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Updated: Jun 27, 2026
Advanced Animal Model of Colorectal Metastasis in Liver: Imaging Techniques and Properties of Metastatic Clones
Published on: November 30, 2016
Preclinical Models of Colorectal Cancer Liver Metastasis: Therapeutic Evaluation and Translational Implications
Ye Ri Han1, Sang Bong Lee2,3,4
1Department of Chemistry, Duksung Women's University, Seoul, Republic of Korea.
Abstract:
Colorectal cancer liver metastasis (CRLM) remains a leading cause of cancer-related mortality, with clinical outcomes limited by biological heterogeneity and inconsistent therapeutic responses. Despite advances in systemic chemotherapy, targeted agents, immunotherapy, and liver-directed interventions, the translation of preclinical efficacy into clinical benefit remains suboptimal, highlighting the need for predictive experimental models. However, therapeutic efficacy in CRLM is highly model-dependent, and discrepancies between preclinical findings and clinical outcomes often arise from differences in biological fidelity across experimental platforms. This review critically examines preclinical platforms used to study CRLM, with emphasis on orthotopic and metastatic models that recapitulate hepatic colonization, tumor-microenvironment interactions, and immune regulation. We evaluate methodological innovations that enhance anatomical fidelity and reproducibility, including tissue adhesive-based implantation and biomaterial-assisted strategies. Importantly, we analyze how different models influence therapeutic assessment across systemic, immune-based, metabolic, and liver-directed treatments, and discuss their ability to predict clinical responses. By integrating insights from experimental studies with key clinical evidence, we delineate the strengths and limitations of current platforms and propose principles for rational model selection to improve translational success in CRLM research.
Insights
Developing better preclinical models is crucial for improving colorectal cancer liver metastasis (CRLM) treatments. This review evaluates current models and suggests principles for selecting the best ones to enhance clinical success.
Area of Science:
- Oncology
- Translational Research
- Preclinical Modeling
Background:
- Colorectal cancer liver metastasis (CRLM) is a major cause of cancer mortality, with limited treatment efficacy due to biological heterogeneity.
- Current preclinical models often lack biological fidelity, leading to discrepancies between experimental findings and clinical outcomes.
- Advances in systemic therapy, immunotherapy, and liver-directed interventions have not fully translated to improved patient benefit.
Purpose of the Study:
- To critically review existing preclinical platforms for studying CRLM.
- To evaluate how different models influence therapeutic assessment and predict clinical responses.
- To propose principles for rational model selection to enhance translational success in CRLM research.
Main Methods:
- Examination of orthotopic and metastatic models that mimic hepatic colonization and tumor microenvironment.
- Evaluation of methodological innovations like tissue adhesive-based implantation and biomaterial-assisted strategies.
- Analysis of how various models impact the assessment of systemic, immune-based, metabolic, and liver-directed treatments.
Main Results:
- Therapeutic efficacy in CRLM is highly model-dependent, with significant discrepancies between preclinical data and clinical outcomes.
- Orthotopic and metastatic models show promise in recapitulating key aspects of CRLM, including tumor-microenvironment interactions and immune regulation.
- Methodological innovations can enhance the anatomical fidelity and reproducibility of preclinical models.
Conclusions:
- Current preclinical platforms for CRLM have distinct strengths and limitations that affect their ability to predict clinical responses.
- Rational selection of appropriate models is essential for improving the translation of preclinical findings to clinical benefit.
- Further development and validation of high-fidelity models are needed to accelerate progress in CRLM therapeutics.
