Gastrointestinal (GI) cancers constitute a group of highest morbidity worldwide, with colorectal cancer (CRC) and gastric cancer being among the most frequently diagnosed. The majority of gastrointestinal cancer patients already present metastasis by the time of diagnosis, which is widely associated with cancer-related death. Accumulating evidence suggests that epithelial-to-mesenchymal transition (EMT) in cancer promotes circulating tumor cell (CTCs) formation, which ultimately drives metastasis development. These cells have emerged as a fundamental tool for cancer diagnosis and monitoring, as they reflect tumor heterogeneity and the clonal evolution of cancer in real-time. In particular, EMT phenotypes are commonly associated with therapy resistance. Thus, capturing these CTCs is expected to reveal important clinical information. However, currently available CTC isolation approaches are suboptimal and are often targeted to capture epithelial CTCs, leading to the loss of EMT or mesenchymal CTCs. Here, we describe size-based CTCs isolation using the RUBYchip™, a label-free microfluidic device, aiming to detect EMT biomarkers in CTCs from whole blood samples of GI cancer patients. We found that, for most cases, the mesenchymal phenotype was predominant, and in fact a considerable fraction of isolated CTCs did not express epithelial markers. The RUBYchip™ can overcome the limitations of label-dependent technologies and improve the identification of CTC subpopulations that may be related to different clinical outcomes.

Cancer is a leading cause of death worldwide, with metastasis playing a significant role. Circulating Tumour Cells (CTCs) can provide important real-time insights into tumour heterogeneity and clonal evolution, making them an important tool for early diagnosis and patient monitoring. Isolated CTCs are typically identified by immunocytochemistry using positive biomarkers (cytokeratin) and exclusion biomarkers (CD45). However, some white blood cell (WBC) populations can express low levels of CD45 and stain non-specifically for cytokeratin, increasing their risk of misclassification as CTCs. There is a clear need to improve CTC detection and enumeration criteria to unequivocally eliminate interfering WBC populations. This study showed that, indeed, some granulocyte subpopulations expressed low levels of CD45 and stained non-specifically for cytokeratin, misidentifying them as CTCs. These same cells, however, strongly expressed CD15, allowing them to be identified as WBCs and excluded from CTC classification. Flow cytometry confirmed the specificity of the CD15 antibody for the granulocyte subpopulation. False positives were considerably reduced from 25 % to 0.2 % by double exclusion, combining a CD15 antibody with a highly specific CD45 antibody. Furthermore, complete elimination of potential false positives was achieved using double exclusion in combination with improved selection of cytokeratin antibody. The study emphasises the importance of a robust exclusion criteria and high antibody specificity in CTC immuno-assays for accurate identification of CTC candidates and thorough exclusion of interfering WBC subpopulations. This study demonstrated how misidentifying a granulocyte subpopulation can lead to inaccurate CTC evaluation. However, sensitivity and specificity of CTC identification may be improved by using high-performing antibodies and by including a second exclusion biomarker, in turn, allowing for a more comprehensive clinical application of CTCs.

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.