and MRI between January 2015 and December 2018 for initial tumor staging. Of these patients, 73 were subsequently treated via definitive breast surgery following neoadjuvant chemotherapy (NAC), of whom 17 exhibited a complete pathologic response (pCR) to NAC. Results: BSGI and MRI were associated with respective 76.8% and 69.6% sensitivity values as a means of detecting residual tumors following NAC, while both of these approaches exhibited comparable specificity in this diagnostic context (58.8% vs 70.6%, P=0.473). Conclusion: These results demonstrate that BSGI is a useful auxiliary approach to evaluating pCR to NAC treatment.

Protein-drug interactions are crucial for understanding drug delivery and cell functions. Jacalin is a suitable molecule for such targeting, as it specifically recognizes the tu-mor-associated Thomsen-Friedenreich antigen that is expressed on the glycosylated proteins in cancer cells. The present paper describes the interaction of curcumin and jacalin, a possible carrier molecule for the delivery of antitumor drugs due to its ability to recognize tumor cells. Our results have shown that both steady state fluorescence and fluorescent label-ling of jacalin are two reliable methods to determine jacalin-curcumin interactions. The affinity of jacalin for curcumin is consistently within the micromolar range (using flu-orescence and microscale thermophoresis) showing high-affinity binding of the com-plex. In vitro experiments on the triple negative breast cancer MDA-MB-231 cells indi-cated inhibition of cell growth after treating with the jacalin-curcumin complex for 48 h. The cell survival fraction was significantly reduced to 50% after combined treatment. In this paper, we report for the first time about the jacalin-curcumin interaction. We quantified this unique biomolecular interaction and gathered additional information on the binding event. We observed that the jacalin-curcumin complex inhibits the proliferation of the triple negative breast cancer MDA-MB-231 cells.

Formation of new blood (angiogenesis) and lymphatic (lymphangiogenesis) vessels are major events associated with most epithelial malignancies, including breast cancer. Angiogenesis is essential for cancer cell survival. Lymphangiogenesis is critical in maintaining tumoral interstitial fluid balance and importing tumor-facilitatory immune cells. Both vascular routes also serve as conduits for cancer metastasis. Intratumoral hypoxia promotes both events by stimulating multiple angiogenic/lymphangiogenic growth factors. Studies on tumor-associated lymphangiogenesis and its exploitation for therapy have received less attention from the research community than those on angiogenesis. Inflammation is a key mediator of both processes, hijacked by many cancers by aberrant expression of the inflammation-associated enzyme cyclo-oxygenase (COX)-2. In this review, we focus on breast cancer and show that COX-2 is a major promoter of both events, primarily resulting from the activation of Prostaglandin (PG) E receptor EP4 on tumor cells, tumor-infiltrating immune cells, and endothelial cells; and induction of oncogenic microRNAs. COX-2/EP4 pathway also promotes additional events in breast cancer progression, such as cancer cell migration, invasion, and stimulation of stem–like cells. Based on a combination of studies using multiple breast cancer models, we show that EP4 antagonists hold a major promise in breast cancer therapy in combination with other modalities including immune check-point inhibitors

Dietary pattern (DP) and its relationship with disease biomarkers has received recognition in nutritional epidemiology investigations. However, DP relationships with adipokines (i.e., adiponectin and leptin) among breast cancer survivors remain unclear. Therefore, we assessed relationships between DP with high molecular weight (HMW) adiponectin and leptin concentration among breast cancer survivors. This cross-sectional study involved 128 breast cancer survivors who attended the oncology outpatient clinic at two main government hospitals in East Coast of Peninsular Malaysia. The serum concentration of HMW adiponectin and leptin were measured using enzyme-linked immunosorbent assay (ELISA) kits. Reduced rank regression method was used to analyze DP. Relationships between DP with HMW adiponectin and leptin were examined using regression models. Findings showed that a one-unit increase in the ‘energy-dense, high-saturated fat and low-fiber’ DP z-score was associated with a 0.41 µg/mL lower HMW adiponectin (95% CI: -0.806, -0.014) which was independent of age, BMI, cancer stage, duration since diagnosis, education level and occupation status. A similar relationship with leptin concentration was not observed. In conclusion, ‘energy-dense, high-saturated fat and low-fiber’ DP, which is characterized by high sugar-sweetened drink and fat-based spread but low intake of fruits and vegetables, is an unhealthy dietary pattern and unfavorable for HMW adiponectin concentration but not for leptin. These findings could serve as a basis in developing specific preventive strategies that are tailored to the growing population of breast cancer survivors.

Breast cancer is the most common malignancies in women and the second leading cause of cancer death in women. Triple negative breast cancer (TNBC) subtype is a breast cancer subset without ER, PR and HER2 expression, limiting treatment options and presenting a poorer survival rate. Thus, we investigated whether HDACi would be used as potential anti-cancer therapy on breast cancer cells. In this study, we found TNBC and HER2-enrich breast cancers are extremely sensitive to Panobinostat, Belinostat of HDACi via experiments of cell viability assay, apoptotic marker identification and flow cytometry measurement. On the other hand, we developed a bioluminescence based live cell non-invasive apoptosis detection sensor (IADS) detection system to evaluate the quantitative and kinetic analyses of apoptotic cell death by HDAC treatment on breast cancer cells. In addition, the use of HDACi may also be accompanied with chemotherapeutic agent such as doxorubicin to synergic drug sensitivity on TNBC cell (MDA-MB-231), but not in breast normal epithelia cells (MCF-10A), providing therapeutic benefits against breast tumor in clinic.

With cancer often classified as a disease that has an important epigenetic component, natural compounds that have the ability to regulate the epigenome become ideal candidates for study. Humans have a complex diet, which illustrates the need to elucidate the mechanisms of interaction between these bioactive compounds in combination. The natural compounds withaferin A (WA), from the Indian winter cherry, and sulforaphane (SFN), from cruciferous vegetables, have numerous anti-cancer effects and some report their ability to regulate epigenetic processes. Our study is the first to investigate the combinatorial effects of low physiologically achievable concentrations of WA and SFN on breast cancer cell proliferation, histone deacetylase1 (HDAC1) and DNA methyltransferases (DNMTs). No adverse effects were observed on control cells at optimal concentrations. There was synergistic inhibition of cellular viability in MCF-7 cells and a greater induction of apoptosis with the combinatorial approach than with either compound administered alone in both MDA-MB-231 and MCF-7 cells. HDAC expression was down-regulated at multiple levels. Lastly, we determined the combined effects of these bioactive compounds on the pro-apoptotic BAX and anti-apoptotic BCL-2 and found decreases in BCL-2 and increases in BAX. Taken together, our findings demonstrate the ability of low concentrations of combinatorial WA and SFN to promote cancer cell death and regulate key epigenetic modifiers in human breast cancer cells.

Cancers overexpressing the ERBB2 oncogene are aggressive and associated with a poor prognosis. Trastuzumab is a ERBB2 specific recombinant antibody employed for the treatment of these diseases since it blocks ERBB2 signaling causing growth arrest and survival inhibition. While the effects of Trastuzumab on ERBB2 cancer cells are well known, those on the extracellular vesicles released from these cells are scarce. This study focused on ERBB2+ breast cancer cells and aimed to establish what type of EVs they release and whether Trastuzumab affects their morphology and molecular composition. To these aims, we performed immunoelectron microscopy, immunoblot, and high-resolution mass spectrometry analyses on EVs purified by differential centrifugation of culture supernatant. Here we show that EVs released from ERBB2+ breast cancer cells are polymorphic in size and appearance, and that ERBB2 is preferentially associated with large (120 nm) EVs. Moreover, we report that Tz induces the expression of a specific glycosylated 50 kDa isoform of the CD63 tetraspanin and modulates the expression of 51 EVs proteins, including TOP1. As these proteins are functionally associated with organelle organization, cytokinesis, and response to lipids, we suggest that Tz may influence these cellular processes in target cells at distant sites via modified EVs.

With advances in next-generation sequencing(NGS) technologies, large number of multiple types of high-throughput genomics data are available. A great challenge in exploring cancer mechanism is to identify the driver genes from the mutation genes by analyzing and integrating multi-types genomics data. Breast cancer is known as a heterogeneous disease. The identification of subtype-specific driver genes is critical to guide the diagnosis, assessment of prognosis and treatment of breast cancer. We developed an integrated frame based on gene expression profilings and copy number variation(CNV) data to identify breast cancer subtype-specific driver genes. In this frame, we employed statistical machine-learning method to select gene subsets and utilized an module-network analysis method to identify potential candidate driver genes. The final subtype-specific driver genes were acquired by paired-wise comparison in subtypes. To validate specificity of the driver genes, the gene expression data of these genes were applied to classify the patient samples with 10-fold cross validation and the enrichment analysis were also conducted on the identified driver genes. The experimental results show that the proposed integrative method can identify the potential driver genes and the classifier with these genes acquired better performance than with genes identified by other methods.

Chemical combinations are believed to reduce drug toxicity, delay cancer cell growth, and achieve enhanced efficacy compared with single active drugs. This research investigated the synergistic effect of DOX and Zm-093, a new sulfonamide derivative, on improving the potential for inducing apoptosis in breast cancer (BC) cell lines. First, the Zm-093 compound was synthesized and its structure was confirmed by FT-IR and NMR. Then, the IC50 values for DOX and Zm-093 were calculated to be 1.21 and 51.24 μM, respectively. To investigate the synergistic effect, Compusyn software was utilized to calculate the combination index (CI). Different methods, including western blotting, flow cytometry, and TUNEL, were used to evaluate the potential synergistic effects of these compounds on inducing apoptosis in MCF-7 cells. Combining the indexes obtained at all concentrations revealed synergistic results. The proapoptotic proteins Bax, tBid, and caspase-3, however, increased 2.4, 3.3, and 5.7 times more than those in the control group. Flow cytometry analysis and the TUNEL method in cells treated with DOX and Zm-093 showed that apoptosis was significantly higher than in other groups. The results confirmed the synergistic effect of DOX and ZM-093 on apoptotic factors expression in MCF-7 cells.

Background: Assessing the impact of bone health clinical management in breast cancer (BC) patients receiving adjuvant endocrine therapy and designing a personalized clinical pathway to reduce bone loss, in an Italian research hospital. Methods: The primary endpoint was to assess (through the process improvement organizational method) the clinical pathway that post-surgical BC patients prescribed with endocrine therapy undergo to prevent bone loss. The secondary endpoint was to design a personalized clinical pathway for a prompt implementation of guidelines, to assess and possibly prescribe antiresorptive therapy. Results: During the first year of the new diagnostic therapeutic assistance pathway execution, an 60% increase in Dual-Energy X-ray Absorptiometry evaluations within 30 days and a 39.5% increase in antiresorptive therapy prescription within 90 days (since prescription of endocrine therapy) were shown, thus increasing patients’ compliance. Conclusion: Case managers and bone health specialists in this context can improve patients’ adherence to therapies and bone health, helping physicians to expand their collaboration.

The emergence of CDK4/6 inhibitors, such as palbociclib, ribociclib, and abemaciclib, has revolutionized the treatment landscape for hormone receptor-positive breast cancer. These agents have demonstrated significant clinical benefits in terms of both progression-free survival and overall survival. However, resistance to CDK4/6 inhibitors remains a challenge, limiting their long-term efficacy. Understanding the complex mechanisms driving resistance is crucial for the development of novel therapeutic strategies and improvement of patient outcomes. Translational research efforts, such as preclinical models and biomarker studies, offer valuable insight into resistance mechanisms and may guide the identification of novel combination therapies. This review paper aims to outline the reported mechanisms underlying CDK4/6 inhibitor resistance, drawing insights from both clinical data and translational research in order to help direct the future of treatment for hormone receptor positive metastatic breast cancer.

Background: Metastasis is a complex process that involves the spread of the tumor to distant parts of the body from its original site. Metastatic dissemination represents the main physiopathology of cancer. Soluble factors such as cytokines have been closely related to breast cancer (BC) metastasis. Bisphenol A (BPA) is an endocrine disrupting chemical compound with estrogenic properties, which exposure in the early stages of neonatal life leads to an increase in the size and weight of breast tumors and cellular changes in the tumoral immune microenvironment. Methods: Thus, we used female BALB/c mice that were exposed neonatally to a single dose of BPA. Once sexual maturity was reached, a mammary tumor was induced injecting 4T1 cells in situ. After 25 days of injection, we evaluated endocrine alterations, cytokine expression, tissue alterations denoted by macro and micro metastases in the lung, and metastasis-induced cell infiltration. Results: BPA neonatal treatment did not show significant endocrine alterations. Nevertheless, BPA induced a great rate of metastasis to the lung associated with higher intratumoral expression of IL-1b, IL-6, IFN-g, TNF-a and VEGF. Conclusions Our data suggest that cytokines are key players in BC metastasis induction, and that BPA is a risk factor to be considered. This knowledge must be considered with the aim of recognizing environmental pollution in the clinical history of patients to possibly counter BC metastases.

Background: DSCAM-AS1 is a cancer-related long noncoding RNA with higher expression levels in Luminal A, B and HER2-positive Breast Cancer (BC), where its expression is strongly dependent on Estrogen Receptor Alpha (ERα). Methods: To decipher its function, DSCAM-AS1 expression was measured by qRT-PCR in tissue samples from 93 BC patients in addition to a meta-analysis of 30 gene expression datasets, together with the evaluation of its association with clinical data. By computational analyses of our RNA-Seq in MCF-7 cells, we investigated the DSCAM-AS1 knock-down effects at both gene and isoform levels. Results: We confirmed DSCAM-AS1 overexpression in high grade Luminal A, B and HER2+ BCs and found a significant correlation with disease relapse. 908 genes were regulated by DSCAM-AS1-silencing, primarily involved in cell cycle and inflammatory response. Noteworthy, the analysis of alternative splicing and isoform regulation revealed 2,085 splicing events regulated by DSCAM-AS1, enriched in differential polyadenylation sites and 3’UTR shortening events. Finally, the DSCAM-AS1-interacting splicing factor hnRNPL was predicted as the most enriched RBP for exon skipping and 3’UTR events. Conclusion: The relevance of DSCAM-AS1 overexpression in BC is confirmed by clinical data and further enhanced by its possible involvement in the regulation of RNA processing, which is emerging as one of the most important dysfunctions in cancer.

Pregnancy associated plasma protein-A (PAPP-A) plays an integral role in breast cancer (BC), especially triple negative breast cancer (TNBC). This subtype accounts for the most aggressive BC, possesses high tumor heterogeneity, is least responsive to standard treatments and has the poorest clinical outcomes. There is a critical need to address the lack of effective targeted therapeutic options available. PAPP-A is a protein that is highly elevated during pregnancy. Frequently, higher PAPP-A expression is detected in tumors than in healthy tissues. The increase in expression coincides with increased rates of aggressive cancers. In BC, PAPP-A has been demonstrated to play a role in tumor initiation, progression, metastasis including epithelial-mesenchymal transition (EMT), as well as acting as a biomarker for predicting patient outcomes. In this review, we present the role of PAPP-A, with specific focus on TNBC. The structure and function of PAPP-A, belonging to the pappalysin subfamily, and its proteolytic activity are assessed. We highlight the link of BC and PAPP-A with respect to the IGFBP/IGF axis, EMT, the window of susceptibility and the impact of pregnancy. Importantly, the relevance of PAPP-A as a TNBC clinical marker is reviewed and its influence on immune-related pathways are explored. The relationship and mechanisms involving PAPP-A reveal the potential for more treatment options that can lead to successful immunotherapeutic targets and the ability to assist with better predicting clinical outcomes in TNBC.

Breast cancer is a leading cause of death among women. Conventional screening methods, such as mammography, and ultrasound diagnosis are expensive and have significant limitations. Digital Image Elasto Tomography (DIET) is a new noninvasive breast cancer screening system that has a potential to be a low cost and reliable breast cancer screening tool. It is based on modal analysis of the breast mass, and stereographic 3D image analysis to detect the stiffer abnormal tissues. However, camera sensor noise, especially Gaussian noise is a major source of Optical Flow (OF) error in this approach to tumor detection. This work studies the performance of different conventional filters, including the standard Gaussian filter tool to remove this noise and produce more robust screening results. A radical approach, Multiple Frame Noise Removal (MFNR) is proposed, for use in this type of medical image processing instead of a Gaussian filter or other typical image noise removal tools. Its a multiple frame noise removal method where Probability Density Function (PDF) of noise is extracted from the multiple images by characterizing the same pixel positions in multiple images. The noise becomes deterministic, and hence easily removed. The proposed algorithm was applied to a data set from 10 phantom breast tests with a prototype DIET system, and 10 in-vivo samples from healthy women. Comparisons were made to an optimal Gaussian filter form that is commonly used. Reductions in OF error using these digitally imaged data sets was used to compare performance. Refinement of the images for medical applications requires higher PSNR, which was successfully achieved by using MFNR algorithm. In this study, the algorithm was used to improve the imaging results of a DIET system. The conventional wisdom that states that noise removal and detail preservation are contrasting effects is

Development of targeted therapies for triple-negative breast cancer (TNBC) is an unmet medical need. Cisplatin has demonstrated its promising potential for the treatment of TNBC in clinical trials; however, cisplatin treatment is associated with hypoxia that in turn promotes cancer stem cell (CSC) enrichment and drug resistance. Therapeutic approaches to attenuate this may lead to increased cisplatin efficacy in the clinic for the treatment of TNBC. In this report, we analyzed clinical dataset of TNBC and found that TNBC patients possessed higher levels of EGFR and hypoxia gene expression. A similar expression pattern was also observed in cisplatin-resistant ovarian cancer cells. We thus developed a new therapeutic approach to inhibit EGFR and hypoxia by combination of metformin and gefitinib that sensitized TNBC cells to cisplatin and led to the inhibition of both CD44+/CD24- and ALDH+ CSCs. We demonstrated a similar inhibition efficacy on organotypic cultures of TNBC patient samples ex vivo. Since these drugs have already been used frequently in the clinic, this study illustrates a novel, clinically translatable therapeutic approach to treat patients with TNBC.

The standard care for metastatic breast cancer (MBC) is systemic therapies with imbrication of focal treatment for symptoms. Recently, thanks to implementation of radiological and metabolic exams and development of new target therapies, oligometastatic and oligoprogressive settings are even more common, paving the way to a paradigm change of focal treatments role. In fact, according to immunophenotype, radiotherapy can be considered with radical intent in these settings of patients. The aim of this literature review is to analyse available clinical data on prognosis of bone metastases from breast cancer and benefits of available treatments for developing a practical guide for clinicians.

Two related tumor suppressor genes, Brca1 and Brca2, attract a lot of attention from both fundamental and clinical points of view. Oncogenic hereditary mutations in these genes are firmly linked to the early onset of breast and ovarian cancers. However, the molecular mechanisms that drive extensive mutagenesis in these genes are not known. In this review we hypothesize that one of the potential mechanisms behind this phenomenon can be mediated by Alu mobile genomic elements. Linking mutations in the BRCA1 and BRCA2 genes to the general mechanism(s) of genome stability and DNA repair is critical to ensure the rationalized choice of anti-cancer therapy. Accordingly, we review the literature available on mechanisms of DNA damage repair where these proteins are involved in and how the inactivating mutations in these genes (BRCAness) can be exploited in anti-cancer therapy. We also propose a hypothesis that explains why breast and ovarian epithelial tissues are preferentially susceptible to mutations in BRCA genes. Finally, we discuss perspectives of novel therapeutic approaches for treating BRCAness cancers.

BTB domain and CNC homology 1 (BACH1) is a highly expressed transcription factor in tumors including breast and lung, relative to their non-tumor tissues. BACH1 is known to regulate multiple physiological processes including heme homeostasis, oxidative stress response, senescence, cell cycle, and mitosis. In a tumor, BACH1 promotes invasion and metastasis of cancer cells, and the expression of BACH1 presents a poor outcome for cancer patients including breast cancer patients. Recent studies identified novel functional roles of BACH1 in the regulation of metabolic pathways in cancer cells. BACH1 inhibits mitochondrial metabolism through transcriptional suppression of mitochondrial membrane genes. In addition, BACH1 suppresses activity of pyruvate dehydrogenase (PDH), a key enzyme that converts pyruvate to acetyl-CoA for the citric acid (TCA) cycle through transcriptional activation of pyruvate dehydrogenase kinase (PDK). Moreover, BACH1 increases glucose uptake and lactate secretion in aerobic glycolysis through the expression of metabolic enzymes involved such as hexokinase 2 (HK2) and glyceraldehyde 3- phosphate dehydrogenase (GAPDH). Pharmacological or genetic inhibition of BACH1 could reprogramme metabolic pathways, subsequently rendering metabolic vulnerability of cancer cells. Furthermore, inhibition of BACH1 decreased antioxidant-induced glycolysis rates as well as reduced migration and invasion of cancer cells, suggesting BACH1 as a potentially useful cancer therapeutic target.

(1) Background: The aim of the present study was to evaluate the effect of ETS homologous factor (EHF) in malignant breast cancer cells. (2) Methods: Overexpression and knockdown of the EHF gene in human and mouse breast cancer cells were performed, and the TCGA dataset and Q-omics were analyzed. (3) Results: We found that the tumor suppressor NDRG2 is correlated with EHF gene expression in triple-negative breast cancer cells, that EHF overexpression results in reduced cell proliferation and that apoptosis is promoted by chemotherapeutic reagent treatment of EHF-overexpressing cells. By EHF overexpression, senescence-associated β-galactosidase activity and p21WAF1/CIP1 expression were increased, suggesting that EHF may induce cellular senescence. In addition, overexpression of EHF reduced the migratory ability and inhibited epithelial-mesenchymal transition (EMT). Furthermore, EHF inhibited the phosphorylation of STAT3. Overexpression of EHF also reduced tumor size, and lung metastasis in vivo. At the tumor site, β-galactosidase activity was increased by EHF. Finally, Kaplan-Meier-plotter analysis showed that TNBC patients with high expression of EHF had a longer relapse-free survival rate. (4) Conclusions: Our findings demonstrated that EHF inhibits breast tumor progression by inducing senescence and regulating EMT in TNBC cells.

Breast cancer is the most common cause of mortality due to cancer for woman both in Lithuania and worldwide. Chances of survival after diagnosis differ significantly depending on the stage of disease at the time of diagnosis and other factors. One way to estimate survival is to construct a Kaplan-Meier estimate for each factor value separately. However, in cases when it is impossible to observe a large number of patients (for example, in case of countries with lower numbers of inhabitants) dividing data into subsets, say, by stage at diagnosis may lead to results where some subsets contain too little data so that results of Kaplan Meier (or any other) method will become statistically incredible. The problem may become even more acute if the researcher would like to use more risk factors, such as stage at diagnosis, sex, place of living, treatment method, etc. Alternatively, Cox models are used to analyse survival data with covariates, and they don’t require dividing the data into subsets according to chosen risks factors (hazards).

Breast cancer is the most common cause of death for women worldwide. Thus, the ability of artificial intelligence systems to predict and classify breast cancer is very important. In this paper, a hybrid ensemble method classification mechanism is proposed based on a majority voting mechanism. First, the performance of different state-of-the-art machine learning classification algorithms for the Wisconsin Breast Cancer Dataset (WBCD) were evaluated. The three best classifiers were then selected based on their F3 score. F3 score is used to emphasize the importance of false negatives (recall) in breast cancer classification. Then, these three classifiers, simple logistic Regression learning, stochastic gradient descent learning and multilayer perceptron network, are used for ensemble classification using a voting mechanism. We also evaluated the performance of hard and soft voting mechanism. For hard voting, majority-based voting mechanism was used and for soft voting we used average of probabilities, product of probabilities, maximum of probabilities and minimum of probabilities-based voting methods. The hard voting (majority-based voting) mechanism shows better performance with 99.42% as compared to the state-of-the-art algorithm for WBCD.

To investigate whether high body mass index (BMI) increases the risk of recurrence and corre-lates with higher glucose uptake in recurrent lesions in post-menopausal female patients with breast cancer. The hospital database was searched to retrieve breast cancer patients, who had undergone an [18F]FDG PET/CT scan before neoadjuvant chemotherapy and curative-intent sur-gery. BMI was calculated at the baseline [18F]FDG PET/CT scan. There was a median follow-up of 5 years after the baseline PET/CT scan to identify: recurrence in the breast (T_rec); lymph nodes (N_rec); distant locations (M_rec). Furthermore, SUVmax was measured in the sites of recur-rence. A chi-square test was used to investigate any difference in the frequency of any recur-rence, T_rec, N_rec, and M_rec between overweight women (BMI≥25 kg/m2) and women with a BMI<25 kg/m2 (p<0.05). SUVmax, was compared using a t-test (p<0.05) between the two groups. A total of post-menopausal 142 women (BMI: 26.84±5.59; 84 overweight and 58 with normal weight) were retrieved. There were 48 recurrences at the follow-up. The chi-square test demon-strated in overweight women an increased frequency of any recurrence (35 vs. 13; p=0.025) and T_rec (15 vs. 2; p=0.018) and a higher T_rec SUVmax (4.74±2.90 vs. 1.85 ± 0.63; p=0.09) compared to women with a BMI<25 kg/m2. BMI seems to correlate with an increased rate of recurrence, espe-cially in the breast, and a higher glucose uptake in post-menopausal patients with recurrent breast cancer.

As breast cancer continues to take a devasting public health toll, most primary prevention approaches are targeted at individual actions. We have proposed, instead, developing systemic, population approaches to preventing the disease. We used a combined qualitative-quantitative methodology, Group Concept Mapping (GCM), to identify Importance and Feasibility ratings of systemic interventions across a wide spectrum of approaches and stakeholders. Participants (n=351) from across the state of California sorted 84 potential interventions into topical piles, and then rated each intervention on perceived Importance and Feasibility. Multidimensional scaling and cluster analysis identified eleven clusters or themes of interventions. Participants rated interventions on Importance and Feasibility differently depending on the region of the state in which they lived. The results of this study underscore the importance of sharing health information with and seeking public health solutions from community partners in general and from beyond the urban areas usually studied.

Obesity is one of the most prevalent chronic diseases and has become a global epidemic. Obesity leads to a greater risk of breast cancer (BC), metastases, recurrence, and decreased survival. For sustained weight loss, bariatric surgery is effective as a long-term solution. Bariatric surgery is associated with improved outcomes of several cancers including BC, although the mechanisms mediating this protection are unknown. We hypothesized that elevated bile acid pools detected after bariatric surgery may be factors that contribute to improved BC outcomes. Indeed, patients with greater expression of the bile acid receptor FXR displayed improved survival in specific BC subtypes. Patients with tumors that are estrogen receptor negative (ER-) displayed significantly elevated survival with higher FXR (NR1H4) expression compared to lower expression. FXR is a nuclear hormone receptor activated by bile acids. Therefore, we posited that activating FXR using an established FDA-approved agonist would display anticancer effects. Indeed, FXR agonism by the bile acid mimetic known commercially as OCALIVA (“OCA”), or Obeticholic acid (INT-747), significantly reduced BC progression and overall tumor burden in a pre-clinical model. In human and murine BC analyses in vitro, agonism of FXR significantly and dose-dependently inhibited proliferation, migration, and viability. In contrast, synthetic agonism of another common bile acid receptor, the G protein-coupled bile acid receptor (GPBAR1, TGR5) which is mainly activated by secondary bile acids, failed to significantly alter cancer cell dynamics. In conclusion, agonism of FXR by primary bile acid memetic OCA yields potent anti-tumor effects potentially through inhibition of proliferation and migration and reduced cell viability. Findings suggest that FXR is a tumor suppressor gene with high potential for personalized therapeutic strategies for individuals with BC.

The epithelial cell adhesion molecule (EpCAM) is a stem cell and carcinoma antigen, which mediates cellular adhesion and proliferative signaling by the proteolytic cleavage. In contrast to low expression in normal epithelium, EpCAM is frequently overexpressed in various carcinomas, which correlates with poor prognosis. Therefore, EpCAM has been considered as a promising target for tumor diagnosis and therapy. Using the Cell-Based Immunization and Screening (CBIS) method, we previously established an anti‐EpCAM monoclonal antibody (EpMab-37; mouse IgG1, kappa). In this study, we investigated the antibody‐dependent cellular cytotoxicity (ADCC), complement‐dependent cytotoxicity (CDC), and an antitumor activity by a defucosylated mouse IgG2a-type of EpMab-37 (EpMab-37-mG2a-f) against an EpCAM‐expressing breast cancer cell line (BT-474). EpMab-37-mG2a-f recognized BT-474 cells with a moderate binding-affinity [a dissociation constant (KD): 2.9x10-8 M] by flow cytometry. EpMab-37-mG2a-f exhibited ADCC and CDC for BT-474 cells by murine splenocytes and complements, respectively. Furthermore, administration of EpMab-37-mG2a-f significantly suppressed the BT-474 xenograft tumor development compared with the control mouse IgG. These results indicated that EpMab-37-mG2a-f exerts antitumor activities against the BT-474 xenograft, and could provide valuable therapeutic regimen for the breast cancers.

Using a breast cancer (BC) cellular model: MDA-MB-231 cells with blocked synthesis of galacto-sylceramide (GalCer; MDA.Δ.UGT8.4) and MCF7 and T47D cells that over-produced GalCer (MCF7.UGT8 and T47D.UGT8), we found that GalCer increased resistance to doxorubicin, paclitaxel, and cisplatin serving as an anti-apoptotic molecule. These results were supported by a study using murine mammary carcinoma 4T1 cells over-producing GalCer, which were trans-planted into Balb/c mice and were more resistant to doxorubicin therapy than the control. Sub-sequent studies revealed that GalCer specifically downregulated the level of pro-apoptotic TNFRSF1B and TNFRSF9 genes and increased the level of the anti-apoptotic BCL2 gene expres-sion, suggesting that GalCer regulates their expression at the level of transcription. Consistent with this hypothesis, MDA-MB-231 and MCF7.UGT8 cells with high GalCer content showed lower activity of TNFRSF1B and TNFRSF9 promoters than cells lacking GalCer. In contrast, the activity of the BCL2 promoter in MCF7.UGT8 was higher than in MCF7 cells without GalCer. However, no difference in BCL2 promoter activity was observed between MDA-MB-231 cells with high GalCer level and GalCer-negative MDA.Δ.UGT8.4 cells. Instead, we found that GalCer increased the stability of Bcl-2 mRNA. As a candidate protein that simultaneously increases the expression of TNFRSF1B and TNFRSF9 genes and decreases the expression of BCL2 gene and stability of Bcl-2 transcripts is probably p53, its expression was analysed in BC cells containing various amounts of GalCer. In agreement with this hypothesis, BC cells with high GalCer con-tent are characterized by significantly lower expression of p53, and inhibition of p53 using siR-NA resulted in decreased expression of TNFRS1B and TNFRS9 genes and increased expression of BCL2 gene.

Breast cancer has become the most diagnosed cancer in women globally with 2.3 million new diagnosis each year. Accurate early staging is essential for improving survival rates with metastatic spread from loco regional to distant metastasis decreasing rates by 50%. Current guidelines do not advice the routine use of Positron Emission Tomography (PET)-Computed Tomography (CT) in staging of early breast cancer in the absence of symptoms. However, there is a growing body of evidence to suggest that PET-CT used in this early stage can benefit the patient by improving staging and as a result treatment and outcome as well as psychological burden without increasing costs to the health service. Ongoing research in PET radiomics and artificial intelligence is showing promising future prospects in its use in diagnosis, staging, prognosticatication and assessing response to treatment in breast cancer. Furthermore ongoing research to address current limitations of PET-CT by improving techniques and tracers is encouraging.

Chemotherapy is a standard therapeutic option for triple-negative breast cancer (TNBC); however, its effectiveness is often compromised by drug-related toxicity and resistance development. Herein, we aimed to evaluate whether an improved antineoplastic effect could be achieved in vitro and in vivo in TNBC by combining dovitinib, a multi-kinase inhibitor, with calcitriol, a natural anti-cancer hormone. In vitro, cell proliferation and cell-cycle distribution were studied by sulforhodamine B-assays and flow cytometry. In vivo, dovitinib/calcitriol effects on tumor growth, angiogenesis and endothelium activation were evaluated in xenografted mice by caliper measures, Itgb3-immunohistochemistry and 99mTc-RGD2-tumor uptake. The drug combination elicited a synergistically improved antiproliferative effect in TNBC-derived cells, which allowed a 7-fold dovitinib dose-reduction. Mechanistically, the co-treatment induced cell death and accumulation in S and G2/M phases, while inhibited tumor growth to a greater extent than each compound alone. Tumor uptake of 99mTc-RGD2 was reduced by dovitinib, suggesting angiogenesis inhibition, which was corroborated by decreased endothelial cell growth and tumor vessel density. In summary, calcitriol synergized dovitinib anticancer effects in vitro and in vivo, allowing for a significant dose-reduction of dovitinib, while maintaining its antiproliferative potency. Our results suggest the beneficial convergence of independent antitumor mechanisms of dovitinib and calcitriol to inhibit TNBC-tumor growth.

The prompt and accurate diagnosis of breast lesions, including the distinction between cancer, non-cancer, and suspicious cancer, plays a crucial role in the prognosis of breast cancer. In this paper, we introduce a novel method based on feature extraction and reduction for detection of breast cancer in mammography images. First, we extract features from multiple pre-trained convolutional neural network (CNN) models, and then concatenate them. The most informative features are selected based on their mutual information with the target variable. Subsequently, the selected features can be classified using a machine learning algorithm. We evaluate our approach using four different machine learning algorithms, and our results demonstrate that the neural network-based classifier yields an accuracy as high as 92% for the RSNA dataset which is a new dataset that provides two views and additional features such as age. We compare our proposed algorithm with state-of-the-art methods and demonstrate its superiority, particularly in terms of accuracy and sensitivity. For the MIAS dataset, we achieve an accuracy as high as 94.5%, and for the DDSM dataset, an accuracy of 96% is attained. These results highlight the effectiveness of our method in accurately diagnosing breast lesions and surpassing existing approaches.

Background: Pathologic complete response (pCR) of breast cancer after neoadjuvant chemotherapy (NAC) is highly related to molecular subtypes. Patients who achieved tumor pCR after NAC have a better prognosis. However, despite of better prognosis, pCR patients have a potential for recurrence. There is little evidence of risk factors of recurrence in patients with pCR. We aim to analyze factors associated with tumor recurrence in patients who achieved pCR. Methods: This study retrospectively reviewed the data of patients diagnosed with breast cancer who achieved pCR after receiving NAC between January 2009 and December 2018 in Samsung Medical Center. pCR was defined as no residual invasive cancer in the breast and axillary nodes even if there is residual ductal carcinoma in situ (ypT0 or ypTis with ypN0). Breast cancers are classified into 4 subtypes based on hormone receptors (HR) and human epithelial growth factor receptor 2 (HER2) status. Patients who had bilateral breast cancer, inflammatory breast cancer, distant metastasis, unknown subtype, and histologically unique case were excluded from the study. Results: In total 483 patients were included in this study except for patients who corresponded to the exclusion criteria. The median follow-up duration was 59.0 months (range, 0.5-153.3 months). Breast cancer recurred in 4.1% of patients (20 of 483). There was a significant difference in clinical T (p = .004) and clinical N (p = .034) stage in the Kaplan-Meier curve for disease-free survival. Molecular subtypes (p = .573), Ki67 (p = 1.000), and breast surgery type (p = .574) were not associated with tumor recurrence in patients who achieved pCR after NAC. In the clinical T stage and clinical N stage, there was a significant difference between recurrence and no-recurrence groups (clinical T stage; p = .045, clinical N stage; p = .002). Univariable Cox regression revealed statistical significance in the clinical T stage (p = .049) and clinical N stage (p = .010), while multivariable Cox regression demonstrated non-significance in the clinical T stage (p = .320) and clinical N stage (p = .073). Conclusion: Results in this study showed that clinical T, clinical N stage, and molecular subtypes were not statistically significant predictors of recurrence in patients who achieved pCR after NAC. It is hypothesized that a multicenter-based study would lead to the identification of factors as predictors of recurrence after achieving pCR.

The aim of this study was to determine whether a rowing training program improved the quantity and quality of physical activity and quality of life in female breast cancer survivors (stage I - 4.35%; II - 30.43%; III - 52.17%; and IV - 8.7%) diagnosed 6.57 ± 5.02 years previously, who had undergone a subsequent intervention (preservation 53.52%; total mastectomy 39.13% and double mastectomy 4.35%) and had a current mean age of 53.70 ± 7.88 years. The participants (N = 30) engaged in a 12-week training program, each week comprising three sessions and each session lasting 60-90 minutes. An anthropometric evaluation was performed before and after the program. The short form of the International Physical Activity Questionnaire (IPAQ-SF) and the Short Form 36 Health Survey (SF-36) were also administered. The results showed statistically significant improvements in levels of physical activity and in the dimensions of quality of life. We can conclude that a 12-week rowing training program tailored to women who have had breast cancer increases physical activity levels, leading to improved health status and quality of life.

The aim of this study was to determine whether a rowing training program improved the quantity and quality of physical activity and quality of life in female breast cancer survivors (stage I - 4.35%; II - 30.43%; III - 52.17%; and IV - 8.7%) diagnosed 6.57 ± 5.02 years previously, who had undergone a subsequent intervention (preservation 53.52%; total mastectomy 39.13% and double mastectomy 4.35%) and had a current mean age of 53.70 ± 7.88 years. The participants (N = 30) engaged in a 12-week training program, each week comprising three sessions and each session lasting 60-90 minutes. An anthropometric evaluation was performed before and after the program. The short form of the International Physical Activity Questionnaire (IPAQ-SF) and the Short Form 36 Health Survey (SF-36) were also administered. The results showed statistically significant improvements in levels of physical activity and in the dimensions of quality of life. We can conclude that a 12-week rowing training program tailored to women who have had breast cancer increases physical activity levels, leading to improved health status and quality of life.