BOLD-100, a ruthenium-based complex, sodium trans-[tetrachloridobis(1H-indazole)ruthenate(III)] (also known as IT-139, NKP1339 or KP1339), is a novel small molecule drug that demonstrated a manageable safety profile at the maximum tolerated dose and modest antitumor activity in a phase I clinical trial. BOLD-100 has been reported to inhibit the upregulation of the endoplasmic reticulum stress sensing protein GRP78. However, response to BOLD-100 varies in different cancer models and the precise mechanism of action in high-response versus low-response cancer cells remains unclear. In vitro studies have indicated that BOLD-100 induces cytostatic rather than cytotoxic effects as a monotherapy. To understand BOLD-100 mediated signaling mechanism in breast cancer cells, we used estrogen receptor positive (ER+) MCF7 breast cancer cells to obtain gene-metabolite integrated models. Particularly, BOLD-100 significantly reduced expression of genes involved in the DNA repair pathway. BOLD-100 also induced reactive oxygen species (ROS) and phosphorylation of histone H2AX, gH2AX (Ser139), suggesting disruption of proper DNA surveillance. In estrogen receptor negative (ER-) breast cancer cells, combination of BOLD-100 with a PARP inhibitor, olaparib, induced significant inhibition of cell growth and xenografts and increased gH2AX. Thus, BOLD-100 is a novel DNA repair pathway targeting agent and can be used with other chemotherapies in ER- breast cancer.

Venoms are a rich source of bioactive compounds, and among them is leberagin-C (Leb-C), a disintegrin-like protein derived from the venom Macrovipera lebetina transmediterrannea snakes. Leb-C has shown promising inhibitory effects on platelet aggregation. Previous studies have demonstrated that this SECD protein specifically targets α5β1, αvβ3 and αvβ6 integrins through a mimic mechanism of RGD disintegrins. In our current study, we focused on exploring the potential effects of Leb-C on metastatic breast cancer. Our findings revealed that Leb-C disrupted the adhesion, migration, and invasion capabilities of MDA-MB-231 breast cancer cells and its highly metastatic D3H2LN sub-population. Additionally, we observed significant suppression of adhesion, migration, and invasion of Human Umbilical Vein Endothelial Cells (HUVECs). Furthermore, Leb-C demonstrated a strong inhibitory effect on fibroblast growth factor 2-induced proliferation of HUVEC. We conducted in vivo experiments using nude mice and found that treatment with 2 µM of Leb-C resulted in a remarkable 73% reduction in D3H2LN xenograft tumor size. Additionally, quantification of intratumor microvessels revealed a 50 % reduction in tumor angiogenesis in xenograft after 21 days of twice-weekly treatment with 2 µM of Leb-C. Collectively, these findings suggest the potential utility of this dinsintegrin-like protein for inhibiting aggressive and resistant metastatic breast cancer.

MiRNAs are 20-22 nucleotide long single-stranded non-coding RNA sequences, which can regulate post transcriptional activity of mRNA by binding with it at 3’UTR region (untranslated region). Thus deregulation of miRNA expression is responsible for dysregulating mRNA function which contributes in developing various diseases as well as cancerous phenotypes. Alteration of single nucleotide in miRNA sequence is one of the reasons behind deregulation of miRNA expression. The most frequent carcinoma in current day is breast cancer which causes a high mortality among women around the world as well as India. Despite of the advancement of diagnostic tools, strategies and treatment, the cases of breast cancer is increasing every year. There are plenty of biomarkers like ER, PR, Her2, Ki-67, etc available which are frequently used in diagnosis and treatment of breast cancer. After the discovery of MiRNA in 1993 in Caenorhabiditis elegans, it is attracting all the limelight in diagnosis and treatment of different carcinomas as well as breast cancer. In this review we will discuss on involvement of different types of MiRNAs and miR SNPs in breast cancer occurrence and susceptibility in a detailed manner.

ABSTRACT Background It is important to be able to predict, for each individual patient, the likelihood of later metastatic occurrence, because the prediction can guide treatment plans tailored to a specific patient to prevent metastasis and to help avoid under- or over-treatment. Deep Neural Network (DNN) learning, commonly referred to as deep learning, has become popular due to its success in image detection and prediction, but questions such as whether deep learning outperforms other machine learning methods when using non-image clinical data remain unanswered. Grid search has been introduced to deep learning hyperparameter tunning for the purpose of improving its prediction performance, but the effect of grid search on other machine learning methods are under-studied. In this research, we take the empirical approach to study the performance of deep learning and other machine learning methods when using non-image clinical data to predict the occurrence of breast cancer metastasis (BCM) 5, 10, or 15-years after the initial treatment. We developed DNN models as well as models using 9 other machine learning methods including Naive Bayes (NB), Logistic Regression (LR), Support Vector Machine (SVM), LASSO, Decision Tree (DT), k-Nearest Neighbors (KNN), Random Forrest (RF), AdaBoost (ADB), and XGBoost (XGB). We used grid search to tune hyperparameters for all methods. We then compared the deep learning models to the models trained using the 9 other machine learning methods. Results Based on the mean test AUC results, DNN ranks 6th, 4th, and 3rd when predicting 5-year, 10-year, and 15-year BCM respectively, out of 10 machine learning methods. The top performing methods in predicting 5-year BCM are XGB(1^st), RF(2^nd), and KNN(3^rd). For predicting 10-year BCM the top performers are XGB (1^st), RF(2^nd), and NB(3^rd) . Finally, for 15-year BCM the top performers are SVM (1^st), LR and LASSO (tied for 2^nd), and DNN (3^rd). The ensemble methods RF and XGB outperform other methods when data are less balanced, while SVM, LR, LASSO, and DNN outperform other methods when data are more balanced. Our statistical testing results show that at a significance level of 0.05 DNN overall performs no worse than other machine learning methods when predicting 5-year, 10-year, and 15-year BCM. Conclusions Our results show that deep learning with grid search overall performs at least as well as other machine learning methods when using non-image clinical data. It is interesting to note that some of the other machine learning methods such as XGB, RF, and SVM are very strong competitors of DNN when incorporating grid search. It is also worth noting that the computation time required to do grid search with DNN is way more than that required to do grid search with the other 9 machine learning methods.

Despite all efforts, the treatment of breast cancer (BC) cannot be considered to be a success story. The advances in surgery, chemotherapy and radiotherapy have not been sufficient. Indeed, the accumulated experience clearly indicates that new perspectives and non-main stream approaches are needed to better characterize the etiopathogenesis and treatment of this disease. This contibution deals with how the new pH-centric anticancer paradigm plays a fundamental role in reaching a more integral understanding of the etiology, etiopathogenesis and treatment of this multifactorial disease. For the first time the armamentarium available for the treatment of the different types and phases of BC is approached here from a Unitarian perspective based upon the hydrogen ion dynamics of cancer. The wide-ranged pH-related molecular, biochemical and metabolic model is able to embrace most the fields and subfields of breast cancer pathology. This single and integrated approach allows to advance a unidirectional program to treatment. Further efforts in this line are likely to first improve the therapeutics of each subtype of this tumor, then every phase of the disease and finally every individual patient.

Breast Cancer diagnosis is one of the most studied problems in the medical domain. In the medical domain, cancer diagnosis has been studied extensively which instantiates the need of early prediction of cancer disease. For obtaining advance prediction, health records are exploited and given as input to an automated system. This paper focuses on constructing an automated system by employing deep learning based recurrent neural network models. A stacked GRU-LSTM-BRNN is proposed in this paper that accepts health records of a patient for determining possibility of being affected by breast cancer. Proposed model is compared against other baseline classifiers such as stacked Simple-RNN model, stacked LSTM-RNN model, stacked GRU-RNN model. Comparative results obtained in this study indicate that stacked GRU-LSTM-BRNN yield better classification performance for predictions related to breast cancer disease.

The present investigation has been conducted on one hundred tissue fragments of breast cancer, collected and immediately cryopreserved following the surgical resection. The fragments were selected from patients with invasive ductal carcinoma of the breast, the most common and potentially aggressive type of mammary cancer, with the objective to increase the knowledge of breast cancer molecular markers, useful for diagnostic and prognostic categorization of patients, in assessing post-surgical therapeutic regimes. The proteomic screening, by 2D-IPG and mass spectrometry, allowed us to identify two main classes of protein clusters: proteins expressed ubiquitously at high levels in all patients, and proteins expressed sporadically among the same patients. Within the group of ubiquitous proteins, glycolytic enzymes and proteins with anti-apoptotic activity were predominant. Among the sporadic ones, proteins involved in cell motility, molecular chaperones and proteins involved in the detoxification appeared prevalent. The data of the present study indicates that the primary tumor growth is generally supported by two concurrent pathways: the inhibition of apoptosis and the stimulation of cellular proliferation. The second phase of the evolution of the tumor can be prematurely scheduled by the occasional presence of proteins involved in cell motility and in the defenses of the oxidative stress. To our knowledge this report on large-scales proteomics of breast cancer is currently a unique approach in the literature that offers the opportunity to evaluate the presence and recurrence of proteins to be used as prognostic indicators and susceptibility to metastasis in patients operated on for invasive ductal carcinoma of the breast.

This document summarizes the evidence currently available about the effects of the anesthetic agents and techniques used in primary cancer surgery and long-term oncologic outcomes, and the biomolecular mechanisms involved in their interaction..

Breast Angiosarcoma is a rare malignancy, accounting less than 1% of all soft tissue. It comprises primitive and secondary subtypes, such as radiogenic breast angiosarcoma (RAS). Despite the multimodal treatment, angiosarcomas represent an incurable disease for many patients and represent a cause of substantial deterioration of their quality of life. Surgery represents the cornerstone in the management, but high recurrence rates are reported. Electrochemotherapy (ECT) is practicable locoregional treatment in patients with advanced angiosarcoma, in a multimodal therapeutic strategy. ECT palliative benefit includes optimal patient compliance, good local hemostasis control, and local responses. Considering that only 22 cases are described in literature, we reported a rare case of RAS treated with ECT, after a multidisciplinary approach including Next Generation Sequencing (NGS). A literature review about the feasibility of ECT in RAS management was also performed.

Male breast cancers are uncommon, as men account for less than 1 percent of all breast carcinomas. Among the predisposing risk factors for male breast cancer, the following appear to be significant: a) breast/chest radiation exposure, b) estrogen use, diseases associated with hyper-estrogenism, such as cirrhosis or Klinefelter syndrome, and c) family health history. Furthermore, there are clear familial tendencies, with a higher incidence among men who have a large number of female relatives with breast cancer and d) major inheritance susceptibility. Moreover, in families with BRCA mutations, there is an increased risk of male breast cancer, although the risk appears to be greater with inherited BRCA2 mutations than with inherited BRCA1 mutations. Due to diagnostic delays, male breast cancer is more likely to present at an advanced stage. A core biopsy or a fine needle aspiration must be performed to confirm suspicious findings. Infiltrating ductal cancer is the most prevalent form of male breast cancer, while invasive lobular carcinoma is extremely uncommon. Male breast cancer is almost always positive for hormone receptors. A worse prognosis is associated with a more advanced stage at diagnosis for men with breast cancer. And randomized controlled trials which recruit both female and male patients should be developed in order to gain more consistent data on the optimal clinical approach.

Published in July 2018, TAILORx aimed to establish non-inferiority of endocrine therapy (ET) compared to addition of chemotherapy (CHT-ET) in hormone receptor positive, human epidermal receptor 2 negative (HR+/HER2-) breast cancer (BC) patients with a 21-gene intermediate (11-25) recurrence score (RS). While this hypothesis proved correct, the study did show benefit of addition of chemotherapy (CHT) in a subgroup of women under 50 years of age, and particularly in the RS 16-25. The aim of this present study was to look at how TAILORx findings, including changes in RS categories, impacted CHT implementation at one oncologic center in Basel, Switzerland, and to identify main factors leading to these changes. Methods: We conducted a retrospective study on HR+/HER2-, BC patients who underwent 21-gene genomic testing between 2010-2021, at our center. Patients with metastatic disease were not included. We identified 326 eligible patients, of which 165 had a BC diagnosis before TAILORx (cohort A) and 161 after TAILORx publication (cohort B). Results: Demographic and tumor characteristics were similar in the two cohorts, although cohort B included significantly more women under the age of 50 when compared to A (34% vs. 24%, p<0.001). Median age and mean RS results were comparable 59 (IQR 16) in A and 58 (IQR 19) years in B and 17.72 (SD9.59) in A and 17.89 (SD9.53) in B, respectively. Patients in cohort A were slightly more overweight when compared to B (55% vs. 40% respectively, p<0.001). Most patients had stage II tumors of NST histologic type. Tumors in cohort B had higher Ki-67 than cohort A (39% vs. 32%, p=0.010). When compared based on manufacturer’s and based on TAILORx thresholds there were no significant differences in RS distribution. However, changes in score category led to shifts in patient population distribution, leading to a 40% drop in the low RS (from 60% to 20%), a doubling in the intermediate RS (from 30% to 60%) and an increase of 5% in the high RS (from 8-10% to 15%). Most patients had conservative surgery, adjuvant radiotherapy (RT) and ET. Overall CHT recommendation and application did not differ significantly in B vs. A. There was a reduction of 1% in the intermediate RS (11-25) and an increase of 13% CHT-ET application in the high RS (>26) category. In cohort B we noticed an increase in CHT-ET application among women <50 years old (by 12.5%), in lobular carcinomas (by 10%), grade 3 tumors (by 2%), node positive BC (by 3%) and node negative (by 2%). Tumor board recommendation for CHT dropped by 1% in the post TAILORx era, with a notable reduction of 5% in the intermediate RS (11-25) category. However, overall CHT administration rate was 19% in cohort A and 22% in B (p=0.763). Tumor Board recommended CHT for 90% of the BC patients that would have otherwise been assigned to CHT according to new RS guidelines in A and for 85% in B, showing a trend for undertreatment. Logistic regression analysis showed significance of age in both cohort A (OR 1.05, 95% CI 1.01-1.11, p=0.03) and cohort B (OR 0.89, 95% CI 0.84-0.94), p<0.001), and of nodal status in both cohort A (=R 3.32 95% CI 1.09-10-06, p=0.034) and cohort B (OR 3.31, 95% CI 1.29-8.53, p=0.013), while intermediate and high RS seem to be more relevant in cohort A (OR 0.12, 95% CI 0.03-0.43, p=0.01 and OR 0.04, 95% CI 0.01-0.21, p<0.01). Overall logistic regression analysis showed relevance of age (OR 0.93, 95% CI 0.08-0.97, p=0.001), pN (OR 4.77, 95% CI 2.03-11.22, p<0.001) and RS categories (RS 11-25: OR 0.02, 95% CI 0.01-0.07, p<0.001; RS>26: OR 617.93, 95% CI 57.97-6587.16, p<0.001). Conclusion: Our findings are similar to those reported across several studies: while tumor board recommendation for CHT decreases in the intermediate RS category, there is an increase being reported in the high RS category, leading to overall minor changes in CHT application. Administration of CHT-ET seems to be increasing among younger women, with unfavorable histo-pathological factors, such as lobular carcinoma and G3 histologic grade. Before TAILORx there is a tendency for undertreatment (-10%), especially among older BC patients, which seems to be maintained and even deepened (-15%) in the post TAILORx era, pointing to a personalized decision-making approach among Swiss oncologists.

Background: Galectins are innate immune system regulators, associated with disease progression in cancer. This paper aims to investigate the correlation between mutated cancer-critical genes and galectin levels in breast cancer patients to determine whether galectins and genetic profiles can be used as biomarkers for disease and potential therapy targets. Materials and Methodology: Prisma Health Cancer Institute’s Biorepository provided seventy-one breast cancer patient samples, including all four stages as well as major molecular subtypes and histologies of breast cancer. Hotspot mutation statuses of cancer-critical genes were determined using multiplex PCR in tumor samples from the same patients by Precision Genetics and the University of South Carolina Functional Genomics Core Facility. The galectin levels of patients’ sera were analyzed using enzyme-linked immunosorbent assay (ELISA) to measure the concentrations of galectins-1, -3, and -9. Analysis was performed using JMP software to compare mean and median serum galectin levels between samples with and without specific cancer-critical genes including pooled t-test, Wilcoxon test, ANOVA, Tukey’s range test, and Steel Dwass Method (α=0.05). Results: Our analysis indicates that KIT mutations correlate with elevated serum levels of galectin-1 and -9 in patients with breast cancer. In patients with Luminal A subtype, FLT3 mutation correlates with lower serum galectin-1 and -9 levels and TP53 mutations correlate with higher serum galectin-3 levels. Patients with invasive ductal carcinoma had significantly higher serum galectin-3 levels than patients with ductal carcinoma in situ. Patients with both TP53 and PIK3CA mutations exhibit elevated serum galectin-3 levels, while patients with one or neither mutation show no significant difference in serum galectin-3 levels. In addition, metastatic breast cancer samples were more likely to have KIT or PIK3CA mutation compared to primary breast cancer samples. Conclusion: The relationship between genetic mutations and galectin levels has the potential to identify appropriate candidates for combined therapy, targeting genetic mutations and galectins. Further understanding of the effect of genetic mutations and galectin levels on cancer progression and metastasis could aid in the search for biomarkers for breast cancer diagnosis, disease progression, and prognosis.

Background. Implementing mammogram screening means that clinicians are seeing many breast cancers that will never develop metastases. The purpose of this study was to identify subgroups of breast cancer patients who did not present events related to long-term breast cancer mortality, taking into account diagnosis at breast screening, absence of palpability and axillary involvement, and genomic analysis with PAM50. Patients and Methods. To identify them, a retrospective observational study was carried out selecting patients without palpable tumour, without axillary involvement, and a genomic analysis was performed with PAM50. Results. The probability of distant metastasis-free interval (DMFI) of 337 patients was 0.92 (95% CI, 0.90-0.93) at 20 years and 0.96 (95% CI, 0.92-1.00) in 95 patients (28%) with available PAM50 tests. In 22 (23.15%) luminal A tumours and in 9 (9.47%) luminal B tumours smaller than 1 cm and in HER2 and basal type tumours there were no metastatic events (20-year DMFI of 1.00). Conclusion. Patients with nonpalpable breast cancer found at screening with negative nodes are at very low risk. It is possible to identify subgroups without metastatic events by determining the intrinsic subtype and tumour size less than 1 cm. De-escalation of treatment should be considered.

Breast cancer is the foremost common in women, and its early diagnosis will help treat and increase patients' survival. This review article aims to studies on recent findings of standard imaging techniques and their characteristics for breast cancer diagnosis and recent nanoparticles (NPs) which are used for breast cancer detection. Herein, The search was performed in the literature through scientific citation websites, including Google Scholar, PubMed, Scopus, and Web of Science until May 2023. A comprehensive study on different imaging modalities and NPs for breast cancer diagnosis is reviewed, and their successes, challenges, and limitations are discussed.

Mammography is the gold standard for breast cancer screening and diagnostic imaging; however, there is an unmet clinical need for complementary methods to detect lesions not characterized by mammography. Far-infrared 'thermogram' breast imaging can map the skin temperature, and signal inversion with components analysis can be used to identify the mechanisms of thermal image generation of the vasculature using dynamic thermal data. This work focuses on using dynamic infrared breast imaging to identify the thermal response of the stationary vascular system and the physiologic vascular response to a temperature stimulus affected by vasomodulation. The recorded data is analyzed by converting the diffusive heat propagation into a virtual wave and identifying the reflection using component analysis. Clear images of passive thermal reflection and thermal response to vasomodulation were obtained. Validation of this proposed paradigm through further clinical exploration may demonstrate clinical utility for the IR modality in diagnostic imaging, offering a potential solution to the current unmet clinical need.

The DNA methylation profile of breast cancer differs from that in healthy tissue and can be used as a diagnostic and prognostic biomarker. Aim of the study: to compare gene methylation in small malignant breast tumors less than 2 cm and in healthy tissue and fibroadenoma. Methylation of the following 15 genes was studied: MAST1, PRDM14, ZNF177, DNM2, SSH1, AP2M1, CACNA1E, CPEB4, DLGAP2, CCDC181, GCM2, ITPRIPL1, POM121L2, KCNQ1, TIMP3. Methods: analysis was made by our modified MS-HRM method followed confirmation of the results by pyrosequencing. The genes were selected from publications that studied DNA methylation in breast cancer with high genome coverage. The study group included 48 samples of breast cancer, the control group included 24 samples of fibroadenoma and 24 samples of healthy tissue. Results: significant differences were found in methylation of 8 genes: CCDC181, GSM2, ITPRIPL1, ZNF177, CACNA1E, DLGAP2, TIMP3 (all р<0.001), and PRDM14 (р=0.002). The most accurate diagnostic value, based on logistic regression, was shown with the compound of two genes – CCDC181 and ZNF177 (AUC=0.99) in pyrosequencing analysis. Conclusion: small breast cancer tumors have a specific DNA methylation profile that distinguishes them from healthy tissue and benign proliferative lesions.

Breast cancer remains one of the most deadly non-communicable diseases in the world. The incidence of breast cancer in South Africa is increasing, with rural African women presenting with advanced stages of the disease. In this study, we aim to explore sociocultural factors influencing breast cancer screening practices among rural African women. A qualitative exploratory study was conducted using semi-structured interviews with 22 rural African women selected by purposive sampling. Thematic analysis was used to analyze the data. In this study, four sociocultural factors were identified as influencing breast cancer screening practices among rural African women. These factors included psychological factors, habits, beliefs, and healthcare perception. Women in rural African communities have deep-rooted traditional beliefs and practices regarding breast cancer. Consequently, this influences women's preventative health behaviours regarding breast cancer screening. To increase the number of women participating in breast cancer screenings, it is vital to develop culturally sensitive health education programs. Engaging community healers will also help to increase the number of women participating in breast cancer screening.

Background: Circulating tumor cells (CTC) have relevance as prognostic markers in breast cancer. However, the functional properties of CTCs or their molecular characterization have not been well-studied. Experimental models indicate that only a few cells can survive in the circulation and eventually metastasize. Thus, it is essential to identify these surviving cells capable of forming such metastases. Methods: We isolated viable CTCs from 50 peripheral blood samples obtained from 35 patients with advanced metastatic breast cancer using RosetteSepTM for ex vivo culture. The CTCs were seeded and monitored on plates under low adherence conditions and with media supplemented with growth factors and Nanoemulsions. Phenotypic analysis was performed by immunofluorescence and gene expression analysis using RT-PCR and CTCs counting by Cellsearch® system. Results: We found that in 75% of samples the CTC cultures lasted more than 23 days, predicting a shorter Progression-Free Survival in these patients, independently of having ≥ 5 CTC by Cellsearch®. We also observed that CTCs before and after culture showed a different gene expression profile. Conclusions: the cultivability of CTCs is a predictive factor. Furthermore, the subset of cells capable of growing ex vivo show stem or mesenchymal features and may represent the CTC population with metastatic potential in vivo.

Obesity in Australia is rapidly rising, and is a major public health concern. Obesity increases risk of breast cancer and worse associated outcomes, yet breast screening participation rates in Australia are suboptimal and can be lower in higher risk, obese women. This study qualitatively explored barriers to breast screening participation in obese women in Australia. In-depth interviews (n=29), were conducted with obese women (BMI 30) and key health stakeholders. A disconnect between stakeholders’ and women’s perceptions was found. For women, low knowledge around a heightened need to screen existed, they reported limited desire to prioritize personal health needs, reluctance to screen due to poor body image and prior negative mammographic experiences due to issues with weight. Stakeholders perceived few issues in screening obese women beyond equipment limitations, and health and safety issues. Overall, weight was a taboo topic among our interviewees, indicating that a lack of discourse around this issue may be putting obese women at increased risk of breast cancer morbidity and mortality. Consideration of breast screening policy in obese women is warranted. Targeted health promotion on increased breast cancer risk in obese women is required as is a need to address body image issues and encourage screening participation.

To screen and validate immunosuppressive factors in luminal- and basal-like breast cancer cell lines and tissue samples associated with malignant phenotypes. The mRNA microarray datasets, GSE40057 and GSE1561, were downloaded and remodelled. Differentially expressed genes (DEGs) were identified. Enrichment analyses performed and the online resources, GOBO and Kaplan-Meier Plotter, were employed to screen for immunosuppressive factors associated with breast cancer malignant phenotypes. qRT-PCR and western blot were used to validate the expression of CD274 and IL8 in cell lines and immunohistochemical detected the MIF and VEGFA on tissue microarrays. The results showed that CD274 and IL8 were both upregulated in basal-like cell lines. That MIF expression was dramatically increased in patients with breast cancer metastases (p<0.05) and that VEGFA expression positively correlates with breast cancer pathologic grade (p<0.05).During the formation and development of breast cancer, immune-related genes are always activated, and immunosuppressive factors CD274, IL8, MIF and VEGFA are upregulated. Such molecules could be used as biomarkers for breast cancer prognosis. However, because individual immune-related factors can play several biological roles, the mechanistic relationship between immunosuppressive factors and breast cancer malignant phenotypes and the feasibility of their application as drug targets require further investigation.

Breast cancer is a global health concern, necessitating continuous advancements in diagnostic medical imaging technologies for early detection and improvement of treatment. This paper presents an overview of the past, present and future of breast cancer imaging using light and some results from the current studies. The paper specifically presents the role of Diffuse Optical Tomography (DOT) in breast cancer imaging. Conventional methods, such as X-ray mammography, face limitations. Diffuse Optical Tomography, a non-invasive light-based imaging modality can provide quantitative descriptive and architectural information about breast tissue. The paper discusses the key challenges and recent developments in breast cancer imaging using DOT to overcome some key challenges. This paper aims to contribute to the understanding of the evolving technological landscape in breast cancer imaging using light for improving early detection and patient outcomes.

Breast cancer prevention is very important for a woman's health worldwide. We have demonstrated a correlation between mammography and ultrasound with diagnoses using passive microwave radiometry (MWR) and a miRNA oncopanel. While mammography screening dynamics could be completed in 3-6 months, MWR will provide us with a prediction in a matter of weeks or even days with the potential for complementary miRNA diagnostics. An early breast cancer diagnosis may be accomplished using either one of these novel techniques alone or in conjunction with more established techniques

Brain metastases are highly evolved manifestations of breast cancer arising in a unique microenvironment, giving them exceptional adaptability in the face of new extrinsic pressures. The incidence is rising in line with population ageing, and use of newer therapies that stabilise metastatic disease burden with variable efficacy throughout the body. Historically, there has been a widely held view that brain metastases do not respond to circulating therapeutics because the blood-brain-barrier (BBB) restricts their uptake. However, emerging data are beginning to paint a far more complex picture where the brain acts as a sanctuary for dormant, subclinical proliferations that are initially protected by the BBB, but then exposed to dynamic selection pressures as tumours mature and vascular permeability increases. Here, we review key experimental approaches and landmark studies that have charted the genomic landscape of breast cancer brain metastases. These findings are contextualised with the factors impacting on clonal outgrowth in the brain: intrinsic breast tumour cell capabilities required for brain metastatic fitness, and the neural niche, which is initially hostile to invading cells but then engineered into a tumour-support vehicle by the successful minority. We also discuss how late detection, abnormal vascular perfusion and interstitial fluid dynamics underpin the recalcitrant clinical behaviour of brain metastases, and outline active clinical trials in the context of precision management.

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.

Background: We previously found that QNBC tumors are more frequent in African Americans compared to TNBC tumors. To characterize this subtype further, we sought to determine the miRNA-mRNA profile in QNBC patients based on race. Methods: Both miRNA and mRNA expression data were analyzed from TCGA and validated using datasets from the METABRIC, TCGA proteomic, and survival analysis by KMPLOT. Results: miRNA-mRNAs which include FOXA1 and MYC (mir-17/20a targets); GATA3 and CCNG2 (mir-135b targets); CDKN2A, CDK6, and B7-H3 (mir-29c targets); and RUNX3, KLF5, IL1-β, and CTNNB1 (mir-375 targets) were correlated with basal-like and immune subtypes in QNBC patients and associated with a worse survival. Conclusion: Thus, QNBC tumors have an altered gene signature implicated in racial disparity and poor survival.

(1) Background: This case presents a rare and challenging clinical scenario involving a 50-year-old female patient diagnosed with Inflammatory Carcinoma, a particularly aggressive and rapidly growing form of breast cancer. The disease is characterized by heat, redness, swelling and noticeable changes in the breast's skin texture, resembling the skin of an orange (peau d'orange). This case is important because it contributes to the limited clinical literature on such aggressive forms of breast cancer.; (2) Methods: The multidisciplinary approach was employed. Diagnostic procedures such as imaging tests, biopsy, and histopathological examination were performed to confirm the diagnosis of Inflammatory Carcinoma and assess the extent of the disease. The presence of the HER2 protein on the tumor cells supported the selection of a combination therapy involving systemic chemotherapy and targeted biological therapy.; (3) Results: The patient responded positively to the combination therapy consisting of systemic chemotherapy and targeted biological therapy. The aggressive nature of Inflammatory Carcinoma, characterized by rapid growth and distinct skin changes, was effectively addressed. The presence of the HER2 protein on the tumor cells indicated the potential efficacy of the combination therapy in aggressive forms of breast cancer.; (4) Conclusions: This case highlights the critical importance of a multidisciplinary approach in managing complex cases of breast cancer, especially rare and aggressive subtypes like Inflammatory Carcinoma. The positive response of the patient to the combination therapy involving systemic chemotherapy and targeted biological therapy demonstrates the potential for favorable outcomes in aggressive disease presentations.

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.

Background and Objective: Type 2 diabetes mellitus (DM2) and breast cancer (BC) are diseases of high prevalence worldwide. Both alter lung function separately. So suffering both tables would increase this decrease in lung function. The objetive was to determine the effects of DM2 and BC on ventilation volumes and pressures in adult women. Material and Methods: Forty-two women patients were recruited, of whom 40 were accepted under the exclusion criteria. They were divided into four groups: control group (CG), DM2, BC and DM2+BC. Body plethysmography was used to measure forced vital capacity, lung volumes, airway resistance and muscle pressures. Finally the normality of the data was determined using Student's t test or the Mann-Whitney U test; the threshold of significance was p<0.05. Results: No significant differences were observed in the anthropometric variables between the control group and the other groups. The ventilation flows showed no significant differences, while the lung volumes presented significant differences in the inspiratory capacity (IC) variables (p<0,002). Maximum inspiratory and expiratory pressures (MIP-MEP) also presented significant diminution (p<0,001; p<0,041, respectively). Conclusions: From the results obtained we can conclude that the combination of type 2 diabetes mellitus with breast cancer caused a diminution in ventilation volumes and pressures, specifically in IC, MIP and MEP.

Introduction: Breast cancer affects worldwide almost 1.5 million women below the age of 45 years each year. Many of these women will be advised to undergo adjuvant chemotherapy to minimize the risk of death or recurrence of the tumor. For these patients, chemotherapy is a known cause of infertility, as it can damage primordial follicles which can lead to early menopause or premature ovarian insufficiency. This systematic review aims to synthesize the current evidence of the most suitable treatments for fertility preservation. Methodology: This review is performed following the PRISMA guidelines. The authors conducted an extensive search from the last 15 years. Relevant studies were pursued in PubMed, Embase and the Cochrane Library up until the July 31, 2023. A total of 7 eligible studies were identified. Discussion: The most suitable treatments for fertility preservation in young patients, is the temporary suppression with luteinizing hormone-releasing analogs, while the patient undergoes chemotherapy and cryopreservation. For cryopreservation, the physicians might deem it necessary to either cryopreserve ovarian tissue taken from the patient before any treatment or cryopreserve embryos/oocytes. Cryopreservation of oocytes and/or embryos is the most effective solution for fertility preservation in women of reproductive age, who have sufficient ovarian reserve and are diagnosed with breast cancer, regardless of the histological type of the tumor. Since approximately 50% of young breast cancer patients are interested in becoming pregnant right after completion of therapy, the evolution and development of fertility preservation techniques promise to be very exciting.

Bromodomain-containing protein 4 (BRD4) is an intracellular protein that regulates expression of various cellular functions. This study investigated whether BRD4 inhibition can alter the immunomodulatory and antitumor effects of radiation therapy (RT). A murine breast cancer cell line was implanted into BALB/c mice. The dual-tumor model was used to evaluate the abscopal effects of RT. A total of 24 Gy was delivered and BRD4 inhibitor was injected intravenously. Tumor size was measured and in vivo imaging was performed to evaluate tumor growth. Flow cytometry and immunohistochemistry were performed to examine immunologic changes upon treatment. The combination of BRD4 inhibitor and RT significantly suppressed tumor growth compared to RT alone. BRD4 inhibitor reduced the size of the unirradiated tumor indicating that it may induce systemic immune responses. Expression of HIF-1α and PD-L1 in tumor was significantly downregulated by the BRD4 inhibitor. Proportion of M1 tumor-associated macrophages (TAMs) increased, and proportion of M2 TAMs decreased upon BRD4 inhibition. BRD4 inhibitor expanded CD4+ and CD8+ T cell populations and reduced the population of monocytic myeloid-derived suppressor cells (M-MDSCs). RT-induced splenic M-MDSCs decreased upon addition of BRD4 inhibitor. Therefore, addition of BRD4 inhibition significantly enhanced the systemic antitumor responses of local RT.

Hypoxia, a condition of low oxygenation frequently found in triple-negative breast tumors (TNBC), promotes extracellular vesicle (EV) secretion and favors cell invasion, a complex process in which cell morphology is altered, dynamic focal adhesion spots are created, and ECM is re-modeled. Here, we investigated the invasive properties triggered by TNBC-derived hypoxic small EV (SEVh) in vitro in cells cultured under hypoxic and normoxic conditions, using pheno-typical and proteomic approaches. SEVh characterization demonstrated increased protein abundance and diversity over normoxic SEV (SEVn), with enrichment in pro-invasive pathways. In normoxic cells, SEVh promotes invasive behavior through pro-migratory morphology, in-vadopodia development, ECM degradation and matrix metalloprotease (MMP) secretion. Pro-teome profiling of normoxic cells exposed to SEVh determined enrichment in metabolic processes and cell cycle, modulating cell health to escape apoptotic pathways. In hypoxia, SEVh was re-sponsible for proteolytic and catabolic pathway inducement, interfering with integrin availabil-ity and gelatinase expression. Overall, our results demonstrate the importance of hypoxic signal-ing via SEV in tumors for the early establishment of metastasis.

Regulatory T cell master transcription factor, Forkhead box P3 (Foxp3) has been detected in cancer cells, but its role in breast tumor pathogenesis remains controversial. Here we assessed Foxp3 tumor intrinsic effects in experimental breast cancer using a Foxp3 binder peptide (P60) that impairs Foxp3 nuclear translocation. Cisplatin upregulated Foxp3 expression in HER2+ and triple negative breast cancer (TNBC) cells. Foxp3 inhibition with P60 enhanced chemosensitivity and reduced cell survival and migration in human and murine breast tumor cells. We also developed an adenoviral vector encoding P60 (Ad.P60) that efficiently transduced breast tumor cells, reduced cell viability and migration, and improved the cytotoxic response to cisplatin. Conditioned medium from transduced breast tumor cells contained lower levels of IL-10 and improved the activation of splenic lymphocytes. Intratumor administration of Ad.P60 in breast tumor-bearing mice significantly reduced tumor infiltration of Tregs, delayed tumor growth and inhibited the development of spontaneous lung metastases. Our results suggest that Foxp3 exerts protumoral intrinsic effects in breast cancer cells, and that gene therapy-mediated blockade of Foxp3 could constitute a therapeutic strategy to improve the response of these tumors to standard treatment.

Several studies have suggested that pre and/or postdiagnosis physical activity can reduce the risk of recurrence in breast cancer patients, however its effect according to follow-up time has not yet been investigated. We analyzed recurrence and mortality dynamics in randomized clinical trials (RCTs) from Australia and Canada. The combined Australian RCTs evaluated, at median follow-up of 8.3 years, an 8-month pragmatic exercise intervention in 337 women with newly diagnosed breast cancer, while the Canadian RCT evaluated, at median follow-up of 7.4 years, supervised aerobic or resistance exercise during chemotherapy in 242 patients. For each RCT, the control arm consisted of patients undergoing usual care. We estimated the event dynamics by the discrete hazard function, through flexible regression of yearly conditional event probabilities with generalized additive models. In the considered RCTs, the recurrence and mortality risk of patients enrolled in the physical activity arm was stably reduced at medium/long term after five year of follow-up. In the Australian RCTs where patients were recruited by urban versus rural area, the latter group did not display benefit from physical activity. Estimated Odds Ratios (95% Confidence Intervals) for Disease Free Survival (DFS) in urban women were 0.63 (0.22-1.85); 0.27 (0.079-0.90); 0.11 (0.013-0.96) at the 3rd, 5th and 7th year of follow-up, respectively. For rural women, DFS patterns were overlapping with ORs approximating 1 at the different years of follow-up. Although not reaching statistical evidence, the estimates in the Canadian trial were in line with the results from the Australian urban women with ORs (95% CI) forDFS of 0.70 (0.33-1.50); 0.47 (0.19-1.18); 0.32 (0.077-1.29) at 3rd, 5th, 7th follow-up year, respectively. While we acknowledge that the analyzed RCTs were not designed for investigating disease recurrence over time, these results support the evidence that physical activity reduces the risk of developing medium/long-term metastases. Additional translational research is needed to clarify the mechanisms underlying these observations.

The intracellular calcium concentration ([Ca2+]i) modulation plays a key role in the regulation of cellular growth and survival in normal cells and failure of [Ca2+]i homeostasis is involved in tumor initiation and progression. Here we show that inhibition of Furin by its naturally occurring inhibitor the prodomain ppFurin in the MDA-MB-231 breast cancer cells resulted in enhanced SOCE through TRPC6 activation that associated reduced cells malignant phenotype. Expression of ppFurin in a stable manner in MDA-MB-231 and the melanoma MDA-MB-435 cell lines inhibits Furin activity as assessed by in vitro digestion assays. Accordingly, cell transfection experiments, revealed that the ppFurin-expressing cells are unable to process adequately the PC substrates proVEGF-C and proIGF-1R. Compared to MDA-MB-435 cells, expression of ppFurin in MDA-MB-231 significantly induces Ca2+ entry which is impaired by silencing of TRPC6 expression. Analysis of TRPC6 activation revealed its up-regulated tyrosine phosphorylation in ppFurin-expressing MDA-MB-231 cells. The expression of ppFurin in MDA-MB-231 cells reduced their viability and ability to migrate and enhanced their sensitization to the apoptosis inducer hydrogen peroxide. These findings suggest that Furin inhibition by ppFurin may be a useful strategy to interfere with Ca2+ mobilization leading to breast cancer cells malignant phenotype repression and reduction of their resistance to treatments.

Breast cancer is a common malignant tumour and studies have shown that early and accurate detection is crucial for patients. With the maturity of medical imaging and deep learning development, significant progress has been made in breast cancer classification, which greatly improves the accuracy and efficiency of classification. This review focuses on deep learning, migration learning, GAN, and lifelong learning to elaborate and summarise the important roles arising from breast cancer detection. This review also examines the dataset and labeling issues required for breast cancer classification. In conclusion, at the end of the article, we look at future directions for breast cancer classification research, including cross-migration learning, multimodal data fusion, model interpretability, and lifelong learning, and also explore how to provide personalized treatment plans for patients.

We studied the prognostic impact of tumor immunoglobulin kappa C (IGKC) mRNA expression as a marker of the humoral immune system in the FinHer trial patient population, where 1,010 patients with early breast cancer were randomly allocated to either docetaxel-containing or vinorelbine-containing adjuvant chemotherapy. HER2-positive patients were additionally allocated to either trastuzumab or no trastuzumab. Hormone receptor-positive patients received tamoxifen. IGKC was evaluated in 909 tumors using quantitative real-time polymerase chain reaction, and the influence on distant disease-free survival (DDFS) was examined using univariable and multivariable Cox regression and Kaplan-Meier estimates. Interactions were analyzed using Cox regression. IGKC expression, included as continuous variable, was independently associated with DDFS in a multivariable analysis including also age, molecular subtype, grade, and pT and pN stage (HR 0.930, 95% CI 0.870 – 0.995, P = 0.034). An independent association with DDFS was also found in a subset analysis of triple-negative breast cancers (TNBC) (HR 0.843, 95% CI 0.724 – 0.983, P = 0.029), but not in luminal (HR 0.957, 95% CI 0.867 – 1.056, P = 0.383) or HER2-positive (HR 0.933, 95% CI 0.826 – 1.055, P = 0.271) cancers. No significant interaction between IGKC and chemotherapy or trastuzumab administration was detected (Pinteraction = 0.855 and 0.684, respectively). These results show that humoral immunity beneficially influences the DDFS of patients with early TNBC.

Signaling from estrogen receptor alpha (ER) and its ligand estradiol (E2) is critical for growth of ~70% of breast cancers. Therefore, several drugs that inhibit ER functions are in clinical use for decades and new classes of anti-estrogens are continuously being developed. Although a significant number of ER+ breast cancers respond to anti-estrogen therapy, ~30% of these breast cancers recur, sometimes even after 20 years of initial diagnosis. Mechanism of resistance to anti-estrogens is one of the intensely studied disciplines in breast cancer. Several mechanisms have been proposed including mutations in ESR1, crosstalk between growth factor and ER signaling, and interplay between cell cycle machinery and ER signaling. ESR1 mutations as well as crosstalk with other signaling networks lead to ligand independent activation of ER thus rendering anti-estrogens ineffective, particularly when treatment involved anti-estrogens that do not degrade ERa. As a result of these studies, several therapies that combine anti-estrogens that degrade ER with PI3K/AKT/mTOR inhibitors targeting growth factor signaling or CDK4/6 inhibitors targeting cell cycle machinery are used clinically to treat recurrent ER+ breast cancers. In this review, we discuss nexus between ER-PI3K/AKT/mTOR pathways and how understanding of this nexus has helped to develop combination therapies.

The employment of breast silicone implants, both in aesthetic and reconstructive medicine, is widespread thanks to their recognized biocompatibility and durability. Some critical situations, as for example in case of accidental impacts, may however induce concerns by potential patients about their use. Experimental data is collected by means of static compressive and tensile tests. Aging at 37, 60, 75° and 90° Celsius is performed in a physiological saline solution (0,9% NaCl). Impact dynamic tests are carried out using a Hybrid II anthropomorphic test dummy with the prostheses implanted. Mechanical tensile and compressive tests show mechanical degradation of the prostheses characteristics after aging. Impact dynamic tests show a great probability of breast implant rupture at speeds up to 90 km/h. Accidental events like car crashes or bad falls, are con-firmed as possible causes of significant damages to implanted prostheses. In addition, the possi-ble long-term aging of the silicone shell, although of limited relevance in terms of body compati-bility or reaction, can lead to some degradation of mechanical properties, rendering the outcome of accidental events even more worthy of attention.

Standard of care for triple negative breast cancer (TNBC) involves the use of microtubule poisons like paclitaxel, which are proposed to work by inducing lethal levels of aneuploidy in tumor cells. While these drugs are initially effective in treating cancer, dose-limiting peripheral neuropathies are common. Unfortunately, patients often relapse with drug resistant tumors. Identifying agents against targets that limit aneuploidy may be a valuable approach for therapeutic development. One potential target is the microtubule depolymerizing kinesin, MCAK, which limits aneuploidy by regulating microtubule dynamics during mitosis. Using publicly available datasets, we found that MCAK is upregulated in triple negative breast cancer and is associated with poorer prognoses. Knockdown of MCAK in tumor-derived cell lines caused a two- to five-fold reduction in the IC50 for paclitaxel, without affecting normal cells. Using FRET and image-based assays, we screened compounds from the ChemBridge 50k library and discovered three putative MCAK inhibitors. These compounds reproduced the aneuploidy-inducing phenotype of MCAK loss, reduced clonogenic survival of TNBC cells regardless of taxane-resistance, and the most potent of the three, C4, sensitized TNBC cells to paclitaxel. Collectively, our work shows promise that MCAK may serve as both a biomarker of prognosis and as a therapeutic target.

(1) Background: Breast cancer-associated lymphedema (BCRL) is a major complication of breast cancer treatment, affects the quality of life of breast cancer survivors who develop it. Manual lymphatic drainage has a beneficial result in combating lymphedema in patients who have undergone breast cancer surgery. The hypothesis consists in complete decongestive therapy reduces the lymphedema at the level of the upper limb on the side of mastectomy. (2) Methods: Twenty-five patients with radical mastectomy and upper limb lymphedema on the mastectomy side were included in this study. Upper limb circumferences were measured with a tape measure at the following levels: metacarpophalangeal joint; distal radioulnar joint; 10 cm distal to lateral epicondyle; 5 cm proximal to elbow joint; 10 cm proximal to lateral epicondyle. (3) Results: Patients received twice weekly manual lymphatic drainage, multi-layer compression bandaging and upper limb muscle stimulation exercises on the mastectomy side twice weekly. The circumference assessed at the level of the metacarpophalangeal joints and distal radio-carpal joint decreased at the final evaluation. Forearm perimetery - 5 and 10 cm distal to the lateral epicondyle the circumference decreased at the final assessment. (4) Conclusions: Patients with breast cancer-related lymphedema should receive comprehensive decongestive therapy in the early stage of lymphedema to achieve rapid clinical results and improved quality of life

During the progression from ductal carcinoma in situ (DCIS) to invasive breast cancer (IBC), cells have to overcome the physically restraining basement membrane (BM) which compartmentalizes the epithelium from the stroma. Since the extracellular matrix (ECM) of the epithelial and stromal compartment is biochemically and physically distinct from one another, the progression demands a certain degree of cellular plasticity being essentially required for a primary tumor to become invasive. The Epithelial-to-Mesenchymal Transition depicts such a cell program equipping cancer cells with features allowing for dissemination from the epithelial entity and stromal invasion on the single-cell level. Here, we investigated the reciprocal interference between an altering tumor microenvironment and the EMT-phenotype in vitro. BM-typical collagen IV and stroma-typical collagen I coatings were applied as provisional 2-D matrices. Pro-inflammatory growth factors were introduced to improve tissue mimicry. Whereas the growth on coated surfaces did only slightly affect the EMT-phenotype, the combinatorial action of collagen with growth factor TGF-β1 induced prominent phenotypic changes. However, the EMT-induction was independent of the collagen type and cellular accessibility for EMT-like changes was strongly cell line dependent. Summarizing the entire body of data, we computed an EMT-phenotyping model that was used to decide on cellular EMT-status and estimate EMT-like changes. We confirmed that miR200c-mediated reversion of mesenchymal MDA-MB-231 cells is reflected by our EMT-phenotype model emphasizing its potential to predict the therapeutic efficacy of EMT-targeting drugs in the future.

(1) Background: This work aimed to conduct the first comparative study providing long-term data about patient reported outcome measures as well as donor-site scar assessment and aesthetic evaluation of the reconstructed breasts in patients with DIEP versus PAP flap breast reconstruction. (2) Methods: This prospective, single-center, matched cohort study included a total of 36 patients after DIEP and PAP flap breast reconstruction. Evaluation was done using the Breast-Q and POSAS questionnaire as well as the Breast Aesthetic Scale for cosmetic analysis by four plastic surgeons. (3) Results: Post-operative Breast-Q evaluation revealed no significant differences between both patient groups for the categories physical well-being donor-site, physical well-being breast and satisfaction with the breast. Scar evaluation of the donor-site region showed equivalent results for the thigh and the abdomen concerning the overall opinion of patients and observers. There was no significant difference between both methods of reconstruction for all aspects of breast aesthetics. (4) Conclusions: Similar results of donor-site morbidity, scar quality and aesthetic outcome of the breast in both the DIEP and PAP patient group have been demonstrated. Hence, in cases suitable for both types of reconstruction, the decision can be based on factors such as patients’ lifestyle, leisure activities and preferences.

Objectives: Few studies have evaluated and compared artificial intelligence (AI) models for breast cancer detection on the same database. The purpose is to compare the performances of 3 artificial intelligence algorithms on the same dataset at a free operative threshold and to evaluate how the performance is impacted by the chosen threshold. Materials: In this retrospective single-center study, a dataset of 314 2D screening mammograms performed between 2012 and 2020 was established with a prevalence of 19.6% of histologically proven cancer. Three AI constructors using CE (European conformity) marking algorithms have agreed to take part in the study by submitting the cancer-enriched cohort to their algorithm. They chose a free operative threshold to distinguish benign and malignant mammograms. The most suspicious lesion was marked and correctly located by the AI algorithm. Statistical parameters were analyzed and compared between the algorithms. Results: Regarding both sensitivity and specificity, at the chosen threshold, AI 1 had the best compromise between sensitivity (74%) and specificity (79%). AI 2 had a statistically lower sensitivity (52%; p<0.05) with a higher specificity (98.4%) than the other AI algorithms. AI 3 had a nonsignificant sensitivity difference (69.9%) but a significantly lower specificity (45.3%; p<0.001) than the other two. The performances varied depending on the chosen threshold; when the AI 2 threshold was lowered, the sensitivity increased (69.9%), while a higher specificity (86.1%) was maintained. Conclusion: Two AI algorithms stood out in terms of performance when the threshold was optimized, resulting in an acceptable sensitivity and specificity.

: Nonylphenol is an endocrine disruptor who belongs to alkylphenol group of chemicals and its high occurrence in the environment can caused an adverse effect on human health. The breast milk can serve as a marker to take measure of human exposure to these chemicals through different routes of exposure. In this study, the influence of different factors (kind of wastes mothers drink, consummation of fish, pork and beef; using gloves, mail polish, using vitamins and medication) on the concentration on nonylphenol in breast milk were studied. Concentrations of nonylphenol in breast milk were determined by high-performance liquid chromatography (HPLC) with fluorescence detection. The lowest and highest concentration of nonylphenol in breast milk was 0.97 ng/mL and 4.37 ng/mL, respectively. The selected factors such as pork, beef, fish consumption, vitamin supplementation, medication, using of gloves, nail polish and gel nails were observed in relation to 4-nonylphenol concentration.

This study utilised an ensemble of pre-trained networks and digital mammograms to develop a supplementary diagnostic tool for radiologists. Digital mammograms and their associated information were collected from the department of radiology and pathology, Hospital Universiti Sains Malaysia. Thirteen pre-trained networks were selected and explored in this study. ResNet101V2 and ResNet152 had the highest mean PR-AUC, MobileNetV3Small and ResNet152 had the highest mean precision, ResNet101 had the highest mean F1 score, and ResNet152 and ResNet152V2 had the highest mean Youden J index. Subsequently, three ensemble models were developed using the top three pre-trained networks based on PR-AUC, precision, and F1 score. The final ensemble model had a mean precision, F1 score, and Youden J index of 0.82, 0.68, and 0.12, respectively. Additionally, the final model demonstrated a balanced performance across mammographic density. In conclusion, this study exhibited the good performance of the ensemble transfer learning on digital mammograms for the purpose of breast cancer risk estimation. This model can be utilised as a supplementary diagnostic tool for radiologists, thus, reducing their workloads.

(1) Background: Premature infants require mothers’ milk fortification to meet nutrition needs, but breast milk composition may be variable leading to a risk of inadequate nutrition. We aimed at determining factors influencing mothers’ milk macronutrients. (2) Methods: Milk samples were analyzed for the first 5 weeks after premature delivery, by infrared spectroscopy. Mothers’ nutritional intake data were obtained during standardized interviews with dieticians then analyzed with reference software. (3) Results: Composition of 367 milk samples from 81 mothers was (Median [range]g/100mL): Carbohydrates 6.8[4.4-7.3], lipids 3.4[1.3-6.4], proteins 1.3[0.1-3.1]. There was a relationship of milk composition with mothers’ carbohydrates intake only (r=0.164; p<.01). Postnatal age was correlated with milk proteins (r=-0.505 p<.001) & carbohydrates (r=+0.202, p<.001). Multiple linear regression analyses showed (coefficient) a relationship between milk proteins r=0.547 and postnatal age (-0.028), carbohydrates intake (+0.449) and the absence of maturation (-0.066); and between milk lipids r=0.295 and carbohydrates intake (+1.279) and smoking (-0.557). Finally, between milk carbohydrates concentration r=0.266 and postnatal age (+0.012) and smoking (-0.167). (4) Conclusions: Variability of mothers’ milk composition is differentially associated for each macronutrient with maternal carbohydrates intake, antenatal steroids, smoking, and postnatal age. Improvement in milk composition could be achieved by modification of these related factors.

Siam weed, scientifically known as Chromolaena odorata and belonging to the Asteraceae family, is a fast-growing plant with prolific seed production. Although it is a traditional medicinal plant, it has become an agricultural weed in Africa and Asia, posing a threat to biodiversity and causing environmental damage. Despite this, C. odorata is highly regarded as a medicinal herb in tropical Africa, with anticancer effects on breast, liver, and colorectal cancer. However, it is important to regulate the intake of the plant extract as it can have a hepatotoxic effect on liver cells at higher doses. Further research needs to be conducted on the plant extract, and proper orientation and knowledge of its oral daily administration are necessary. This review summarizes current scientific investigations using ethanolic and methanolic aqueous extracts of C. odorata leaves on various cancer cells, to uncover its potential as an anticancer agent. The investigations were sourced from online databases like Google Scholar, PubMed, and other online-based journals.

SAMHD1 is a deoxynucleotide triphosphate (dNTP) triphosphohydrolase with important roles in the control of cell proliferation and apoptosis, either through the regulation of intracellular dNTPs levels or the modulation of the DNA damage response. However, SAMHD1 role in cancer evolution is still unknown. We performed the first in-depth study of SAMHD1 role in advanced solid tumors, by analyzing samples of 128 patients treated with chemotherapy agents based on platinum derivatives and/or antimetabolites and developing novel in vitro knock-out models to explore the mechanisms driving SAMHD1 function in cancer. Low or no expression of SAMHD1 was associated with a positive prognosis in breast, ovarian and non-small cell lung cancer (NSCLC) cancer patients. A predictive value was associated to low-SAMHD1 expression in NSCLC and ovarian patients treated with antimetabolites in combination with platinum derivatives. In vitro, SAMHD1 knock-out cells showed increased γ-H2AX and apoptosis suggesting that SAMHD1 depletion induces DNA damage leading to cell death. In vitro treatment with platinum-derived drugs significantly enhanced γ-H2AX and apoptotic markers expression in knock-out cells, indicating a synergic effect of SAMHD1 depletion and platinum-based treatment. SAMHD1 expression represents a new strong prognostic and predictive biomarker in solid tumors and thus, modulation of SAMHD1 function may constitute a promising target for the improvement of cancer therapy.

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.

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

Patients diagnosed with unresectable locally advanced Triple Negative Breast Cancer (TNBC) usually have poor outcome for its aggressive clinical behaviour. Atezolizumab plus nanoparticle albumin-bound (nab)-Paclitaxel prolonged progression-free survival (PFS) and overall survival (OS) among patients with unresectable locally advanced TNBC but its use is hampered by the lack of reliable predictors of tumor response. Seventy-seven consecutive patients with unresectable locally advanced TNBC treated with Atezolizumab plus nab-Paclitaxel were studied by blood draws at baseline, 28 days and 56 days after initiation of treatment. Exosomal PD-L1 mRNA in plasma was determined using Bio-Rad QX100 digital droplet PCR system and exoRNeasy kit and objective responses were defined following the RECIST criteria v.1.1. The study evaluates whether PD-L1 mRNA copies per ml in plasma-derived exosomes may predict response to anti-PD-L1 antibodies early in the course of therapy. Our data showed patients with unresectable locally advanced TNBC and higher levels of PD-L1 mRNA expression in plasma-derived exosomes at baseline demonstrated greater response to atezolizumab plus nab-paclitaxel. Furthermore, the levels of mRNA decreased with successful treatment while the copy number increased in patients experiencing disease progression following atezolizumab plus nab-paclitaxel. For the first time, our data showed the usefulness of assessment of exosomal PD-L1 as non-invasive real-time biopsy in patients diagnosed with TNBC suggesting exosomal PD-L1 is significantly associated with outcome and response to Atezolizumab plus nab-Paclitaxel.

Near-infrared spectroscopy (NIRS) has become a key modality in medical imaging, finding application in both brain and breast imaging. This paper discusses the current trends in NIRS for brain and breast imaging, exploring advances in multi-modal integration with modalities such as functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). Challenges related to spatial resolution, depth sensitivity, and the impact of extracerebral tissues on signal specificity are examined. In addition, ongoing efforts to enhance hemodynamic measurements’ quantitative accuracy. Challenges, including limited spatial resolution and tissue heterogeneity, are discussed. The discussion extends to diffuse optical tomography and ongoing instrumentation development, clinical trials and studies validating NIRS diagnostic efficacy in breast imaging. The paper emphasizes the need for standardization, integration into routine clinical practice, and motivates for future work.

Objective: To evaluate the use of CDK4/6 inhibitors as a risk factor for medication-related osteonecrosis of the jaw (MRONJ) in a cohort of patients with metastatic breast cancer treated with denosumab. Methods: multicentre, retrospective, observational study. All patients with breast cancer treated with denosumab (January 2011-December 2022) were included. The relationship between CDK4/6 inhibitors and MRONJ was analysed. Results: 243 patients were included, ninety-five (44.2%) used a CDK4/6 inhibitor. There were 21 patients with MRONJ. In patients treated with denosumab without CDK4/6 inhibitors the incidence of MRONJ and mean time to the occurrence of MRONJ was 6.6% (8/120) and 16.8 months (SD 7.8) respectively. In patients treated with denosumab and CDK4/6 inhibitor 13.7% (13/95) and 15.4 month (SD 8.7) respectively. The difference in the incidence was not significant (p=0.085). Conclusion: it suggest that the incidence of MRONJ in patients with metastatic breast cancer treated with denosumab was higher and the onset of MRONJ occurred earlier in the presence of CDK4/6 inhibitors. Although the difference was not significant, given that the use of this combination is very common in routine clinical practice, it would be advisable to carry out larger prospective studies to clarify the risk of this association.

Cancer is a leading cause of morbidity and mortality worldwide, yet much is still unknown about its mechanism of establishment and destruction. Recently, studies had shown that tumor cells cannot survive under the high temperature conditions. This treatment technique is called Hyperthermia. This report presents the case of radiative microwave heating of hyperthermia therapy on breast cancer in a porous medium. In this study, the steady state is solved analytically while unsteady state is solved using semi-implicit finite difference to get a more accurate prediction of blood temperature distributions within the breast tissues. A moderate temperature hyperthermia treatment is apply which results into cell death due to an increase in the level of cell sensitivity to radiation therapy and blood flow in tumor and oxygen. The results show that by applying metabolic heat generation rate of $3.97 X 10^{5}Wm^{-3}$, it takes upto 2 minutes for the tumor cells to get the require therapeutic temperature point.

Abstract: Exercise has been repeatedly shown to be safe and beneficial for cancer survivors. However, there is no normative guideline for exercise prescription, and it is under exploration. Therefore, this literature review aims to provide some advice for the formulation of exercise prescriptions for patients with breast cancer-related lymphedema (BCRL) from the perspective of reducing lymphedema severity. A review of relevant studies published before November 2023 was conducted using three scientific databases PubMed, Embase, and Scopus. A total of 2696 articles were found. Eventually, 13 studies fulfilled the inclusion criteria and were included in this literature review. We concluded daily, or nearly daily exercise at home can be recommended. Moreover, reduced lymphedema severity may not be maintained after ceasing the exercise program, so exercise should be a lifelong practice.

(1) Background: Breast cancer is a frequent heterogeneous disorder diagnosed in woman and is a high cause of mortality of them in reason to rapid metastasis and disease recurrence. Ferroptosis can inhibit breast cancer cell growth, improve the sensitivity of chemotherapy and radiotherapy and inhibit distant metastases so potentially acts on tumor micro-environment; (2) Methods: Ferroptosis/Extracellular matrix remodeling literature text-mining results were integrated in breast cancer transcriptome cohort according their distant relapse free survival (DRFS) under adjuvant therapy (anthracyclin+taxanes) and also in MDA-MB-231 transcriptome functional experiments with ferroptosis activations (GSE173905); (3) Results: Ferroptosis/Extracellular matrix remodeling text-mining identified 910 associated genes in at list 10 articles. Univariate Cox analyses censored on breast cancer (GSE25066) selected 252 individual significant genes and 171 of them found with an adverse expression. Functional enrichment of these 171 adverse genes predicted basal breast cancer signatures. By text-mining some ferroptosis significant adverse selected genes shared citations in domain of ECM remodeling such as: TNF, IL6, SET, CDKN2A, EGFR, HMGB1, KRAS, MET, LCN2, HIF1A, TLR4. A molecular score based on expression the eleven genes was found predictive of worst prognosis breast cancer at univariate level: basal subtype, short DRFS, high grade values 3 and 4, estrogen and progesterone receptors negative and nodal stages 2 and 3. This eleven gene signature was validated as regulated by ferroptosis inductors (erastin and RSL3) in triple negative breast cancer cellular model MDA-MB-231.; (4) Conclusions: Crosstalk between ECM remodeling-Ferroptosis functionalities allowed to define a molecular score which have been characterized as an independent adverse parameter in prognosis of breast cancer patients. Gene signature of this molecular score have been validated to be regulated by erastin/RSL3 ferroptosis activators. This molecular score could be promising to evaluate ECM impact of ferroptosis target therapies in breast cancer.

Triple-negative breast cancer (TNBC) is a subtype of breast cancer characterized by the lack of estrogen receptors (ER), progesterone receptors, and HER-2 receptors. Thus, TNBC tumours do not benefit from the current therapies targeting ER or HER-2. Therefore, there is an urgent need to develop novel treatment for this subtype of breast cancer. Marijuana is a common name given to Cannabis plants, a group of plants in the Cannabis genus of the Cannabaceae family. Cannabis plants are among the oldest cultivated crops, traced back at least 12,000 years and are well known for their multi-purpose usage, including medicinal purposes. The main active compounds extracted from Cannabis plants are 21-carbon-containing terpenophenolics, which are referred to as phytocannabinoids. Of these, the tetrahydrocannabinol (THC) group contains highly potent cannabinoids, including delta-9-tetrahydrocannabinol (∆9-THC) and delta-8-tetrahydrocannabinol (∆8-THC), which are the most abundant THCs and are largely responsible for psychological and physiological effects of marijuana. The use of Cannabis plants for medicinal purposes was first recorded in 2337 BC in China, where Cannabis plants were used to treat pains, rheumatism, and gout. Recently, several cannabinoids have been approved for a number of treatments, one of which is the treatment of nausea and vomiting caused by chemotherapy in cancer patients. Furthermore, increasing evidence shows that cannabinoids not only attenuate side effects due to cancer treatment, but might also potentially possess direct antitumor effects in several cancer types, including breast cancer. However, anti-tumour activity of marijuana has been variable in different studies and even promoted tumour growth in some cases. In addition, the mechanisms of cannabinoid action in cancer remain unclear. This review summarizes evidence about the mixed actions of cannabinoids in cancer in general and triple-negative breast cancer in particular.

Triple negative breast cancer (TNBC) is an aggressive subtype of the disease with poor clinical outcomes and limited therapeutic options. Immune checkpoint blockade (CP) has surged to the forefront of cancer therapies with widespread clinical success in a variety of cancer types. However, the percentage of TNBC patients that benefit from CP as a monotherapy is low and clinical trials have shown the need for combined therapeutic modalities. Specifically, there has been interest in combining CP therapy with radiation therapy where clinical studies primarily with external beam have suggested their therapeutic synergy, contributing to the development of anti-tumor immunity. Here, we have developed a therapeutic platform combining radionuclide therapy (RT) and immunotherapy utilizing a radiolabelled biomolecule and CP in an E0771 murine TNBC tumor model. Survival studies show that while neither monotherapy is able to improve therapeutic outcomes, the combination of RT + CP extended overall survival. Histologic analysis showed that RT + CP increased necrotic tissue within the tumor and decreased levels of F4/80+ macrophages. Flow cytometry analysis of the peripheral blood also showed that RT + CP suppressed macrophages and myeloid-derived suppressive cells, both of which actively contribute to immune escape and tumor relapse.

Breast cancer (BC) is the most frequent form of malignancy and the second only to lung cancer as common cause of cancer-causing deaths in women. Notwithstanding many progresses in the field, metastatic BC has a very poor prognosis. As therapies are becoming more personalized to meet patients‘ needs, a better knowledge of the molecular biology leading to the disease unfolds the possibility to project more precise compounds or antibodies targeting definite alteration at the molecular level expressed in cancer cells of patients or as antigens on the surface of cell membranes. Fibroblast growth factor receptor (FGFR) is a druggable target -which is activated by its own ligands -namely the Fibroblast Growth Factors (FGFs). This pathway provides a vast range of interesting molecular targets pursued at different levels of clinical investigation. Herein we provide an update on the knowledge on genetic alterations of the receptors in breast cancer, their role in tumorigenesis and the most recent drugs against this particular receptor to treat the disease.

Nonylphenol is a endocrine disruptors who belongs to alkyphenol groups. It´s high occurrence in the environment can caused an adverse effect on human health. The breast milk can serve as a marker to take measure of human exposure to these chemicals through different routes of exposure. In this study, the influence of different factors (including the length of accommodation, kind of wastes mothers drink, con summation of fish, pork and beef; using gloves, mail polish, using vitamins and medication) on the concentration on nonylphenol in breast milk were studied. The length of accommodation has a statistically significant effect on nonylphenol, concentration in breast milk (p value was 0.02). Other mentioned factors had not a significant influence on nonylphenol values.

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.

Breast cancer stands as a predominant health concern for women globally. As mammography is the primary screening tool for breast cancer detection, improving the detection of breast cancer at screening could save more lives. This mammography re-view paper provides a systematic review of computer-aided techniques during a specific time frame for the segmentation and classification of microcalcification, evaluating image processing, machine learning, and deep learning techniques. The systematic review is meticulously carried out, adhering closely to the preferred reporting items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. This article focuses on mammographic breast cancer detection approaches based on automated systems, discussed chronologically from 1970 through 2023. This article encompasses the breadth of artificial intelligence-based methods from the most primitive to the most sophisticated models. Image processing and machine learning-based methods are compre-hensively reviewed. The evaluation of a deep learning architecture based on self-extracted features for classification tasks demonstrated outclass performance. Large-scale datasets required for a broader and in-depth analysis of novel methods for breast cancer detection are also discussed in this article. This research work is aligned with the United Nations' sustainability de-velopment goals.

Computer-aided image diagnostics (CAD) have been used in many fields of diagnostic medicine. It relies heavily on classical computer vision and artificial intelligence. Quantum neural network (QNN) has been introduced by many researchers around the world and presented recently by research corporations such as Microsoft, Google, and IBM. In this paper, the investigation of the validity of using the QNN algorithm for machine-based breast cancer detection was performed. To validate the learnability of the QNN, a series of learnability tests were performed alongside with classical convolutional neural network (CCNN). QNN is built using the Cirq library to perform the assimilation of quantum computation on classical computers. Series of investigations were performed to study the learnability characteristics of QNN and CCNN under the same computational conditions. The comparison was performed for real Mammogram data sets. The investigations showed success in terms of recognizing the data and training. Our work shows better performance of QNN in terms of successfully training and producing a valid model for smaller data set compared to CCNN.

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.

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 (BC) is the most common malignancy among women worldwide. In recent years, significant progress has been made in BC therapy. However, serious side effects resulting from the use of standard chemotherapeutic drugs, as well as the phenomenon of multidrug resistance (MDR), limit the effectiveness of approved therapies. Advanced research in the BC area is necessary to create more effective and safer forms of therapy to improve the outlook for individuals diagnosed with this aggressive neoplasm. For decades, plants and natural products with anti-cancer properties have been successfully utilized in treating various medical conditions. Anthracene derivatives are tricyclic secondary metabolites of natural origin that have been identified in plants, lichens, and fungi. They represent a few botanical families, e.g., Rhamnaceae, Rubia-ceae, Fabaceae, Polygonaceae, and others. The review comprehensively covers and analyzes the most recent advances in the anticancer activity of anthracene derivatives (emodin, aloe-emodin, hypericin, chrysophanol, rhein, and physcion) applied both individually, or in combination with other chemotherapeutic agents in in vitro and in vivo BC models.

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.

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.

Background. The molecular mechanisms underlying de novo metastasis of luminal breast cancer (dnMBC) remain largely unknown. Materials & Methods. Newly diagnosed dnMBC patients (grade 2/3, ER+, PR+/-, HER2-), with available core needle biopsy (CNB), collected from the primary tumor, were selected from our clinical-pathological database. Tumors from dnMBC patients were 1:1 pairwise matched (n=32) to tumors from newly diagnosed patients who had no distant metastases at baseline (eBC group). RNA was extracted from 5 x 10µm sections of FFPE CNBs. RNA sequencing was performed using the Illumina platform. Differentially expressed genes (DEG)s were assessed using EdgeR, deconvolution was performed using CIBERSORTx to assess immune cell fractions. Paired Wilcoxon test was used to compare dnMBC and eBC groups, and corrected for false discovery rate (FDR). Results. Many regulatory DEGs were significantly downregulated in dnMBC compared to eBC. Also, immune-related and hypoxia-related signatures were significantly upregulated. Paired Wilcoxon analysis showed that CCL17 and neutrophils fraction were significantly upregulated, whereas the memory B-cell fraction was significantly downregulated in the dnMBC group. Conclusion. Primary luminal tumors of dnMBC patients display significant transcriptomic and immunological differences compared to comparable tumors from eBC patients.

This study aimed to evaluate contrast-enhanced mammography (CEM) and compare breast lesions on CEM and breast magnetic resonance imaging (MRI) using 5 features. We propose to create a flowchart for BI-RADS classification of breast lesions on CEM based on the Kaiser score (KS) flowchart for breast MRI. Included were 68 subjects (women and men; median age 61.4 ± 11.6 years) who were suspected of having a malignant process in the breast based on digital mammography (MG) findings. The patients underwent breast ultrasound (US), CEM, MRI, and biopsy of the suspicious lesion. There were 47 patients with malignant lesions confirmed by biopsy and 21 patients with benign lesions, for each of which a KS was calculated. In the patients with malignant lesions, the MRI-derived KS was 9 (IQR 8-9), its CEM equivalent was 9 (IQR 8-9), and BI-RADS was 5 (IQR 4-5). In patients with benign lesions, MRI-derived KS was 3 (IQR 2-3), its CEM equivalent was 3 (IQR 1.7-5), and BI-RADS was 3 (IQR 0-4). There was no significant difference between the ROC-AUC of CEM and MRI (P=0.749). In conclusion, there were no significant differences in KS results between CEM and breast MRI. The KS flowchart is useful for evaluating breast lesions on CEM.

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.

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.

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).

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.

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.

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.

Human visual system (HVM) can quickly localize the most salient object in scenes, which has been widely applied on natural image segmentation [15]-[19]. In ultrasound (US) breast images, compared with background areas, tumor is more salient because of its higher contrast. In this paper, we develop a novel automatic localization method based on HVM for automatic segmentation of ultrasound (US) breast tumors. First, the input image is smoothed by convolution with a linearly separable Gaussian filter and then subsampled into a 9-layer Gaussian pyramid. Then intensity, blackness ratio, and superpixel contrast features are combined to compute saliency map, in which Winner Take All algorithm is used to localize the most salient region, presenting with a circle on the localized target. Finally the circle is taken as the initial contour of CV level set to finish the extraction of breast tumor. The localization method has been tested on 400 US beast images, among which 378 images have higher saliency than background areas and succeed in localization, with high accuracy 92.00%. The HVM localization method can be used to localize the tumors, combined with this method, CV level set can achieve the fully automatic segmentation of US breast tumors. By combing intensity, blackness ratio and superpixel contrast features, the proposed localization method can successfully avoid the interference caused by background areas with low echo and high intensity. Moreover, multi-object localization of US breast images can be considered in future employment.

Enterocins are bacteriocins synthesized by Enterococcus strains that show an interesting antimi-crobial effectiveness against foodborne pathogens such as Listeria monocytogenes. The objectives of this study were identify and analyze the expression of enterocin genes of Enterococcus isolated from breast-fed infants and evaluate the ability to inhibit three human isolates of virulent Lis-teria monocytogenes, as well as some probiotic bacteria. The susceptibility of the strains of L. mon-ocytogenes to fifteen antibiotics was tested, detecting resistance to cefoxitin (constitutive-ly resistant), oxacillin and clindamycin. Production of enterocins A, B and P were observed in Enterococcus faecium isolates, and enterocin AS-48 in an Enterococcus faecalis isolate. AS-48 showed antilisterial activity by itself, while the joint action of enterocins A and B, or B and P was neces-sary for inhibiting L. monocytogenes, demonstrating a synergistic effect of those combinations. The presence of multiple enterocin genes does not assured the inhibition of L. monocytogenes strains. However, the expression of multiple enterocin genes showed a good correlation with the inhibition capacity of these strains. Furthermore the potential beneficial strains of lactobacil-li and bifidobacteria examined were not inhibited by any of the enterocins produced individu-ally or in combination, with the exception of Bifidobacterium longum BB536, which was inhibited by enterocin AS-48 and the joint production of enterocins A and B or B and P. The enterocins studied here could be candidates for developing alternative treatments against antibi-otic-resistant bacterial infections. Moreover, these selected enterocin-producing E. faecium strains isolated from breast-fed infants could be used as probiotic strains due to their antilisterial effect as well as the absence of virulence factors.

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.

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.

(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.

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.

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.

The Carbonic Anidrase isoform IX (hCA IX) is one of the main player in extracellular tumor pH regulation and it is known to be overexpressed in breast cancer as well as in many common tu-mors. hCA IX has shown to contribute to the growth and survival of tumor cells and its expres-sion is correlated to metastasis and resistance to therapies making it an interesting biomarker for diagnosis and potential image-guided therapy. The aim of this work is the development of an MRI Imaging probe able to target the extracellular non catalytic PG domain of CAIX. A new specific nano probe has been designed by conjugating a peptidic interactor of PG domain on the surface of a liposome loaded with Gd-based contrast agents. Mouse Mammary Adenocarcinoma Cell Line (TS/A ) has been chosen as in vitro breast cancer model to test the efficacy of the de-veloped probe. MRI results display a high selectivity towards hCA IX marker and a good sensi-tivity of the Imaging probe. These findings make this approach promising for future develop-ment of in vivo diagnostic protocols aimed at visualizing this enzyme expression.

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.

Cancer cells are adept at reprogramming energy metabolism and the precise manifestation of this metabolic reprogramming exhibits heterogeneity across individuals (and from cell to cell). In this study, we analyzed the metabolic differences between interpersonal heterogeneous cancer phenotypes. We used divergence analysis on gene expression data of 1156 breast normal and tumor samples from The Cancer Genome Atlas (TCGA) and integrated this information with a genome-scale reconstruction of human metabolism to generate personalized, context-specific metabolic networks. Using this approach, we classified the samples into four distinct groups based on their metabolic profiles. Enrichment analysis of the subsystems indicated that amino acid metabolism, fatty acid oxidation, citric acid cycle, androgen and estrogen metabolism and ROS detoxification distinguished these four groups. Additionally, we developed a workflow to identify potential drugs that can selectively target genes associated with the reactions of interest. MG-132 (a proteasome inhibitor) and OSU-03012 (a celecoxib derivative) were the top-ranking drugs identified from our analysis and known to have anti-tumor activity. Our approach has the potential to provide mechanistic insights into cancer-specific metabolic dependencies, ultimately enabling the identification of potential drug targets for each patient independently, contributing to a rational personalized medicine approach.