Personalized cancer therapy using a patient-derived tumor tissue xenograft model: a translational field worthy of exploring further?

It has long been observed that interpatient variability in response to anticancer drugs is associated with different outcomes. Oncologists continually hold the desire of matching the right therapeutic regimen with the right cancer patient, which is termed 'personalized cancer therapy'. Rapid advances in genetics, genomics and related technologies are promising a new era of personalized cancer therapy based on individual molecular biomarkers. However, these molecular predictors of tumor response are far from perfect. Because of the inherent limitations in the current approaches for anticancer drugs response prediction, the need for new techniques to predict tumor response to therapy is urgent. Using a patient-derived human tumor tissue (PDTT) xenograft model to predict tumor response to therapy might be an ideal candidate method to choose. This article provides an overview of the achievements and limitations of genetic, genomic and proteomic molecular markers for personalized cancer therapy, and further discusses the potentials of using a PDTT xenograft model as a candidate strategy for personalized cancer therapy.