Spectral flow cytometry has emerged as a powerful high-dimensional platform for resolving immune heterogeneity and functional states at the single-cell level. By capturing the full emission spectra of fluorophores and applying computational spectral unmixing, it expands the multiparameter profiling capacity of conventional flow cytometry and enables more comprehensive characterization of immune cell phenotypes and functional states. In this review, we summarize the technological evolution of spectral flow cytometry and discuss how spectral acquisition and computational unmixing support multidimensional analysis of immune composition, cellular states, and functional programs. We then examine its applications in immune ecosystem mapping, tumor immunology, immune development and regeneration, vaccination, autoimmune diseases, and translational immune monitoring, with particular emphasis on biomarker discovery, disease stratification, therapeutic response assessment, and precision immunology. We further discuss the integration of spectral flow cytometry with mass cytometry, artificial intelligence, single-cell transcriptomics and proteomics, spatial profiling, imaging technologies, and functional assays. These multimodal approaches provide complementary phenotypic, molecular, spatial, and functional information, creating opportunities for more comprehensive reconstruction of immune ecosystems and deeper interpretation of cellular states. Despite these advances, challenges remain in standardization and cross-platform reproducibility, autofluorescence management, high-dimensional data analysis, and clinical validation. Future development will therefore require not only continued advances in spectral acquisition and computational analysis but also harmonized workflows, robust analytical frameworks, and effective multimodal integration. Overall, spectral flow cytometry is evolving from a high-parameter immunophenotyping technology into a scalable platform for ecosystem-level immune profiling, providing an important bridge between cellular phenotyping, mechanistic discovery, biomarker development, and precision immunology.
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Zhu et al. (2026) studied this question.
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