ArticlePloS one2010
Dynamic, large-scale profiling of transcription factor activity from live cells in 3D culture.
Article in PloS one, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
23 citing papers in PubMed, 29 citations in OpenAlex.
- Article
- Nanoparticle dose and antigen loading attenuate antigen-specific T-cell responses.Biotechnology and bioengineering · 2023Article
- Towards systems tissue engineering: Elucidating the dynamics, spatial coordination, and individual cells driving emergent behaviors.Biomaterials · 2020Review
- Cargo-less nanoparticles program innate immune cell responses to toll-like receptor activation.Biomaterials · 2019Article
- Synergy of Paracrine Signaling During Early-Stage Mouse Ovarian Follicle DevelopmentCellular and molecular bioengineering · 2018Article
- Design of Large-Scale Reporter Construct Arrays for Dynamic, Live Cell Systems Biology.ACS synthetic biology · 2018Article
- Embryonic stem cell secreted factors decrease invasiveness of triple-negative breast cancer cells through regulome modulation.Cancer biology & therapy · 2018Article
- Synergistic effect of eribulin and CDK inhibition for the treatment of triple negative breast cancer.Oncotarget · 2017Article
- Secretome identification of immune cell factors mediating metastatic cell homing.Scientific reports · 2015Article
- Dynamic transcription factor activity and networks during ErbB2 breast oncogenesis and targeted therapy.Integrative biology : quantitative biosciences from nano to macro · 2014Article
- Lentiviral arrays for live-cell dynamic monitoring of gene and pathway activity during stem cell differentiation.Molecular therapy : the journal of the American Society of Gene Therapy · 2014Article
- Dynamic transcription factor activity profiles reveal key regulatory interactions during megakaryocytic and erythroid differentiation.Biotechnology and bioengineering · 2014Article
- In vivo fate mapping of cryopreserved murine ovarian grafts.Journal of ovarian research · 2014Article
- Inhibition of CDK-mediated phosphorylation of Smad3 results in decreased oncogenesis in triple negative breast cancer cells.Cell cycle (Georgetown, Tex.) · 2014Article
- Article
- Polysaccharide-modified scaffolds for controlled lentivirus delivery in vitro and after spinal cord injury.Journal of controlled release : official journal of the Controlled Release Society · 2013Article
- Non-invasive molecular imaging for preclinical cancer therapeutic development.British journal of pharmacology · 2013Review
- Transcription factor networks in invasion-promoting breast carcinoma-associated fibroblasts.Cancer microenvironment : official journal of the International Cancer Microenvironment Society · 2013Article
- Dynamic transcription factor activity profiling in 2D and 3D cell cultures.Biotechnology and bioengineering · 2013Article
- Dynamic transcription factor networks in epithelial-mesenchymal transition in breast cancer models.PloS one · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
backgroundExtracellular activation of signal transduction pathways and their downstream target transcription factors (TFs) are critical regulators of cellular processes and tissue development. The intracellular signaling network is complex, and techniques that quantify the activities of numerous pathways and connect their activities to the resulting phenotype would identify the signals and mechanisms regulating tissue development. The ability to investigate tissue development should capture the dynamic pathway activity and requires an environment that supports cellular organization into structures that mimic in vivo phenotypes. Taken together, our objective was to develop cellular arrays for dynamic, large-scale quantification of TF activity as cells organized into spherical structures within 3D culture. METHODOLOGY/PRINCIPAL
findingsTF-specific and normalization reporter constructs were delivered in parallel to a cellular array containing a well-established breast cancer cell line cultured in Matrigel. Bioluminescence imaging provided a rapid, non-invasive, and sensitive method to quantify luciferase levels, and was applied repeatedly on each sample to monitor dynamic activity. Arrays measuring 28 TFs identified up to 19 active, with 13 factors changing significantly over time. Stimulation of cells with β-estradiol or activin A resulted in differential TF activity profiles evolving from initial stimulation of the ligand. Many TFs changed as expected based on previous reports, yet arrays were able to replicate these results in a single experiment. Additionally, arrays identified TFs that had not previously been linked with activin A. CONCLUSIONS/SIGNIFICANCE: This system provides a method for large-scale, non-invasive, and dynamic quantification of signaling pathway activity as cells organize into structures. The arrays may find utility for investigating mechanisms regulating normal and abnormal tissue growth, biomaterial design, or as a platform for screening therapeutics.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.