ArticleIntegrative biology : quantitative biosciences from nano to macro2016
Self-assembly of vascularized tissue to support tumor explants in vitro.
Article in Integrative biology : quantitative biosciences from nano to macro, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed.
- Immortalized smooth muscle cells enhance in vitro vasculogenesis.Angiogenesis · 2026Article
- Immortalized smooth muscle cells enhance in vitro vasculogenesis.Research square · 2026Article
- Advances and challenges in human 3D solid tumor models.Advanced functional materials · 2025Article
- Microfluidic Modulation of Microvasculature in Microdissected Tumors.bioRxiv : the preprint server for biology · 2024Article
- Making In Vitro Tumor Models Whole Again.Advanced healthcare materials · 2023Review
- Inhibition of CXCR4 Enhances the Efficacy of Radiotherapy in Metastatic Prostate Cancer Models.Cancers · 2023Article
- A Self-Assembly Method for Creating Vascularized Tumor Explants Using Biomaterials for 3D Culture.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Towards principled design of cancer nanomedicine to accelerate clinical translation.Materials today. Bio · 2022Review
- A model of guided cell self-organization for rapid and spontaneous formation of functional vessels.Science advances · 2019Article
- Vascular beds maintain pancreatic tumour explants for ex vivo drug screening.Journal of tissue engineering and regenerative medicine · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Testing the efficacy of cancer drugs requires functional assays that recapitulate the cell populations, anatomy and biological responses of human tumors. Although current animal models and in vitro cell culture platforms are informative, they have significant shortcomings. Mouse models can reproduce tissue-level and systemic responses to tumor growth and treatments observed in humans, but xenografts from patients often do not grow, or require months to develop. On the other hand, current in vitro assays are useful for studying the molecular bases of tumorigenesis or drug activity, but often lack the appropriate in vivo cell heterogeneity and natural microenvironment. Therefore, there is a need for novel tools that allow rapid analysis of patient-derived tumors in a robust and representative microenvironment. We have developed methodology for maintaining harvested tumor tissue in vitro by placing them in a support bed with self-assembled stroma and vasculature. The harvested biopsy or tumor explant integrates with the stromal bed and vasculature, providing the correct extracellular matrix (collagen I, IV, fibronectin), associated stromal cells, and a lumenized vessel network. Our system provides a new tool that will allow ex vivo drug-screening and can be adapted for the guidance of patient-specific therapeutic strategies.
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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.