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Related Concept Videos

Mouse Models of Cancer Study02:43

Mouse Models of Cancer Study

Mice have long served as models for studying human biology and pathology because of their phylogenetic and physiological similarity with humans. They are also easy to maintain and breed in the laboratory, and hence, many inbred strains are now available for research. Studies on mice have contributed immeasurably to our understanding of cancer biology.
The development of transgenic, knockout, and knock-in mice has led to an exponential increase in their use as model organisms in research,...

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Orthotopic Transplantation of Breast Tumors as Preclinical Models for Breast Cancer
07:45

Orthotopic Transplantation of Breast Tumors as Preclinical Models for Breast Cancer

Published on: May 18, 2020

How can grafted breast cancer models be optimized?

Séverine Mollard1, Yoanne Mousseau, Yasser Baaj

  • 1Molecular Biology, School of Medicine, University of Limoges, Limoges, France.

Cancer Biology & Therapy
|November 8, 2011
PubMed
Summary

Realistic animal models are crucial for advancing breast cancer research. This review highlights key biological criteria and suggests adopting human RECIST criteria for improved treatment evaluation in preclinical studies.

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Published on: February 8, 2015

Area of Science:

  • Oncology
  • Translational Medicine
  • Preclinical Research

Background:

  • Breast cancer, a common malignancy in women, exhibits histological diversity and can develop resistance to therapies.
  • Current animal models offer insights but possess limitations in predicting clinical efficacy of novel treatments.
  • Metastatic potential and treatment resistance are key challenges in breast cancer progression.

Purpose of the Study:

  • To review and define essential biological criteria for developing realistic breast cancer animal models.
  • To emphasize the need for standardized and stringent monitoring criteria in preclinical breast cancer research.
  • To propose the adoption of human RECIST criteria for evaluating treatment response in animal models.

Main Methods:

  • Discussion of biological criteria for realistic breast cancer xenografts and syngeneic models.
  • Analysis of factors influencing model predictability, including tumor implantation site and animal immune status.
  • Review of modern imaging techniques for monitoring tumor growth and response.

Main Results:

  • Identification of critical biological factors for accurate breast cancer modeling: implantation site, immune status, histological diversity, and imaging.
  • Highlighting limitations of current models in reflecting human disease complexity and treatment response.
  • Proposal for enhanced monitoring and evaluation standards.

Conclusions:

  • Revised animal models incorporating specific biological criteria are necessary for reliable breast cancer therapy assessment.
  • Adoption of RECIST (Response Evaluation Criteria in Solid Tumors) criteria can standardize treatment evaluation in preclinical models.
  • Improved preclinical models will enhance the translation of research findings to clinical applications for breast cancer patients.