Cell shape and the microenvironment regulate nuclear translocation of <scp>NF</scp>‐κB in breast epithelial and tumor cells

Sero, Julia E.; Sailem, Heba; Ardy, Rico Chandra; Almuttaqi, Hannah; Zhang, Tongli; Bakal, Chris

doi:10.15252/msb.20145644

Cited by 117 publications

(149 citation statements)

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“…We speculated that these genes should either regulate cell shape and/or act as part of mechanotransduction pathways that alter gene expression in response to changes in cell shape. To generate these networks, we made use of (1) a data set where we measured shape features in 307,643 cells across 18 BCLs (Supplemental Table S1; Sailem et al 2015;Sero et al 2015), and (2) a data set describing the expression of 28,376 genes across these same 18 BCLs (Grigoriadis et al 2012). Ten morphological features that we have previously shown to be predictive of TF activation were used in our analysis .…”

Section: Resultsmentioning

confidence: 99%

“…Expression profiling in Grigoriadis et al (2012) and image profiling in Sero et al (2015) were performed using the same batches of cell lines and under similar culture conditions. For imaging experiments, 1000 cells per well were seeded in 384-well plates and cultured for three days.…”

Section: Experimental Methodsmentioning

confidence: 99%

“…5A; Neve et al 2006;Sero et al 2015). Clustering of expression profiles of the genes in the SMAD3-NF-κB mechanosensitive subnetwork reveals two main clusters of BCLs that also correlate with BCL luminal and basal subtypes (Fig.…”

Section: Smad3 and Rela Targets That Correlate With Cell Shapementioning

confidence: 97%

“…To test this hypothesis, we defined a metagene that correlates with RELA activation in response to TNF across 18 BCLs which is measured as the ratio between nuclear RELA intensity and cytoplasmic RELA intensity (Methods; Fig. 7A; Sero et al 2015). The response of RELA to TNF is defined as the log of the average RELA ratio (+TNF) divided by the average RELA ratio (−TNF).…”

Section: Nf-κb Activation Metagenementioning

confidence: 99%

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Identification of clinically predictive metagenes that encode components of a network coupling cell shape to transcription by image-omics

Sailem¹,

Bakal²

2016

Genome Res.

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The associations between clinical phenotypes (tumor grade, survival) and cell phenotypes, such as shape, signaling activity, and gene expression, are the basis for cancer pathology, but the mechanisms explaining these relationships are not always clear. The generation of large data sets containing information regarding cell phenotypes and clinical data provides an opportunity to describe these mechanisms. Here, we develop an image-omics approach to integrate quantitative cell imaging data, gene expression, and protein-protein interaction data to systematically describe a "shape-gene network" that couples specific aspects of breast cancer cell shape to signaling and transcriptional events. The actions of this network converge on NF-κB, and support the idea that NF-κB is responsive to mechanical stimuli. By integrating RNAi screening data, we identify components of the shape-gene network that regulate NF-κB in response to cell shape changes. This network was also used to generate metagene models that predict NF-κB activity and aspects of morphology such as cell area, elongation, and protrusiveness. Critically, these metagenes also have predictive value regarding tumor grade and patient outcomes. Taken together, these data strongly suggest that changes in cell shape, driven by gene expression and/or mechanical forces, can promote breast cancer progression by modulating NF-κB activation. Our findings highlight the importance of integrating phenotypic data at the molecular level (signaling and gene expression) with those at the cellular and tissue levels to better understand breast cancer oncogenesis.[Supplemental material is available for this article.]

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Section: Resultsmentioning

confidence: 99%

Section: Experimental Methodsmentioning

confidence: 99%

Section: Smad3 and Rela Targets That Correlate With Cell Shapementioning

confidence: 97%

Section: Nf-κb Activation Metagenementioning

confidence: 99%

See 2 more Smart Citations

Identification of clinically predictive metagenes that encode components of a network coupling cell shape to transcription by image-omics

Sailem¹,

Bakal²

2016

Genome Res.

Self Cite

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“…Apart from this, nuclear factor kappa-B (NF-κB) activation is associated with the spreading parameter of (Nuclear/Cytoplasm) [26]. NF-κB is known to be involved in the inflammatory and tumor development including cellular proliferation, apoptosis and drug sensitivity [8,[25][26][27][28][29]. Additionally several groups reported NF-κB was regulated by actomyosin contractility [27,30,31].…”

Section: Discussionmentioning

confidence: 99%

Cellular Morphology-Mediated Proliferation and Drug Sensitivity of Breast Cancer Cells

Domura¹,

Sasaki²,

Ishikawa³

et al. 2017

Preprint

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Abstract:The interpretation of the local microenvironment of extracellular matrix for malignant tumor cells is in intimate relation with metastatic spread of cancer cells involving the associated issues of cellular proliferation and drug responsiveness. This study was aimed to assess the combination of both surface topographies (fiber alignments) and different stiffness of the polymeric substrates (PLLA and PCL) and collagen substrates (coat and gel) to elucidate the effect of the cellular morphology on cellular proliferation and drug sensitivities of two different types of breast cancer cells (MDA-MB-231 and MCF-7). The morphological spreading parameter of (Nuclear/Cytoplasm) induced by the anthropogenic substrates has correlated intimately with the cellular proliferation and the drug sensitivity (IC50) of cancer cells. This study demonstrated the promising results of the parameter for the evaluation of cancer cell malignancy.

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Benchmarking to the Gold Standard: Hyaluronan‐Oxime Hydrogels Recapitulate Xenograft Models with In Vitro Breast Cancer Spheroid Culture

et al. 2019

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Many 3D in vitro models induce breast cancer spheroid formation; however, this alone does not recapitulate the complex in vivo phenotype. To effectively screen therapeutics, it is urgently needed to validate in vitro cancer spheroid models against the gold standard of xenografts. A new oxime‐crosslinked hyaluronan (HA) hydrogel is designed, manipulating gelation rate and mechanical properties to grow breast cancer spheroids in 3D. This HA‐oxime breast cancer model maintains the gene expression profile most similar to that of tumor xenografts based on a pan‐cancer gene expression profile (comprising 730 genes) of three different human breast cancer subtypes compared to Matrigel or conventional 2D culture. Differences in gene expression between breast cancer cultures in HA‐oxime versus Matrigel or 2D are confirmed for 12 canonical pathways by gene set variation analysis. Importantly, drug response is dependent on the culture method. Breast cancer cells respond better to the Rac inhibitor (EHT‐1864) and the PI3K inhibitor (AZD6482) when cultured in HA‐oxime versus Matrigel. This study demonstrates the superiority of an HA‐based hydrogel as a platform for in vitro breast cancer culture of both primary, patient‐derived cells and cell lines, and provides a hydrogel culture model that closely matches that in vivo.

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Cell shape and the microenvironment regulate nuclear translocation of NF‐κB in breast epithelial and tumor cells

Cited by 117 publications

References 58 publications

Identification of clinically predictive metagenes that encode components of a network coupling cell shape to transcription by image-omics

Identification of clinically predictive metagenes that encode components of a network coupling cell shape to transcription by image-omics

Cellular Morphology-Mediated Proliferation and Drug Sensitivity of Breast Cancer Cells

Benchmarking to the Gold Standard: Hyaluronan‐Oxime Hydrogels Recapitulate Xenograft Models with In Vitro Breast Cancer Spheroid Culture

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