Breast self-Examination (BSE) is the cheapest most recommended Breast Cancer (BC) preventive tool for resource-deprived settings. There is paucity in the attitude research domain and comparative gender assessments of the BSE knowledge, attitude and performance (KAP) literature. Purpose: The purpose of this study was to assess the combined and exclusive gender BSE attitude of undergraduate health trainees and to determine significant differences between scores of both genders. Methodology: participants included 5 undergraduate health trainee classes purposively sampled from 2 faculties. Online cross-sectional method was used to assess BSE attitude of 336 purposively sampled Kwame Nkrumah University of Science and technology (KNUST) College of Health Sciences (CoHS) students. Data was analyzed using descriptive and inferential statistical analyses. Main findings: Compared to the construction groups’ average norm of 101.17 (SD = 9.55), our study participants’ (SPs) BSE attitude was lower (92.51; SD = 11.80). However, using popular mid-point and 3- part attitude scoring methods, our SPs’ attitude scores were comparable to sub-regional and national findings. Moreover,the male participants scored a generally high BSE attitude but significantly lower compared to their female counterparts (p < 0.5). Recommendations: There is the need to adjust the curriculum of all health trainees in developing nations to reflect relevant BC preventive measures. Furthermore, BSE research, education as well as advocacy should involve more males as important BC BSE stake holders.

Purpose: Surgical site infection (SSI) is a significant complication of non-reconstructive and reconstructive breast. This study aimed to assess SSI after breast surgery over 5 years in a single center in Poland. The microorganisms responsible for SSI and their antibiotic susceptibility were determined. Materials/methods: Data of 2129 patients acquired over 5 years postoperatively by the [center] were analyzed. Results: SSI was diagnosed in 132 patients (6.2%) and was an early infection in most cases (65.2%). The incidence of SSI was highest in patients who underwent subcutaneous amputation with simultaneous reconstruction using an artificial prosthesis (14.6%) and breast reconstruction via the TRAM flap method (14.3%). Gram-positive bacteria were responsible for SSI in most cases (72.1%), and these were mainly Staphylococcus strains (53.6%). These strains were 100% susceptible to all beta-lactam antibiotics (except penicillin), but were less susceptible to macrolides and lincosamides. Conclusions: SSI is a serious problem, and attention should be focused on its prevention. Reconstruction using an artificial prosthesis or via the TRAM flap method is connected to increased SSI incidence. Further studies are required to prevent SSI following breast surgery.

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.

Mitochondrial production of 2-hydroxyglutarate (R-2HG) can be catalyzed by wild-type isocitrate dehydrogenase 2 (IDH2) and alcohol dehydrogenase, iron-containing 1 (ADHFE1). We investigated whether biochemical background and substrate concentration in breast cancer cells promote 2HG production. To estimate its role in 2HG production, we analyzed 2HG levels and its enantiomers in breast cancer cells using analytical approaches for metabolomics. By manipulation of mitochondrial substrate fluxes, including glutaminolysis, using genetic and pharmacological approaches we demonstrated the existence of an active competition between 2HG producing enzymes, i.e. IDH2 and ADHFE1. Moreover, we show that distinct fractions of IDH2 enzyme molecules operate in distinct oxido-reductive modes, providing NADPH and producing 2HG simultaneously. We have also detected 2HG release into breast cancer patient´s urine undergoing adjuvant therapy and detected a correlation with stages of breast carcinoma development. In summary, we provide a background for vital mitochondrial production of 2HG in breast cancer cells with outcomes towards cancer biology and possible future diagnosis of breast carcinoma.

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.

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

Gambogic acid, a common traditional Chinese medicine and widely distributed throughout South China, Vietnam, Cambodia, and Thailand. It is prenylated xanthone which is the significant bioactive compound of gamboge. Gambogic acid is known as a strong apoptotic inducer in cancer cells. It has been found as strong anticancer agent against various types of cancer cells lines such as breast cancer, pancreatic, and cervical cancer. It induces apoptosis, down regulates the anti-apoptotic proteins (survivin and BCL2,) and down regulates the activities of P-glycoprotein in drug sensitive human breast MCF-7 and drug-resistant MCF-7/ADR cells. Similarly, it also exerts alteration in P13K, AKT, p21, MMP-2 &-9, and phosphorylated-AKT expressions. The current review highlights the anticancer and chemo-preventive perspectives of gambogic acid and its mechanistic role against human and animal cancers.

An emerging picture in cancer biology is that, paradoxically, chemotherapy can actively induce changes that favor cancer progression. These pro-cancer changes can be either inside (intrinsic) or outside (extrinsic) the cancer cells. In this review, we will discuss the extrinsic pro-cancer effect of chemotherapy; that is, the effect of chemotherapy on the non-cancer host cells to promote cancer progression. We will focus on metastasis, and will first discuss recent data from mouse models of breast cancer. Intriguingly, despite reducing the size of primary tumors, chemotherapy changes the tumor microenvironment, resulting in an increased escape of cancer cells into the blood stream. Furthermore, chemotherapry changes the tissue microenvironment at the distant sites, making it more hospitable to cancer cells upon their arrival. We will then discuss the idea and evidence that these devastating pro-metastatic effects of chemotherapy can be explained in the context of stress response. At the end, we will discuss the potential relevance of these mouse data to human breast cancer and their implication on chemotherapy in the clinic.

Objective: Lipids are secreted into milk as bilayer-coated structures: milk lipid globules (MLGs). Adipophilin (ADRP) and perilipin 3 (TIP47) are associated with MLGs in human breast milk; however, the role of these proteins in milk lipid secretion is not fully understood. The aim of the study was to investigate levels of ADRP, TIP47 and total lipid content in human breast milk, their mutual correlations and dynamics during lactation. Research Methods & Procedures: Milk samples from 22 healthy lactating women (Caucasian, Central European) were collected at five time points during lactation (1–3, 12–14, 29–30, 88–90 and 178–180 days postpartum). Mass spectrometry-based method was used for quantification of ADRP and TIP47 in the samples. The gravimetric method was used to determine milk total lipid content. Results: We observed distinctive trends in ADRP, TIP47 levels and lipid content in human breast milk during the first 6 months of lactation. We also found a significant association between lipid content and ADRP, lipid content and TIP47, and ADRP and TIP47 concentrations in breast milk at all sampling points. Moreover, we derived an equation for estimating the mean lipid content of milk based on ADRP concentration in human breast milk. Conclusions: A mass spectrometry-based method was developed for quantifying ADRP and TIP47 in human breast milk. Strong mutual correlations were found between ADRP, TIP47 and total lipid content in human breast milk.

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

Prevalence of asthma in Australian children is amongst the highest in the world. Although breastfeeding positively influences infants’ immunity, early introduction of Milk Other than Breast Milk (MOTBM) may also play an important role in the development of Asthma. The aim of this study was to investigate the association between the introduction of MOTBM in the first six months after birth and the development of reported persistent asthma in children 3-years old. As sample of 1,121 children were extracted from the Environments for Healthy Living longitudinal birth cohort study. Introduction of MOTBM during the first six months after birth increased the risk of development of persistent asthma by almost two-folds (Adjusted Relative Risk (ARR): 1.71, 95%CI: 1.03-2.83, p= 0.038). This study indicates that the introduction of MOTBM in the first six months of life is a risk factor for asthma incidence among children 3 years old or younger. This result is important in explaining the benefits of breastfeeding as part of public health interventions to encourage mothers to increase breastfeeding initiation and duration and avoid introduction of MOTBM in the first six months after childbirth.

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

Background: 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.

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.

Congenital breast asymmetry represents a particular challenge to the classical techniques of plastic surgery due to a young group of patients. This study compares traditional breast augmentation using silicone implants to the more innovative lipograft technique regarding long-term results. To achieve this, we not only captured subjective parameters like satisfaction with outcome and symmetry, but also objective parameters such as breast volume and anthropometric measurements. Objective examination was performed manually and by using the Vectra® H2 photogrammetry scanning system. Patients who underwent implant augmentation and lipograft both showed no significant differences in patient´s satisfaction with surgical outcome (p = 0.55) and symmetry (p = 0.69). Furthermore, a breast symmetry of 93 % in both groups was reported. Likewise, no statistically significant volume difference between left and right breast was observed in both groups (p<0.41). However, on average, lipograft patients needed 1.3 procedures more until the desired result was achieved. In contrast, patients treated with implant-based breast augmentation usually need several implant changes during their life. In conclusion, both methods should be considered for patients with congenital breast asymmetry.

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.

Immune checkpoint blockade (ICB)-based therapy is revolutionizing cancer treatment by fostering successful immune surveillance and effector cell responses against various types of cancers. However, patients with HER2+ cancers are yet to benefit from this therapeutic strategy. Precisely, several questions regarding the right combination of drugs, drug modality, and effective dose recommendations pertaining to the use of ICB-based therapy for HER2+ patients remain unanswered. In this study, we use a mathematical modeling-based approach to quantify the growth inhibition of HER2+ breast cancer (BC) cell colonies (ZR75) when treated with anti-HER2; trastuzumab (TZ) and anti-PD-1/PD-L1 (BMS-202) agents. Our data show that a combination therapy of TZ and BMS-202 can significantly reduce the viability of ZR75 cells and trigger several morphological changes. The combination decreased the cell’s invasiveness along with altering several key pathways, such as Akt/mTor and ErbB2 compared to monotherapy. In addition, BMS-202 causes dose-dependent growth inhibition of HER2+ BC cell colonies alone, while this effect is significantly improved when used in combination with TZ. Based on the in-vitro monoculture experiments conducted, we argue that BMS-202 can cause tumor growth suppression not only by mediating immune response but also by interfering with the growth signaling pathways of HER2+ BC. Nevertheless, further studies are imperative to substantiate this argument and to uncover the potential crosstalk between PD-1/PD-L1 inhibitors and HER2 growth signaling pathways in breast cancer.

The development of a highly specific drug delivery system (DDS) for anti-cancer therapeutics is an area of intense research focus. Chemical engineering of a “smart” DDS to specifically target tumor cells has gained interest, designed for safer, more efficient, and effective use of chemotherapeutics for the treatment of cancer. However, the selective targeting and choosing the critical cancer surface biomarker are essential for targeted treatments to work. The folic acid receptor alpha (FRalpha) has gained popularity as a potential target in triple-negative breast cancer (TNBC). We have previously reported on a functionalized folic acid (FA)-conjugated amphiphilic alternating copolymer poly(styrene-alt-maleic anhydride) (FA-DABA-SMA) via a biodegradable linker 2,4-diaminobutyric acid (DABA) that has the essential features for efficient “smart” DDS. This biocompatible DDS self-assembles in a pH-dependent manner, providing stimuli-responsive, active targeting, extended-release of hydrophobic chemotherapeutic agents, and can effectively penetrate the inner core of 3-dimensional cancer spheroid models. The empty FA-DABA-SMA decreased spheroid volume, revealing a previously unknown mechanism of action. Upon further investigation, a size- and shape-dependent interaction FA-DABA-SMA with FR reduced the expression of p53, the product of the highly mutated TP53 gene, and additional oncogenic c-Myc and STAT3 proteins. Here, we investigated how this copolymer influences FR behavior and disrupting the receptor’s functions. Results indicate that FA-DABA-SMA increases FR expression levels in breast MDA MB-231 cancer cells and disrupting FR signaling by the reduction in HES1 and NOTCH1 protein expression levels. Also, FA-DABA-SMA induces apoptosis and further causes a change in the morphology of the MDA MB-231 cells, as well as significantly reduces their ability to migrate in a Scratch wound assay. Collectively, these findings provide a novel insight into the functionalized FA-DABA-SMA copolymer. The 350 kDa and 20 kDa copolymers actively target FRα to initialize internationalization. However, only the large size and sheet-shaped 350 kDa copolymers disrupt FRα signaling. The significance of these novel findings reveals the intracellular activity of the copolymer that is critically dependent on the size and structural shape. This report offers novel therapeutic insight into a dual mechanism of FA-DABA-SMA copolymer for its therapeutic potential for the treatment of cancer.

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.

Neutrophil to lymphocyte ratio (NLR) is a promising predictive and prognostic factor in breast cancer. We investigated its ability to predict disease-free survival (DFS) and overall survival (OS) in patients with luminal A or luminal B-HER2-negative breast cancer who received neoadjuvant chemotherapy (NACT). Pre-treatment complete blood cell counts from 168 consecutive patients with luminal breast cancer were evaluated to assess NLR. The study population was stratified into NLRlow or NLRhigh according to a cut-off value established by receiving operator curve (ROC) analysis. Data on additional pre- and post-treatment clinical-pathological characteristics were also collected. Kaplan-Meier curves, log-rank tests, and Cox proportional hazards models were used for statistical analyses. Patients with pre-treatment NLRlow showed a significantly shorter DFS (HR 6.97, 95% CI 1.65-10.55, p= 0.002) and OS (HR 7.79, 95% CI 1.25-15.07, p= 0.021) compared to those with NLRhigh. Non-ductal histology, luminal B subtype, and post-treatment Ki67≥ 14% were also associated with worse DFS (p= 0.016, p= 0.002, and p= 0.001, respectively). In multivariate analysis, luminal B subtype, post-treatment Ki67≥ 14%, and NLRlow remained independent prognostic factors for DFS, while only post-treatment Ki67≥ 14% and NLRlow affected OS. The present study provides evidence that pre-treatment NLRlow helps identify women at higher risk of recurrence and death among patients affected by luminal breast cancer treated with NACT.

Background and Aim: Cancer is a disease characterized by uncontrolled cell growth and invasion of tissues. It seems that personality differences and psychological factors are important factors that lead to different reactions to cancer. Therefore, the main purpose of the present study was to investigate the relationship between type D, stress level of life events, personality traits, and anxiety sensitivity in people with breast cancer attending to Tehran Bu-ali Hospital. Methods: The study was a correlational study in which 100 cancer patients referred to Bu-ali Hospital in Tehran, selected by the available sampling method from April to June 2018. The tools used included the Denollet DS-14 Type D Questionnaire, the Paykel Life events Questionnaire, the Eysenck Personality Questionnaire, the ASI Anxiety Scale, Floyd et al., Data analysis in this study is taken place by using SPSS software, two descriptive levels (percentage, frequency, etc.) and regression. Results: The study results showed that there is a relationship between type D personality with stress of life events, neurosis, extraversion, and psychopath dimensions of personality and anxiety sensitivity in breast cancer patients. Conclusion: Psychological factors play a role in the incidence and exacerbation of breast cancer, and ultimately patients with personality type D and personality traits such as psychosis and high anxiety sensitivity and more stress of life events show more symptoms.

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.

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

Triple-negative breast cancer (TNBC) 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.

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.

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.

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.

Lipid-based drugs are emerging as an interesting class of novel anticancer drugs with the potential to target specific cancer cell metabolic pathway linked to their proliferation and invasiveness. In particular, ω−3 polyunsaturated fatty acids (PUFA) derivatives such as epoxides and their bioisosteres have demonstrated the potential to suppress growth and promote apoptosis in triple-negative human breast cancer cells MDA-MB-231. In this study 16-(4’-chloro-3’-trifluorophenyl)carbamoylamino]hexadecanoic acid (ClFPh-CHA), an anticancer lipid derived from ω−3,17,18-epoxyeicosanoic acid, was formulated as a stable nanoemulsion with size around 150 nm and narrow droplet size distribution (PDI<0.200) through phase-inversion emulsification process followed by high pressure homogenization in view of an oral administration. The ClFPh-CHA-loaded nanoemulsions were able to significantly decrease the relative tumor volume in mice bearing an intramammary tumor xenograft at all doses tested (2.5, 10 and 40 mg/kg) after 32 days of daily oral administration. Furthermore, absolute tumor weight was decreased to 50% of untreated control at 10 and 40 mg/kg, while intraperitoneal administration could achieve a significant reduction only at the highest dose of 40 mg/kg. Results suggest that oral administration of ClFPh-CHA formulated as a nanoemulsion has a sufficient bioavailability to provide an anticancer effect in mice and that the activity is at least equal if not superior to that obtained by a conventional parenteral administration of equivalent doses of the same drug.

Background: transcriptome data provide a valuable resource for the study of cancer molecular mechanisms, but technical biases, samples’ heterogeneity and small sample sizes result in poorly reproducible lists of regulated genes. Additionally, the presence of multiple cellular components contributing to cancer development complicate the interpretation of bulk transcriptomic profiles. Methods: we collected 48 microarray datasets of laser capture microdissected breast tumors, and performed a meta-analysis to identify robust lists of genes differentially expressed in these tumors. We created a database with carefully harmonized metadata to be used as a resource for the research community. Results: combining the results of multiple datasets improved the statistical power, and the analysis of stroma and epithelium separately allows identifying genes with different contribution in each compartment. Conclusions: our database can profitably help biomarkers’ discovery and is readily accessible through a user-friendly web interface (https://aurorasavino.shinyapps.io/metalcm/).

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

Breast 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.

Breast (BC) and gynecological (GC) cancers constitute a group of female neoplasms that has a worldwide significant contribution to cancer morbidity and mortality. Evidence suggests that polymorphisms influencing miRNA function can provide useful information to predict the risk of female neoplasms. To facilitate the genetic screening of miRNA polymorphisms even during childhood or adolescence, and their use as predictors of future malignancies, inconsistent findings in the literature should be detected and resolved. This study represents a comprehensive systematic review and meta-analysis of the association between miRNA polymorphisms and the risk of female neoplasms. Meta-analysis was performed by pooling odds-ratios (ORs) and generalized ORs using a random-effects model for 15 miRNA polymorphisms. The results suggest that miR-146a rs2910164 is implicated in the susceptibility to GC. Moreover, miR-196a2 rs11614913-T had a moderate protective effect against female neoplasms, especially GC, in Asians but not in Caucasians. MiR-27a rs895819-G may pose a protective effect against BC among Caucasians. MiR-499 rs3746444-C may slightly increase the risk of female neoplasms especially BC. MiR-124 rs531564-G may be associated with a lower risk of female neoplasms. The current evidences do not support the association of the remaining polymorphisms and the risk of female neoplasms.

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.

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

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.

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.

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

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.

(1) Background: Mouse-mammary tumor virus (MMTV) might play a role in the etiology of some breast cancers in humans. The purpose of our study was to identify MMTV DNA sequences in breast tissue samples from breast cancer patients operated in our regional center from Romania. (2) Methods: 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. (3) Results: None of the examined samples was positive for MMTV-like target sequences on PCR. (4) Conclusions: We could not prove that MMTV plays a role in the etiology of breast cancer in our patient group. This finding is similar to findings 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 and some parts of Asia.

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.

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.

The epidermal growth factor receptor (EGFR) exon-19 deletion is one of the most common mutations detected in lung cancer patients. Although exon-19 deletion is frequently detected in adenocarcinoma, observing this mutation in germline cells is very rare. Besides, the co-occurrence of homozygous and heterozygous mutations in dual primary cancers in a person is very uncommon. This article presents a 53-year-old Iranian woman with no history of smoking who was diagnose with two primary cancers; invasive ductal carcinoma, and primary pulmonary lung adenocarcinoma. The case reported a history of breast cancer in her sister and a history of lung cancer in her father. To select the best choice of treatment the EGFR gene was analyzed with Sanger’s sequencing method from DNA extracted from the patient’s lung tissue sample. Observing two primary cancers in this patient and considering her family pedigree, germline cells were also analyzed using samples recruited from the patient’s peripheral blood to investigate any EGFR mutations in her germline cells. The obtained data revealed that the lung tissue of the patient carried a homozygous form of EGFR exon-19 deletion while her peripheral blood contained a heterozygous form of this mutation, which is exceptionally rare.

Mammography is often used as the most common laboratory method for the detection of breast cancer, yet associated with the high cost and many side effects. Machine learning prediction as an alternative method has shown promising results. This paper presents a method based on a multilayer fuzzy expert system for the detection of breast cancer using an extreme learning machine (ELM) classification model integrated with radial basis function (RBF) kernel called ELM-RBF, considering the Wisconsin dataset. The performance of the proposed model is further compared with a linear-SVM model. The proposed model outperforms the linear-SVM model with RMSE, R², MAPE equal to 0.1719, 0.9374 and 0.0539, respectively. Furthermore, both models are studied in terms of criteria of accuracy, precision, sensitivity, specificity, validation, true positive rate (TPR), and false-negative rate (FNR). The ELM-RBF model for these criteria presents better performance compared to the SVM model.

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

Inherited mutations in BRCA1 and BRCA2 genes increase risks for breast, ovarian, and other cancers. Both genes encode proteins for accurately repairing chromosome breaks. If mutations inactivate this function, chromosome fragments may not be restored correctly. Resulting chromosome rearrangements can become critical breast cancer drivers. Because I had data from thousands of cancer structural alterations that matched viral infections, I wondered whether infections contribute to chromosome breaks and rearrangements in hereditary breast cancers. There are currently no interventions to prevent chromosome breaks because they are thought to be unavoidable. However, if chromosome breaks come from infections, they can be treated or prevented. I used bioinformatic analyses to test publicly available breast cancer sequence data around chromosome breaks for DNA similarity to all known viruses. Human DNA flanking breakpoints usually had the strongest matches to Epstein-Barr virus (EBV) tumor variants HKHD40 and HKNPC60. Many breakpoints were near sites that anchor EBV genomes, human EBV tumor-like sequences, EBV-associated epigenetic marks, and fragile sites. On chromosome 2, sequences near EBV genome anchor sites accounted for 90% of breakpoints (p<0.0001). On chromosome 4, 51/52 inter-chromosomal breakpoints were close to EBV-like sequences. Five EBV genome anchor sites were near breast cancer breakpoints at precisely defined, disparate gene or LINE locations. Breakpoint flanking regions resembled known EBV-cancers. Twenty-five breakpoints in breast cancers were within 1.25% of EBV cancer breakpoints. In addition to BRCA1 or BRCA2 mutations, all the breast cancers had mutated genes essential for immune responses. Because of this immune compromise, herpes viruses can activate and produce nucleases that break chromosomes. Alternatively, anchored viral episomes can obstruct break repairs, whatever the cause. The results, therefore, imply proactive treatment and prevention of herpes viral infections may prevent some chromosome breaks and benefit BRCA mutation carriers.

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.

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.

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.

Inherited mutations in BRCA1 and BRCA2 genes increase risks for breast, ovarian, and other cancers. Both genes encode proteins for accurately repairing chromosome breaks. If mutations inactivate this function, broken chromosomes may not be restored correctly, allowing breaks to persist or rearrange chromosomes. These abnormalities are potentially catastrophic events that can originate from viral infections. I used bioinformatic analyses of publicly available breast cancer patient data to show that the distribution of chromosome breaks in hereditary breast cancers differs markedly from sporadic breast cancers. Then I tested hereditary breast cancer sequence data around chromosome breaks for DNA similarity to all known viruses. Human DNA flanking breakpoints usually had decisive matches to Epstein-Barr virus (EBV / HHV4) tumor variants HKHD40 and HKNPC60. Many breakpoints were near EBV genome anchor sites, human EBV tumor-like sequences, EBV-associated epigenetic marks, and some fragile sites. On chromosomes 2 and 12, sequences near EBV genome anchor sites accounted for 90% and 88% of breakpoints (p<0.0001), respectively. On chromosome 4, 51/52 inter-chromosomal breakpoints were close to EBV-like sequences in 19 hereditary breast cancers. In contrast, 19 sporadic breast cancers only had 12 interchromosomal breakpoint regions on chromosome 4 near EBV-like sequences. On various other chromosomes, five EBV genome anchor sites were near hereditary breast cancer breakpoints at precisely defined, disparate gene or LINE locations. Independent evidence further implicating EBV in hereditary breast cancer breakpoints is that 25 breast cancer break positions are within 1.25% of breakpoints in model EBV cancers. In addition to BRCA1 or BRCA2 mutations, all the hereditary breast cancers had mutated genes essential for immune responses. This compromise facilitates reactivation of herpes viruses which produce nucleases capable of breaking chromosomes. EBV also causes other deleterious effects: anchored EBV episomes can interfere with normal replication and obstruct DNA break repairs; even very early infection causes massive transcription changes. The results, therefore, imply proactive treatment and prevention of herpes viral infections may prevent some chromosome breaks and benefit BRCA mutation carriers.

Objective: Radiomics and deep transfer learning are two popular technologies used to develop computer-aided detection and diadnosis (CAD) schemes of medical images. This study aims to investigate and compare advantages and potential limitations of applying these two technologies in developing CAD schemes. Methods: A relatively large and diverse retrospective dataset including 3,000 digital mammograms is assembled in which 1,496 images depict malignant lesions and 1,054 images depict benign lesions. Two CAD schemes are developed to classify breast lesions. The first scheme is developed using four steps namely, applying an adaptive multi-layer topographic region growing algorithm to segment lesions, computing initial radiomics features, applying a principal component algorithm to generate an optimal feature vector, and building a support vector machine classifier. The second CAD scheme is built based a pre-trained residual net architecture (ResNet50) as a transfer learning model to classify breast lesions. Both CAD schemes are trained and tested using a 10-fold cross-validation method. Several score fusion methods are also investigated to classify breast lesions. CAD classification performance is evaluated by the area under ROC curve (AUC). Results: ResNet50 model-based CAD scheme yields AUC = 0.85±0.02, which is significantly higher than radiomics feature-based CAD scheme with AUC = 0.77±0.02 (p < 0.01). Additionally, fusion of classification scores generated by two CAD schemes does not further improve classification performance. Conclusion: This study indicates that using deep transfer learning is more efficient to develop CAD schemes and enables to yield higher lesion classification performance than CAD schemes developed using radiomics-based technology.

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.

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.

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.

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.

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.

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.

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.

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

A developed six-port reflectometry (SPR) system was integrated to measure the relative permittivity of tumor and normal breast tissue for medical diagnostic purpose. In order to obtain an accurate and precise measurement, the calibration process was done to the SPR using the well-known three-standard technique. Next, the studied dielectric probe was connected to the calibrated measurement-port of the SPR. The open end of the probe aperture was dibbed into the normal and tumor synthetic breast tissue samples to measure the synthetic breast tissues dielectric constant, ɛrʹ, and loss factor, ɛrʺ in the frequency range of 1.5 GHz to 3.3 GHz. Finally, the comparative studies were conducted between commercial VNA with Keysight 85070E dielectric probe and the studied SPR-probe system based on the measured magnitude of the reflection coefficient, phase shift, dielectric constant, and loss factor of the synthetic breast samples. The maximum absolute errors of the measured reflection coefficient magnitude, phase shift, dielectric constant, and loss factor were found to be 0.01, 1.07°, 1.12, and 0.75, respectively. It was ascertained that the predicted dielectric constant, ɛrʹ, is able to differentiate between normal, (ɛrʹ &lt; 50) and tumor, (ɛrʹ &gt; 50) breast tissues.

To gain new insights into the potential of mother-to-child transmission of Zika virus (ZIKV) through breast milk or breastfeeding practices, we systematically searched regional and international databases and screened 1,658 non-duplicate records describing women with suspected or confirmed ZIKV infection, intending to breastfeed or give breast milk to an infant. Fourteen studies met our inclusion criteria and inform this analysis. These studies reported on 97 mother-children pairs who provided breast milk for ZIKV assessment. Seventeen breast milk samples from different women were found positive for ZIKV via RT-PCR, and ZIKV replication was found in cell cultures from five out of seven breast milk samples from different women. Only three out of six infants who had ZIKV infection were breastfed, no evidence of clinical complications were found to be associated with ZIKV RNA in breast milk. This review updates our previous report by synthesizing the evidence from 12 new articles and we find no evidence of mother-to-child transmission through breast milk intake or breastfeeding. As the certainty of the present evidence is low, additional studies are still warranted to completely understand any potential of transmission of ZIKV through breastfeeding.

(1) Background: Considering highly selected patients with ductal carcinoma in situ (DCIS), active surveillance is a valid alternative to surgery. Our study is aimed at showing the reliability of post-biopsy complete lesion removal, documented by mammogram, as additional criterion to select these patients. (2) Methods: 2173 Vacuum Assisted Breast Biopsies (VABB) documented as DCIS have been reviewed. Surgery has been performed in all cases. We retrospectively collected the reports of post-VABB complete lesion removal and the histological results of the biopsy and surgery. We calculated the rate of upgrade of DCIS identified on VABB upon excision for patients with post-biopsy complete lesion removal and for those showing residual lesion. (3) Results: We observed 2173 cases of DCIS: 408 classified as low grade; 1262 as intermediate grade; 503 as high grade. The overall upgrading rate to invasive carcinoma was 15.2% (330/2173). The upgrade rate was significantly lower (8.2%) when considering patients showing mammographically documented complete removal of the lesion. (4) Conclusion: The absence of mammographically documented residual lesion following VABB is associated to a lower upgrading rate of DCIS to invasive carcinoma on surgical excision and should be considered when deciding the proper management DCIS diagnosis.

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.

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: 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 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.

Patients with metastatic triple negative breast cancer (TNBC) need new therapies to improve the low survival rates achieved with standard treatments. In this work, we show that the survival of mice with metastatic TNBC can be markedly increased by replacing their normal diet with artificial diets in which the levels of amino acids (AAs) and lipids are strongly manipulated. After observing selective anticancer activity in vitro, we prepared five artificial diets and evaluated their anticancer activity in a challenging model of metastatic TNBC. The model was established by injecting 4T1 murine TNBC cells into the tail vein of immunocompetent BALB/cAnNRj mice. First-line drugs doxorubicin and capecitabine were used as positive controls. AA manipulation led to modest improvements in mice survival when the levels or lipids were normal. Reducing lipid levels to 1% markedly improved the activity of several diets with different AA content. Mice fed the artificial diets as monotherapy lived longer than mice treated with doxorubicin and capecitabine. An artificial diet without 10 non-essential AAs, with reduced levels of essential AAs, and with 1% lipids improved the survival not only of mice with TNBC but also of mice with other types of metastatic cancers.

The main objective of this work was to evaluate the application of individual and ensemble machine learning models to classify malignant and benign breast masses using features from two-dimensional (2D) correlated spectroscopy spectra extracted from five-dimensional Echo Planar-Correlated Spectroscopic Imaging (5D EP-COSI) and Diffusion-weighted imaging (DWI). Twenty-four different metabolite and lipid ratios with respect to 2D diagonal peaks at 1.4ppm and 5.4ppm, and water from one-dimensional non-water-suppressed (NWS) spectra were used as the features. Additionally, water fraction, fat fraction and water-to-fat ratios from NWS spectra and apparent diffusion coefficients (ADC) from DWI were included. Nine most important features were identified using recursive feature elimination. XGBoost (AUC:93.0%, Accuracy:85.7%, F1-score:87.6%), GradientBoost (AUC:94.4%, Accuracy:87.0%, F1-score:89.4%), CatBoost (AUC:95.2%, Accuracy:86.9%, F1-score:88.4%) and RandomForest (AUC:92.2%, Accuracy:85.3%, F1-score:87.6%) were the best performing models. While the conventional biomarkers like choline, myo-Inositol, and glycine were statistically significant predictors, the key features contributing to the classification were ADC, 2D diagonal peaks at 0.9ppm, 2.1ppm and 2.3ppm, cross peaks between 1.4 and 0.9ppm, 4.3 and 4.1ppm, 2.1 and 1.4ppm and the triglyceryl-fat cross peak. The results highlight the contribution of the 2D spectral peaks to the model, and they demonstrate the potential of 5D EP-COSI for early breast cancer detection.

Connexin 43 (Cx43) forms gap junctions that mediate the direct intercellular diffusion of ions and small molecules between adjacent cells. Cx43 displays both pro- and anti-tumorigenic properties, but the mechanisms underlying these characteristics are not fully understood. Tunneling nanotubes (TNTs) are long and thin membrane projections that connect cells, facilitating the exchange of not only small molecules, but also larger proteins, organelles, bacteria, and viruses. Typically, TNTs exhibit increased formation under conditions of cellular stress and are more prominent in cancer cells, where they are generally thought to be pro-metastatic and to provide growth and survival advantages. Cx43 has been described in TNTs, where it is thought to regulate small molecule diffusion through gap junctions. Here, we developed a high-fidelity CRISPR/Cas9 system to knockout (KO) Cx43. We found that loss of Cx43 expression was associated with significantly reduced TNT length and number in breast cancer cell lines. Notably, secreted factors present in conditioned medium stimulated TNTs more potently when derived from Cx43-expressing cells than from KO cells. Moreover, TNT formation was significantly induced by inhibition of several key cancer signaling pathways that both regulate Cx43 and are regulated by Cx43, including RhoA kinase (ROCK), protein kinase A (PKA), focal adhesion kinase (FAK), and p38. Intriguingly, drug-induced stimulation of TNTs was more potent in Cx43 KO cells than in wild-type cells. In conclusion, this work describes a novel non-canonical role for Cx43 in regulating TNTs, identifies key cancer signaling pathways that regulate TNTs in this setting, and provides mechanistic insight into a pro-tumorigenic role of Cx43 in cancer.

TomoBreast hypothesized that hypofractionated 15 fractions/3 weeks image-guided radiation therapy (H-IGRT) can reduce lung-heart toxicity, as compared with normofractionated 25-33 fractions/5-7 weeks conventional radiation therapy (CRT). 123 women with stage I-II operated breast cancer were randomized to receive CRT (N=64) or H-IGRT (N=59). The primary endpoint used a four-items measure of the time to 10% alteration in any of patient self-reported measure, physician clinical evaluation, echocardiography or lung function tests, analyzed by intention-to-treat without exclusion. Results found comparable survivals, but H-IGRT significantly reduced the toxicity measured by lung diffusion capacity and alveolar volume as compared with CRT, G1 in 53% (31/59) versus 72% (44/61) patients, P=0.006; G2, 29% versus 48%, P=0.020. H-IGRT significantly reduced the risk of composite cardio-pulmonary alteration at 5 years, 10.2% versus 26.7%, P=0.024. In conclusion, TomoBreast is a proof-of-concept that image-guided radiation-therapy can improve the overall balance of lung-heart outcomes in breast cancer adjuvant therapy. Furthermore, the significance of the findings supports the efficacy of a small trial size design, which can be critical when clinical research resources are limited.

Circulating tumor cells (CTCs) in the peripheral blood are the precursors to distant metastasis but the underlying mechanisms are poorly understood. This study aims at understanding the molecular features within CTCs in relation to their metastatic potential. Using in vitro CTC models, in which breast cancer cell lines are cultured in non-adherent conditions simulating the microenvironment in the blood stream, we found that suspension culture resulted in resistance to TNF-related apoptosis inducing ligand (TRAIL)-mediated cell death. Such a resistance was directly correlated with a reduction in surface and total levels of DR5 protein. In the non-adherent state, cells underwent rapid autophagic flux characterized by an accumulation of autophagosome organelles. Notably, DR5 was translocated to autophagosomes and underwent lysosomal degradation. Our data suggest that CTCs may evade TNF cytokine mediated immune surveillance through downregulation of DR expression. The data warrants further studies in cancer patients to find the status of DRs and other molecular features within primary CTCs in relation to disease progression or chemoresistance.

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

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.

Purpose: Recently introduced molecules namely long non-coding RNAs (lncRNAs) are associated with various diseases, including breast cancer, and they may have the potential to act as biomarkers. Invasive ductal carcinoma (IDC) is a frequently observed type of breast cancer that diagnosis through immunohistochemical methods. However, no reliable non-invasive markers such as circulating markers have been introduced for it, so far. Materials and methods: The relative quantitation (RQ) of two lncRNAs, RP11-445H22.4 and TINCR, was measured in tumoral tissues and paired adjacent non-tumoral tissues (PANTs) as well as in plasma samples using real-time polymerase chain reaction (RT-PCR). Furthermore, promoter methylation of the two lncRNAs genes was assessed using methylation-specific PCR (MSP). In order to compare the diagnostic values, plasma levels of CA 15-3 were measured as a conventional circulating biomarker using ELISA. The receiver operating characteristic (ROC) curve was used to illustrate the sensitivity and specificity of the potential biomarkers. Results: The RP11-445H22.4 and TINCR genes were upregulated in tumor tissues compared to PANTs (RQ_{RP11-445H22.4} = 2.7, RQ_TINCR = 4.4). Furthermore, the presence of RP11-445H22.4 and TINCR in the plasma of patients was significantly more than healthy controls (RQ_{c.RP11-445H22.4} = 4.12, RQ_c.TINCR = 4.16, P<0.001). The promoters of RP11-445H22.4 and TINCR genes were hypomethylated in the tumoral tissues with a negative correlation with their gene expression. Conclusion: Based on the findings, it can be speculated that the expression levels of these two lncRNAs as well as their promoter methylation can be considered as a therapeutic target and potential biomarker for breast carcinoma.

Breast cancer is among the most common and fatal diseases for women, and no permanent treatment has been discovered. Thus, early detection is a crucial step to control and cure breast cancer that can save the lives of millions of women. For example, in 2020, more than 65% of breast cancer patients were diagnosed in early-stage of cancer, from whom all survived cancer. Although early detection is the most effective approach for cancer treatment, breast cancer screening conducted by radiologists is very expensive and time-consuming. More importantly, conventional methods of analyzing breast cancer images suffer from high false detection rates. Different breast cancer imaging modalities are used to extract and analyze the key features affecting diagnosis and treatment of breast cancer. These imaging modalities can be divided into subgroups such as mammograms, ultrasound, magnetic resonance imaging, histopathological images, or any combination of them. Radiologists or pathologists analyze images produced by these methods manually that leads to increase the risk of wrong decisions for cancer detection. Thus, utilization of new automatic methods to analyze all kinds of breast screening images to assist radiologists to interpret images is required. Recently, artificial intelligence (AI) has been widely utilized to automatically improve the early detection and treatment of different types of cancer, specifically breast cancer, thereby enhancing the survival chance of patients. Advances in AI algorithms, such as deep learning, and availability of datasets obtained from various imaging modalities have opened an opportunity to surpass limitations of current breast cancer analysis methods. In this article, we first review breast cancer imaging modalities, and their strengths and limitations. Then, we explore and summarize the most recent studies that employed AI in breast cancer detection using various breast imaging modalities. In addition, we report available datasets on the breast cancer imaging modalities which are important in developing AI-based algorithms and training deep learning models. In conclusion, this review paper tries to provide a comprehensive resource to help researchers working in breast cancer imaging analysis.

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.

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.

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.

Triple-negative breast cancer (TNBC) is characterized by an active immune response. We evalu-ated intratumoral interrelation between FOXP3+ tumor-infiltrating lymphocytes and other cy-tokines in TNBC. Network analysis refined cytokines significantly correlate with FOPX3 in TNBC. Treatment response and prognosis imformation of patients and survival data from the TGCA and METABRIC databases were analyzed according to refined cytokines. Interleukin (IL)-33 was sig-nificantly expressed by TNBC cell lines than luminal cell lines (log2 fold change: 5.31, p <0.001) and IL-33 and TGFB2 showed a strong correlation with FOXP3 in the TNBC cell line. Immunohisto-chemistry demonstrated IL-33 high group was a significant predictor of complete response of neoadjuvant chemotherapy (odds ratio (OR) 4.12, p<0.05) and a favorable survival compared to IL-33 low group (OR 6.48, p<0.05) in TNBC. Survival data from TGCA and METABRIC revealed that FOXP3 was a significantly favorable marker in IL-33 high group com-pared to the low IL-33 low group (hazard ratio (HR) 2.1, p=0.02), and IL-33 high/TGFB2 high subgroup showed significant favorable prognosis in the FOXP3 high group compared to the FOPX3 low group in TNBC (HR 3.5, p=0.01). IL-33 and TGFB2 were key cytokines of intratumoral interrelation among FOXP3 in TNBC.

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.

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.

Background: Human epidermal growth factor receptor 2 (HER-2) overexpression can be found in 15-20% of breast cancers, and it strongly correlates with aggressive clinical behavior and adverse prognosis. The first-line treatment for HER-2 positive metastatic breast cancers is the combination of trastuzumab, pertuzumab, and taxane (PTH). ABP 980 is a biosimilar of the innovator trastuzumab and is characterized by highly comparable effectiveness. Methods: The group of 61 patients with HER-2 positive MBC received biosimilar ABP 980 plus pertuzumab and docetaxel from November, 18, 2018 to December, 24, 2019. The response to therapy, overall survival (OS), progression-free survival (PFS), metastases, and adverse effects among patients were determined and analyzed. Results: Initially, 42 women responded partially to the treatment and their median PFS was 27 months. Median PFS for the whole group was 18 months. Cardiotoxicity of treatment was noticed in all patients in the form of the reduction in left ventricular ejection fraction but only in 2 cases, it was the reason for withdrawing from therapy. Conclusion: Biosimilar ABP 980 is registered in the same indications as the innovator trastuzumab and their effectiveness, as well as side effects, are comparable. The costs of biosimilar make the therapy more accessible and thus more patients with MBC around the world can receive relevant treatment.

The association between autoimmune diseases, mostly rheumatoid arthritis, systemic lupus erythematous, celiac disease and Sjögren syndrome, and lymphoma has been widely demonstrated by several epidemiologic studies. By a not yet entirely elucidated mechanism, chronic activation/stimulation of the immune system, along with the administration of specific treatments, may lead to persistent stimulation of both of B- and T-cells, and to the onset of different types of lymphoma in such patients. Specifically, patients affected by may develop lymphomas may years after the original diagnosis. Several epidemiologic, hematologic and histological factors may anticipate the progression from Sjögren syndrome into lymphoma but, to the best of our knowledge, a definite pathogenetic mechanism for such progression is still missing. In fact, while the association between Sjögren syndrome and non-Hodgkin lymphoma, mostly diffuse large B-cell and extranodal marginal zone lymphomas is well established, many other variables, such as time of onset, gender predilection, sites of occurrence, subtype of lymphoma and predictive factors still remain unclear. We report on a rare case of primary breast lymphoma occurring three years after the diagnosis of Sjögren syndrome in a 57 y.o. patient. The diagnostic work-up, including radiograms, core needle biopsy and histological examination are discussed, along with emerging data from the recent literature, thus highlighting the usefulness of breast surveillance in Sjögren syndrome patients.

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

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

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.

Noninvasive and portable diagnoses via angle-resolved coherent spectral data are presented. ACTIRS (Angle- resolved coherent tomographic IR spectroscopy) through angle-coherent return spectra from photonic quantum ring laser of whispering gallery modes, which is not photocurrent-converted after the cortical, vascular or muscular diffuse paths, can be a new method for brain/heart studies. Also it will be eligible for frequent do-it-yourself diagnoses of breast cancer before hospital visits. The unique angle-coherent multi-spectra will eventually lead to study ionic or protein contents of cranial, arterial or lactiferous ducts that have been obtained only from uncomfortable biopsy, NMR, CT or mammography. The spectral data can be spatially or temporally improved and correlated for extracting more meaningful diagnostic conclusions

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.

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

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.

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

Background: We aimed to create a model of radiological and pathological criteria able to predict the upgrade rate of low-grade ductal carcinoma in situ (DCIS) to invasive carcinoma, in patients undergoing vacuum-assisted breast biopsy (VABB) and subsequent surgical excision. Methods: 3100 VABBs were retrospectively reviewed among which we reported 295 low-grade DCIS who subsequently underwent surgery. The association between patients’ features and the upgrade rate to invasive breast cancer (IBC) was evaluated by univariate analysis. Finally, we developed a predictive multivariable model based on the features which were significantly associated with the univariate analysis outcome. Results: the upgrade rate to invasive carcinoma was 10.8 %. At univariate analysis, the risk of upgrade was significantly lower in the absence of post- biopsy residual lesion (p<0.001), age > 50 (p=0.029), and in presence of low-grade DCIS only in specimens with microcalcifications (p=0.002). According to the final multivariable model, the predicted probability of diagnostic underestimation for a patient with all the three favourable features selected at univariate analysis was 1% (95% CI: 0.3%-4%). Conclusions: An easy to use predictive model of radiological and pathological criteria is able to identify patients with low-grade carcinoma in situ with low risk of upstaging to infiltrating carcinomas.

Breast Cancer metastasis remains a formidable challenge in cancer research, contributing significantly to patient mortality despite advances in medical research. Lung metastasis, associated with breast cancer, poses an ongoing clinical dilemma with limited curative treatment options. This study delves into the intricate mechanisms underlying Breast Cancer-Lung Metastasis (BC-LM) primarily focusing on the function of SH3PXD2B in maturation of invadopodia, inducing epithelial-to-mesenchymal transition, disruption of proteostasis network, and ultimately leading to metastasis of Breast Cancer (BC) cells. With an extensive analysis of differential gene expression using RNASeq data, comparing normal breast cancer cells to metastatic sub-populations in lung. Employing the New Tuxedo pipeline our investigation notably observes SH3PXD2B as a key regulator in lung metastasis samples. This trend is further substantiated by data from the Cancer Cell Line Encyclopedia (CCLE), and Human Protein Atlas (HPA) which highlights elevated SH3PXD2B expression in MDA-MB-468 cells, underscoring its significance in metastatic adenocarcinoma. Additionally, we checked the overall survival (OS) of metastatic breast cancer (MBC) patients pinpointing SH3PXD2B and its associated partners like SH3PXD2A, MMPs, CTTN, ADAMs, and EMT markers with substantial expression in both BC and lung cancer, prognosticating poorer patient survival. Further, our transcription factor – target gene (TFTG) network essentially elucidated the role of SH3PXD2B as a key node in the network unveiling its roles in regulating cell migration, communication, and developmental processes. Proteomics and Western blotting assays consistently confirm heightened SH3PXD2B expression in BC cell lines, reaffirming our findings. By employing computational structure biology along with cancer systems biology approach, we generated a high-confidence structural model of SH3PXD2B, indicating its SH3_2 and SH3_3 domains crucial for interactions with the drug molecules. Molecular docking simulations identify Eribulin as a promising therapeutic agent capable of targeting these domains. Thus, our multidisciplinary approach seamlessly amalgamates systems medicine principles, aiming to repurpose existing drugs that target SH3PXD2B based on molecular signatures. Targeted therapies have emerged as a promising avenue for addressing MBC and this mechanistic model introduces novel therapeutic avenues for the treatment of BC-LM patients.

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.

The botanical species Ceratonia siliqua L., commonly referred to as the Carob tree, and locally as “L’Kharrûb”, holds significance as an agro-sylvo-pastoral species, and is traditionally utilized in Morocco for treating a variety of ailments. This current investigation aims to ascertain the antioxidant, antimicrobial, and cytotoxic properties of the ethanolic extract of C. siliqua leaves (CSEE). Initially, we analyzed the chemical composition of CSEE through high-performance liquid chromatography with Diode-Array Detection (HPLC-DAD). Subsequently, we conducted various assessments, including DPPH scavenging capacity, β-carotene bleaching assay, ABTS scavenging, and total antioxidant capacity assays, to evaluate the antioxidant activity of the extract. In this study, we investigated the antimicrobial properties of CSEE against five bacterial strains (two gram-positive, Staphylococcus aureus, and Enterococcus faecalis; and three gram-negative bacteria, Escherichia coli, Escherichia vekanda, and Pseudomonas aeruginosa) and two fungi (Candida albicans, and Geotrichum candidum). Additionally, we evaluated the cytotoxicity of CSEE on three human breast cancer cell lines (MCF-7, MDA-MB-231, and MDA-MB-436) and assessed the potential genotoxicity of the extract using the comet assay. Through HPLC-DAD analysis, we determined that phenolic acids and flavonoids were the primary constituents of the CSEE extract. The results of the DPPH test indicated a potent scavenging capacity of the extract with an IC50 of 302.78 ± 7.55 µg/mL, which was comparable to that of ascorbic acid with an IC50 of 260.24 ± 6.45 µg/mL. Similarly, the β-carotene test demonstrated an IC50 of 352.06 ± 12.16 µg/mL, signifying the extract's potential to inhibit oxidative damage. The ABTS assay revealed IC50 values of 48.13 ± 3.66 TE µmol/mL, indicating a strong ability of CSEE to scavenge ABTS radicals, and the TAC assay demonstrated an IC50 value of 165 ± 7.66 µg AAE/mg. The results suggest that the CSEE extract had potent antioxidant activity. Regarding its antimicrobial activity, the CSEE extract was effective against all five tested bacterial strains, indicating its broad-spectrum antibacterial properties. However, it only showed moderate activity against the two tested fungal strains, suggesting it may not be as effective against fungi. The CSEE exhibited a noteworthy dose-dependent inhibitory activity against all the tested tumor cell lines in vitro. The extract did not induce DNA damage at the concentrations of 6.25, 12.5, 25, and 50 µg/ml, as assessed by the comet assay. However, the 100 µg/ml concentration of CSEE resulted in a significant genotoxic effect compared to the negative control. A computational analysis was conducted to determine the physicochemical and pharmacokinetic characteristics of the constituent molecules present in the extract. The Prediction of Activity Spectra of Substances (PASS) test was employed to forecast the potential biological activities of these molecules. Additionally, the toxicity of the molecules was evaluated using the Protox II webserver.

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.

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.

Abstract Background and Objective: Medical Microwave Radiometry (MWR) is used to capture the thermal properties of internal tissues and has usages in breast cancer detection. Our goal in this paper is to improve classification performance and investigate automated neural architecture search methods. Methods: We investigate optimizing the weights of a weight agnostic neural network using bi-population covariance matrix adaptation evolution strategy (BIPOP-CMA-ES) once the topology is found. We compare it against a weight agnostic and cascade correlation neural network. Results: The experiments are conducted on a breast cancer dataset of 4912 patients. Our proposed weight agnostic BIPOP-CMA-ES model achieved the best performance. It obtained an F1-score of 0.9225, accuracy of 0.9219, precision of 0.9228, recall of 0.9217 and topology of 153 connections. Conclusions: The results are an indication of the potential of MWR utilizing a neural network-based diagnostic tool for cancer detection. By separating the tasks of topology search and weight training, we are able to improve the overall performance.

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.

Endophytic fungi are a diverse group of microorganisms that colonize the inter- or intracellular spaces of plants for mutual benefits. The interactions with a host plant and other microbiomes are multidimensional and play a crucial role in the production of secondary metabolites. We screened bioactive compounds present in the extracts of Aspergillus flavus, an endophytic fungus isolated from the roots of the medicinal grass Cynodon dactylon, for its anticancer potential. Ethyl acetate extract from isolated A. flavus showed significant cytostatic effects (IC50: 16.25 μg mL−1) against breast cancer cells (MCF-7). Morphology of cells and DAPI stained nuclei along with the results of flow cytometry annexin V/PI assay suggested apoptosis to be the main process leading to cells’ death. While investigating the mechanism that triggers apoptosis, we found that the extract of A. flavus increased ROS generation and caused loss of mitochondrial membrane potential of MCF-7 cells. To identify the metabolites that might be responsible for the anticancer effect, the extract was examined using gas chromatography-mass spectrometry (GC-MS). Interestingly, nine phytochemicals were found to have potential inhibitory effects of anti-apoptotic protein (Bcl-2) in the breast cancer cells. In the in silico molecular docking and molecular dynamics simulation studies revealed that two compounds: 2,4,7-Trinitrofluorenone and 3alpha, 5alpha-Cyclo-ergosta-7,9(11),22t-triene-6beta-ol exhibited significant binding affinities (-9.20, and -9.50 Kcal mol-1, respectively) against Bcl-2 along with binding stability and intermolecular interactions of its ligand-Bcl-2 complexes. Overall, the study found that the endophytic A. flavus from C. dactylon contains plant-like bioactive compounds that have a promising effect in breast cancer.