Development a low-cost electrical impedance tomography system for non-invasively detecting abnormal in breast tissue - Phantom study-

Electrical Impedance Tomography (EIT) is known as non-invasive method to detect and classify the abnormal breast tissues. Reimaging conductivity distribution within an area of the subject reveal abnormal tissues inside that area. In this work, we have created a very low-cost system with a simple 16-electrode phantom for doing research purposes. The EIT data were measured and reconstructed with EIDORS software.

Potentials of CCL21 and CBS as therapeutic approaches for breast cancer

Objective: The present research set out to ascertain the roles of CCL21 and CBS in breast cancer (BC) cell biological behaviors and the relationship of CCL21 and CBS expression with the clinicopathological features of patients with BC. Methods: Immunohistochemistry of CCL21 or CBS was performed in 18 intraductal cancer tissues, 124 invasive BC tissues, 50 paraneoplastic tissues, 50 lobular hyperplasia tissues, and 30 normal breast tissues. For cell experiments, two human BC cell lines (MDA-MB-231 and MCF-7) and a human breast epithelial cell line (MCF-10A) were utilized to detect the expression of CCL21 and CBS. After loss- and gain-of-function assays for CCL21 or CBS, the expression of CBS and CCL21 was measured by qRT-PCR and Western blot. Additionally, BC cell proliferation was assessed by MTT assay and EdU staining, and BC cell migration was determined by scratch test and Transwell assay. Results: In the clinical data, the positive rate of CCL21 or CBS was significantly higher in invasive BC tissues than in intraductal BC tissues, lobular hyperplasia tissues, paraneoplastic tissues, and normal breast tissues (P < 0.05 or P < 0.01). CBS or CCL21 expression shared close association with the clinicopathological characteristic and the poor prognosis of BC patients. In cell experiments, overexpression of CCL21 or CBS enhanced the proliferative and migratory abilities of BC cells. Conclusion: CCL21 and CBS promoted BC cell migration and proliferation. CCL21 or CBS expression was strongly related to the poor prognosis of BC patients.

The Valuable Role of Armc1 in Invasive Breast Cancer as a Novel Biomarker

Background: Invasive breast carcinoma (BRCA) is a common type of breast cancer with high incidence in clinics, so it is significant to find an effective biomarker for BRCA diagnosis and treatment. Although some Armadillo (Arm)-repeat proteins families are confirmed to be biomarkers in cancers, the role of Armadillo repeat-containing 1 (ARMC1) in BRCA remains unknown.Methods: We analyzed the ARMC1 expression in normal breast tissues and BRCA samples, and its association with overall survival by the public database. χ² test evaluated the risks associated with ARMC1 expression in TCGA-BRCA patient samples. The ARMC1 mutations in BRCA were explored in the cBioportal database. Besides, the GO and KEGG analysis was used to explore the potential signaling pathways of ARMC1 in BRCA. Lastly, Immunohistochemistry and immunohistochemistry were performed to validate the ARMC1 expression in BRCA.Results: ARMC1 level in tumor sample was significantly higher than that in normal tissue, and it was also related to lower survival. The factors in clinical patients such as tumor stage and grade and histology were associated with ARMC1 expression. There were 32% of ARMC1 genetic mutations in BRCA, and the amplification and high expression made up the majority of them. Also, ARMC1 might regulate BRCA by involving in the cell cycle. Increased ARMC1 expression was found in clinical breast carcinoma tissues by our confirmatory experiments.Conclusions: All the results revealed that ARMC1 may play a significant role in BRCA as a biomarker, it provides valuable clues for the treatment and diagnosis of invasive breast cancer.

Microbiome composition indicate dysbiosis and lower richness in tumor breast tissues compared to healthy adjacent paired tissue, within the same women

Background Breast cancer (BC) is the most common malignancy in women, in whom it reaches 20% of the total neoplasia incidence. Most BCs are considered sporadic and a number of factors, including familiarity, age, hormonal cycles and diet, have been reported to be BC risk factors. Also the gut microbiota plays a role in breast cancer development. In fact, its imbalance has been associated to various human diseases including cancer although a consequential cause-effect phenomenon has never been proven. Methods The aim of this work was to characterize the breast tissue microbiome in 34 women affected by BC using an NGS-based method, and analyzing the tumoral and the adjacent non-tumoral tissue of each patient. Results The healthy and tumor tissues differed in bacterial composition and richness: the number of Amplicon Sequence Variants (ASVs) was higher in healthy tissues than in tumor tissues (p = 0.001). Moreover, our analyses, able to investigate from phylum down to species taxa for each sample, revealed major differences in the two richest phyla, namely, Proteobacteria and Actinobacteria. Notably, the levels of Actinobacteria and Proteobacteria were, respectively, higher and lower in healthy with respect to tumor tissues. Conclusions Our study provides information about the breast tissue microbial composition, as compared with very closely adjacent healthy tissue (paired samples within the same woman); the differences found are such to have possible diagnostic and therapeutic implications; further studies are necessary to clarify if the differences found in the breast tissue microbiome are simply an association or a concausative pathogenetic effect in BC. A comparison of different results on similar studies seems not to assess a universal microbiome signature, but single ones depending on the environmental cohorts’ locations.

Long Noncoding RNAs-LET Behave as a Noncoding Signature for Early-Onset Menarche and Late-Onset Menopause in Breast Cancer Patients

Background: Breast cancer (BC) as a major cause of cancer-related death in women shows a very complex molecular and clinical phenotype, which has reduced the effectiveness of medical interventions. Evidence suggests that long noncoding RNAs (lncRNAs) are responsible for an important part of this complexity. This study aims to assess the expression and clinical implication of lncRNA LET in the pathobiology of BC. Materials and Methods: Quantitative real-time polymerase chain reaction was used to measure the expression of lncRNA-LET in breast tumors and adjacent normal-appearing tissues from 4 BC patients, as well as normal mammary tissues. Moreover, a bioinformatics approach was applied to uncover the potential lncRNA-LET-mediated sponge regulatory network as LET/miRNA/mRNA crosstalk. Results: Our study revealed that lncRNA-LET was significantly down-expressed not only in breast tumors but also in normal appearing breast tissues samples from BC subjects compared with true normal breast tissues obtained from healthy women. The low level of lncRNA-LET was meaningfully associated with early-onset menarche (≤13 years) and late-onset menopause (≥50) in patients. Moreover, the bioinformatics analyses support that lncRNA-LET could function as a tumor suppressor miRNA sponge. Conclusion: The results indicate that normal appearing breast tissues can undergo tumor-related molecular changes. Furthermore, they reveal the potential role of the dysregulation in LET-mediated ceRNA network in the pathophysiology of BC.

Electro-impedance mammograms for automatic breast cancer screening: First insights on Mexican patients

Breast cancer is a very important health concern around the world. Early detection of such a disease increases the chances of survival. Among the available screening tools, there is the Electro-Impedance Mammography (EIM), which is a novel and less invasive method that captures the potential difference stored in breast tissues under the assumption that electrical properties among normal and pathologically altered tissues are different. In this paper, we address breast cancer detection as a multi-class problem aiming to determine the corresponding label in terms of the Breast Imaging Electrical Impedance classification system, the standard used by physicians for interpreting an EIM mammogram. For experimental purposes, for the first time in the literature, we took advantage of a dataset comprising EIM of Mexican patients. Aiming to establish a baseline for this task, traditional supervised learning methods were used together with two different feature extraction techniques: raw pixel data and transfer learning. Besides, data augmentation was exploited for compensating data imbalance. Different experimental settings were evaluated reaching classification rates over 0.85 in F-score. KNN emerges as a very promising classifier for addressing this task. The obtained results allow us to validate the usefulness of traditional methods for classifying electro-impedance mammograms.

Therapeutic Targets In Breast Cancer Signaling: A Review

For women, the most dominant type of cancer is breast cancer and perhaps one of the most recognizedreasons of death. This is a disorder of many distinct traits, many of which are known as positive hormone receptor, human epidermal receptor-2 (HER2+), and three negative breast cancers (TNBC). Drugs that directly target and kill tumors constitute a rapidly-growing form of molecular therapy for cancer patients. Analysis reveals that stable breast tissue cells exhibit receptors which aren't usually present. As a result, it is imperative to cognize the molecular roots of breast cancer and the myriad compromised pathology-related processes and pathways to ensure progresses in early diagnosis and prevention. This study demonstrates essential cellular pathways relevant for breast cancer including improvements in cell proliferation, apoptosis, and hormone balances in breast tissues. On the basis of these notions, we consider how breast cancer is associated to the creation of potentially therapeutic interventions and predictive biomarkers.

Multicenter Study of Whole Breast Stiffness Imaging by Ultrasound Tomography (SoftVue) for Characterization of Breast Tissues and Masses

We evaluated whole breast stiffness imaging by SoftVue ultrasound tomography (UST), extracted from the bulk modulus, to volumetrically map differences in breast tissues and masses. A total 206 women with either palpable or mammographically/sonographically visible masses underwent UST scanning prior to biopsy as part of a prospective, HIPAA-compliant multicenter cohort study. The volumetric data sets comprised 298 masses (78 cancers, 105 fibroadenomas, 91 cysts and 24 other benign) in 239 breasts. All breast tissues were segmented into six categories, using sound speed to separate fat from fibroglandular tissues, and then subgrouped by stiffness into soft, intermediate and hard components. Ninety percent of women had mammographically dense breasts but only 11.2% of their total breast volume showed hard components while 69% of fibroglandular tissues were softer. All smaller masses (<1.5 cm) showed a greater percentage of hard components than their corresponding larger masses (p < 0.001). Cancers had significantly greater mean stiffness indices and lower mean homogeneity of stiffness than benign masses (p < 0.05). SoftVue stiffness imaging demonstrated small stiff masses, mainly due to cancers, amongst predominantly soft breast tissues. Quantitative stiffness mapping of the whole breast and underlying masses may have implications for screening of women with dense breasts, cancer risk evaluations, chemoprevention and treatment monitoring.