Bottom-Up Programming of Cell States in Cancer Organoids with Defined Synthetic Adhesion Cues

Area of Science:

• Biomaterials Science
• Cancer Biology
• Stem Cell Biology
• Transcriptomics

Background:

• Current organoid models have limited control over transcriptomic states, restricted by genetic factors or general microenvironments.
• Programmable control over cellular states is crucial for advancing organoid applications in disease modeling and drug discovery.

Purpose of the Study:

• To introduce a novel biomaterial-based platform for programmable control of cell state changes in pancreatic cancer organoids.
• To demonstrate the ability to precisely tune transcriptomic states by modulating adhesion cues within a synthetic matrix.

Main Methods:

• Development of a bottom-up biomaterial platform to present tunable adhesion cues.
• Application of a Design of Experiments framework to model patient-specific transcriptomic responses to adhesion cues.
• Utilizing multiobjective optimization to identify matrix compositions that enrich specific cellular programs like epithelial-mesenchymal transition (EMT).

Main Results:

• Optimized matrices successfully enriched EMT-associated transcriptional programs in pancreatic cancer organoids.
• Organoids exhibited transcriptomic signatures and regulatory shifts consistent with EMT enrichment.
• Secretome profiling indicated changes in cytokines related to inflammation, hypoxia, and TGF-β signaling pathways.

Conclusions:

• Quantitative modulation of defined adhesion cues provides programmable control over transcriptomic states in pancreatic cancer organoids.
• This platform offers a new strategy for engineering organoid models with specific cellular phenotypes for research and therapeutic development.