Publication / Advanced Microfluidics for Single Cell-Based Cancer Research

A) Models of cancer evolution. The linear model (on top) supports that each mutation is gradually superseded by the next, resulting in a single, dominant tumour clone. The branched model (on the bottom), where mutations extend and increase like the branches of a tree, demonstrates how different subclones evolve in parallel from a common ancestor, leading to intra-tumoral heterogeneity with various subclones coexisting within the tumour. B) Tumour heterogeneity, intravasation and extravasation. Schematic representation of intra-tumoral heterogeneity within the primary tumour, with various sub-clonal populations. It shows the steps of cancer dissemination, including the detachment of cancer cells from the primary tumour, intravasation into the bloodstream as circulating tumour cells (CTCs), and the subsequent extravasation of CTCs into distant tissues, leading to the formation of metastatic lesions. C) Comparison of bulk and single cell analyses. Bulk analyses provide an averaged molecular profile of the tumour, which can miss critical variations among cells. Single-cell analyses capture the diversity of individual cells, uncovering heterogeneous gene expression, detecting rare subpopulations, and offering detailed insights into the cellular architecture and functional states within the tumour

Cancer remains one of the leading causes of mortality worldwide, accounting for ≈10 million deaths annually. Critically, it is metastasis and not the primary tumour that causes most of these deaths. Understanding the mechanisms behind cancer dissemination and therapy resistance is thus a pressing challenge. Traditional bulk tissue analyses have failed to capture the full spectrum of intra-tumour heterogeneity and the dynamic interactions within the tumour microenvironment. Studying cancer at the single-cell level allows unravelling the roles of rare subpopulations, cell–cell interactions, and spatial dynamics that govern tumour evolution, metastasis, and immune evasion. This review explores how recent advances in microfluidic technologies are transforming ability to model and study cancer at the single-cell level. Cutting-edge platforms are highlighted, including droplet microfluidics, single cell-derived spheroids, and tumour-chips, that enable physiologically relevant 3D cancer models. By integrating immune components, biosensing, and patient-derived materials, these platforms hold promise for advancing drug screening, immunotherapy assessment, and personalised medicine. It is concluded by identifying key challenges and priorities for future work, which should focus on increasing model complexity, reproducibility, and integration of spatiotemporal multiomics to better dissect tumour heterogeneity and accelerate clinical translation.

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