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

BMC Cancer ◽  
2022 ◽  
Vol 22 (1) ◽  
Author(s):  
Maria Valeria Esposito ◽  
Bruno Fosso ◽  
Marcella Nunziato ◽  
Giorgio Casaburi ◽  
Valeria D’Argenio ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Tissue ◽  
Microbial Composition ◽  
Bacterial Composition ◽  
Therapeutic Implications ◽  
Microbiome Composition ◽  
Paired Samples ◽  
Number Of Factors ◽  
Tumor Tissues ◽  
Breast Tissues

Abstract 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.

scholarly journals The Key Role of Human Microbiota in Breast Cancer

2021 ◽  
Author(s):  
Alessio Filippone ◽  
Cristina Rossi ◽  
Maria Maddalena Rossi ◽  
Donatella Guarino ◽  
Claudia Maggiore ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Immune Modulation ◽  
Intestinal Barrier ◽  
Microbial Composition ◽  
Bacterial Gene ◽  
Microbiome Composition ◽  
Increased Risk ◽  
Health And Disease ◽  
Complex Scenario ◽  
Risk Of Cancer

Sound evidence recognizes the microbiota as one of the major players in human health and disease, including cancer. Every human being is an holobiont, a shared human and microbial ecosystem, in which microbial composition is individually set by behaviours and environmental factors during the first years of life. Thereafter it is modulated by diet, physical activity, emotions and drugs (in particularly antibiotics and chemotherapeutics). As a consequence, a shift in medicine is needed toward a more comprehensive practice that takes into account every individual's genoma and, in addition, his or her metagenome, known as microbiome: a "microbiota revolution". As regards breast cancer (BC), a clear link between microbiota and oncogenesis is still to be confirmed. Specific microbes display unique features regulating their host niche in a number of body sites, which can result in an increased risk of cancer; in addition, gut microbiota composition plays a role in immune modulation within the intestinal barrier, affecting local and systemic inflammation, recognized drivers of cancer. Moreover, part of the bacterial gene mass inside the gut, constituting the so called “estrobolome”, influences the sexual hormonal balance and subsequentely may impact on the onset, progression and treatment of hormonal dependent cancers. Microbiota is also clearly involved in modulating the response to anticancer treatments, and above all to the emerging immunotherapy. Based on these premises, the microbiome is becoming a potential target, in order to enhance efficacy of antitumoral treatments as well as to lower their toxicity. The complex scenario that links microbiome composition to oncogenesis and response to anticancer treatments defines the frames of a new “oncobiotic” perspective.

An Intelligent-Based Wavelet Classifier for Accurate Prediction of Breast Cancer

2018 ◽  
pp. 306-319 ◽  
Author(s):  
Anandakumar Haldorai ◽  
Arulmurugan Ramu
Keyword(s):  
Breast Cancer ◽  
Neural Network ◽  
Roc Curve ◽  
Breast Tissue ◽  
Wavelet Neural Network ◽  
Clinical Database ◽  
New Approach ◽  
X Ray ◽  
Breast Tissues

The detection of cancer in the breast is done using mammograms (x-ray images). The authors propose a CAD framework for distinguishing little changes in mammogram which may demonstrate malignancies which are too little to be felt either by the lady herself or by a radiologist. In this chapter, they build up a framework for analysis, visualization, and prediction of cancer in breast tissue by utilizing Intelligent based wavelet classifier. Intelligent-based wavelet classifier is a new approach constructed using texture value and wavelet neural network. The proposed framework is applied to the genuine clinical database of 160 mammograms gathered from mammogram screening focuses. The execution of the CAD framework is examined utilizing ROC curve. This will help the specialists in determination of the breast tissues either cancerous or noncancerous in an accurate way.

scholarly journals Genomic Changes in Normal Breast Tissue in Women at Normal Risk or at High Risk for Breast Cancer

2016 ◽  
Vol 10 ◽  
pp. BCBCR.S39384 ◽  
Author(s):  
David N. Danforth
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
High Risk ◽  
Breast Tissue ◽  
Sporadic Breast Cancer ◽  
Normal Breast Tissue ◽  
Normal Breast ◽  
Breast Carcinogenesis ◽  
Molecular Changes ◽  
Breast Tissues

Sporadic breast cancer develops through the accumulation of molecular abnormalities in normal breast tissue, resulting from exposure to estrogens and other carcinogens beginning at adolescence and continuing throughout life. These molecular changes may take a variety of forms, including numerical and structural chromosomal abnormalities, epigenetic changes, and gene expression alterations. To characterize these abnormalities, a review of the literature has been conducted to define the molecular changes in each of the above major genomic categories in normal breast tissue considered to be either at normal risk or at high risk for sporadic breast cancer. This review indicates that normal risk breast tissues (such as reduction mammoplasty) contain evidence of early breast carcinogenesis including loss of heterozygosity, DNA methylation of tumor suppressor and other genes, and telomere shortening. In normal tissues at high risk for breast cancer (such as normal breast tissue adjacent to breast cancer or the contralateral breast), these changes persist, and are increased and accompanied by aneuploidy, increased genomic instability, a wide range of gene expression differences, development of large cancerized fields, and increased proliferation. These changes are consistent with early and long-standing exposure to carcinogens, especially estrogens. A model for the breast carcinogenic pathway in normal risk and high-risk breast tissues is proposed. These findings should clarify our understanding of breast carcinogenesis in normal breast tissue and promote development of improved methods for risk assessment and breast cancer prevention in women.

scholarly journals Therapeutic Targets In Breast Cancer Signaling: A Review

2021 ◽  
pp. 82-99
Author(s):  
Emmanuel Ifeanyi Obeagu ◽  
Quratulain Babar ◽  
C. C. N. Vincent ◽  
Chikwendu Lawrence Udenze ◽  
Richard Eze ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Tissue ◽  
Predictive Biomarkers ◽  
Molecular Therapy ◽  
Therapeutic Interventions ◽  
Breast Cancers ◽  
Dominant Type ◽  
Cellular Pathways ◽  
Breast Tissues ◽  
Human Epidermal Receptor

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.

scholarly journals Aberrant epigenetic and transcriptional events associated with breast cancer risk

2021 ◽  
Author(s):  
Natascia Marino ◽  
Rana German ◽  
Ram Podicheti ◽  
Douglas B. Rush ◽  
Pam Rockey ◽  
...  
Keyword(s):  
Breast Cancer ◽  
High Risk ◽  
Breast Cancer Risk ◽  
Epithelial Cells ◽  
Cancer Risk ◽  
Breast Tissue ◽  
Cancer Susceptibility ◽  
Breast Cancer Susceptibility ◽  
Normal Breast ◽  
Breast Tissues

ABSTRACTBackgroundGenome-wide association studies have identified several breast cancer susceptibility loci. However, biomarkers for risk assessment are still missing. Here, we investigated cancer-related molecular changes detected in tissues from women at high risk for breast cancer prior to disease manifestation. Disease-free breast tissue cores donated by healthy women (N=146, median age=39 years) were processed for both methylome (MethylCap) and transcriptome (Illumina’s HiSeq4000) sequencing. Analysis of tissue microarray and primary breast epithelial cells was used to confirm gene expression dysregulation.ResultsTranscriptomic analysis identified 69 differentially expressed genes between women at either high and those at average risk of breast cancer (Tyrer-Cuzick model) at FDR<0.05 and fold change≥2. The majority of the identified genes were involved in DNA damage checkpoint, cell cycle, and cell adhesion. Two genes, FAM83A and NEK2, were overexpressed in tissue sections (FDR<0.01) and primary epithelial cells (p<0.05) from high-risk breasts. Moreover, 1698 DNA methylation aberrations were identified in high-risk breast tissues (FDR<0.05), partially overlapped with cancer-related signatures and correlated with transcriptional changes (p<0.05, r≤0.5). Finally, among the participants, 35 women donated breast biopsies at two time points, and age-related molecular alterations enhanced in high-risk subjects were identified.ConclusionsNormal breast tissue from women at high risk of breast cancer bears molecular aberrations that may contribute to breast cancer susceptibility. This study is the first molecular characterization of the true normal breast tissues and provides an opportunity to investigate molecular markers of breast cancer risk, which may lead to new preventive approaches.

scholarly journals Breast cancer identification based on artificial intelligent system

2020 ◽  
Vol 2 (2) ◽  
pp. 109-118
Author(s):  
Hassan Khalil Silman ◽  
Akbas Ezaldeen Ali
Keyword(s):  
Breast Cancer ◽  
Breast Tissue ◽  
Intelligent System ◽  
High Rate ◽  
Computer Assisted ◽  
Fine Needle Aspirates ◽  
Manual Intervention ◽  
Breast Tissue Density ◽  
Breast Tissues ◽  
Background Area

Worldwide, breast cancer causes a high mortality rate. Early diagnosis is important for treatment, but high-density breast tissues are difficult to analyze. Computer-assisted identification systems were introduced to classify by fine needle aspirates FNA with features that better represent the images to be classified as a major challenge. This work is fully automated, and it does not require any manual intervention from user. In this analysis, various texture definitions for the portrayal of breast tissue density on mammograms are examined within addition to contrasting them with other techniques. We have created an algorithm that can be divided into three classes: fatty, fatty-glandular and dense-glandular. The suggested system works in a spatial-related domain and it results with extreme immunity to noise and background area, with a high rate of precision.

scholarly journals Long non-coding RNA UCA1 promotes breast cancer by upregulating PTP1B expression via inhibiting miR-206

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Yi Li ◽  
Qingan Zeng ◽  
Jiliang Qiu ◽  
Ting Pang ◽  
Jianzhong Xian ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Cells ◽  
Breast Tumor ◽  
Breast Cancer Cells ◽  
Transcriptional Level ◽  
Normal Tissues ◽  
Non Coding Rna ◽  
Tumor Tissues ◽  
Breast Tissues ◽  
Long Non Coding Rna

Abstract Background The long non-coding RNA (lncRNA) urothelial carcinoma-associated 1 (UCA1) is involved in various cancers and often functions through microRNAs. The pro-survival protein PTP1B is known to play important roles in cancer development. However, the connection between UCA1 and PTP1B in breast cancer is not well studied. Methods In this study, we first evaluated the correlation between UCA1 level and PTP1B expression in breast tissues, which showed the expression of PTP1B were much higher in the breast tumor tissues than in the peritumor normal tissues. The UCA1 level was positively associated with PTP1B expression in breast tumor tissues. Results We observed that UCA1 could up-regulate PTP1B expression in breast cancer cells. We also found that miR-206 could inhibit the expression of PTP1B by directly binding to the 3′-UTR of its mRNA. Interestingly, UCA1 could increase the expression of PTP1B through sequestering miR-206 at post-transcriptional level. The results also suggested that UCA1-induced PTP1B expression facilitated the proliferation of breast cancer cells. Conclusions We conclude that UCA1 can up-regulates PTP1B to enhance cell proliferation through sequestering miR-206 in breast cancer. Our finding provides new insights into the mechanism of breast cancer regulation by UCA1, which could be a potential target for breast cancer treatment. Trial registration 2012N5hSYSU48573. Registered at Oct 12, 2012

ESR1 and GPX1 genes expression level in human malignant and non-malignant breast tissues

2018 ◽  
Vol 65 (1) ◽  
pp. 51-57 ◽  
Author(s):  
Magdalena Beata Król ◽  
Michał Galicki ◽  
Peter Grešner ◽  
Edyta Wieczorek ◽  
Ewa Jabłońska ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Estrogen Receptor ◽  
Breast Tissue ◽  
Mrna Level ◽  
Clinicopathological Factors ◽  
Down Regulation ◽  
Expression Levels ◽  
Genes Expression ◽  
Malignant Breast ◽  
Breast Tissues

Background: The aim of this study was to find out whether the mRNA expression of estrogen receptor alpha (encoded by ESR1) correlates with the expression of glutathione peroxidase 1 (encoded by GPX1) in tumor and adjacent tumor-free breast tissue and whether this correlation is affected by breast cancer. Such relationships may give further insights into breast cancer pathology with respect to the status of estrogen receptor. Methods: We used the quantitative real-time PCR technique to analyze differences in the expression levels of the ESR1 and GPX1 genes in paired malignant and non-malignant tissues from breast cancer patients. Results: ESR1 and GPX1 expression levels were found to be significantly down-regulated by 14.7% and 7.4% (respectively) in the tumorous breast tissue compared to the non-malignant one. Down-regulation of these gene were independent of tumor histopathology classification and clinicopathological factors while ESR1 mRNA level was reduced with increasing tumor grade (G1: 103% vs. G2: 85.8% vs. G3: 84.5%; p<0.05). In the non-malignant and malignant breast tissues, the expression levels of ESR1 and GPX1 were significantly correlated with each other (Rs=0.450 and Rs=0.360; respectively). Conclusion: These data suggest that down-regulation of ESR1 and GPX1 are independent on clinicopathological factors. Down-regulation of ESR1 gene expression enhanced with the development of the disease. Moreover, GPX1 and ESR1 genes expression are interdependent in the malignant breast tissue and further work is needed to determine the mechanism underlying this relationship.

scholarly journals Breast Mammographic Density: Stromal Implications on Breast Cancer Detection and Therapy

2020 ◽  
Vol 9 (3) ◽  
pp. 776
Author(s):  
Patricia Fernández-Nogueira ◽  
Mario Mancino ◽  
Gemma Fuster ◽  
Paloma Bragado ◽  
Miquel Prats de Puig ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Mammographic Density ◽  
Cancer Detection ◽  
Breast Tissue ◽  
Normal Development ◽  
Mammary Cells ◽  
Breast Cancer Patients ◽  
Therapeutic Implications ◽  
Clinical Meaning

Current evidences state clear that both normal development of breast tissue as well as its malignant progression need many-sided local and systemic communications between epithelial cells and stromal components. During development, the stroma, through remarkably regulated contextual signals, affects the fate of the different mammary cells regarding their specification and differentiation. Likewise, the stroma can generate tumour environments that facilitate the neoplastic growth of the breast carcinoma. Mammographic density has been described as a risk factor in the development of breast cancer and is ascribed to modifications in the composition of breast tissue, including both stromal and glandular compartments. Thus, stroma composition can dramatically affect the progression of breast cancer but also its early detection since it is mainly responsible for the differences in mammographic density among individuals. This review highlights both the pathological and biological evidences for a pivotal role of the breast stroma in mammographic density, with particular emphasis on dense and malignant stromas, their clinical meaning and potential therapeutic implications for breast cancer patients.

scholarly journals Differential Expression of Blood Group Precursor Antigen in Human Breast Cancer Tissue

2020 ◽  
pp. 1-3
Author(s):  
Denong Wang ◽  
Yi Jiang ◽  
Denong Wang
Keyword(s):  
Breast Cancer ◽  
Blood Group ◽  
Breast Tissue ◽  
Tissue Microarrays ◽  
Breast Cancer Tissue ◽  
Cancer Tissue ◽  
Human Breast ◽  
Human Breast Cancer Tissue ◽  
Breast Tissues ◽  
Conserved Epitope

There is a pressing need for biomarkers for targeted immunotherapy against breast cancer (BCA), the leading cause of cancer death in women. Previously, a blood group precursor O-core epitope gpC1 was found to be highly expressed in breast circulating tumor cells (BCTCs) and BCA cell lines with cancer stem cell (BCSC) features. In this pilot study, the breast tissue distribution of gpC1 was examined using tissue microarrays (TMAs). Notably, gpC1 positive cells were detected in the major histological types of neoplastic breast tissues. Conversely, none of the breast tissues derived from subjects without BCA were gpC1 positive. Thus, gpC1 expression seems to be tumor-specific but not histological type-dependent, reflecting perhaps its characteristics as a conserved epitope of oncofetal blood group precursor antigens.

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