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Invasive three-dimensional organotypic neoplasia from multiple normal human epithelia
Todd W Ridky1, Jennifer M Chow, David J Wong
1Programs in Epithelial Biology and Cancer Biology, Stanford University, Stanford, California, USA.
Nature Medicine
|November 25, 2010
Summary
Researchers developed advanced 3D human tissue cancer models using genetic pathways. These organotypic models accurately mimic tumor progression and gene expression, aiding rapid therapeutic target assessment.
Area of Science:
- Oncology
- Biotechnology
- Tissue Engineering
Background:
- Developing clinically relevant cancer models is crucial for evaluating novel therapeutics.
- Existing models often lack the complexity and rapid turnaround time needed for target assessment.
Purpose of the Study:
- To engineer a three-dimensional (3D) human tissue cancer model that recapitulates key features of tumor progression.
- To establish a platform for rapid screening of cancer therapeutics and identification of clinically relevant gene signatures.
Main Methods:
- Primary human epithelial cells from various sites were transformed using tumor-associated genetic pathways within a 3D tissue environment.
- The engineered organotypic tissues incorporated cell-populated stroma and intact basement membranes.
- Gene expression profiles were analyzed and compared between 3D models and spontaneous human cancers.
Main Results:
- Engineered tissues exhibited natural tumor progression features, including basement membrane invasion, potentiated by stromal cells.
- Oncogenic signaling in 3D models closely resembled gene expression profiles of spontaneous human cancers, unlike 2D cultures.
- Screening of 3D organotypic neoplasia with pathway inhibitors identified a clinically faithful cancer gene signature.
Conclusions:
- Multitissue 3D human tissue cancer models offer an efficient and relevant complement to existing cancer research approaches.
- These models facilitate the assessment of numerous potential cancer therapeutic targets in a biologically accurate context.
- The developed models show promise for accelerating cancer drug discovery and development.

