Patient-derived tumour xenografts as models for oncology drug development

Abstract

Progress in oncology drug development has been hampered by a lack of preclinical models that reliably predict clinical activity of novel compounds in cancer patients. In an effort to address these shortcomings, there has been a recent increase in the use of patient-derived tumour xenografts (PDTX) engrafted into immune-compromised rodents such as athymic nude or NOD/SCID mice for preclinical modelling. Numerous tumour-specific PDTX models have been established and, importantly, they are biologically stable when passaged in mice in terms of global gene-expression patterns, mutational status, metastatic potential, drug responsiveness and tumour architecture. These characteristics might provide significant improvements over standard cell-line xenograft models. This Review will discuss specific PDTX disease examples illustrating an overview of the opportunities and limitations of these models in cancer drug development, and describe concepts regarding predictive biomarker development and future applications.

Figures

Figure 1

Establishment and testing of PDTX models. Excess tumour specimens not needed for clinical diagnosis are obtained from the consented patients (F0). Non-necrotic areas of these tumours are sectioned into ~3 mm3 pieces and, after processing, implanted subcutaneously into anaesthetized 5-week to 6-week-old female athymic nude mice. During the engraftment phase, tumours are allowed to establish and grow and then are harvested upon reaching a size of 1,500 mm3 (F1). Similar protocols are employed for subsequent expansion cohort (F2) and treatment cohort (F3 … Fn). Typically, biological assays are performed on tumours in early generations (≤F5); these biological assays include drug efficacy studies, rational combination studies and the development of predictive biomarkers for novel targeted therapies. If the developed biomarkers achieved accurate prediction in a validation set of PDTX models (or ‘xenopatients’), they might be translated into early phase clinical trials as tools for patient selection strategies. Abbreviations: PDTX, patient-derived tumour xenografts; RES, resistant; SEN, sensitive.

Figure 2

Comparison of genome-wide gene-expression profiles between primary patient tumours and PDTX tumours. a | Matched patient primary CRC tumour (F0) and PDTX (F3). Genome-wide gene-expression profiles of a patient with CRC and their matched PDTX were profiled with Affymetrix® HuGene 1.0 ST arrays. b | Matched patient primary PDA tumour (F0) and PDTX (F5). Genome-wide gene-expression profiles of a patient with PDA and their matched PDTX were profiled with Affymetrix® HG-U133 Plus 2.0 arrays. High correlations were observed in both PDTX models and their matched primary tumours. Abbreviations: CRC, colorectal cancer; PDA, pancreatic ductal adenocarcinoma; PDTX, patient-derived tumour xenografts.

Figure 3

Predictive biomarker development strategy in PDTX models. A novel targeted therapy (drug X) will be screened in a cohort of tumour-specific PDTX models to determine efficacy and the PDTX will be classified into SEN, RES and intermediate groups. These models will be used as the training set to develop predictive biomarkers. Multiple layers of ‘omics’ technologies will be employed to characterize these PDTX training sets to derive an integrative genomic classifier to predict SEN and RES models in response to drug X. A cross-validation step can be used to refine the classifier, which could be developed into assays for predicting responsiveness to drug X in fresh frozen or FFPE tissue samples. The classifier would require validation by correct prediction in an independent cohort of PDTX models (test set). If the classifier achieved a high level of accuracy in the test set, it could potentially be translated into early clinical trials to select patients to be treated with drug X. Abbreviations: FFPE, formalin-fixed, paraffin-embedded; PDTX, patient-derived tumour xenograft; RES, resistant; SEN, sensitive.