Metastasis remains the leading cause of mortality in gastrointestinal (GI) cancers, including colorectal, gastric, pancreatic, and esophageal malignancies. Despite advances in treatment, the biological mechanisms driving metastatic dissemination, colonization, and therapy resistance remain poorly understood. In recent years, patient-derived and experimental models—such as organoids, mouse models, and zebrafish xenografts—have provided powerful tools to study the metastatic process in a physiologically relevant and clinically actionable context.

This collection aims to highlight novel insights into GI cancer metastasis that have emerged through the use of preclinical models. We seek submissions and discussions around the following key themes:
• Development and Application of Preclinical Model Systems: Including zebrafish xenografts, patient-derived organoids, spheroids, PDX, and engineered murine models for GI cancer metastasis research.
• Modeling Metastasis and Functional Screening: In vitro and in vivo strategies to investigate and dissect the metastatic cascade.
• Dissecting Molecular, Metabolic, and Microenvironmental Drivers: Studies on genetic mutations, metabolic rewiring, and tumor-stromal interactions that contribute to metastasis, tumor aggressiveness, and therapy resistance.
• Unraveling Phenotypic Diversity for Patient Stratification: Approaches that use model systems to explore mechanisms behind differences in tumor aggressiveness and responses to treatment, with implications for personalized medicine.
• Innovative Technologies and Translational Impact: Integration of advanced technologies such as single-cell omics, genome editing, high-throughput drug screening, and imaging, with a focus on how discoveries advance our understanding of GI cancer progression.

By integrating these themes, the collection will highlight how innovative preclinical models and techniques are deepening our understanding of metastatic pathways, elucidating why certain patients experience more aggressive GI cancer phenotypes, and accelerating the identification of patient-tailored therapeutic vulnerabilities—ultimately bringing the vision of precision medicine closer to clinical reality.

Please note: manuscripts consisting solely of bioinformatics, computational analysis, or predictions of public databases which are not accompanied by validation (independent clinical or patient cohort, or biological validation in vitro or in vivo, which are not based on public databases) are not suitable for publication in this journal.

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Insights into Gastrointestinal Cancer Metastasis from Preclinical Models

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