Catharina Hagerling

Metastatic cancer remains largely incurable and is responsible for the majority of cancer-related deaths. Despite this, therapeutic strategies are still predominantly guided by insights from primary tumors, often overlooking the distinct biological features of clinical metastases. In this Review, we provide an overview of current knowledge on clinical metastatic cancer, spanning dissemination, dormancy, colonization, and therapy resistance. We examine the genomic evolution of metastatic clones, including evidence for both early and late dissemination, as well as the impact of treatment-driven selection. Furthermore, we highlight how organ-specific microenvironments shape metastatic outgrowth and therapeutic response and explore how wound-healing and regenerative programs are co-opted during colonization. Finally, we discuss clinical perspectives on treating metastases and outline how advances in single-cell and spatial multi-omics technologies are transforming our ability to interrogate metastatic disease at high resolution, concluding with future perspectives.

ToF-SIMS combined with machine learning reveals a robust mammary tumor-associated multi-ion signature. The signature strongly distinguishes mammary tumor tissue, while fur shows exploratory evidence of tumor-associated chemical information.

Descriptive statistics of the distances from each tumor core (TC) region of interest and the nearest immune infiltrate, measured using QuPath on the digital scan of the microscope slide. All distances are given in micrometers.

S5. Comprehensive cell counts from the multiplex immunohistochemistry analysis.

S1. Prognostic Effect of CD45+ Infiltration in Lung Cancer Brain Metastases.

S4. Immune signatures in the lung cancer brain metastasis cohort.

Predicted ligand-target interactions between immune and MTC networks across all networks (first sheet), adjacent networks (second sheet), immune networks including those not spatially adjacent (third sheet) and interactions plotted in Fig. 4c-d (fourth sheet).

S9. Immune-MTC cellular Networks in Lung Cancer Brain Metastasis.

Differentially expressed genes between all TI ROIs and TC ROIs with log2-fold change, p-value and q-value, for comparison with all patients (first sheet) as well as comparison per patient (second sheet).

Differentially expressed genes (first sheet) and cytokine genes (second sheet) from each tumor cell network with log2-fold changes, p-values, q-values calculated within each network and q-values calculated across all comparisons.