A Genomically and Clinically Annotated Patient-Derived Xenograft Resource for Preclinical Research in Non-Small Cell Lung Cancer.

Patient-derived xenograft (PDX) models are an effective preclinical in vivo platform for testing the efficacy of novel drugs and drug combinations for cancer therapeutics. Here we describe a repository of 79 genomically and clinically annotated lung cancer PDXs available from The Jackson Laboratory that have been extensively characterized for histopathologic features, mutational profiles, gene expression, and copy-number aberrations. Most of the PDXs are models of non-small cell lung cancer (NSCLC), including 37 lung adenocarcinoma (LUAD) and 33 lung squamous cell carcinoma (LUSC) models. Other lung cancer models in the repository include four small cell carcinomas, two large cell neuroendocrine carcinomas, two adenosquamous carcinomas, and one pleomorphic carcinoma. Models with both de novo and acquired resistance to targeted therapies with tyrosine kinase inhibitors are available in the collection. The genomic profiles of the LUAD and LUSC PDX models are consistent with those observed in patient tumors from The Cancer Genome Atlas and previously characterized gene expression-based molecular subtypes. Clinically relevant mutations identified in the original patient tumors were confirmed in engrafted PDX tumors. Treatment studies performed in a subset of the models recapitulated the responses expected on the basis of the observed genomic profiles. These models therefore serve as a valuable preclinical platform for translational cancer research. SIGNIFICANCE: Patient-derived xenografts of lung cancer retain key features observed in the originating patient tumors and show expected responses to treatment with standard-of-care agents, providing experimentally tractable and reproducible models for preclinical investigations.

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 .

Probabilistic modeling of personalized drug combinations from integrated chemical screen and molecular data in sarcoma.

BACKGROUND: Cancer patients with advanced disease routinely exhaust available clinical regimens and lack actionable genomic medicine results, leaving a large patient population without effective treatments options when their disease inevitably progresses. To address the unmet clinical need for evidence-based therapy assignment when standard clinical approaches have failed, we have developed a probabilistic computational modeling approach which integrates molecular sequencing data with functional assay data to develop patient-specific combination cancer treatments. METHODS: Tissue taken from a murine model of alveolar rhabdomyosarcoma was used to perform single agent drug screening and DNA/RNA sequencing experiments; results integrated via our computational modeling approach identified a synergistic personalized two-drug combination. Cells derived from the primary murine tumor were allografted into mouse models and used to validate the personalized two-drug combination. Computational modeling of single agent drug screening and RNA sequencing of multiple heterogenous sites from a single patient's epithelioid sarcoma identified a personalized two-drug combination effective across all tumor regions. The heterogeneity-consensus combination was validated in a xenograft model derived from the patient's primary tumor. Cell cultures derived from human and canine undifferentiated pleomorphic sarcoma were assayed by drug screen; computational modeling identified a resistance-abrogating two-drug combination common to both cell cultures. This combination was validated in vitro via a cell regrowth assay. RESULTS: Our computational modeling approach addresses three major challenges in personalized cancer therapy: synergistic drug combination predictions (validated in vitro and in vivo in a genetically engineered murine cancer model), identification of unifying therapeutic targets to overcome intra-tumor heterogeneity (validated in vivo in a human cancer xenograft), and mitigation of cancer cell resistance and rewiring mechanisms (validated in vitro in a human and canine cancer model). CONCLUSIONS: These proof-of-concept studies support the use of an integrative functional approach to personalized combination therapy prediction for the population of high-risk cancer patients lacking viable clinical options and without actionable DNA sequencing-based therapy.

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.

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.

COX-2/sEH Dual Inhibitor PTUPB Potentiates the Antitumor Efficacy of Cisplatin.

Cisplatin-based therapy is highly toxic, but moderately effective in most cancers. Concurrent inhibition of cyclooxygenase-2 (COX-2) and soluble epoxide hydrolase (sEH) results in antitumor activity and has organ-protective effects. The goal of this study was to determine the antitumor activity of PTUPB, an orally bioavailable COX-2/sEH dual inhibitor, in combination with cisplatin and gemcitabine (GC) therapy. NSG mice bearing bladder cancer patient-derived xenografts were treated with vehicle, PTUPB, cisplatin, GC, or combinations thereof. Mouse experiments were performed with two different PDX models. PTUPB potentiated cisplatin and GC therapy, resulting in significantly reduced tumor growth and prolonged survival. PTUPB plus cisplatin was no more toxic than cisplatin single-agent treatment as assessed by body weight, histochemical staining of major organs, blood counts, and chemistry. The combination of PTUPB and cisplatin increased apoptosis and decreased phosphorylation in the MAPK/ERK and PI3K/AKT/mTOR pathways compared with controls. PTUPB treatment did not alter platinum-DNA adduct levels, which is the most critical step in platinum-induced cell death. The in vitro study using the combination index method showed modest synergy between PTUPB and platinum agents only in 5637 cell line among several cell lines examined. However, PTUPB is very active in vivo by inhibiting angiogenesis. In conclusion, PTUPB potentiated the antitumor activity of cisplatin-based treatment without increasing toxicity in vivo and has potential for further development as a combination chemotherapy partner. Mol Cancer Ther; 17(2); 474-83. ©2017 AACR.

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.-Wang, M., Yao, L.-C., Cheng, M., Cai, D., Martinek, J., Pan, C.-X., Shi, W., Ma, A.-H., De Vere White, R. W., Airhart, S., Liu, E. T., Banchereau, J., Brehm, M. A., Greiner, D. L., Shultz, L. D., Palucka, K., Keck, J. G. Humanized mice in studying efficacy and mechanisms of PD-1-targeted cancer immunotherapy.

Preclinical testing of the glycogen synthase kinase-3ß 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. GSK3ß 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 GSK3ß 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 GSK3ß-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, GSK3ß inhibitors may not be a viable treatment for aRMS or eRMS.

The Phosphatidylinositol 3-Kinase Pathway as a Potential Therapeutic Target in Bladder Cancer.

Purpose: Activation of the PI3K pathway occurs in over 40% of bladder urothelial cancers. The aim of this study is to determine the therapeutic potential, the underlying action, and the resistance mechanisms of drugs targeting the PI3K pathway.Experimental Design: Urothelial cancer cell lines and patient-derived xenografts (PDXs) were analyzed for alterations of the PI3K pathway and for their sensitivity to the small-molecule inhibitor pictilisib alone and in combination with cisplatin and/or gemcitabine. Potential predictive biomarkers for pictilisib were evaluated, and RNA sequencing was performed to explore drug resistance mechanisms.Results: The bladder cancer cell line TCCSUP, which harbors a PIK3CA E545K mutation, was sensitive to pictilisib compared to cell lines with wild-type PIK3CA Pictilisib exhibited stronger antitumor activity in bladder cancer PDX models with PI3KCA H1047R mutation or amplification than the control PDX model. Pictilisib synergized with cisplatin and/or gemcitabine in vitro, significantly delayed tumor growth, and prolonged survival compared with single-drug treatment in the PDX models. The phosphorylation of ribosomal protein S6 correlated with response to pictilisib both in vitro and in vivo, and could potentially serve as a biomarker to predict response to pictilisib. Pictilisib activated the compensatory MEK/ERK pathway that likely contributed to pictilisib resistance, which was reversed by cotreatment with the RAF inhibitor sorafenib. RNA sequencing of tumors resistant to treatment suggested that LSP1 downregulation correlated with drug resistance.Conclusions: These preclinical results provide new insights into the therapeutic potential of targeting the PI3K pathway for the treatment of bladder cancer. Clin Cancer Res; 23(21); 6580-91. ©2017 AACR.

Modeling of Patient-Derived Xenografts in Colorectal Cancer.

Developing realistic preclinical models using clinical samples that mirror complex tumor biology and behavior are vital to advancing cancer research. While cell line cultures have been helpful in generating preclinical data, the genetic divergence between these and corresponding primary tumors has limited clinical translation. Conversely, patient-derived xenografts (PDX) in colorectal cancer are highly representative of the genetic and phenotypic heterogeneity in the original tumor. Coupled with high-throughput analyses and bioinformatics, these PDXs represent robust preclinical tools for biomarkers, therapeutic target, and drug discovery. Successful PDX engraftment is hypothesized to be related to a series of anecdotal variables namely, tissue source, cancer stage, tumor grade, acquisition strategy, time to implantation, exposure to prior systemic therapy, and genomic heterogeneity of tumors. Although these factors at large can influence practices and patterns related to xenotransplantation, their relative significance in determining the success of establishing PDXs is uncertain. Accordingly, we systematically examined the predictive ability of these factors in establishing PDXs using 90 colorectal cancer patient specimens that were subcutaneously implanted into immunodeficient mice. Fifty (56%) PDXs were successfully established. Multivariate analyses showed tissue acquisition strategy [surgery 72.0% (95% confidence interval (CI): 58.2-82.6) vs. biopsy 35% (95% CI: 22.1%-50.6%)] to be the key determinant for successful PDX engraftment. These findings contrast with current empiricism in generating PDXs and can serve to simplify or liberalize PDX modeling protocols. Better understanding the relative impact of these factors on efficiency of PDX formation will allow for pervasive integration of these models in care of colorectal cancer patients. Mol Cancer Ther; 16(7); 1435-42. ©2017 AACR.

Microdose-Induced Drug-DNA Adducts as Biomarkers of Chemotherapy Resistance in Humans and Mice.

We report progress on predicting tumor response to platinum-based chemotherapy with a novel mass spectrometry approach. Fourteen bladder cancer patients were administered one diagnostic microdose each of [14C]carboplatin (1% of the therapeutic dose). Carboplatin-DNA adducts were quantified by accelerator mass spectrometry in blood and tumor samples collected within 24 hours, and compared with subsequent chemotherapy response. Patients with the highest adduct levels were responders, but not all responders had high adduct levels. Four patient-derived bladder cancer xenograft mouse models were used to test the possibility that another drug in the regimen could cause a response. The mice were dosed with [14C]carboplatin or [14C]gemcitabine and the resulting drug-DNA adduct levels were compared with tumor response to chemotherapy. At least one of the drugs had to induce high drug-DNA adduct levels or create a synergistic increase in overall adducts to prompt a corresponding therapeutic response, demonstrating proof-of-principle for drug-DNA adducts as predictive biomarkers. Mol Cancer Ther; 16(2); 376-87. ©2016 AACR.

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.

A Patient-Derived Xenograft Model of Parameningeal Embryonal Rhabdomyosarcoma for Preclinical Studies.

Embryonal rhabdomyosarcoma (eRMS) is one of the most common soft tissue sarcomas in children and adolescents. Parameningeal eRMS is a variant that is often more difficult to treat than eRMS occurring at other sites. A 14-year-old female with persistent headaches and rapid weight loss was diagnosed with parameningeal eRMS. She progressed and died despite chemotherapy with vincristine, actinomycin-D, and cyclophosphamide plus 50.4 Gy radiation therapy to the primary tumor site. Tumor specimens were acquired by rapid autopsy and tumor tissue was transplanted into immunodeficient mice to create a patient-derived xenograft (PDX) animal model. As autopsy specimens had an ALK R1181C mutation, PDX tumor bearing animals were treated with the pan-kinase inhibitor lestaurtinib but demonstrated no decrease in tumor growth, suggesting that single agent kinase inhibitor therapy may be insufficient in similar cases. This unique parameningeal eRMS PDX model is publicly available for preclinical study.

Development and Characterization of Bladder Cancer Patient-Derived Xenografts for Molecularly Guided Targeted Therapy.

BACKGROUND: The overarching goal of this project is to establish a patient-derived bladder cancer xenograft (PDX) platform, annotated with deep sequencing and patient clinical information, to accelerate the development of new treatment options for bladder cancer patients. Herein, we describe the creation, initial characterization and use of the platform for this purpose. METHODS AND FINDINGS: Twenty-two PDXs with annotated clinical information were established from uncultured unselected clinical bladder cancer specimens in immunodeficient NSG mice. The morphological fidelity was maintained in PDXs. Whole exome sequencing revealed that PDXs and parental patient cancers shared 92-97% of genetic aberrations, including multiple druggable targets. For drug repurposing, an EGFR/HER2 dual inhibitor lapatinib was effective in PDX BL0440 (progression-free survival or PFS of 25.4 days versus 18.4 days in the control, p = 0.007), but not in PDX BL0269 (12 days versus 13 days in the control, p = 0.16) although both expressed HER2. To screen for the most effective MTT, we evaluated three drugs (lapatinib, ponatinib, and BEZ235) matched with aberrations in PDX BL0269; but only a PIK3CA inhibitor BEZ235 was effective (p<0.0001). To study the mechanisms of secondary resistance, a fibroblast growth factor receptor 3 inhibitor BGJ398 prolonged PFS of PDX BL0293 from 9.5 days of the control to 18.5 days (p<0.0001), and serial biopsies revealed that the MAPK/ERK and PIK3CA-AKT pathways were activated upon resistance. Inhibition of these pathways significantly prolonged PFS from 12 day of the control to 22 days (p = 0.001). To screen for effective chemotherapeutic drugs, four of the first six PDXs were sensitive to the cisplatin/gemcitabine combination, and chemoresistance to one drug could be overcome by the other drug. CONCLUSION: The PDX models described here show good correlation with the patient at the genomic level and known patient response to treatment. This supports further evaluation of the PDXs for their ability to accurately predict a patient's response to new targeted and combination strategies for bladder cancer.

Bridging tumor genomics to patient outcomes through an integrated patient-derived xenograft platform.

New approaches to optimization of cancer drug development in the laboratory and the clinic will be required to fully achieve the goal of individualized, precision cancer therapy. Improved preclinical models that more closely reflect the now recognized genomic complexity of human cancers are needed. Here we describe a collaborative research project that integrates core resources of The Jackson Laboratory Basic Science Cancer Center with genomics and clinical research facilities at the UC Davis Comprehensive Cancer Center to establish a clinically and genomically annotated patient-derived xenograft (PDX) platform designed to enhance new drug development and strategies for targeted therapies. Advanced stage non-small-cell lung cancer (NSCLC) was selected for initial studies because of emergence of a number of "druggable" molecular targets, and recent recognition of substantial inter- and intrapatient tumor heterogeneity. Additionally, clonal evolution after targeted therapy interventions make this tumor type ideal for investigation of this platform. Using the immunodeficient NOD scid gamma mouse, > 200 NSCLC tumor biopsies have been xenotransplanted. During the annotation process, patient tumors and subsequent PDXs are compared at multiple levels, including histomorphology, clinically applicable molecular biomarkers, global gene expression patterns, gene copy number variations, and DNA/chromosomal alterations. NSCLC PDXs are grouped into panels of interest according to oncogene subtype and/or histologic subtype. Multiregimen drug testing, paired with next-generation sequencing before and after therapy and timed tumor pharmacodynamics enables determination of efficacy, signaling pathway alterations, and mechanisms of sensitivity-resistance in individual models. This approach should facilitate derivation of new therapeutic strategies and the transition to individualized therapy.