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Metastasis is a dynamic succession of events involving the dissemination of tumour cells to distant sites within the body, ultimately reducing the survival of patients with cancer. To colonize distant organs and, therefore, systemically disseminate within the organism, cancer cells and associated factors exploit several bodily fluid systems, which provide a natural transportation route. Indeed, the flow mechanics of the blood and lymphatic circulatory systems can be co-opted to improve the efficiency of cancer cell transit from the primary tumour, extravasation and metastatic seeding. Flow rates, vessel size and shear stress can all influence the survival of cancer cells in the circulation and control organotropic seeding patterns. Thus, in addition to using these fluids as a means to travel throughout the body, cancer cells exploit the underlying physical forces within these fluids to successfully seed distant metastases. In this Review, we describe how circulating tumour cells and tumour-associated factors leverage bodily fluids, their underlying forces and imposed stresses during metastasis. As the contribution of bodily fluids and their mechanics raises interesting questions about the biology of the metastatic cascade, an improved understanding of this process might provide a new avenue for targeting cancer cells in transit.This Review discusses the role of bodily fluids and their underlying forces and imposed stresses in metastasis, highlighting the contributions of fluid mechanics to tumour cell intravasation, intravascular arrest and extravasation as well as to dissemination of tumour-derived factors.

Cancer's notorious heterogeneity poses significant challenges, as each tumor comprises a unique ecosystem. While single‐cell and spatial transcriptomics advancements have transformed our understanding of spatial diversity within tumors, the temporal dimension remains underexplored. Tumors are dynamic entities that continuously evolve and adapt, and relying solely on static snapshots obscures the intricate interplay between cancer cells and their microenvironment. Here, we advocate for integrating temporal dynamics into cancer research, emphasizing a fundamental shift from traditional endpoint experiments to data‐driven, continuous approaches. This integration involves, for instance, the development of advanced live imaging techniques, innovative temporal omics methodologies, and novel computational tools. This article advocates integrating temporal dynamics into cancer research. Rather than relying on static snapshots, researchers should increasingly consider adopting dynamic methods—such as live imaging, temporal omics, and liquid biopsies—to track how tumors evolve over time. These continuous approaches could reveal hidden patterns in cancer progression and metastasis, paving the way for more effective, personalized treatments.

Live-cell super-resolution microscopy enables the imaging of biological structure dynamics below the diffraction limit. Here we present enhanced super-resolution radial fluctuations (eSRRF), substantially improving image fidelity and resolution compared to the original SRRF method. eSRRF incorporates automated parameter optimization based on the data itself, giving insight into the trade-off between resolution and fidelity. We demonstrate eSRRF across a range of imaging modalities and biological systems. Notably, we extend eSRRF to three dimensions by combining it with multifocus microscopy. This realizes live-cell volumetric super-resolution imaging with an acquisition speed of ~1 volume per second. eSRRF provides an accessible super-resolution approach, maximizing information extraction across varied experimental conditions while minimizing artifacts. Its optimal parameter prediction strategy is generalizable, moving toward unbiased and optimized analyses in super-resolution microscopy. Enhanced super-resolution radial fluctuations (eSRRF) offers improved image fidelity and resolution compared to the popular SRRF method and further enables volumetric live-cell super-resolution imaging at high speeds.

Tumor progression and metastatic dissemination are driven by cell-intrinsic and biomechanical cues that favor the growth of life-threatening secondary tumors. We recently identified pro-metastatic vascular regions with blood flow profiles that are permissive for the arrest of circulating tumor cells. We have further established that such flow profiles also control endothelial remodeling, which favors extravasation of arrested CTCs. Yet, how shear forces control endothelial remodeling is unknown. In the present work, we aimed at dissecting the cellular and molecular mechanisms driving blood flow-dependent endothelial remodeling. Transcriptomic analysis of endothelial cells revealed that blood flow enhanced VEGFR signaling, among others. Using a combination of in vitro microfluidics and intravital imaging in zebrafish embryos, we now demonstrate that the early flow-driven endothelial response can be prevented upon specific inhibition of VEGFR tyrosine kinase and subsequent signaling. Inhibitory targeting of VEGFRs reduced endothelial remodeling and subsequent metastatic extravasation. These results confirm the importance of VEGFR-dependent endothelial remodeling as a driving force of CTC extravasation and metastatic dissemination. Furthermore, the present work suggests that therapies targeting endothelial remodeling might be a relevant clinical strategy in order to impede metastatic progression.

Despite abundant evidence demonstrating that platelets foster metastasis, anti-platelet agents have low therapeutic potential due to the risk of hemorrhages. In addition, whether platelets can regulate metastasis at the late stages of the disease remains unknown. In this study, we subject syngeneic models of metastasis to various thrombocytopenic regimes to show that platelets provide a biphasic contribution to metastasis. While potent intravascular binding of platelets to tumor cells efficiently promotes metastasis, platelets further support the outgrowth of established metastases via immune suppression. Genetic depletion and pharmacological targeting of the glycoprotein VI (GPVI) platelet-specific receptor in humanized mouse models efficiently reduce the growth of established metastases, independently of active platelet binding to tumor cells in the bloodstream. Our study demonstrates therapeutic efficacy when targeting animals bearing growing metastases. It further identifies GPVI as a molecular target whose inhibition can impair metastasis without inducing collateral hemostatic perturbations. It is unclear if platelets regulate the growth of established metastases. Using syngeneic mouse models of metastasis, the authors show that platelets support the outgrowth of established metastases via immune suppression, and that targeting the platelet-specific receptor GPVI, efficiently reduces established metastases, providing a promising therapeutic avenue for inhibiting cancer metastasis.

Zika virus (ZIKV) invades and persists in the central nervous system (CNS), causing severe neurological diseases. However the virus journey, from the bloodstream to tissues through a mature endothelium, remains unclear. Here, we show that ZIKV-infected monocytes represent suitable carriers for viral dissemination to the CNS using human primary monocytes, cerebral organoids derived from embryonic stem cells, organotypic mouse cerebellar slices, a xenotypic human-zebrafish model, and human fetus brain samples. We find that ZIKV-exposed monocytes exhibit higher expression of adhesion molecules, and higher abilities to attach onto the vessel wall and transmigrate across endothelia. This phenotype is associated to enhanced monocyte-mediated ZIKV dissemination to neural cells. Together, our data show that ZIKV manipulates the monocyte adhesive properties and enhances monocyte transmigration and viral dissemination to neural cells. Monocyte transmigration may represent an important mechanism required for viral tissue invasion and persistence that could be specifically targeted for therapeutic intervention. Zika virus (ZIKV) can infect the central nervous system, but it is not clear how it reaches the brain. Here, Ayala-Nunez et al. show in ex vivo and in vivo models that ZIKV can hitch a ride in monocytes in a Trojan Horse manner to cross the endothelium and disseminate the virus.

The ability of cells to migrate is a fundamental physiological process involved in embryonic development, tissue homeostasis, immune surveillance, and wound healing. Therefore, the mechanisms governing cellular locomotion have been under intense scrutiny over the last 50 years. One of the main tools of this scrutiny is live-cell quantitative imaging, where researchers image cells over time to study their migration and quantitatively analyze their dynamics by tracking them using the recorded images. Despite the availability of computational tools, manual tracking remains widely used among researchers due to the difficulty setting up robust automated cell tracking and large-scale analysis. Here we provide a detailed analysis pipeline illustrating how the deep learning network StarDist can be combined with the popular tracking software TrackMate to perform 2D automated cell tracking and provide fully quantitative readouts. Our proposed protocol is compatible with both fluorescent and widefield images. It only requires freely available and open-source software (ZeroCostDL4Mic and Fiji), and does not require any coding knowledge from the users, making it a versatile and powerful tool for the field. We demonstrate this pipeline's usability by automatically tracking cancer cells and T cells using fluorescent and brightfield images. Importantly, we provide, as supplementary information, a detailed step-by-step protocol to allow researchers to implement it with their images.

The ability of cells to migrate is a fundamental physiological process involved in embryonic development, tissue homeostasis, immune surveillance, and wound healing. Therefore, the mechanisms governing cellular locomotion have been under intense scrutiny over the last 50 years. One of the main tools of this scrutiny is live-cell quantitative imaging, where researchers image cells over time to study their migration and quantitatively analyze their dynamics by tracking them using the recorded images. Despite the availability of computational tools, manual tracking remains widely used among researchers due to the difficulty setting up robust automated cell tracking and large-scale analysis. Here we provide a detailed analysis pipeline illustrating how the deep learning network StarDist can be combined with the popular tracking software TrackMate to perform 2D automated cell tracking and provide fully quantitative readouts. Our proposed protocol is compatible with both fluorescent and widefield images. It only requires freely available and open-source software (ZeroCostDL4Mic and Fiji), and does not require any coding knowledge from the users, making it a versatile and powerful tool for the field. We demonstrate this pipeline's usability by automatically tracking cancer cells and T cells using fluorescent and brightfield images. Importantly, we provide, as supplementary information, a detailed step-by-step protocol to allow researchers to implement it with their images.

The expanding scale and complexity of microscopy image datasets require accelerated analytical workflows. NanoPyx meets this need through an adaptive framework enhanced for high-speed analysis. At the core of NanoPyx, the Liquid Engine dynamically generates optimized central processing unit and graphics processing unit code variations, learning and predicting the fastest based on input data and hardware. This data-driven optimization achieves considerably faster processing, becoming broadly relevant to reactive microscopy and computing fields requiring efficiency. NanoPyx optimizes bioimage analysis workflows by dynamically selecting code variations based on input data and hardware. This ensures maximum computational efficiency, enabling fast analysis of large datasets and real-time reactive microscopy.