Spectral cytometry: maximising information with superior overlap control

Conventional flow cytometry has been an essential tool for cell characterisation in immunology, oncology and translational research. However, one of its main limitations remains spectral overlap between fluorochromes, which requires laborious compensation and restricts the complexity of multicolour panels.

Spectral cytometry emerges as a natural evolution: a technology capable of capturing the full emission spectrum of each fluorophore and applying mathematical unmixing algorithms to accurately discriminate signals that would overlap in a conventional cytometer.

How does spectral cytometry work?

Instead of dividing fluorescence into channels restricted by filters, the system acquires continuous spectral information at multiple wavelengths. Subsequently:
1. A reference spectral signature is generated for each fluorochrome.
2. Using spectral unmixing algorithms, the exact contribution of each fluorochrome to the overall signal is assigned.
3. The intrinsic autofluorescence of the sample is also corrected, a critical factor in complex tissues.

Advantages over conventional cytometry

Spectral cytometry offers benefits that directly impact experimental design and data quality:

• Greater number of simultaneous parameters: allows for more than 40 colours in state-of-the-art equipment.
• Reduction of errors due to spectral overlap: improves the resolution of nearby populations.
• Autofluorescence correction: particularly useful in bone marrow samples, solid tissues or cell cultures with high basal fluorescence.
• More efficient use of the fluorochrome repertoire: integration of previously incompatible dyes.
• Flexibility in panel expansion: progressive scaling without redesigning the entire set of markers.

Advanced applications in biomedical research

Spectral cytometry is expanding analytical capabilities in fields where multiparametric resolution is critical:

• Advanced immunology: comprehensive definition of T, B and NK cell subpopulations, with direct applications in immunotherapy.
• Translational oncology: characterisation of heterogeneous tumour microenvironments, identifying minority populations associated with therapeutic resistance.
• CAR-T and cell therapies: accurate monitoring of the expansion and persistence of modified cells, even in samples with high autofluorescence.
• Biomarker discovery: detection of low-intensity signals without losing analytical specificity.

Strategies for designing spectral panels

Although spectral cytometry reduces technical restrictions, panel planning remains a critical step in avoiding redundancy and optimising resolution:
1. Define the biological hypothesis: prioritise key markers for populations of interest.
2. Select fluorochromes with well-characterised spectra: rely on reference libraries.
3. Include specific unmixing controls for each fluorochrome, even if they are used infrequently.
4. Validate reproducibility: repeat under different conditions to ensure robustness.
5. Gradually scale up the panel, incorporating new markers after validating the initial set.

Conclusion

Flow cytometry is establishing itself as a new standard in multiparametric cell analysis. By allowing more information to be extracted with less overlap, it offers researchers the possibility of exploring complex biological systems with an unprecedented level of resolution.
For professionals in immunology, oncology, or advanced therapies, implementing this technology not only expands the experimental scope but also opens up new opportunities in biomarker discovery and the clinical validation of emerging therapies.