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.

Breast cancer is an important disease that threatens the lives of women. The majority of breast screening health education is printed promotional material, which is ineffective in enhancing women’s knowledge on breast screening in Taiwan, and showed low breast cancer screening rate in women. This provided the impetus for us to carry out this study to understand the major barrier of women on breast cancer and screening procedures. This study used quasi-experimental design and purposive sampling. The study participants were 45–69 year-old women. Data collection was carried out before and after intervention. The health belief model was used as a research framework to examine changes in the study participants after multimedia health education intervention for detecting which factors most affect women's breast cancer screening behavior. Then we could make the policy for enhancing women's breast cancer screening in the future. Our study showed that after multimedia health education intervention, the scores of perceived susceptibility, perceived seriousness, perceived benefits, perceived barriers, cues to action, and self-efficacy in the experimental group were all significantly higher than the control group. We believe that the effectiveness of multimedia health education is better than traditional health education methods, and can enhance women to receive breast cancer screening.

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.

Abstract On the background of new research results in screening of breast cancer, together with the expectation of the participants in a screening for breast cancer, the conventional mammography requires supplementation by means of tomosynthesis or additive ultrasound. Alternatively, ultrasound now seems to be an independent method of early detection of breast cancer because of its superior sensitivity, especially in the case of aggressive mammary carcinoma types. The MRI remains at present still a preferred method in high-risk cases and as an additive examination in case of insufficient presentation of the glandular tissue by conventional methods. MRI is also preoperatively valuable for more accurately measuring the extent of multifocal carcinomas.

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

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

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

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

Despite the recognized benefits of fecal occult blood test (FOBT) and mammography screenings, participation in breast (BC) and colorectal cancer (CRC) screening programs is still suboptimal. This study investigates municipal characteristics associated with their BC/CRC screening uptake profiles among women aged 55–69 years. Using data from 308 municipalities of Flanders from 2014 to 2017, a profile for each municipality based on its BC/CRC screening uptake compared with the median screening uptake was created. Logistic regression with generalized estimating equations was used to assess the associations between municipal characteristics and BC/CRC screening uptake profiles. The overall median uptake of cancer screening was higher for CRC (57.4%) than for BC (54.6%). The following municipal characteristics were associated with worse performance in terms of only CRC, only BC, or both CRC and BC screening uptake, respectively: foreign nationality, self-employment rate, (early) retirement rate, diabetes, disabilities; (early) retirement rate; age group 65–69, foreign nationality, self-employment rate, (early) retirement rate, wage-earners, diabetes. The following municipal characteristics were associated with better performance in terms of only CRC, only BC, or both CRC and BC screening uptake respectively: residential stability, having a partner, having children, jobseeker rate, GP visits, preventive dental visits; having children, GP visits; age group 55–59, residential stability, having a partner, having children, jobseeker rate, higher education, GP visits, preventive dental visits. This study’s results regarding the interrelation between the BC and CRC screening could be used to tailor interventions to improve the participation of the target population in both programs.

Current oncological developments are based on improved understanding of genetics, and especially the discovery of genes whose alterations affect cell functions with consequences for the whole body. Our work is focused on the one of these genes, the BARD1 and its oncogenic role in breast cancer. Most importantly, the study points to new avenues in the treatment and prevention of the most frequent female cancer based on BARD1 research. The BARD1 and BRCA1 proteins have similar structures and functions, and they combine to form the new molecule BARD1-BRCA1 heterodimer. The BARD1-BRCA1 complex is involved in genetic stabilization at the cellular level. It allows to mark abnormal DNA fragments by attaching ubiquitin to them. In addition, it blocks (by ubiquitination of RNA polymerase II) the transcription of damaged DNA. Ubiquitination, as well as stabilizing chromatin, or regulating the number of centrosomes, confirms the protective cooperation of BARD1 and BRCA1 in the stabilization of the genome. The overexpression of the oncogenic isoforms BARD1β and BARD1δ permit cancer development. The introduction of routine tests, for instance, to identify the presence of the BARD1β isoform, would make it possible to detect patients at high risk of developing cancer. On the other hand, introducing BARD1δ isoform blocking therapy, which would reduce estrogen sensitivity, may be a new line of cancer therapy with potential to modulate responses to existing treatments. It is possible that the BARD 1 gene offers new hope for improving breast cancer therapy.

Current oncological developments are based on improved understanding of genetics, and especially the discovery of genes whose alterations affect cell functions with consequences for the whole body. Our work is focused on the most important of these genes, the BARD1 and its oncogenic role in breast cancer. Most importantly, the study points to new avenues in the treatment and prevention of the most frequent female cancer based on BARD1 research. The BARD1 and BRCA1 proteins have similar structures and functions, and they combine to form the new molecule BARD1-BRCA1 heterodimer. Through ubiquitination, this heterodimer has significant effects on individual proteins, enabling, among others, the destruction of damaged DNA fragments. Ubiquitination, as well as stabilizing chromatin, or regulating the number of centrosomes, confirms the protective cooperation of BARD1 and BRCA1 in the stabilization of the genome. The overexpression of the oncogenic isoforms BARD1β and BARD1δ permit cancer development. The introduction of routine tests, for instance, to identify the presence of the BARD1β isoform, would make it possible to detect patients at high risk of developing cancer. On the other hand, introducing BARD1δ isoform blocking therapy, which would reduce estrogen sensitivity, may be a new line of cancer therapy with potential to modulate responses to existing treatments. It is possible that the BARD 1 gene offers new hope for improving breast cancer therapy.

In this study, we described the most critical risk factors for different malignancies including: breast, prostate, lung, and colorectal carcinoma among others, with an emphasis on modifiable risk factors. We revised the literature review about risk factors involved in the genesis of cancer in various databases, including articles indexed in PUBMED, SCOPUS, PMC, and Google Scholar. Awareness of risk factors enables conscious decisions to be made in an effort to combat malignancies. Knowing risk factors is a mode of fighting malignancy. Diet, lifestyle, practises, and laboratory/clinical interventions were among risk factors of diverse malignancy. Diet, lifestyle, laboratory/clinical interventions all contribute to the genesis and prognosis in a variety of malignancies. We concluded that abstaining from risk factors can prevent the development of many malignancies in a century where this conundrum is raising disproportionately. By informing the public about modifiable risk factors cancer mortality rates can be reduced. It is treated here is to make the public aware of the modifiable risks of cancers.

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.

Epidemiological studies on micronutrient consumption have reported protective associations in the incidence and/or progression of various cancer types. Supplementation with some of these micronutrients has been analyzed, showing chemoprotection, low toxicity, antiproliferation, and the ability to modify epigenetic signatures in various cancer models. The following review inves-tigates the reported effects of micronutrient intake or supplementation in breast cancer progres-sion. A PubMed search was conducted with the keywords “micronutrients breast cancer progres-sion,” and the results were analyzed. The selected micronutrients were: Vitamins (A, C, D, and E), Folic Acid, metals (Cu, Fe, Se, and Zn), fatty acids, polyphenols, and iodine. The majority of in vitro models showed antiproliferative, cell cycle arrest, and antimetastatic effects for almost all the micronutrients analyzed, but these effects do not reflect animal or human studies. Only one clinical trial with Vitamin D and one pilot study with molecular iodine showed favorable overall survival and disease-free interval.

The purpose of this study was to determine the change in overall survival (OS) for patients with de novo metastatic breast cancer (dnMBC) over time. We conducted a retrospective cohort study with 1981 patients with dnMBC diagnosed between January 1995 and December 2017 at The University of Texas MD Anderson Cancer Center. OS was measured from the date of diagnosis of dnMBC. OS was compared between patients diagnosed during different time periods: 5-year periods and periods defined according to when key agents were approved for clinical use. The median OS was 3.4 years. The 5- and 10-year OS rates improved over time across both types of time periods. A subgroup analysis showed that OS improved significantly over time for the estrogen-receptor-positive/HER2-positive (ER+/HER2+) subtype, and exhibited a tendency toward improvement over time for the ER-negative (ER-)/HER2+ subtype. Median OS was significantly longer in patients with non-inflammatory breast cancer (P = .02) and in patients with ER+ disease, progesterone-receptor-positive disease, HER2+ disease, lower nuclear grade, locoregional therapy, and metastasis to a single organ (all P &lt;.0001). These findings showed that OS at 5 and 10 years after diagnosis in patients with dnMBC improved over time. The significant improvements in OS over time for the ER+/HER2+ subtype and the tendency toward improvement for ER-/HER2+ subtype suggest the contribution of HER2-targeted therapy to survival.

Background: Metformin is a drug used to treat patients with type 2 diabetes, especially those who suffer from obesity. It is also used in the treatment of women with polycystic ovary syndrome (PCOS). This disease has been shown to be related to insulin resistance and multiplied blood sugar ranges. Further, it has been found that the use of metformin improves the menstrual cycles and ovulation rates of these women. Methods: A structured questionnaire will be conducted to determine the prevalence of breast cancer among women using metformin in the Ha’il region. Result: Incidence of breast cancer among women using metformin in the Ha’il region is very low. Conclusions: According to previous findings, metformin has been linked to lower breast cancer risk in women with type 2 diabetes. Furthermore, the findings of this study have corroborated the literature for the same by indicating that there is a substantial connection between metformin use and a lower risk of breast cancer in women with type 2 diabetes

Metastasis is a major cause factor for breast cancer (BC)-associated mortality. During the metastatic process, disseminated tumor cells (DTCs) detach from the primary sites, and enter the bloodstream and establish the secondary colonies. Recent studies have provided substantial evidence for the importance of Notch signaling in BC metastasis. Therefore, this review focuses on the mechanisms by which Notch contributes to the origin of BC DTCs, increases their motility, regulates their intravasation and extravasation, protects them from host surveillance, and finally facilitates colonization. Identification of the mechanisms underlying Notch-related BC metastasis will lead to the development of novel Notch-targeted therapeutic strategies to reduce metastasis and significantly improve outcomes.

To systematically investigate the epidemiology of breast cancer risk factors in Iran, we performed a systematic search via PubMed, Scopus, Web of Science and Persian databases for identifying studies published on breast cancer risk factors up to March 2019. Meta-analyses were done for risk factors reported in more than one study. We calculated odds ratios (ORs) with corresponding 95% confidence intervals (CIs) using a fixed/random-effects models.Thirty-nine studies entered into the meta-analysis. Pooling of ORs showed a significant harmful effect for risk factors including family history (OR: 1.80, 95%CI 1.47-2.12), HRT (OR: 5.48, 95%CI 0.84-1.74), ER positive (OR: 1.87, 95%CI 1.41-2.33), PR positive (OR: 1.84, 95%CI 1.38-2.29), stress condition (OR: 2.67, 95%CI 1.84-3.50), passive smokers (OR: 1.68, 95%CI 1.34-2.03), full-term pregnancy at age 30 (OR: 3.41, 95%CI 1.19-5.63), abortion (OR: 1.84, 95%CI 1.35-2.33), sweets consumption (OR: 1.71, 95%CI 1.32-2.11) and genotype Arg/Arg (crude OR: 1.59, 95%CI 1.07-2.10), whereas a significant protective effect for late menarche (OR: 0.58, 95%CI 0.32-0.83), nulliparity (OR: 0.68, 95%CI 0.39-0.96), 13 to 24 months of breastfeeding (OR: 0.68, 95%CI 0.46-0.90), daily exercise (OR: 0.59, 95%CI 0.44-0.73) and vegetable consumption (crude OR: 0.28, 95%CI 0.10-0.46).This study suggest that factors such as family history, HRT, ER and PR positive status, stress condition, passive smokers, late full-term pregnancy, abortion, sweets consumption and genotype Arg/Arg might increase risk of breast cancer development, whereas late menarche, nulliparity, 13-24 months breastfeeding, daily exercise and vegetable consumption had an inverse association with breast cancer development.

Regardless of the advances in our ability to detect early and treat breast cancer, it is still one of the common types of malignancy worldwide, with the majority of patients decease upon metastatic disease. Nevertheless, due to these advances, we have extensively characterized the drivers and molecular profiling of breast cancer and further dividing it into subtypes. These subgroups are based on immunohistological markers (Estrogen Receptor-ER, Progesterone Receptor-PR and Human Epidermal Growth Factor Receptor 2-HER-2) and transcriptomic signatures, with distinct therapeutic approaches and regiments. These therapeutic approaches include targeted therapy (HER-2+), endocrine therapy (HR+) or chemotherapy (TNBC) with optional combination radiotherapy, depending on clinical stage. Technological and scientific advances in the identification of molecular pathways that contribute to therapy-resistance and establishment of metastatic disease, have provided the rationale for revolutionary targeted approaches against Cyclin-Dependent Kinases 4/6 (CDK4/6), PI3 Kinase (PI3K), Poly ADP Ribose Polymerase (PARP) and Programmed Death-Ligand 1 (PD-L1), among others. In this review, we focus on the comprehensive overview of epidemiology and current standard of care treatment of metastatic breast cancer, along with ongoing clinical trials. Towards this goal, we utilized available literature from PubMed and ongoing clinical trial information from clinicaltrials.gov to reflect the up to date and future treatment options for metastatic breast cancer.

The aim of this study was to investigate the possible role of 99mTc-sestamibi in the regulation of cancer cell proliferation and apoptosis. To this end, Te in vivo values of 99mTc-sestamibi uptake have been associated to the in-situ expression of both Ki67 and caspase-3. For in vitro investiga-tions BT-474 cells were incubated with three different concentration of 99mTc-sestamibi: 10µg/ml –1µg/ml – 0,1µg/ml. Expression of caspase-3 and Ki67, as well as the ultrastructure of cancer cells, were evaluated at T0 and after 24, 48, 72 and 120 hours after 99mTc-sestamibi incubation. Ex vivo data strengthened the known association between the sestamibi uptake and the Ki67 expression. Linear regression analysis showed a significant association between the sestamibi uptake and the number of apoptotic cells evaluated as caspase-3 positive breast cancer cells. As concern the in vitro data, a significant decrease of the proliferation index was observed in breast cancer cells incubated with high concentration of 99mTc-sestamibi (10µg/ml). Amazingly, a significant increase in caspase-3 positive cells in cultures incubated with 10µg/ml 99mTc-sestamibi was observed. This study suggested the possible role of sestamibi in the regulation of pathophysiological process involved in breast cancer.

Breast cancer has an important incidence in the worldwide female population. Although alterations in the mitochondrial genome probably play an important role in carcinogenesis, the actual evidence is ambiguous and inconclusive. The purpose of the present work was to explore mitochondrial sequences of clinical cases with breast cancer from different origins and determine the polymorphisms associated. The search for complete and partial mtDNA sequences obtained from breast cancer patients and controls was performed in NCBI Genbank database. We identified 124 mtDNA sequences associated to breast cancer cases of which 86 were complete and 38 partial sequences. Of these 86 complete sequences, 52 belong to patients with a confirmed diagnosis of breast cancer and 34 sequences were obtained from healthy mammary tissue of the same patients used as controls. From mtDNA analysis, two polymorphisms with significative statistical differences were found in D130 in sequences analyzed: m.310del (rs869289246) in 34.6% (27/78) breast cancer cases and 61.7% (21/34) of controls; and m.315dup (rs369786048) in 60.2% (47/78) of breast cancer cases and 38.2% (13/34) of controls. Also, the variant m.16519T>C (rs3937033) was found in 59% of control sequences and 52% of breast cancer sequences with a significant statistical difference. Polymorphic changes are evolutionarily related to haplogroup H of Indo-European and Euro Asiatic origins, however, were found in all non-European sequences with breast cancer.

Breast cancer develops from cells lining the milk ducts and slowly grows into a lump or a tumour. Breast cancer may be invasive or non-invasive. Invasive cancer spreads from the milk duct or lobule to other tissues in the breast, whereas, non-invasive ones lack the ability to invade other breast tissues. Non-invasive breast cancer is called in situ and may remain inactive for entire lifetime. Due to heterogeneity nature of breast, density as well as masses is variable in size and shape. A dataset of 18056 patients are collected from 20 Government Hospitals and 50 Private Hospitals in West Bengal before COVID-19 and after COVID-19. The classification of patients are made on three classes- Normal, Sign of Abnormality and Abnormality. The reports of MRIs of patients in January 2020 and February 2020 are collected from different hospitals. It is treated as dataset before COVID-19 . MRIS of patients in April 2020 and May 2020 are dataset during COVID-19. The entire datasets are accumulated for testing of any change in patients MRIS after the official announcement of new virus COVID-19 in March 2020. The aim of the paper is to make a comparison of any change in size and shape of masses of MRIs of patients before and after COVId-19. All collected MRIs reports are diagnosed by radiologists of hospitals.

Given that 3-Phosphoinositide-dependent kinase 1 (PDK1) plays a crucial role in malignant biological behaviors of a wide-range of cancers, we further review the influence of PDK1 in breast cancer (BC). First, we describe the power of PDK1 in cellular behaviors and extensively demonstrate the interacting networks of PDK1 via PI3K-dependent/ PI3K-independent pathway. Then we enlighten the roles of PDK1 in carcinogenesis, growth and survival, metastasis, and chemoresistance in BC cells. More important, we sort the current preclinical or clinical trials of PDK1 targeted therapy in BC and find that even though at present no selective PDK1 inhibitor is available for BC therapy, but the combination trials of PDK1 targeted therapy and other agents have demonstrated some benefit. Thus, there is increasing anticipations that PDK1 targeted therapy will have its space in future therapeutic concepts of BC, and we hope to feature PDK1 in BC to the clinic and bring the new promising to patients for targeted therapies.

Classification algorithms are very widely used algorithms for the study of various categories of data located in multiple databases that have real-world implementations. The main purpose of this research work is to identify the efficiency of classification algorithms in the study of breast cancer analysis. Mortality rate of women increases due to frequent cases of breast cancer. The conventional method of diagnosing breast cancer is time consuming and hence research works are being carried out in multiple dimensions to address this issue. In this research work, Google colab, an excellent environment for Python coders, is used as a tool to implement machine learning algorithms for predicting the type of cancer. The performance of machine learning algorithms is analyzed based on the accuracy obtained from various classification models such as logistic regression, K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Naïve Bayes, Decision Tree and Random forest. Experiments show that these classifiers work well for the classification of breast cancers with accuracy>90% and the logistic regression stood top with an accuracy of 98.5%. Also implementation using Google colab made the task very easier without spending hours of installation of environment and supporting libraries which we used to do earlier.

CCNs are specific type of matricellular proteins, which are essential signaling molecules, and play multiple roles in multicellular eukaryotes. This family of proteins consists of six separate members in mammals. The architecture of CCN proteins is multimodular and comprises four distinct motifs. CCN proteins achieve their specific physiological functions by binding to integrin receptors. The CCN family has been implicated in both cure and disease with impacts on biological interactions, such as cell adhesion, chemotaxis and migration, mitogenesis, cell survival, angiogenesis, differentiation, tumorigenesis, immune functions, chondrogenesis, and wound healing. Breast cancer is the most commonly diagnosed cancer worldwide and the leading cause of cancer mortality among women triggered by atypical expression of CCNs. A favorable or unfavorable association between various CCNs has been reported in patients with breast carcinomas. Aberrant expression of CCN1 intensifies the proliferation of epithelial cells that line the lobes and ducts of the breast. Evidence also shows that the expression of CCN2 can ameliorate tumor growth and metastasis. However, CCN3 (NOV), CCN5 (WISP-2), and CCN6 (WISP-3) are consistent with neoplastic development and metastasis repression. Particular CCN members can develop tumors and cancer progression, whereas others can competitively counter the processes. Several studies have been conducted on CCN proteins and cancer in recent years. In our study, we intend to provide an overview of those research works while keeping breast carcinoma on focus. We believe that the importance of the CCN protein family in breast cancer should be reconsidered.

The search for improved therapeutic approaches to breast cancer are still on going. Breast tumor kinase (BRK, also known as PTK6) is one of the targets, it is highly expressed in breast carcinomas while displaying low or no expression in the normal mammary gland, which hints at the oncogenic role of this enzyme in breast cancer. In these twenty years, an increasing number of studies have focused on understanding the cellular roles of BRK in breast cancers. This review outlines the advances made towards understanding the cellular and physiological role of BRK, the molecular and chemical inhibitors and its therapeutic significance in breast cancer.

The mammalian STE 20-like protein kinase 4 (MST4) gene is highly expressed in several cancer types, but little is known on the role of MST4 in breast cancer and the function of MST4 during epithelial-mesenchymal transition (EMT) has not been fully elucidated. Here, we report that overexpression of MST4 in breast cancer results in enhanced cell growth, migration, and invasion, whereas inhibition of MST4 expression significantly attenuates these properties. Further study shows that MST4 promotes EMT by activating Akt and its downstream signaling molecules such as E-cadherin/N-cadherin, Snail, and Slug. MST4 also activates AKT and its downstream pro-survival pathway. Furthermore, by analyzing breast cancer patient tissue microarray and silicon datasets, we found that MST4 expression is much higher in breast tumor tissue compared to normal tissue, and significantly correlates with cancer stage, lymph node metastasis and a poor overall survival rate (p<0.05). Taken together, our findings demonstrate the oncogenic potential of MST4 in breast cancer, highlighting its role in cancer cell proliferation, migration/invasion, survival, and EMT, suggesting a possibility that MST4 may serve as a novel therapeutic target for breast cancer.

Background: Monoclonal antibodies against PD-1 or PD-L1 are established in clinical practice for the treatment of both early and advanced/metastatic triple-negative breast cancer. Beyond the established immune checkpoints (ICPs) (PD-1 and CTLA-4) additional ICPs such as lymphocyte activation gene-3 (LAG-3) are subject of current research. In the present retrospective gene ex-pression analysis, we evaluated the prognostic significance of LAG-3 in 461 patients with early breast cancer. In addition, we examined whether there was a correlation between the different ICPs and CD8 expression. Methods: Using microarray-based gene expression analysis, we examined the prognostic signif-icance for metastasis-free survival (MFS) of LAG-3 mRNA expression in the whole cohort of 461 breast cancer patients and among different molecular subtypes. Correlations were analyzed us-ing Spearman-Rho correlation coefficient. Results: In the whole cohort, LAG-3 expression had no significant impact on MFS (p = 0.712, Log Rank). In the subgroup analyses, there was a trend, that higher LAG-3 expression was associated with favorable outcome in the luminal B (p = 0.217), basal-like (p = 0.370) and HER2 (p = 0.089) subtypes, although significance was not reached. In contrast, in multivariate Cox regression analysis adjusted for age, tumor size, axillary nodal status, histological grade of differentiation and the proliferation marker Ki-67, LAG-3 showed a significant influence on MFS (HR 0.574; 95% CI 0.369–0.894; p = 0.014). High LAG-3 significantly correlated with CD8 ( = 0.571; p < 0.001). Conclusion: LAG-3 expression had an independent impact on MFS. In addition to PD-1 and PD-L1, further immune checkpoints such as LAG-3 could serve as therapeutic targets in breast cancer.

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.

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

Endocrine therapy (ET) has established itself as an efficacious treatment for estrogen receptor-positive (ER+) breast cancers, with a reduction in recurrence rates and increased survival rates. The pre-surgical approach with chemotherapy (NCT) has become a common form of management for large, locally advanced or high-risk tumors. However, a good response to NCT is not usually expected in ER+ tumors. Good results with primary ET, mainly in elderly women, have encouraged studies in other stages of life, and nowadays neoadjuvant endocrine treatment (NET) has become a useful approach to many ER+ breast cancers. The aim of this review is to provide an update on the current state of art regarding the present and the future role of NET.

In this paper, a mathematical model of breast cancer governed by a system of ordinary differential equations in the presence of chemotherapy treatment and ketogenic diet is discussed. Several comprehensive mathematical analysis was carried out using varieties of analytical methods to study the stability of the breast cancer model. Also, sufficient conditions on parameter values to ensure cancer persistence in the absence of anti-cancer drugs ketogenic diet and cancer emission when anti-cancer drugs, immune-booster, ketogenic diet are included were established. Furthermore, optimal control theory is applied to find out the optimal drug adjustment as an input control of the system therapies to minimize the number of cancerous cells by considering different controlled combinations of administering the chemotherapy agent and ketogenic diet using the popular Pontryagin’s Maximum Principle. Numerical simulations were presented to validate our theoretical results.

G protein-coupled receptors (GPCRs, also called seven-transmembrane or heptahelical receptors) are a superfamily of cell surface receptor proteins that bind to many extracellular ligands and transmit signals to an intracellular guanine nucleotide-binding protein (G protein). When a ligand binds, the receptor activates the attached G-protein by causing the exchange of Guanosine-5'-triphosphate (GTP) for guanosine diphosphate (GDP). They play a major role in many physiological functions as well as in the pathology of many diseases including cancer progression and metastasis. Only a few GPCR members have been exploited as targets for developing drugs with therapeutic benefit in cancer. Present review deals with the Prostaglandin E receptor EP4, a member of the EP family of GPCR, as a promising newer therapeutic target for treating breast cancer. We show that aberrant over-expression of cyclooxygenase (COX)-2, an inflammation-associated enzyme, occurring in 40-50% of breast cancer patients leads to tumor progression and metastasis due to multiple cellular events resulting from an increased prostaglandin (PG) E2 production in the tumor milieu. They include inactivation of host anti-tumor immune (NK and T) cells, increased immuno-suppressor function of tumor-associated macrophages, promotion of tumor cell migration, invasiveness and tumor-associated angiogenesis (due to upregulation of VEGF-A), lymphangiogenesis (due to upregulation of VEGF-C/D) and a stimulation of stem-like cell (SLC) phenotype in cancer cells. All these events were primarily mediated by activation of the PGE receptor EP4 on tumor or host cells. We show that selective EP4 antagonists (EP4A) could mitigate all these events tested with cells in vitro as well as in vivo in syngeneic COX-2 expressing mammary cancer bearing mice or immune-deficient mice bearing COX-2 over-expressing human breast cancer xenografts. We suggest that EP4A can avoid thrombo-embolic side effects of long term use of COX-2 inhibitors by sparing cardio-protective roles of PGI2 via IP receptor activation or PGE2 via EP3 receptor activation. Furthermore, we identified two COX-2/EP4 induced oncogenic and SLC-stimulating microRNAs - miR526b and miR655, one of which (miR655) appears to be a potential blood biomarker in breast cancer patients, for monitoring SLC-ablative therapies such as with EP4A. We suggest that EP4A will likely produce the highest benefit in aggressive breast cancers such as COX-2 expressing triple-negative breast cancers, when combined with other newer agents such as PD-1 or PD-L1 inhibitors.

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.

For decades since the central dogma, cancer biology research has been focusing on the involvement of genes encoding proteins. It has been not until more recent times that a new molecular class has been discovered, named non-coding RNA (ncRNA), which has been shown to play crucial roles in shaping the activity of cells. An extraordinary number of studies into shown that ncRNAs represent an extensive and prevalent group of RNAs, including both oncogenic or tumor suppressive molecules. Henceforth, various clinical trials involving ncRNAs as extra ordinary biomarkers or therapies have started to emerge. In this review, we will focus on the prognostic and diagnostic role of ncRNAs for breast cancer.

Although mammography has been the gold standard for early detection of breast cancer, if a woman has dense breast tissue, a false negative diagnosis may occur. Breast ultrasound, whether hand-held or automated, is a useful adjunct to mammography but adds extra time and cost. The primary aim was to demonstrate that our second-generation Aceso system, which combines full-field digital mammography (FFDM) and automated breast ultrasound (ABUS) in a single platform, is able to produce improved quality images that provide clinically meaningful results. Aceso was first tested using two industry standards: a CDMAM phantom to assess the FFDM images; and the CIRS 054GS phantom to evaluate the ABUS images. In addition, 25 women participated in a clinical trial: 14 were healthy volunteers while 11 were patients referred by the breast clinic at Groote Schuur Hospital. The CDMAM phantom results showed the FFDM results were better than EUREF’s standard of “acceptable” and were approaching “achievable”. The ABUS results showed lateral and axial spatial resolution of 0.5 mm and adequate depth penetration of 80 mm. Our second-generation Aceso system, with its improved quality of clinical FFDM and ABUS images, has demonstrated its potential for early detection of breast cancer in a busy clinic.

Molecular iodine (I2) induces apoptotic, antiangiogenic, and antiproliferative effects in breast cancer cells. Little is known about its effects on the tumor immune microenvironment. We studied the effect of oral (5 mg/day) I2 supplementation alone (I2) or together with conventional chemotherapy (Cht+I2) on the im-mune component of breast cancer tumors from a previously published pilot study conducted in Mexico. RNA-seq, I2 and Cht+I2 samples showed significant increases in expression of Th1 and Th17 pathways. Tumor immune composition determined by deconvolution analysis revealed significant increases in M0 macrophages and B lymphocytes in both I2 groups. Real-time RT-PCR showed that I2 tumors overexpress T-BET (p = 0.019) and interferon-gamma (IFNγ; p = 0.020) and silence tumor growth factor-beta (TGFβ; p = 0.049); whereas in Cht+I2 tumors, GATA3 is silenced (p = 0.014). Preliminary methylation analysis shows that I2 activates IFNγ gene promoter (by increasing its unmethylated form) and silences TGFβ in Cht+I2. In conclusion, our data showed that I2 supplements induce the activation of the immune response and that when combined with Cht, the Th1 pathways are stimulated. The molecular mechanisms involved in these responses are being analyzed, but preliminary data suggest that methylation/demethylation mechanisms could also participate.

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.

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: 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.

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.

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.

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

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.

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

Sleep is essential for health. Indeed, poor sleep is consistently linked to the development of systemic disease, including depression, metabolic syndrome, and cognitive impairments. Further evidence has accumulated suggesting a role for sleep in cancer initiation and progression (primarily breast cancer). Indeed, patients with cancer and cancer survivors frequently experience poor sleep, manifested as insomnia, circadian misalignment, hypersomnia, somnolence syndrome, hot flushes, and nightmares. These problems are associated with a reduction in patients’ quality of life and increased mortality. Due to the heterogeneity among cancers, treatment regimens, patient populations, and lifestyle factors, the etiology of cancer-induced sleep disruption is largely unknown. Here, we discuss recent advances in understanding the pathways linking cancer and the brain and how this leads to altered sleep patterns. We describe a conceptual framework where tumors disrupt normal homeostatic processes, resulting in aberrant changes in physiology and behavior that are detrimental to health. Finally, we discuss how this knowledge can be leveraged to develop novel therapeutic approaches for cancer-associated sleep disruption, with special emphasis on host-tumor interactions.

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.

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

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

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

Breast cancer 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

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.

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.

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..

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.

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.

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.

Young women with breast cancer represent 15% of cancer cases in Latin America. Genomic studies have found that early-onset breast-cancer cases exhibit a higher genetic susceptibility and a specific genomic signature as compared to their older counterparts. The aim of this study was to describe clinically relevant germline mutations in a cohort of young women with breast cancer. To achieve this, we analyzed hereditary-cancer genes from whole-exome sequencing data in 108 unrelated women with an extreme phenotype of breast cancer (≤40 years of age), diagnosed and treated at the National Cancer Institute of Mexico; 11% of the patients carried a pathogenic variant. BRCA2 comprised 46% of the mutations, followed by BRCA1 with 23%; PALB2 with 15%; and TP53 and RAD51C with 8 % each. This article describes a novel pathogenic mutation in RAD51C c.519dupT. The median age at diagnosis was 35 years overall; however, it was six years younger in patients with mutations. Age at diagnosis (OR=0.82, CI 95% 0.71-0.94; P= 0.008) and first-degree family history of cancer (OR=8.26, CI95% 1.35-50; P= 0.022) were the only epidemiological variables associated with mutational status. We found no differences in disease-free survival (p=0.403) or overall survival (p=0.735) among mutational status subgroups.

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.

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.

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.

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.

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

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

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

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

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

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.

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

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.

The triple-negative breast cancer (TNBC) subtype is one of the most aggressive forms of breast cancer that has poor clinical outcome and still remains as an unmet clinical challenge. Accumulating evidence suggests that intratumoral heterogeneity or the presence of phenotypically heterogeneous cell populations within a tumor plays a crucial role in chemoresistance, tumor progression and metastasis. Increased understanding of the molecular regulators of intratumoral heterogeneity will enable the development of effective therapeutic strategies in TNBC. We have identified a molecular mediator involved in intratumoral heterogeneity in breast cancer using an unbiased approach. We isolated two heterogeneous tumor cell populations from the 4T1 TNBC tumor model and phenotypic characterization revealed that the cells are distinct in terms of their morphology, proliferation and self-renewal ability in vitro; as well as primary tumor formation and metastatic potential in vivo. Further, RNA sequencing on both cell populations was performed to identify the molecular mediators underlying this heterogeneity. Bioinformatic analysis performed on the differentially expressed genes along with the Kaplan-Meier survival analysis in TNBC patients identified Metastasis associated colon cancer 1 (Macc1) as the top candidate gene mediating the aggressive phenotype. The role of Macc1 in regulating the proliferative phenotype was validated using siRNA mediated gene knockdown. The role of Macc1 in the aggressive cancer cell phenotypes and disease progression is being studied further using a small molecule transcriptional inhibitor of Macc1 in cell line and animal models, thus increasing our understanding of the molecular underpinnings of intratumoral heterogeneity in breast cancer that is critical to the improvement in the treatment of women currently living with the highly aggressive TNBC subtype.

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.

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

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.

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.

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.

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

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

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

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.

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

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

Measurement of breast cancer burden and identification of its influencing factors help in the development of public health policy and strategy against the disease. This study aimed to examine the variability of the excess mortality of female breast cancer patients in the North East Region of Peninsular Malaysia. This retrospective cohort study was conducted using breast cancer data from the Kelantan Cancer Registry between 2007 and 2011, and Kelantan general population mortality data. The breast cancer cases were followed up for five years until 2016. Out of 598 cases, 549 cases met the study criteria and were included in the analysis. Modelling of excess mortality was conducted using Poisson regression. Excess mortality of breast cancer varied according to age group (50 years old and below vs above 50 years old, Adj. EHR: 1.47; 95% CI: 1.31, 4.09; P=0.004), ethnicity (Malay vs non-Malay, Adj. EHR: 2.31; 95% CI: 1.11, 1.96; P=0.008), and stage (stage III and IV vs. stage I and II, Adj. EHR: 5.75; 95% CI: 4.24, 7.81; P<0.001). In conclusion, public health policy and strategy aim to improve cancer survival should focus more on patients presented at age below 50 years old, Malay ethnicity, and at a later stage.

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

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

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.

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

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

The HER2 overexpression occurs in 10–20% of breast cancer patients. HER2+ tumors are characterized by increase in Ki67, early relapse and increased metastasis. There is little known about factors influencing early stages of HER2- tumorigenesis and diagnostic markers. Previously, it was shown that deletion of NEDD9 in mouse models of HER2 cancer interferes with tumor growth, but the role of NEDD9 upregulation is currently unexplored. We report that NEDD9 is overexpressed in a significant subset of HER2+ breast cancers and correlates with limited response to anti-HER2 therapy. To investigate the mechanisms through which NEDD9 influences HER2-dependent tumorigenesis, we generated MMTV-Cre-NEDD9 transgenic mice. The analysis of mammary glands shows extensive ductal epithelium hyperplasia, increased branching, and terminal end bud expansion. The addition of oncogene Erbb2 (neu) leads to development of early hyperplastic benign lesions earlier (~16 weeks) with a significantly shorter latency than the control mice. Similarly, NEDD9 upregulation in MCF10A-derived acini leads to hyperplasia like DCIS. This phenotype is associated with activation of ERK1/2 and AURKA kinases leading to an increased proliferation of luminal cells. These findings indicate that NEDD9 is setting permissive conditions for HER2-induced tumorigenesis, thus identifying this protein as a potential diagnostic marker for early detection.

The aim of this study was to examine pathologic complete response (pCR) and overall survival (OS) of patients diagnosed with non-metastatic inflammatory breast cancer (IBC). A total of N=8,550 cases undergoing surgery were identified between 2004-2013, using the National Cancer Database (NCDB). Patients were grouped into 4 biologic subtypes (HR+/HER2-, HR+/HER2+, HR-/HER2+, HR-/HER2-). The median age at diagnosis was 56 years. On average, women were followed for 3.7 years [interquartile range=3.0]. The majority were white (80%), had private health insurance (50%), and presented with poorly differentiated tumors (57%). Approximately 46% of the cancers were >5cm. Most patients underwent mastectomy (94%) and received radiotherapy (71%). Differences by biologic subtypes were observed for grade, lymph node invasion, race, and tumor size (p<.0001). Compared with non-pCR (54%), patients experiencing pCR had superior 5-year survival (77%) (p<.0001). Survival was poor for triple-negative (TN) tumors (37%) vs. other biologic subtypes (60%) (p<.0001). On multivariable analysis, TN-IBC, positive margins, and not receiving either chemotherapy, hormonal therapy or radiotherapy were independently associated with poor 5-year survival (p<.0001). In this large multicentric analysis of IBC, categorized by biologic subtypes, we observed significant differential tumor, patient and treatment characteristics, and OS.

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

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