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SERS in 3D cell models: a powerful tool in cancer research
Lara Troncoso-Afonso1,2, Gail A Vinnacombe-Willson1, Clara García-Astrain1,3
1BioNanoPlasmonics Laboratory, CIC biomaGUNE, Basque Research and Technology Alliance (BRTA), 20014 Donostia-San Sebastián, Spain. llizmarzan@cicbiomagune.es.
Chemical Society Reviews
|April 12, 2024
Summary
Surface-enhanced Raman spectroscopy (SERS) offers a non-invasive method for analyzing 3D cancer models, crucial for advancing cancer diagnosis and therapy. This technique enables detailed cellular and molecular insights previously unattainable with destructive methods.
Area of Science:
- Biomedical Engineering
- Analytical Chemistry
- Cancer Research
Background:
- Understanding cancer requires studying cellular and molecular mechanisms.
- Three-dimensional (3D) cancer models offer more realistic tumor mimicry than 2D cultures.
- Current analysis techniques for 3D models are often destructive, losing vital biochemical data.
Purpose of the Study:
- To review the application of Surface-Enhanced Raman Spectroscopy (SERS) in 3D cancer models for diagnosis and therapy.
- To explore SERS's potential for tracking therapeutics, metabolites, and signaling pathways.
- To highlight SERS's utility in bioimaging cellular components and structural features within 3D tumor models.
Main Methods:
- Utilizing Surface-Enhanced Raman Spectroscopy (SERS) as a non-invasive analytical tool.
- Implementing SERS for biosensing and bioimaging in three-dimensional (3D) cancer models.
- Reviewing strategies for SERS tag design and delivery for enhanced performance.
Main Results:
- SERS provides a molecular fingerprint of complex biological environments without sample destruction.
- SERS enables tracking of therapeutics and cancer-related metabolites in 3D models.
- SERS facilitates imaging of cellular components and structural features, offering insights into signaling pathways.
Conclusions:
- SERS is a powerful technique for evaluating cancer diagnosis and therapy in realistic 3D tumoral models.
- Further development of SERS systems and data analysis methods is needed to overcome current limitations.
- Advancements in SERS-based 3D bioimaging and biosensing promise significant contributions to early disease detection, novel therapies, and personalized medicine.
