High-throughput screening using patient-derived tumor xenografts to predict clinical trial drug response

Abstract

Profiling candidate therapeutics with limited cancer models during preclinical development hinders predictions of clinical efficacy and identifying factors that underlie heterogeneous patient responses for patient-selection strategies. We established ∼1,000 patient-derived tumor xenograft models (PDXs) with a diverse set of driver mutations. With these PDXs, we performed in vivo compound screens using a 1 × 1 × 1 experimental design (PDX clinical trial or PCT) to assess the population responses to 62 treatments across six indications. We demonstrate both the reproducibility and the clinical translatability of this approach by identifying associations between a genotype and drug response, and established mechanisms of resistance. In addition, our results suggest that PCTs may represent a more accurate approach than cell line models for assessing the clinical potential of some therapeutic modalities. We therefore propose that this experimental paradigm could potentially improve preclinical evaluation of treatment modalities and enhance our ability to predict clinical trial responses.

A cancer pharmacogenomic screen powering crowd-sourced advancement of drug combination prediction

“…7 of these associations could be mapped to independent cell lines in the O'Neil et al 4 data set, with an overall Pearson correlation between DREAM and O'Neil effect sizes of 0.32 ( Figure 6B) showing a trend of reproducibility of synergy markers. Multiple validation criteria for quality and independent and in vivo reproducibility (see Methods) 4,7,8 were then applied to prioritize 13 feature-to-combination associations ( Figure 6C, Supp. Table 3), 7 associated with synergy and 6 with non-synergy.…”

“…A key bottleneck in the development of such models has been a lack of public data sets of sufficient size and variety to train computational approaches 4,7,8 , particularly considering the diversity of biological mechanisms that may influence drug response. We shared with Challenge participants ~11,500 experimentally tested drug combinations on 85 cancer cell lines.…”

Ex vivo drug response profiling detects recurrent sensitivity patterns in drug-resistant acute lymphoblastic leukemia

“…Moreover, such alterations may be over-or underrepresented in cell lines, whereas patient-derived xenografts (PDXs) seem to reproduce the genetic driver mutation landscape in leukemia more closely. [12][13][14] To obtain insight into interpatient drug response heterogeneity, we developed an in vitro platform directly using patient-derived leukemia cells. We hypothesized that drug response profiling of ALL, even without a priori information on genetic lesions or activated pathways, will detect sensitivity that may otherwise be overlooked.…”

Iontophoretic device delivery for the localized treatment of pancreatic ductal adenocarcinoma

“…FOLFIRINOX. Pancreatic PDX models such as the one used in this study have been shown to be highly predictive of relapse after surgery, reflective of patient outcome, genetics, and RNA tumor subtypes (19,20,24). These results suggest that the iontophoretic delivery of FOLFIRINOX may translate to improved clinical outcomes by enhancing the therapeutic index of this drug mixture, allowing for resection of localized and locally advanced pancreatic cancer.…”

“…The aim of our study was to evaluate the iontophoretic delivery of FOLFIRINOX for the treatment of localized pancreatic cancer. We evaluated this therapy in xenografts derived from patients with pancreatic cancer, which have been shown to reflect recently defined RNA tumor subtypes in patients, mirror patient outcome, and be highly predictive of clinical response to many targeted agents (19,20). We report the delivery of high levels of the FOLFIRINOX drugs to the tumor, a reduction in systemic exposure of the drugs, and potent tumor regression.…”