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Updated: Apr 3, 2026
Murine Model for Non-invasive Imaging to Detect and Monitor Ovarian Cancer Recurrence
Published on: November 2, 2014
Molecular and clinical implementations of ovarian cancer mouse avatar models
Amira A Zayed1, Sumithra J Mandrekar2, Paul Haluska3
1Department of Oncology, Mayo Clinic, Rochester, MN 55905, USA.
Abstract:
Innovation in oncology drug development has been hindered by lack of preclinical models that reliably predict clinical activity of novel therapies in cancer patients. Increasing desire for individualize treatment of patients with cancer has led to an increase in the use of patient-derived xenografts (PDX) engrafted into immune-compromised mice for preclinical modeling. Large numbers of tumor-specific PDX models have been established and proved to be powerful tools in pre-clinical testing. A subset of PDXs, referred to as Avatars, establish tumors in an orthotopic and treatment naïve fashion that may represent the most clinical relevant model of individual human cancers. This review will discuss ovarian cancer (OC) PDX models demonstrating the opportunities and limitations of these models in cancer drug development, and describe concepts of clinical trials design in Avatar guided therapy.
Insights
Patient-derived xenografts (PDX) offer promising preclinical models for cancer drug development. Avatars, a subset of PDX models, show potential for guiding individualized ovarian cancer therapy and clinical trial design.
Area of Science:
- Oncology
- Translational Research
- Preclinical Drug Development
Background:
- Preclinical models are crucial for predicting cancer drug efficacy in patients.
- Patient-derived xenografts (PDX) are increasingly used for preclinical cancer modeling.
- Limitations exist in current models for predicting clinical outcomes.
Purpose of the Study:
- To review ovarian cancer (OC) patient-derived xenograft (PDX) models.
- To discuss the opportunities and limitations of PDX models in oncology drug development.
- To explore Avatar models and their role in guiding individualized cancer therapy and clinical trial design.
Main Methods:
- Review of existing literature on ovarian cancer PDX models.
- Analysis of PDX model characteristics and their predictive value.
- Discussion of Avatar models as a subset of PDX models.
- Exploration of clinical trial designs incorporating Avatar-guided therapy.
Main Results:
- PDX models are powerful tools for pre-clinical cancer testing.
- Avatar models, a subset of PDX, establish orthotopic, treatment-naïve tumors.
- These models may represent highly clinically relevant representations of individual human cancers.
- Opportunities and limitations of PDX models in drug development are highlighted.
Conclusions:
- PDX models, particularly Avatars, are valuable for advancing ovarian cancer drug development.
- Avatar-guided therapy holds promise for personalized cancer treatment.
- Further research and optimized clinical trial designs are needed to fully leverage these models.
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