Patient-derived xenograft models of breast cancer and their predictive power

Abstract

Despite advances in the treatment of patients with early and metastatic breast cancer, mortality remains high due to intrinsic or acquired resistance to therapy. Increased understanding of the genomic landscape through massively parallel sequencing has revealed somatic mutations common to specific subtypes of breast cancer, provided new prognostic and predictive markers, and highlighted potential therapeutic targets. Evaluating new targets using established cell lines is limited by the inexact correlation between responsiveness observed in cell lines versus that elicited in the patient. Patient-derived xenografts (PDXs) generated from fresh tumor specimens recapitulate the diversity of breast cancer and reflect histopathology, tumor behavior, and the metastatic properties of the original tumor. The high degree of genomic preservation evident across primary tumors and their matching PDXs over serial passaging validate them as important preclinical tools. Indeed, there is accumulating evidence that PDXs can recapitulate treatment responses of the parental tumor. The finding that tumor engraftment is an independent and poor prognostic indicator of patient outcome represents the first step towards personalized medicine. Here we review the utility of breast cancer PDX models to study the clonal evolution of tumors and to evaluate novel therapies and drug resistance.