Factors that influence response classifications in chemotherapy treated patient-derived xenografts (PDX).

In this study, we investigated the impact of initial tumor volume, rate of tumor growth, cohort size, study duration, and data analysis method on chemotherapy treatment response classifications in patient-derived xenografts (PDXs). The analyses were conducted on cisplatin treatment response data for 70 PDX models representing ten cancer types with up to 28-day study duration and cohort sizes of 3-10 tumor-bearing mice. The results demonstrated that a 21-day dosing study using a cohort size of eight was necessary to reliably detect responsive models (i.e., tumor volume ratio of treated animals to control between 0.1 and 0.42)-independent of analysis method. A cohort of three tumor-bearing animals led to a reliable classification of models that were both highly responsive and highly nonresponsive to cisplatin (i.e., tumor volume ratio of treated animals to control animals less than 0.10). In our set of PDXs, we found that tumor growth rate in the control group impacted treatment response classification more than initial tumor volume. We repeated the study design factors using docetaxel treated PDXs with consistent results. Our results highlight the importance of defining endpoints for PDX dosing studies when deciding the size of cohorts to use in dosing studies and illustrate that response classifications for a study do not differ significantly across the commonly used analysis methods that are based on tumor volume changes in treatment versus control groups

Factors that influence response classifications in chemotherapy treated patient-derived xenografts (PDX)

In this study, we investigated the impact of initial tumor volume, rate of tumor growth, cohort size, study duration, and data analysis method on chemotherapy treatment response classifications in patient-derived xenografts (PDXs). The analyses were conducted on cisplatin treatment response data for 70 PDX models representing ten cancer types with up to 28-day study duration and cohort sizes of 3–10 tumor-bearing mice. The results demonstrated that a 21-day dosing study using a cohort size of eight was necessary to reliably detect responsive models (i.e., tumor volume ratio of treated animals to control between 0.1 and 0.42)—independent of analysis method. A cohort of three tumor-bearing animals led to a reliable classification of models that were both highly responsive and highly nonresponsive to cisplatin (i.e., tumor volume ratio of treated animals to control animals less than 0.10). In our set of PDXs, we found that tumor growth rate in the control group impacted treatment response classification more than initial tumor volume. We repeated the study design factors using docetaxel treated PDXs with consistent results. Our results highlight the importance of defining endpoints for PDX dosing studies when deciding the size of cohorts to use in dosing studies and illustrate that response classifications for a study do not differ significantly across the commonly used analysis methods that are based on tumor volume changes in treatment versus control groups

Genomic data analysis workflows for tumors from patient-derived xenografts (PDXs): challenges and guidelines.

BACKGROUND: Patient-derived xenograft (PDX) models are in vivo models of human cancer that have been used for translational cancer research and therapy selection for individual patients. The Jackson Laboratory (JAX) PDX resource comprises 455 models originating from 34 different primary sites (as of 05/08/2019). The models undergo rigorous quality control and are genomically characterized to identify somatic mutations, copy number alterations, and transcriptional profiles. Bioinformatics workflows for analyzing genomic data obtained from human tumors engrafted in a mouse host (i.e., Patient-Derived Xenografts; PDXs) must address challenges such as discriminating between mouse and human sequence reads and accurately identifying somatic mutations and copy number alterations when paired non-tumor DNA from the patient is not available for comparison. RESULTS: We report here data analysis workflows and guidelines that address these challenges and achieve reliable identification of somatic mutations, copy number alterations, and transcriptomic profiles of tumors from PDX models that lack genomic data from paired non-tumor tissue for comparison. Our workflows incorporate commonly used software and public databases but are tailored to address the specific challenges of PDX genomics data analysis through parameter tuning and customized data filters and result in improved accuracy for the detection of somatic alterations in PDX models. We also report a gene expression-based classifier that can identify EBV-transformed tumors. We validated our analytical approaches using data simulations and demonstrated the overall concordance of the genomic properties of xenograft tumors with data from primary human tumors in The Cancer Genome Atlas (TCGA). CONCLUSIONS: The analysis workflows that we have developed to accurately predict somatic profiles of tumors from PDX models that lack normal tissue for comparison enable the identification of the key oncogenic genomic and expression signatures to support model selection and/or biomarker development in therapeutic studies. A reference implementation of our analysis recommendations is available at https://github.com/TheJacksonLaboratory/PDX-Analysis-Workflows

Humanized mice in studying efficacy and mechanisms of PD-1-targeted cancer immunotherapy.

Establishment of an in vivo small animal model of human tumor and human immune system interaction would enable preclinical investigations into the mechanisms underlying cancer immunotherapy. To this end, nonobese diabetic (NOD).Cg- PrkdcscidIL2rgtm1Wjl/Sz (null; NSG) mice were transplanted with human (h)CD34+ hematopoietic progenitor and stem cells, which leads to the development of human hematopoietic and immune systems [humanized NSG (HuNSG)]. HuNSG mice received human leukocyte antigen partially matched tumor implants from patient-derived xenografts [PDX; non-small cell lung cancer (NSCLC), sarcoma, bladder cancer, and triple-negative breast cancer (TNBC)] or from a TNBC cell line-derived xenograft (CDX). Tumor growth curves were similar in HuNSG compared with nonhuman immune-engrafted NSG mice. Treatment with pembrolizumab, which targets programmed cell death protein 1, produced significant growth inhibition in both CDX and PDX tumors in HuNSG but not in NSG mice. Finally, inhibition of tumor growth was dependent on hCD8+ T cells, as demonstrated by antibody-mediated depletion. Thus, tumor-bearing HuNSG mice may represent an important, new model for preclinical immunotherapy research. FASEB J 2018 Mar; 32(3):1537-1549

Preclinical testing of the glycogen synthase kinase-3β inhibitor tideglusib for rhabdomyosarcoma

Rhabdomyosarcoma (RMS) is the most common childhood soft tissue sarcoma. RMS often arise from myogenic precursors and displays a poorly differentiated skeletal muscle phenotype most closely resembling regenerating muscle. GSK3β is a ubiquitously expressed serine-threonine kinase capable of repressing the terminal myogenic differentiation program in cardiac and skeletal muscle. Recent unbiased chemical screening efforts have prioritized GSK3β inhibitors as inducers of myodifferentiation in RMS, suggesting efficacy as single agents in suppressing growth and promoting self-renewal in zebrafish transgenic embryonal RMS (eRMS) models in vivo. In this study, we tested the irreversible GSK3β-inhibitor, tideglusib for in vivo efficacy in patient-derived xenograft models of both alveolar rhabdomyosarcoma (aRMS) and eRMS. Tideglusib had effective on-target pharmacodynamic efficacy, but as a single agent had no effect on tumor progression or myodifferentiation. These results suggest that as monotherapy, GSK3β inhibitors may not be a viable treatment for aRMS or eRMS

Novel theranostic nanoporphyrins for photodynamic diagnosis and trimodal therapy for bladder cancer

The overall prognosis of bladder cancer has not been improved over the last 30 years and therefore, there is a great medical need to develop novel diagnosis and therapy approaches for bladder cancer. We developed a multifunctional nanoporphyrin platform that was coated with a bladder cancer-specific ligand named PLZ4. PLZ4-nanoporphyrin (PNP) integrates photodynamic diagnosis, image-guided photodynamic therapy, photothermal therapy and targeted chemotherapy in a single procedure. PNPs are spherical, relatively small (around 23 nm), and have the ability to preferably emit fluorescence/heat/reactive oxygen species upon illumination with near infrared light. Doxorubicin (DOX) loaded PNPs possess slower drug release and dramatically longer systemic circulation time compared to free DOX. The fluorescence signal of PNPs efficiently and selectively increased in bladder cancer cells but not normal urothelial cells in vitro and in an orthotopic patient derived bladder cancer xenograft (PDX) models, indicating their great potential for photodynamic diagnosis. Photodynamic therapy with PNPs was significantly more potent than 5-aminolevulinic acid, and eliminated orthotopic PDX bladder cancers after intravesical treatment. Image-guided photodynamic and photothermal therapies synergized with targeted chemotherapy of DOX and significantly prolonged overall survival of mice carrying PDXs. In conclusion, this uniquely engineered targeting PNP selectively targeted tumor cells for photodynamic diagnosis, and served as effective triple-modality (photodynamic/photothermal/chemo) therapeutic agents against bladder cancers. This platform can be easily adapted to individualized medicine in a clinical setting and has tremendous potential to improve the management of bladder cancer in the clinic

Image-guided photo-therapeutic nanoporphyrin synergized HSP90 inhibitor in patient-derived xenograft bladder cancer model.

Photodynamic therapy is a promising and effective non-invasive therapeutic approach for the treatment of bladder cancers. Therapies targeting HSP90 have the advantage of tumor cell selectivity and have shown great preclinical efficacy. In this study, we evaluated a novel multifunctional nanoporphyrin platform loaded with an HSP90 inhibitor 17AAG (NP-AAG) for use as a multi-modality therapy against bladder cancer. NP-AAG was efficiently accumulated and retained at bladder cancer patient-derived xenograft (PDX) over 7 days. PDX tumors could be synergistically eradicated with a single intravenous injection of NP-AAG followed by multiple light treatments within 7 days. NP-AAG mediated treatment could not only specifically deliver 17AAG and produce heat and reactive oxygen species, but also more effectively inhibit essential bladder cancer essential signaling molecules like Akt, Src, and Erk, as well as HIF-1α induced by photo-therapy. This multifunctional nanoplatform has high clinical relevance and could dramatically improve management for bladder cancers with minimal toxicity. Nanomedicine 2018 Apr; 14(3):789-799