ReviewBiomaterials2016
Heralding a new paradigm in 3D tumor modeling.
Review in Biomaterials, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 80 papers, 1 of them a synthesis that pooled it.
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
80 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Relevance of humanized three-dimensional tumor tissue models: a descriptive systematic literature review.Cellular and molecular life sciences : CMLS · 2020Pooled it
- Review
- Exploring bone-tumor interactions through 3DJournal of bone oncology · 2025Review
- Engineered Age-Mimetic Breast Cancer Models Reveal Differential Drug Responses in Young and Aged Microenvironments.Advanced healthcare materials · 2025Article
- Energy Metabolism Behavior and Response to Microenvironmental Factors of the Experimental Cancer Cell Models Differ from that of Actual Human Tumors.Mini reviews in medicinal chemistry · 2025Review
- 3D bioprinted breast cancer model reveals stroma-mediated modulation of extracellular matrix and radiosensitivity.Bioactive materials · 2024Article
- Engineered Age-Mimetic Breast Cancer Models Reveal Differential Drug Responses in Young and Aged Microenvironments.bioRxiv : the preprint server for biology · 2024Article
- Three-dimensional breast cancer tumor models based on natural hydrogels: a review.Journal of Zhejiang University. Science. B · 2024Review
- Aged breast matrix bound vesicles promote breast cancer invasiveness.Biomaterials · 2024Article
- Engineered 3D ex vivo models to recapitulate the complex stromal and immune interactions within the tumor microenvironment.Biomaterials · 2024Review
- Advances in screening hyperthermic nanomedicines in 3D tumor models.Nanoscale horizons · 2024Review
- Organoid co-culture models of the tumor microenvironment promote precision medicine.Cancer innovation · 2024Review
- Engineering Heterogeneous Tumor Models for Biomedical Applications.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Review
- Contribution of the ELRs to the development of advancedFrontiers in bioengineering and biotechnology · 2024Review
- Hybrid-integrated devices for mimicking malignant brain tumors ("tumor-on-a-chip") forFrontiers in medicine · 2024Review
- Microphysiological systems as reliable drug discovery and evaluation tools: Evolution from innovation to maturity.Biomicrofluidics · 2023Review
- Elastin-like Recombinamer Hydrogels as Platforms for Breast Cancer Modeling.Biomacromolecules · 2023Article
- A Simple and Fast Method for the Formation and Downstream Processing of Cancer-Cell-Derived 3D Spheroids: An Example Using Nicotine-Treated A549 Lung Cancer 3D Spheres.Methods and protocols · 2023Article
- Three Dimensional Models of Endocrine Organs and Target Tissues Regulated by the Endocrine System.Cancers · 2023Review
- Prostate cancer and bone: clinical presentation and molecular mechanisms.Endocrine-related cancer · 2023Review
20 more citing papers are in PubMed but not listed here.
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
Numerous studies to date have contributed to a paradigm shift in modeling cancer, moving from the traditional two-dimensional culture system to three-dimensional (3D) culture systems for cancer cell culture. This led to the inception of tumor engineering, which has undergone rapid advances over the years. In line with the recognition that tumors are not merely masses of proliferating cancer cells but rather, highly complex tissues consisting of a dynamic extracellular matrix together with stromal, immune and endothelial cells, significant efforts have been made to better recapitulate the tumor microenvironment in 3D. These approaches include the development of engineered matrices and co-cultures to replicate the complexity of tumor-stroma interactions in vitro. However, the tumor engineering and cancer biology fields have traditionally relied heavily on the use of cancer cell lines as a cell source in tumor modeling. While cancer cell lines have contributed to a wealth of knowledge in cancer biology, the use of this cell source is increasingly perceived as a major contributing factor to the dismal failure rate of oncology drugs in drug development. Backing this notion is the increasing evidence that tumors possess intrinsic heterogeneity, which predominantly homogeneous cancer cell lines poorly reflect. Tumor heterogeneity contributes to therapeutic resistance in patients. To overcome this limitation, cancer cell lines are beginning to be replaced by primary tumor cell sources, in the form of patient-derived xenografts and organoids cultures. Moving forward, we propose that further advances in tumor engineering would require that tumor heterogeneity (tumor variants) be taken into consideration together with tumor complexity (tumor-stroma interactions). In this review, we provide a comprehensive overview of what has been achieved in recapitulating tumor complexity, and discuss the importance of incorporating tumor heterogeneity into 3D in vitro tumor models. This work carves out the roadmap for 3D tumor engineering and highlights some of the challenges that need to be addressed as we move forward into the next chapter.
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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.