ReviewIntegrative biology : quantitative biosciences from nano to macro2013
Building risk-on-a-chip models to improve breast cancer risk assessment and prevention.
Review in Integrative biology : quantitative biosciences from nano to macro, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- Application and prospects of lung organ-on-a-chip in the development of new drugs.Biomedical engineering online · 2025Review
- Tumor-on-chip platforms for breast cancer continuum concept modeling.Frontiers in bioengineering and biotechnology · 2024Review
- Modeling chemical effects on breast cancer: the importance of the microenvironment in vitro.Integrative biology : quantitative biosciences from nano to macro · 2020Review
- Sacrificial Bioprinting of a Mammary Ductal Carcinoma Model.Biotechnology journal · 2019Article
- Architecture in 3D cell culture: An essential feature for in vitro toxicology.Toxicology in vitro : an international journal published in association with BIBRA · 2017Review
- Personal samplers of bioavailable pesticides integrated with a hair follicle assay of DNA damage to assess environmental exposures and their associated risks in children.Mutation research. Genetic toxicology and environmental mutagenesis · 2017Article
- A microengineered pathophysiological model of early-stage breast cancer.Lab on a chip · 2015Article
- Taking a chance on epigenetics.Frontiers in genetics · 2014Article
- Suitable trial designs and cohorts for preventive breast cancer agents.Nature reviews. Clinical oncology · 2013Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Preventive actions for chronic diseases hold the promise of improving lives and reducing healthcare costs. For several diseases, including breast cancer, multiple risk and protective factors have been identified by epidemiologists. The impact of most of these factors has yet to be fully understood at the organism, tissue, cellular and molecular levels. Importantly, combinations of external and internal risk and protective factors involve cooperativity thus, synergizing or antagonizing disease onset. Models are needed to mechanistically decipher cancer risks under defined cellular and microenvironmental conditions. Here, we briefly review breast cancer risk models based on 3D cell culture and propose to improve risk modeling with lab-on-a-chip approaches. We suggest epithelial tissue polarity, DNA repair and epigenetic profiles as endpoints in risk assessment models and discuss the development of 'risks-on-chips' integrating biosensors of these endpoints and of general tissue homeostasis. Risks-on-chips will help identify biomarkers of risk, serve as screening platforms for cancer preventive agents, and provide a better understanding of risk mechanisms, hence resulting in novel developments in disease prevention.
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.