Diverse regulation of mammary epithelial growth and branching morphogenesis through noncanonical Wnt signaling

Kessenbrock, Kai; Smith, Prestina; Steenbeek, Sander Christiaan; Pervolarakis, Nicholas; Kumar, Raj; Minami, Yasuhiro; Goga, Andrei; Hinck, Lindsay; Werb, Zena

doi:10.1073/pnas.1701464114

Cited by 57 publications

(58 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This effect was dependent on differential expression of non-canonical Wnt coreceptors such as Ror2and Ryk. Wnt5a interaction with Ror2 resulted in inhibition of mammary epithelial branching, while its interaction with Ryk promoted mammosphere formation[249]. Thus, in addition to the presence of Wnt ligand, the expression of Wnt coreceptors contribute to differential function during mammary gland development.…”

mentioning

confidence: 99%

Notch-Induced Expression of FZD7 Requires Noncanonical NOTCH3 Signaling in Human Breast Epithelial Cells

Bhat

Sun

Weger

et al. 2016

Stem Cells and Development

View full text Add to dashboard Cite

The evolutionarily conserved Notch and Wnt signaling pathways have demonstrated roles in normal mammary gland development and in breast carcinogenesis. We previously reported that in human mammary gland, signaling through NOTCH3 alone regulates the commitment of the undifferentiated bipotential progenitors to the luminal cell fate, indicating that NOTCH3 may regulate the expression of unique genes apart from the other Notch receptors. In this study, we used gain of function and loss of function experiments and found that a Wnt signaling receptor, Frizzled7 (FZD7), is a unique and nonredundant target of NOTCH3 in human breast epithelial cells. Interestingly, neither the constitutively active forms of NOTCH1-2, 4 nor loss of expression of these receptors were able to alter expression of FZD7 in human breast epithelial cells. We further show that FZD7-expressing cells are found more frequently in the luminal progenitor-enriched subpopulation of cells obtained from breast reduction samples compared with the undifferentiated bipotent progenitors. Also, we show that NOTCH3-induced expression of FZD7 occurs in the absence of CSL (CBF1-Suppressor of Hairless-Lag-1). Our data suggest that noncanonical Notch signaling through NOTCH3 could modulate Wnt signaling via FZD7 and in this way, might be involved in luminal cell differentiation.

show abstract

mentioning

confidence: 99%

Notch-Induced Expression of FZD7 Requires Noncanonical NOTCH3 Signaling in Human Breast Epithelial Cells

Bhat

Sun

Weger

et al. 2016

Stem Cells and Development

View full text Add to dashboard Cite

show abstract

“…Supplementary Table 9 shows ten highest ranked communities by CRANK. The highest ranked community is composed of 20 genes, including PORCN, AQP5, FZD6, WNT1, WNT2, WNT3, and other members of the Wnt signaling protein family 81 . Genes in that community are enriched in the Wnt signaling pathway processes (p-value = 6.4 ⇥ 10 23 ), neuron differentiation (p-value = 1.6 ⇥ 10 15 ), cellular response to retinoic S44 acid (p-value = 2.9⇥10 14 ), and in developmental processes (p-value = 9.2⇥10 10 ), among others.…”

Section: Methodsmentioning

confidence: 99%

Prioritizing network communities

2018

View full text Add to dashboard Cite

Uncovering modular structure in networks is fundamental for systems in biology, physics, and engineering. Community detection identifies candidate modules as hypotheses, which then need to be validated through experiments, such as mutagenesis in a biological laboratory. Only a few communities can typically be validated, and it is thus important to prioritize which communities to select for downstream experimentation. Here we develop CRank, a mathematically principled approach for prioritizing network communities. CRank efficiently evaluates robustness and magnitude of structural features of each community and then combines these features into the community prioritization. CRank can be used with any community detection method. It needs only information provided by the network structure and does not require any additional metadata or labels. However, when available, CRank can incorporate domain-specific information to further boost performance. Experiments on many large networks show that CRank effectively prioritizes communities, yielding a nearly 50-fold improvement in community prioritization.

show abstract

“…Considering highest ranked gene communities, CRANK's ranking contains on average 5 times more communities whose genes are significantly enriched for cellular functions, components, and processes 16 than random prioritization, and 13% more significantly enriched communities than modularity-or conductance-based ranking (SI Text, Section S11.4). For example, in the human protein-protein interaction network, the highest ranked community by CRANK is composed of 20 genes, including PORCN, AQP5, FZD6, WNT1, WNT2, WNT3, and other members of the Wnt signaling protein family 26 (SI Text, Section S11.4). Genes in that community form a biologically meaningful group that is functionally enriched in the Wnt signaling pathway processes (p-value = 6.4 × 10 −23 ), neuron differentiation (p-value = 1.6 × 10 −15 ), cellular response to retinoic acid (p-value = 2.9 × 10 −14 ), and in developmental processes (p-value = 9.2 × 10 −10 ).…”

Section: Gene and Protein Interaction Networkmentioning

confidence: 99%

Prioritizing network communities

Žitnik

Sosič

Leskovec

2018

Preprint

View full text Add to dashboard Cite

Uncovering modular structure in networks is fundamental for advancing the understanding of complex systems in biology, physics, engineering, and technology. Community detection provides a way to computationally identify candidate modules as hypotheses, which then need to be experimentally validated. However, validation of detected communities requires expensive and time consuming experimental methods, such as mutagenesis in a wet biological laboratory. As a consequence only a limited number of communities can be experimentally validated, and it is thus important to determine which communities to select for downstream validation and experimentation. Here we develop CRANK, an automatic method for prioritizing network communities and identifying the most promising ones for further experimentation. CRANK efficiently evaluates robustness and magnitude of structural features of each community and then combines these features to obtain the community prioritization. CRANK can be used with any community detection method and scales to large networks. It needs only information provided by the network structure and does not require any additional metadata or labels. However, when available, CRANK can incorporate domain-specific information to further boost performance. Experiments on many diverseand important biological networks demonstrate that the proposed approach effectively prioritizes communities, yielding a near 50-fold improvement in community prioritization over a baseline ordering of detected communities. Taken together, CRANK represents a networkbased approach to identify high-quality communities, even for domains at the frontier of science where supervised meta information is not available.

show abstract

Diverse regulation of mammary epithelial growth and branching morphogenesis through noncanonical Wnt signaling

Cited by 57 publications

References 37 publications

Notch-Induced Expression of FZD7 Requires Noncanonical NOTCH3 Signaling in Human Breast Epithelial Cells

Notch-Induced Expression of FZD7 Requires Noncanonical NOTCH3 Signaling in Human Breast Epithelial Cells

Prioritizing network communities

Prioritizing network communities

Contact Info

Product

Resources

About