The dissemination of primary solid tumor cells to distant organs, termed metastasis, is a major cause of cancer-related deaths. Circulating tumor cells (CTCs), which can exist as individual cells or multicellular clusters, travel through the bloodstream. Their isolation from liquid biopsy samples is increasingly recognized as a valuable tool for diagnosis, prognosis, and treatment guidance for cancer patients. Current isolation methods typically rely on biomarkers like epithelial cell adhesion molecule (EpCAM) and utilize technologies such as magnetic beads or microfluidic chips. However, these methods face limitations due to tumor heterogeneity. Furthermore, tumor cells that transfer into CTCs often undergo epithelial-to-mesenchymal transition, gaining invasive characteristics while losing epithelial markers. As a result, these cells are difficult to detect using EpCAM-based methods. Label-free microscale isolation technologies tackle the limitations of biomarker-based methods by leveraging the distinctive physical properties of CTCs, such as their size, electrical charge, viscoelasticity, and deformability that contrast them from normal blood cells. This review evaluates primary label-free isolation methods, including deterministic lateral displacement, microfiltration, acoustophoresis, and dielectrophoresis, and whether they can offer a deeper insight into tumor heterogeneity and the dynamics of cancer progression and treatment. Additionally, it highlights automated platforms for high-throughput CTC isolation and analysis.

Dielectrophoresis (DEP) is a versatile technique for the solution of difficult (bio-)particle separation tasks based on size and material. Particle motion by DEP requires a highly inhomogeneous electric field. Thus, the throughput of classical DEP devices is limited by restrictions on the channel size to achieve large enough gradients. Here, we investigate dielectrophoretic filtration, in which channel size and separation performance are decoupled because particles are trapped at induced field maxima in a porous separation matrix. By simulating microfluidic model porous media, we derive design rules for DEP filters and verify them using model particles (polystyrene) and biological cells (S. cerevisiae, yeast). Further, we bridge the throughput gap by separating yeast in an alumina sponge and show that the design rules are equally applicable in real porous media at high throughput. While maintaining almost 100% efficiency, we process up to 9 mL min^-1, several orders of magnitude more than most state-of-the-art DEP applications. Our microfluidic approach provides new insight into trapping dynamics in porous media, which even can be applied in real sponges. These results pave the way toward high-throughput retention, which is capable of solving existing problems such as cell separation in liquid biopsy or precious metal recovery.