Despite recent advances in the treatment of patients with breast cancer (BrCa), BrCa remains the third leading cause of cancer death for women in the US due to intrinsic or acquired resistance to therapy. Continued understanding of gene expression profiling and genomic sequencing has clarified underlying intratumoral molecular heterogeneity. Recently, the patient-derived xenograft (PDX) models have emerged as a novel tool to address the issues of BrCa genomics and tumor heterogeneity, and to critically transform translational BrCa research in the preclinical setting. PDX models are generated by xenografting cancer tissue fragments obtained from patients to immune deficient mice, and can be passaged into next generations of mice. Generally, in contrast to conventional xenograft using cancer cell lines, PDXs are biologically more stable and recapitulate the individual tumor morphology, gene expression, and drug susceptibility of each patient. PDX may better model the original patient's tumor by retaining tumor heterogeneity, gene expression, and similar response to treatment. PDX models are thus thought to be more translationally relevant, especially as a drug development tool, because PDXs can capture the genetic character and heterogeneity that exists within a single patient's tumor and across a population of patients' tumors. PDX models also hold enormous potential for identifying predictive markers for therapeutic response. It has been repeatedly shown that PDX models demonstrate similar levels of activity as compared to the clinical response to therapeutic interventions. Therefore, this enables identification of therapeutic interventions that can most likely benefit a patient. This allows us to address the issues of BrCa genomics and tumor heterogeneity using PDXs in "pre-clinical" trials. Herein, we reviewed recent scientific development and future perspectives using PDX models in BrCa.
Keywords: Breast cancer; Patient-derived xenograft model; Preclinical model; Translational research.