In vivo models in breast cancer research: progress, challenges and future directions

• Published in: Disease models & mechanisms 2017-04, Vol.10 (4), p.359-371
• Main Authors: Holen, Ingunn, Speirs, Valerie, Morrissey, Bethny, Blyth, Karen
• Format: Article
• Language: English
• Subjects: Animals; Biomedical Research; Breast cancer; Breast Neoplasms - pathology; Cancer research; CDX; Disease Models, Animal; Drug resistance; Drug Resistance, Neoplasm; EurOPDX; Experiments; Female; GEMM; Genetic Engineering; Humans; Laboratory animals; Medical research; Metastasis; Molecular Targeted Therapy; Mouse models; PDX; Researchers; Review; SEARCHBreast; Tumors; Womens health; Xenografts
• ISSN: 1754-8403; 1754-8411
• DOI: 10.1242/dmm.028274

Research using animal model systems has been instrumental in delivering improved therapies for breast cancer, as well as in generating new insights into the mechanisms that underpin development of the disease. A large number of different models are now available, reflecting different types and stages of the disease; choosing which one to use depends on the specific research question(s) to be investigated. Based on presentations and discussions from leading experts who attended a recent workshop focused on models of breast cancer, this article provides a perspective on the many varied uses of these models in breast cancer research, their strengths, associated challenges and future directions. Among the questions discussed were: how well do models represent the different stages of human disease; how can we model the involvement of the human immune system and microenvironment in breast cancer; what are the appropriate models of metastatic disease; can we use models to carry out preclinical drug trials and identify pathways responsible for drug resistance; and what are the limitations of patient-derived xenograft models? We briefly outline the areas where the existing breast cancer models require improvement in light of the increased understanding of the disease process, reflecting the drive towards more personalised therapies and identification of mechanisms of drug resistance.