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.

In cancer, mutually exclusive or co-occurring somatic alterations across genes can suggest functional interactions. Existing tests for such patterns make the unrealistic assumption of identical gene alteration probabilities across tumors. We present Discrete Independence Statistic Controlling for Observations with Varying Event Rates (DISCOVER), a novel test that is more sensitive than other methods and controls its false positive rate. A pan-cancer analysis using DISCOVER finds no evidence for widespread co-occurrence, and most co-occurrences previously detected do not exceed expectation by chance. Many mutual exclusivities are identified involving well-known genes related to cell cycle and growth factor signaling, as well as lesser known regulators of Hedgehog signaling.