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Circulating Tumor Cell-Derived Pre-Clinical Models for Personalized Medicine
Marta Tellez-Gabriel1, Denis Cochonneau2, Marie Cadé3
1RNA and Molecular Pathology Research Group, Department of Medical Biology, The Artic University of Norway, N-9037 Tromsø, Norway. marta.t.gabriel@uit.no.
Developing preclinical models from circulating tumor cells (CTCs) is crucial for understanding cancer metastasis. These models, including CTC-derived explants (CDX models), offer insights into tumor heterogeneity and aid in developing new therapies.
Area of Science:
- Oncology
- Cancer Research
- Translational Medicine
Background:
- Cancer metastasis is the primary cause of cancer-related death, often untreatable with current therapies.
- Effective preclinical models are essential for studying metastatic disease evolution and developing novel treatments.
- Circulating Tumor Cells (CTCs) offer a non-invasive liquid biopsy approach to capture tumor heterogeneity.
Purpose of the Study:
- To review and discuss the generation and utility of CTC-derived preclinical models.
- To highlight the challenges and strengths of various CTC-derived models, from 2D cultures to CDX models.
- To summarize recent advancements and applications of these models in cancer research.
Main Methods:
- Review of existing literature on CTC-derived models.
- Categorization of models based on complexity (e.g., 2D cultures, CTC-derived explants/CDX models).
- Analysis of studies utilizing these preclinical tools.
Main Results:
- CTCs enable the creation of diverse preclinical models reflecting tumor heterogeneity.
- CTC-derived models, including CDX models, provide valuable insights into spatial and temporal tumor evolution.
- These models facilitate the investigation of cancer biomarkers and therapeutic strategies.
Conclusions:
- CTC-derived models are powerful tools for advancing cancer research, particularly for metastatic disease.
- Continued development and application of these models are vital for improving patient outcomes.
- Understanding CTC heterogeneity through these models is key to personalized cancer therapy.
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