Search results for: women with breast cancer

Authors: Naif Al-Jomah, Falah H Al-Mohanna, Abdelilah Aboussekhra

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Active breast cancer-associated fibroblasts (CAFs), the most influential cells in breast tumor microenvironment, express/secrete high levels of the proinvasive/metastatic interleukin-6 (IL-6). Therefore, we have tested here the effect of the IL-6 receptor (IL-6R) inhibitor tocilizumab (TCZ; Actemra) on different active breast CAFs. We have shown that TCZ potently and persistently suppresses the expression of various CAF biomarkers, namely α-SMA, SDF-1 as well as the STAT3 pathway and its downstream target AUF1. TCZ also inhibited the proliferation, migration and invasion abilities of active breast CAF cells. Additionally, TCZ repressed the ability of CAF cells in promoting epithelial-to-mesenchymal transition, and enhancing the migratory/invasive and proliferative capacities of breast cancer cells in vitro. Importantly, these findings were confirmed in orthotopic humanized breast tumors in mice. Furthermore, TCZ suppressed the expression of the pro-angiogenic factor VEGF-A and its transactivator HIF-1α in CAF cells, and consequently inhibited the angiogenic-promoting effect of active CAFs both in vitro and in orthotopic tumor xenografts. These results indicate that inhibition of the IL-6/STAT3/AUF1 pathway by TCZ can normalize active breast CAFs and suppress their paracrine pro-carcinogenic effects, which paves the way toward development of specific CAF-targeting therapy, badly needed for more efficient breast cancer treatments.

Keywords: angiogenesis, interleukin-6, paracrine, cancer-associated fibroblasts

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Authors: Vandana Gawande, Chandani Satija

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Gnidia glauca is a semi-woody herb of thymelaeaceae family traditionally used as fish poison in India. It is also found in Sri lanka and Africa. In the present study, potential anticancer effect of n-hexane and ethanolic extracts of Gnidia glauca in human breast cancer cells was investigated. Human breast cancer cells (MCF-7) were cultured as monolayers in RPMI 1640 medium. The cells were cultured for 48 hours to allow growth and achieve about 80% confluence in 96-well culture plates. The cells were treated with various concentrations of Gnidia glauca (0.1-100 mg/mL) for 72 hours. Percentage of viable cells after treatment was assessed using a sulforhodamine B colorimetric assay. Both n-hexane and ethanolic extract showed significant cytotoxic activity on MCF-7 cancer cells. This study supports the notion of using Gnidia glauca as a novel anticancer agent for breast cancer.

Keywords: 96 well plate, anticancer activity, Gnidia glauca, MCF-7

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Authors: Zahra Khalid, Gul Muhammad Khan, Arbab Masood Ahmad

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Cartesian Genetic Programming (CGP) is explored to design an optimal circuit capable of early stage breast cancer detection. CGP is used to evolve simple multiplexer circuits for detection of malignancy in the Fine Needle Aspiration (FNA) samples of breast. The data set used is extracted from Wisconsins Breast Cancer Database (WBCD). A range of experiments were performed, each with different set of network parameters. The best evolved network detected malignancy with an accuracy of 99.14%, which is higher than that produced with most of the contemporary non-linear techniques that are computational expensive than the proposed system. The evolved network comprises of simple multiplexers and can be implemented easily in hardware without any further complications or inaccuracy, being the digital circuit.

Keywords: breast cancer detection, cartesian genetic programming, evolvable hardware, fine needle aspiration

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Authors: Cuneyt Yucelbas, Seral Ozsen, Sule Yucelbas, Gulay Tezel

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Due to the fact that there exist only a small number of complex systems in artificial immune system (AIS) that work out nonlinear problems, nonlinear AIS approaches, among the well-known solution techniques, need to be developed. Gaussian function is usually used as similarity estimation in classification problems and pattern recognition. In this study, diagnosis of breast cancer, the second type of the most widespread cancer in women, was performed with different distance calculation functions that euclidean, gaussian and gaussian-euclidean hybrid function in the clonal selection model of classical AIS on Wisconsin Breast Cancer Dataset (WBCD), which was taken from the University of California, Irvine Machine-Learning Repository. We used 3-fold cross validation method to train and test the dataset. According to the results, the maximum test classification accuracy was reported as 97.35% by using of gaussian-euclidean hybrid function for fold-3. Also, mean of test classification accuracies for all of functions were obtained as 94.78%, 94.45% and 95.31% with use of euclidean, gaussian and gaussian-euclidean, respectively. With these results, gaussian-euclidean hybrid function seems to be a potential distance calculation method, and it may be considered as an alternative distance calculation method for hard nonlinear classification problems.

Keywords: artificial immune system, breast cancer diagnosis, Euclidean function, Gaussian function

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Authors: M. Mousavi-Daramoroudi, H. Yousefnia, F. Abbasi-Davani, S. Zolghadri, S. Kakaei

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Despite the appropriate characteristics of ¹⁷⁷Lu and DOTATOC, to our best knowledge, the therapeutic benefit of ¹⁷⁷Lu-DOTATOC complex in breast cancer has not been reported until now. In this study, biodistribution of ¹⁷⁷Lu-DOTA-TOC in mouse tumor model for evaluation of possible utilization of this complex in breast cancer treatment was investigated.¹⁷⁷Lu was prepared with the specific activity of 2.6-3 GBq.mg^-1 and radionuclidic purity higher than 99%. The radiolabeled complex was prepared in the optimized conditions with the radiochemical purity higher than 99%. The final solution was injected to the BALB/c mice with adenocarcinoma breast cancer. The biodistribution results showed major accumulation in the kidneys as the major excretion route and the somatostatin receptor-positive tissues such as pancreas compared with the other tissues. Also, significant uptake was observed in tumor even in longer time after injection. According to the results obtained in this research study, somatostatin receptors expressed in breast cancers can be targeted with DOTATOC analogues especially with ¹⁷⁷Lu-DOTATOC as an ideal therapeutic agent.

Keywords: ¹⁷⁷Lu, adenocarcinoma breast cancer, DOTATOC, BALB/c mice

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Authors: Nandhana Vivek, Bhaskar Gogoi, Ayyavu Mahesh

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Breast cancer metastasis plays a key role in cancer progression and fatality. The present study examines the potential causes of metastasis in breast cancer by investigating the novel interactions between genes and their pathways. The gene expression profile of GSE99394, GSE1246464, and GSE103865 was downloaded from the GEO data repository to analyze the differentially expressed genes (DEGs). Protein-protein interactions, target factor interactions, pathways and gene relationships, and functional enrichment networks were investigated. The proliferation pathway was shown to be highly expressed in breast cancer progression and metastasis in all three datasets. Gene Ontology analysis revealed 11 DEGs as gene targets to control breast cancer metastasis: LYN, DLGAP5, CXCR4, CDC6, NANOG, IFI30, TXP2, AGTR1, MKI67, and FTH1. Upon studying the function, genomic and proteomic data, and pathway involvement of the target genes, DLGAP5 proved to be a promising candidate due to it being highly differentially expressed in all datasets. The study takes a unique perspective on the avenues through which DLGAP5 promotes metastasis. The current investigation helps pave the way in understanding the role DLGAP5 plays in metastasis, which leads to an increased incidence of death among breast cancer patients.

Keywords: genomics, metastasis, microarray, cancer

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Authors: Asma Zaib, Saeed Khan, Ayaz Ahmed Noonari, Sehrish Bint-e-Mohsin

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Breast cancer is the most common cancer among females worldwide and is estimated that more than 450,000 deaths are reported each year. It accounts for about 14% of all female cancer deaths. Angiogenesis plays an essential role in Breast cancer development, invasion, and metastasis. Breast cancer predominantly begins in luminal epithelial cells lining the normal breast ducts. Breast carcinoma likely requires coordinated efforts of both increased proliferation and increased motility to progress to metastatic stages.Resveratrol: a natural stilbenoid, has anti-inflammatory and anticancer effects that inhibits proliferation of variety of human cancer cell lines, including breast, prostate, stomach, colon, pancreatic, and thyroid cancers.The objective of this study is:To investigate anti-neoangiogenesis effects of Resveratrol in breast cancer and to analyze inhibitory effects of resveratrol on aromatase, Erα, HER2/neu, and VEGFR.Docking is the computational determination of binding affinity between molecule (protein structure and ligand).We performed molecular docking using Swiss-Dock and to determine docking effects of (1) Resveratrol with Aromatase, (2) Resveratrol with ERα (3) Resveratrol with HER2/neu and (4) Resveratrol with VEGFR2.Docking results of resveratrol determined inhibitory effects on aromatase with binding energy of -7.28 kcal/mol which shows anticancerous effects on estrogen dependent breast tumors. Resveratrol also show inhibitory effects on ERα and HER2/new with binging energy -8.02, and -6.74 respectively; which revealed anti-cytoproliferative effects upon breast cancer. On the other hand resveratrol v/s VEGFR showed potential inhibitory effects on neo-angiogenesis with binding energy -7.68 kcal/mol, angiogenesis is the important phenomenon that promote tumor development and metastasis. Resveratrol is an anti-breast cancer agent conformed by in silico studies, it has been identified that resveratrol can inhibit breast cancer cells proliferation by acting as competitive inhibitor of aromatase, ERα and HER2 neo, while neo-angiogemesis is restricted by binding to VEGFR which authenticates the anti-carcinogenic effects of resveratrol against breast cancer.

Keywords: angiogenesis, anti-cytoproliferative, molecular docking, resveratrol

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Authors: F. Ghazalnaz Sharifonnasabi, Iman Makhdoom

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Breast cancer is a serious health concern that affects many people around the world. According to a study published in the Breast journal, the global burden of breast cancer is expected to increase significantly over the next few decades. The number of deaths from breast cancer has been increasing over the years, but the age-standardized mortality rate has decreased in some countries. It’s important to be aware of the risk factors for breast cancer and to get regular check- ups to catch it early if it does occur. Machin learning techniques have been used to aid in the early detection and diagnosis of breast cancer. These techniques, that have been shown to be effective in predicting and diagnosing the disease, have become a research hotspot. In this study, we consider two deep learning approaches including: Multi-Layer Perceptron (MLP), and Convolutional Neural Network (CNN). We also considered the five-machine learning algorithm titled: Decision Tree (C4.5), Naïve Bayesian (NB), Support Vector Machine (SVM), K-Nearest Neighbors (KNN) Algorithm and XGBoost (eXtreme Gradient Boosting) on the Breast Cancer Wisconsin Diagnostic dataset. We have carried out the process of evaluating and comparing classifiers involving selecting appropriate metrics to evaluate classifier performance and selecting an appropriate tool to quantify this performance. The main purpose of the study is predicting and diagnosis breast cancer, applying the mentioned algorithms and also discovering of the most effective with respect to confusion matrix, accuracy and precision. It is realized that CNN outperformed all other classifiers and achieved the highest accuracy (0.982456). The work is implemented in the Anaconda environment based on Python programing language.

Keywords: breast cancer, multi-layer perceptron, Naïve Bayesian, SVM, decision tree, convolutional neural network, XGBoost, KNN

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Authors: Kefaya Qaddoum

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The aim of this study is to predict breast cancer and to construct a supportive model that will stimulate a more reliable prediction as a factor that is fundamental for public health. In this study, we utilize general regression neural networks (GRNN) to replace the normal predictions with prediction periods to achieve a reasonable percentage of confidence. The mechanism employed here utilises a machine learning system called conformal prediction (CP), in order to assign consistent confidence measures to predictions, which are combined with GRNN. We apply the resulting algorithm to the problem of breast cancer diagnosis. The results show that the prediction constructed by this method is reasonable and could be useful in practice.

Keywords: neural network, conformal prediction, cancer classification, regression

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Authors: Xiaoping Su, Gabriel G. Malouf

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Introduction: Breast cancer is a heterogeneous disease that can be classified in 4 subgroups using transcriptional profiling. The role of lncRNA expression in human breast cancer biology, prognosis, and molecular classification remains unknown. Methods and results: Using an integrative comprehensive analysis of lncRNA, mRNA and DNA methylation in 900 breast cancer patients from The Cancer Genome Atlas (TCGA) project, we unraveled the molecular portraits of 1,700 expressed lncRNA. Some of those lncRNAs (i.e, HOTAIR) are previously reported and others are novel (i.e, HOTAIRM1, MAPT-AS1). The lncRNA classification correlated well with the PAM50 classification for basal-like, Her-2 enriched and luminal B subgroups, in contrast to the luminal A subgroup which behaved differently. Importantly, estrogen receptor (ESR1) expression was associated with distinct lncRNA networks in lncRNA clusters III and IV. Gene set enrichment analysis for cis- and trans-acting lncRNA showed enrichment for breast cancer signatures driven by breast cancer master regulators. Almost two third of those lncRNA were marked by enhancer chromatin modifications (i.e., H3K27ac), suggesting that lncRNA expression may result in increased activity of neighboring genes. Differential analysis of gene expression profiling data showed that lncRNA HOTAIRM1 was significantly down-regulated in basal-like subtype, and DNA methylation profiling data showed that lncRNA HOTAIRM1 was highly methylated in basal-like subtype. Thus, our integrative analysis of gene expression and DNA methylation strongly suggested that lncRNA HOTAIRM1 should be a tumor suppressor in basal-like subtype. Conclusion and significance: Our study depicts the first lncRNA molecular portrait of breast cancer and shows that lncRNA HOTAIRM1 might be a novel tumor suppressor.

Keywords: lncRNA profiling, breast cancer, HOTAIRM1, tumor suppressor

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Authors: Nana Gorgiladze, Tamar Gaprindashvili, Mikheil Shavdia, Zurab Pagava

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Introduction/Purpose Chemotherapy is a common treatment for breast cancer, but it can also cause damage to the heart and blood vessels. This damage, known as cancer therapy-related cardiovascular toxicity (CTR-CVT), can increase the risk of heart failure and death in breast cancer patients. The left ventricle is often affected by CTR-CVT, but the right ventricle (RV) may also be vulnerable to CTR-CVT and may show signs of dysfunction before the left ventricle. The study aims to investigate how the RV function changes during chemotherapy for breast cancer by using conventional echocardiographic and global longitudinal strain (GLS) techniques. By measuring the GLS strain of the RV, researchers tend to detect early signs of CTR-CVT and improve the management of breast cancer patients. Methods The study was conducted on 28 women with low cardiovascular risk who received anthracycline chemotherapy for breast cancer. Conventional 2D echocardiography (LVEF, RVS’, TAPSE) and speckle-tracking echocardiography (STE) measurements of the left and right ventricles (LVGLS, RVGLS) were used to assess cardiac function before and after chemotherapy. All patients had normal LVEF at the beginning of the study. Cardiotoxicity was defined as a new LVEF reduction of 10 percentage points to an LVEF of 40-49% and/or a new decline in GLS of 15% from baseline, as proposed by the most recent cardio-oncology guideline. ResultsThe research found that the LVGLS decreased from -21.2%2.1% to -18.6%2.6% (t-test = -4.116; df = 54, p=0.001). The change in value LV-GLS was 2.6%3.0%. The mean percentage change of the LVGLS was 11,6%13,3%; p=0.001. Similarly, the right ventricular global longitudinal strain (RVGLS) decreased from -25.2%2.9% to -21.4%4.4% (t-test = -3.82; df = 54, p=0.001). The RV-GLS value of change was 3.8%3.6%. Likewise, the percentage decrease of the RVGLS was 15,0%14,3%, p=0.001.However, the measurements of the right ventricular systolic function (RVS) and tricuspid annular plane systolic excursion (TAPSE) were insignificant, and the left ventricular ejection fraction ( LVEF) remained unchanged.

Keywords: cardiotoxicity, chemotherapy, GLS, right ventricle

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Authors: Hirowati Ali, Aisyah Ellyanti, Dewi Rusnita, Septelia Inawati Wanandi

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Stem cell has been known for its potency to be differentiated in many cells. Recently stem cell has been used for many treatment of degenerative medicine. It is still controversy whether stem cell can be used for therapy or these cells can activate cancer stem cell. SCUBE2 is a novel secreted and membrane-anchored protein which has been reported to its role in better prognosis and inhibition of cancer cell proliferation. Our study aims to observe whether stem cell can up-regulate SCUBE2 gene in MCF7 breast cancer cell line. We used in vitro study using MCF-7 cell treated with stem cell derived from placenta Wharton's jelly which has been known for its stemness and widely used. Our results showed that MCF-7 cell line grows up rapidly in 6-well culture dish. Stem cell was cultured in 6-well dish. After 50%-60% MCF-7 confluence, we co-cultured these cells with stem cells for 24 hours and 48 hours. We hypothesize SCUBE2 gene which is previously known for its higher expression in better prognosis of breast cancer, is up-regulated after stem cells addition in MCF7 culture dishes.

Keywords: breast cancer cells, inhibition of cancer cells, mesenchymal stem cells, SCUBE2

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Authors: Ian Campbell, Gillian Mitchell, Paul James, Na Li, Ella Thompson

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The genetic cause of the majority of multiple-case breast cancer families remains unresolved. Next generation sequencing has emerged as an efficient strategy for identifying predisposing mutations in individuals with inherited cancer. We are conducting whole exome sequence analysis of germ line DNA from multiple affected relatives from breast cancer families, with the aim of identifying rare protein truncating and non-synonymous variants that are likely to include novel cancer predisposing mutations. Data from more than 200 exomes show that on average each individual carries 30-50 protein truncating mutations and 300-400 rare non-synonymous variants. Heterogeneity among our exome data strongly suggest that numerous moderate penetrance genes remain to be discovered, with each gene individually accounting for only a small fraction of families (~0.5%). This scenario marks validation of candidate breast cancer predisposing genes in large case-control studies as the rate-limiting step in resolving the missing heritability of breast cancer. The aim of this study is to screen genes that are recurrently mutated among our exome data in a larger cohort of cases and controls to assess the prevalence of inactivating mutations that may be associated with breast cancer risk. We are using the Agilent HaloPlex Target Enrichment System to screen the coding regions of 168 genes in 1,000 BRCA1/2 mutation-negative familial breast cancer cases and 1,000 cancer-naive controls. To date, our interim analysis has identified 21 genes which carry an excess of truncating mutations in multiple breast cancer families versus controls. Established breast cancer susceptibility gene PALB2 is the most frequently mutated gene (13/998 cases versus 0/1009 controls), but other interesting candidates include NPSR1, GSN, POLD2, and TOX3. These and other genes are being validated in a second cohort of 1,000 cases and controls. Our experience demonstrates that beyond PALB2, the prevalence of mutations in the remaining breast cancer predisposition genes is likely to be very low making definitive validation exceptionally challenging.

Keywords: predisposition, familial, exome sequencing, breast cancer

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Authors: Radoslav Stojchevski, Leonid Poretsky, Dimiter Avtanski

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Proinflammatory cytokines play an important role in cancer initiation and progression by mediating the intracellular communication between the cancer cells and tumor microenvironment. Increased tumor growth causing reduced oxygen concentration and oxygen pressure commonly result in hypoxia. Mechanistically, hypoxia is characterized by stabilization and nuclear translocation of hypoxia-inducible factor 1 alpha (HIF-1α) followed by propagation of molecular pathway cascade involving multiple downstream targets. Cobalt(II) chloride (CoCl₂) is commonly used to mimic hypoxia in experimental conditions since it directly induces the expression of HIF-1α. The aim of the present study was to investigate the in vitro effects and the molecular mechanisms by which hypoxia regulates the cytokine secretory profile of breast cancer cells. As a model for this study, we used several breast cancer cell lines bearing various molecular characteristics and metastatic potential (MDA-MB-231 (clauding low, ER-/PR-/HER²⁻), MCF-7 (luminal A, ER⁺/PR⁺/HER²⁻), and BT-474 (liminal B, ER⁺/PR⁺/HER²⁺)). We demonstrated that breast cancer cells secrete numerous cytokines and cytokine ligands, including interleukins, chemokines, and growth factors. Treatment with CoCl₂significantly modulated the breast cancer cells' cytokine expression in a concentration- and time-dependent manner. These effects were mediated via activation of several signaling pathways (JNK/SAPK1, NF-κB, STAT5A/B, and Erk/MAPK1/2). Taken together, the present data define some of the molecular mechanisms by which hypoxia affects the breast cancer cells' cytokine secretory profile, thus contributing to the development of novel therapies for metastatic breast cancer.

Keywords: breast cancer, cytokines, cobalt(II) chloride (CoCl₂), hypoxia

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Authors: B. Thanasansomboon, S. Choemprayong, N. Parinyanitikul, U. Tanlamai

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Being diagnosed with metastatic breast cancer, the patients as well as their caretakers are affected physically and mentally. Although the medical systems in Thailand have been attempting to improve the quality and effectiveness of the treatment of the disease in terms of physical illness, the success of the treatment also depends on the quality of mental health. Metastatic breast cancer patients have found that social support is a key factor that helps them through this difficult time. It is recognized that social support in different dimensions, including emotional support, social network support, informational support, instrumental support and appraisal support, are contributing factors that positively affect the quality of life of patients in general, and it is undeniable that social support in various forms is important in promoting the quality of life of metastatic breast patients. However, previous studies have not been dedicated to investigating their quality of life concerning affective, cognitive, and behavioral outcomes. Therefore, this study aims to develop integrated social support through social networks to improve the quality of life of metastatic breast cancer patients in Thailand.

Keywords: social support, metastatic breath cancer, quality of life, social network

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Authors: Hiroko Komatsu, Kaori Yagasaki

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Background: Cancer-related cognitive impairment is a common problem seen in cancer patients undergoing chemotherapy. Physical activity may show beneficial effects on the cognitive function in such patients. Therefore, we have developed a self-directed home yoga program for cancer patients with cognitive symptoms during chemotherapy. This program involves a DVD presenting a combination of yoga courses based on patient preferences to be practiced at home. This study was performed to examine the feasibility of this program. In addition, we also examined changes in cognitive function and quality of life (QOL) in these patients participating in the program. Methods: This prospective feasibility study was conducted in a 500-bed general hospital in Tokyo, Japan. The study population consisted of breast cancer patients undergoing chemotherapy as the initial therapy. This feasibility study used a convenience sample with estimation of recruitment rate in a single facility with the availability of trained nurses and physicians to ensure safe yoga intervention. The aim of the intervention program was to improve cognitive function by means of both physical and mental activation via yoga, consisting of physical practice, breathing exercises, and meditation. Information on the yoga program was provided as a booklet, with an instructor-guided group yoga class during the orientation, and a self-directed home yoga program on DVD with yoga logs. Results: The recruitment rate was 44.7%, and the study population consisted of 18 women with a mean age of 43.9 years. This study showed high rates of retention, adherence, and acceptability of the yoga program. Improvements were only observed in the cognitive aspects of fatigue, and there were serious adverse events during the program. Conclusion: The self-directed home yoga program discussed here was both feasible and safe for breast cancer patients showing cognitive symptoms during chemotherapy. The patients also rated the program as useful, interesting, and satisfactory. Participation in the program was associated with improvements in cognitive fatigue but not cognitive function.

Keywords: yoga, cognition, breast cancer, chemotherapy, quality of life

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Authors: Nahush Modak, Meena Pangarkar, Anand Pathak, Ankita Tamhane

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Background: Breast cancer is the prominent cause of cancer and mortality among women. This study was done to show the statistical analysis of a cohort of over 250 patients detected with breast cancer diagnosed by oncologists using Immunohistochemistry (IHC). IHC was performed by using ER; PR; HER2; Ki-67 antibodies. Materials and methods: Formalin fixed Paraffin embedded tissue samples were obtained by surgical manner and standard protocol was followed for fixation, grossing, tissue processing, embedding, cutting and IHC. The Ventana Benchmark XT machine was used for automated IHC of the samples. Antibodies used were supplied by F. Hoffmann-La Roche Ltd. Statistical analysis was performed by using SPSS for windows. Statistical tests performed were chi-squared test and Correlation tests with p<.01. The raw data was collected and provided by National Cancer Insitute, Jamtha, India. Result: Luminal B was the most prevailing molecular subtype of Breast cancer at our institute. Chi squared test of homogeneity was performed to find equality in distribution and Luminal B was the most prevalent molecular subtype. The worse prognostic indicator for breast cancer depends upon expression of Ki-67 and her2 protein in cancerous cells. Our study was done at p <.01 and significant dependence was observed. There exists no dependence of age on molecular subtype of breast cancer. Similarly, age is an independent variable while considering Ki-67 expression. Chi square test performed on Human epidermal growth factor receptor 2 (HER2) statuses of patients and strong dependence was observed in percentage of Ki-67 expression and Her2 (+/-) character which shows that, value of Ki depends upon Her2 expression in cancerous cells (p<.01). Surprisingly, dependence was observed in case of Ki-67 and Pr, at p <.01. This shows that Progesterone receptor proteins (PR) are over-expressed when there is an elevation in expression of Ki-67 protein. Conclusion: We conclude from that Luminal B is the most prevalent molecular subtype at National Cancer Institute, Jamtha, India. There was found no significant correlation between age and Ki-67 expression in any molecular subtype. And no dependence or correlation exists between patients’ age and molecular subtype. We also found that, when the diagnosis is Luminal A, out of the cohort of 257 patients, no patient shows >14% Ki-67 value. Statistically, extremely significant values were observed for dependence of PR+Her2- and PR-Her2+ scores on Ki-67 expression. (p<.01). Her2 is an important prognostic factor in breast cancer. Chi squared test for Her2 and Ki-67 shows that the expression of Ki depends upon Her2 statuses. Moreover, Ki-67 cannot be used as a standalone prognostic factor for determining breast cancer.

Keywords: breast cancer molecular subtypes , correlation, immunohistochemistry, Ki-67 and HR, statistical analysis

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Authors: Farah Naja, Romy Abi Fadel, Yasmin Aridi, Aya Zarif, Dania Hariri, Mohammad Alameddine, Anas Mugharbel, Maya Khalil, Zeina Nahleh, Arafat Tfayli

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The objective of this study is to assess the prevalence and determinants of CAM use among breast cancer patients in Beirut, Lebanon. A secondary objective is to evaluate the association between CAM use and quality of life (QOL). A cross-sectional survey was conducted on 180 breast cancer patients recruited from two major referral centers in Beirut. In a face to face interview, participants completed a questionnaire comprised of three sections: socio-demographic and lifestyle characteristics, breast cancer condition, and CAM use. The assessment of QOL was carried using the FACT-B Arabic version. Prevalence of CAM use since diagnosis was 40%. CAM use was negatively associated with age, treatment at a philanthropic hospital and positively associated with having an advanced stage of disease. The most commonly used CAM was ‘Special food’ followed by ‘Herbal teas’. Only 4% of CAM users cited health care professionals as influencing their choice of CAM. One in four patients disclosed CAM use to their treating physician. There was no significant association between CAM use and QOL. The use of CAM therapies among breast cancer patients is prevalent in Lebanon. Efforts should be dedicated at educating physicians to discuss CAM use with their patients and advising patients to disclose of their use with their physicians.

Keywords: breast cancer , complementary medicine, alternative medicine, lebanon , quality of life

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Authors: Farah Naja, Romy Abi Fadel, Yasmin Aridi, Aya Zarif, Dania Hariri, Mohammad Alameddine, Anas Mugharbel, Maya Khalil, Zeina Nahleh, Arafat Tfayli

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The objective of this study is to assess the prevalence and determinants of CAM use among breast cancer patients in Beirut, Lebanon. A secondary objective is to evaluate the association between CAM use and quality of life (QOL). A cross-sectional survey was conducted on 180 breast cancer patients recruited from two major referral centers in Beirut. In a face to face interview, participants completed a questionnaire comprised of three sections: socio-demographic and lifestyle characteristics, breast cancer condition, and CAM use. The assessment of QOL was carried using the FACT-B Arabic version. Prevalence of CAM use since diagnosis was 40%. CAM use was negatively associated with age, treatment at a philanthropic hospital and positively associated with having an advanced stage of disease. The most commonly used CAM was ‘Special food’ followed by ‘Herbal teas’. Only 4% of CAM users cited health care professionals as influencing their choice of CAM. One in four patients disclosed CAM use to their treating physician. There was no significant association between CAM use and QOL. The use of CAM therapies among breast cancer patients is prevalent in Lebanon. Efforts should be dedicated at educating physicians to discuss CAM use with their patients and advising patients to disclose of their use with their physicians.

Keywords: breast cancer, complementary and aLternative medicine, Lebanon, quality of life

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Authors: Mahdi Bazarganigilani

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Computer-aided diagnosis (CAD) systems can play crucial roles in diagnosing crucial diseases such as breast cancer at the earliest. In this paper, a CAD system for the diagnosis of breast cancer was introduced and evaluated. This CAD system was developed by using spatio-temporal analysis of data on a set of consecutive thermographic images by employing wavelet transformation. By using this analysis, a very accurate machine learning model using random forest was obtained. The final results showed a promising accuracy of 91% in terms of the F1 measure indicator among 200 patients' sample data. The CAD system was further extended to obtain a detailed analysis of the effect of smaller sub-areas of each breast on the occurrence of cancer.

Keywords: computer-aided diagnosis systems, thermographic analysis, spatio-temporal analysis, image processing, machine learning

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Authors: Wooseok Byon, Eunyoung Kim, Junseong Kwon, Byung Joo Song, Chan Heun Park

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Purpose: 18F Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) is a noninvasive imaging modality that can identify nodal metastases in women with primary breast cancer. The aim of this study was to compare the accuracy of FDG-PET with MRI and sonography scanning to determine axillary lymph node status in patients with breast cancer undergoing sentinel lymph node biopsy or axillary lymph node dissection. Patients and Methods: Between January and December 2012, ninety-nine patients with breast cancer and clinically negative axillary nodes were evaluated. All patients underwent FDG-PET, MRI, ultrasound followed by sentinel lymph node biopsy (SLNB) or axillary lymph node dissection (ALND). Results: Using axillary lymph node assessment as the gold standard, the sensitivity and specificity of FDG-PET were 51.4% (95% CI, 41.3% to 65.6%) and 92.2% (95% CI, 82.7% to 97.4%) respectively. The sensitivity and specificity of MRI and ultrasound were 57.1% (95% CI, 39.4% to 73.7%), 67.2% (95% CI, 54.3% to 78.4%) and 42.86% (95% CI, 26.3% to 60.7%), 92.2% (95% CI, 82.7% to 97.4%). Stratification according to hormone receptor status showed an increase in specificity when negative (FDG-PET: 42.3% to 77.8%, MRI 50% to 77.8%, ultrasound 34.6% to 66.7%). Also, positive HER2 status was associated with an increase in specificity (FDG-PET: 42.9% to 85.7%, MRI 50% to 85.7%, ultrasound 35.7% to 71.4%). Conclusions: The sensitivity and specificity of FDG-PET compared with MRI and ultrasound was high. However, FDG-PET is not sufficiently accurate to appropriately identify lymph node metastases. This study suggests that FDG-PET scanning cannot replace histologic staging in early-stage breast cancer, but might have a role in evaluating axillary lymph node status in hormone receptor negative or HER-2 overexpressing subtypes.

Keywords: axillary lymph node metastasis, FDG-PET, MRI, ultrasound

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Authors: Azar Heidarizadi, Mahdieh Salimi, Hossein Mozdarani

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Introduction: As a complex disease, breast cancer results from several genetic and epigenetic changes. Lactoferrin, a member of the transferrin family, is reported to have a number of biological functions, including DNA synthesis, immune responses, iron transport, etc., any of which could play a role in tumor progression. This study aimed to investigate the bioinformatics data and experimental assay to find the pattern of promoter methylation and gene expression of LTF in breast cancer to study its potential role in cancer management. Material and Methods: To evaluate the LTF promoter's methylation status, we studied the MS-PCR and Real-Time PCR on samples from patients with breast cancer and normal cases. This study includes 67 patient samples, including tumoral, plasma, and normal tissue adjacent samples, as well as 30 plasma samples from standard cases and 10 tissue samples of breast reduction cases. Subsequently, bioinformatics analyses such as cBioPortal databases, string, and geomatics were conducted to disclose the prognostic value of LTF in breast cancer progression. Results: The analysis of LTF expression showed an inverse relationship between the expression level of LTF and the stages of tissues of breast cancer patients (p<0.01). In fact, stages 1 and 2 had a high expression in LTF, while, in stages 3 and 4, a significant reduction was observable (p < 0.0001). LTF expression frequently alters with a decrease in the expression in ER+, PR+, and HER2+ patients (P < 0.01) and an increase in the expression in the TNBC, LN¯, ER¯, and PR- patients (P < 0.001). Also, LTF expression is significantly associated with metastasis and lymph node involvement factors (P < 0.0001). The sensitivity and specificity of LTF were detected, respectively. A negative correlation was detected between the results of level expression and methylation of the LTF promoter. Conclusions: The altered expression of LTF observed in breast cancer patients could be considered as a promotion in cell proliferation and metastasis even in the early stages of cancer.

Keywords: LTF, expression, methylation, breast cancer

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Authors: Sally Shepherd, Craig Murphy

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Introduction: The uterus or cervix are unusual locations as metastatic sites for cancers. It is further unusual for it to be a site of metastasis, whilst the primary malignancy remains occult. Case Report: A 63-year-old female with three months of altered bowel habits underwent a CT scan of the abdomen and pelvis, revealing a bulky uterus and left ovary, nonspecific colonic thickening, and diffuse peritoneal changes. She underwent colposcopy, which revealed a large endocervical polyp that was excised, revealing strongly hormone-positive metastatic invasive lobular breast cancer. She subsequently underwent a PET scan, which showed moderately diffuse activity in the cervix and left adnexa. Breast examination was unremarkable, and screening mammography, ultrasound, and MRI of the breast did not identify any lesions. Her blood tests revealed a Ca 15-3 of 934, CA-125 of 220, and CEA of 27. She was commenced on letrozole and ribociclib with an improvement in her symptoms. Conclusion: It is rare for occult breast cancer to be established and diagnosed by pelvic imaging and biopsy. Suspicion of uterine or cervical metastasis should be heightened in patients with an active or past history of breast cancer.

Keywords: occult breast cancer, cervical metastasis, invasive lobular carcinoma, metastasis

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Authors: Jiwan Kumar, Pooja, Sandeep Negi, Anjum Rouf, Amit Kumar, Naveen Lakra

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In modern times where, health issues are increasing day by day, breast cancer is also one of them, which is very crucial and really important to find in the early stages. Doctors can use this model in order to tell their patients whether a cancer is not harmful (benign) or harmful (malignant). We have used the knowledge of machine learning in order to produce the model. we have used algorithms like Logistic Regression, Random forest, support Vector Classifier, Bayesian Network and Radial Basis Function. We tried to use the data of crucial parts and show them the results in pictures in order to make it easier for doctors. By doing this, we're making ML better at finding breast cancer, which can lead to saving more lives and better health care.

Keywords: Bayesian network, radial basis function, ensemble learning, understandable, data making better, random forest, logistic regression, breast cancer

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Authors: Ika Wulansari, Yati Afiyanti, Indang Trihandini

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Sleeping disorder experienced by patients with breast cancer can affect the physical, mental, health, and well-being. This study examines the effect of progressive muscle relaxation training and sleep hygiene education to change sleep quality scores of the patient with breast cancer. The study design using quasi-experiment with pre-post test within the control group, involving 62 breast cancer patients using consecutive sampling method in Jakarta. Statistical test results with independent t-test showed a significant difference in score of sleep quality between in intervention group and the control group (6,66±3,815; 9,30±3,334, p-value = 0,005). Progressive muscle relaxation exercise and sleep hygiene education proven to be affective to change the patients sleeping quality, so that it can be an alternative therapeutic option to overcome sleeping disorders.

Keywords: sleeping disorders, breast cancer, progressive muscle relaxation, sleep hygiene education

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Authors: Jing Chen, Jun-E Liu, Peng Yue

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Objective: The objective of this study was to develop a psychological adjustment and adaptation status scale for breast cancer survivors, and to examine the reliability and validity of the scale. Method: 37 breast cancer survivors were recruited in qualitative research; a five-subject theoretical framework and an item pool of 150 items of the scale were derived from the interview data. In order to evaluate and select items and reach a preliminary validity and reliability for the original scale, the suggestions of study group members, experts and breast cancer survivors were taken, and statistical methods were used step by step in a sample of 457 breast cancer survivors. Results: An original 24-item scale was developed. The five dimensions “domestic affections”, “interpersonal relationship”, “attitude of life”, “health awareness”, “self-control/self-efficacy” explained 58.053% of the total variance. The content validity was assessed by experts, the CVI was 0.92. The construct validity was examined in a sample of 264 breast cancer survivors. The fitting indexes of confirmatory factor analysis (CFA) showed good fitting of the five dimensions model. The criterion-related validity of the total scale with PTGI was satisfactory (r=0.564, p<0.001). The internal consistency reliability and test-retest reliability were tested. Cronbach’s alpha value (0.911) showed a good internal consistency reliability, and the intraclass correlation coefficient (ICC=0.925, p<0.001) showed a satisfactory test-retest reliability. Conclusions: The scale was brief and easy to understand, was suitable for breast cancer patients whose physical strength and energy were limited.

Keywords: breast cancer survivors, rehabilitation, psychological adaption and adjustment, development of scale

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Authors: Marta E. Hernandez-Caballero, Veronica Borgonio-Cuadra, Antonio Miranda-Duarte, Xochitl Rojas-Toledo, Normand Garcia-Hernandez, Maura Cardenas-Garcia, Teresa Abad-Camacho

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Breast cancer (BC) is the most common tumor in women over the world. DNA methylation is an epigenetic modification critical in CpG sites, aberrant methylation of CpG islands in promoters is a hallmark of cancer. So, gene expression can be regulated by alterations in DNA methylation. In cell lines DACT2 gene reduces the growth and migration of tumor cells by its participation in the suppression of TGFb/SMAD2/3. PHF20L1 is involved in histone acetylation therefore, it regulates transcription. Our aim was to analyze the methylation status of the DACT2 and PHF20L1 promoter regions in tumoral and healthy mammary tissue from women with BC in different progression states. The study included 77 patients from Centro Medico Nacional La Raza in Mexico City. After identifying a CpG island in DACT2 and PHF20L1 promoters, DNA methylation status was analyzed through sodium bisulfite with subsequent amplification using methylation-specific PCR. Results revealed no changes in methylation status of PHF20L1 and cancer stages (II y III) or in comparison to healthy tissues, it was demethylated. DACT2 promoter methylation was no significant between tumoral stages (II, P = 0.37; III, P = 0.17) or with healthy tissue. Previous data reported DACT2 methylated in nasopharyngeal carcinoma but in this study promoter methylation was not observed. PHF20L1 protein contains N-terminal Tudor and C-terminal plant homeodomain domains, it has been suggested that can stabilize DNMT1 regulating DNA methylation, therefore, was associated with poor prognostic in BC. We found no evidence of methylation in patients and controls in PHF20L1 promoter, so its association with BC may have no direct relation with promoter methylation. More studies including other methylation sites in these genes in BC are necessary.

Keywords: bisulfite conversion, breast cancer, DACT2, DNA methylation, PHF20L1, tumoral status

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Authors: Leila Anoosheh

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Aim: The aim of this study was to assess The effects of aerobic training on microRNA let-7a expression and levels of tumor tissue IL-6 in mice with breast cancer. Method: Twenty BALB/c c mice (4-5 weeks,17 gr mass) were cancerous by injection of estrogen-dependent receptor breast cancer cells MC4-L2 and divided into two groups: tumor-training(TT) and tumor-control(TC) group. Then TT group completed aerobic training for 6 weeks, 5 days per week (14-18 m/min). After tumor emersion, tumor width and length were measured by digital caliper every week. 48 hours after the last exercise subjects were killed. Tissue sampling were collected and stored in -70ᵒ. Tumor tissue was homogenized and let-7a expression and IL-6 levels were accounted with Real time-PCR and ELISA Kit respectively. Statistical analysis of let-7a was conducted by the REST software. Repeated measures and independent tests were used to assess tumor size and IL-6, respectively. Results: Tumor size and IL-6 levels were significantly decreased in TT group compare with TC group (p<0.05). microRNA let-7a was increased significantly in TT against control group respectively (p=0/000). Conclusion: Reduction in tumor size, followed by aerobic exercise can be attributed to the loss of inflammatory factors such as IL-6; It seems that regarding to up regulation effects of aerobic exercise training on let-7a and down regulation effects of that on IL-6 in mice with breast cancer, This type of training can be used as adjuvant therapy in conjunction with other therapies for breast cancer.

Keywords: breast cancer, aerobic training, microRNA let-7a, IL-6

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Authors: Siddhant Rao

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Studies estimate that there will be 266,120 new cases of invasive breast cancer and 40,920 breast cancer induced deaths in the year of 2018 alone. Despite the pervasiveness of this affliction, the current process to obtain an accurate breast cancer prognosis is tedious and time consuming. It usually requires a trained pathologist to manually examine histopathological images and identify the features that characterize various cancer severity levels. We propose MITOS-RCNN: a region based convolutional neural network (RCNN) geared for small object detection to accurately grade one of the three factors that characterize tumor belligerence described by the Nottingham Grading System: mitotic count. Other computational approaches to mitotic figure counting and detection do not demonstrate ample recall or precision to be clinically viable. Our models outperformed all previous participants in the ICPR 2012 challenge, the AMIDA 2013 challenge and the MITOS-ATYPIA-14 challenge along with recently published works. Our model achieved an F- measure score of 0.955, a 6.11% improvement in accuracy from the most accurate of the previously proposed models.

Keywords: breast cancer, mitotic count, machine learning, convolutional neural networks

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Authors: S. Sushma, S. Balasubramanian, K. C. Latha, R. Sridhar

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Structural texture measures are used to address the aspect of breast cancer risk assessment in screening mammograms. The current study investigates whether texture properties characterized by local Fractal Dimension (FD) and lacunarity contribute to assess breast cancer risk. Fractal Dimension represents the complexity while the lacunarity characterize the gap of a fractal dimension. In this paper, we present our result confirming that the lacunarity value resulted in algorithm using mammogram images states that level of lacunarity will be low when the Fractal Dimension value will be high.

Keywords: breast cancer, fractal dimension, image analysis, lacunarity, mammogram

Procedia PDF Downloads 351