Notch and Wnt Dysregulation and Its Relevance for Breast Cancer and Tumor Initiation

Braune, Eike-Benjamin; Seshire, Anita; Lendahl, Urban

doi:10.3390/biomedicines6040101

Cited by 32 publications

(20 citation statements)

References 142 publications

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“…Specifically, Notch signaling pathway is involved in mammary development and homeostasis as well as in the promotion of breast cancer when dysregulated [34]. Indeed, accumulating evidence sustains the importance of Notch pathway in mammary stem cells (MaSCs) generation and maintenance during mammary gland development [35].…”

Section: Notch Signaling Overview In Tnbcmentioning

confidence: 99%

Notch Signaling Activation as a Hallmark for Triple-Negative Breast Cancer Subtype

Giuli

Giuliani

Screpanti

et al. 2019

Journal of Oncology

129

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Triple-negative breast cancer (TNBC) is a subgroup of 15%-20% of diagnosed breast cancer patients. It is generally considered to be the most difficult breast cancer subtype to deal with, due to the lack of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2), which usually direct targeted therapies. In this scenario, the current treatments of TNBC-affected patients rely on tumor excision and conventional chemotherapy. As a result, the prognosis is overall poor. Thus, the identification and characterization of targets for novel therapies are urgently required. The Notch signaling pathway has emerged to act in the pathogenesis and tumor progression of TNBCs. Firstly, Notch receptors are associated with the regulation of tumor-initiating cells (TICs) behavior, as well as with the aetiology of TNBCs. Secondly, there is a strong evidence that Notch pathway is a relevant player in mammary cancer stem cells maintenance and expansion. Finally, Notch receptors expression and activation strongly correlate with the aggressive clinicopathological and biological phenotypes of breast cancer (e.g., invasiveness and chemoresistance), which are relevant characteristics of TNBC subtype. The purpose of this up-to-date review is to provide a detailed overview of the specific role of all four Notch receptors (Notch1, Notch2, Notch3, and Notch4) in TNBCs, thus identifying the Notch signaling pathway deregulation/activation as a pathognomonic feature of this breast cancer subtype. Furthermore, this review will also discuss recent information associated with different therapeutic options related to the four Notch receptors, which may be useful to evaluate prognostic or predictive indicators as well as to develop new therapies aimed at improving the clinical outcome of TNBC patients.

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Section: Notch Signaling Overview In Tnbcmentioning

confidence: 99%

Notch Signaling Activation as a Hallmark for Triple-Negative Breast Cancer Subtype

Giuli

Giuliani

Screpanti

et al. 2019

Journal of Oncology

129

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“…Physiological regulators such as Notch receptors and ligands, along with Wnt ligands, can induce EMT in mammary epithelial cells. Notch and Wnt factors are also important for different steps of breast cancer initiation and progression [29,30,31,32,33]. In addition, EMT in normal mammary epithelial cells can be induced by overexpression of the apoptosis regulator B-cell lymphoma/leukemia gene 2 (BCL2), highlighting a novel role of BCL2 in EMT [34].…”

Section: Breast Cancer Subtypes and Their Association With Emtmentioning

confidence: 99%

Consequences of EMT-Driven Changes in the Immune Microenvironment of Breast Cancer and Therapeutic Response of Cancer Cells

Singh

Chakrabarti

2019

JCM

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Epithelial-to-mesenchymal transition (EMT) is a process through which epithelial cells lose their epithelial characteristics and cell–cell contact, thus increasing their invasive potential. In addition to its well-known roles in embryonic development, wound healing, and regeneration, EMT plays an important role in tumor progression and metastatic invasion. In breast cancer, EMT both increases the migratory capacity and invasive potential of tumor cells, and initiates protumorigenic alterations in the tumor microenvironment (TME). In particular, recent evidence has linked increased expression of EMT markers such as TWIST1 and MMPs in breast tumors with increased immune infiltration in the TME. These immune cells then provide cues that promote immune evasion by tumor cells, which is associated with enhanced tumor progression and metastasis. In the current review, we will summarize the current knowledge of the role of EMT in the biology of different subtypes of breast cancer. We will further explore the correlation between genetic switches leading to EMT and EMT-induced alterations within the TME that drive tumor growth and metastasis, as well as their possible effect on therapeutic response in breast cancer.

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“…Prior study also reported that dysregulation and decrease in NOTCH signaling pathway are associated with endometriosis (Su et al, 2015; González-Foruria et al, 2017). NOTCH3 has also been reported as a major driver for breast cancer development (Braune et al, 2018). It plays an important role in maintaining the tumor phenotype in pancreatic ductal adenocarcinoma (PDAC) (Song et al, 2018), lung carcinogenesis (Su et al, 2018), and endometrial carcinoma (Mitsuhashi et al, 2012).…”

Section: Discussionmentioning

confidence: 99%

Machine Learning Classifiers for Endometriosis Using Transcriptomics and Methylomics Data

Akter

Nagel

et al. 2019

Front. Genet.

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Endometriosis is a complex and common gynecological disorder yet a poorly understood disease affecting about 176 million women worldwide and causing significant impact on their quality of life and economic burden. Neither a definitive clinical symptom nor a minimally invasive diagnostic method is available, thus leading to an average of 4 to 11 years of diagnostic latency. Discovery of relevant biological patterns from microarray expression or next generation sequencing (NGS) data has been advanced over the last several decades by applying various machine learning tools. We performed machine learning analysis using 38 RNA-seq and 80 enrichment-based DNA methylation (MBD-seq) datasets. We experimented how well various supervised machine learning methods such as decision tree, partial least squares discriminant analysis (PLSDA), support vector machine, and random forest perform in classifying endometriosis from the control samples trained on both transcriptomics and methylomics data. The assessment was done from two different perspectives for improving classification performances: a) implication of three different normalization techniques and b) implication of differential analysis using the generalized linear model (GLM). Several candidate biomarker genes were identified by multiple machine learning experiments including NOTCH3, SNAPC2, B4GALNT1, SMAP2, DDB2, GTF3C5, and PTOV1 from the transcriptomics data analysis and TRPM6, RASSF2, TNIP2, RP3-522J7.6, FGD3, and MFSD14B from the methylomics data analysis. We concluded that an appropriate machine learning diagnostic pipeline for endometriosis should use TMM normalization for transcriptomics data, and quantile or voom normalization for methylomics data, GLM for feature space reduction and classification performance maximization.

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Notch and Wnt Dysregulation and Its Relevance for Breast Cancer and Tumor Initiation

Cited by 32 publications

References 142 publications

Notch Signaling Activation as a Hallmark for Triple-Negative Breast Cancer Subtype

Notch Signaling Activation as a Hallmark for Triple-Negative Breast Cancer Subtype

Consequences of EMT-Driven Changes in the Immune Microenvironment of Breast Cancer and Therapeutic Response of Cancer Cells

Machine Learning Classifiers for Endometriosis Using Transcriptomics and Methylomics Data

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