Establishing a human renal cell carcinoma tumorgraft platform for preclinical drug testing.
Ontology highlight
ABSTRACT:
SUBMITTER: Pavia-Jimenez A
PROVIDER: S-EPMC4314943 | biostudies-literature | 2014 Aug
REPOSITORIES: biostudies-literature
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Project description:Renal cell carcinoma (RCC) encompasses a heterogenous group of tumors, but representative preclinical models are lacking. We previously showed that patient-derived tumorgraft (TG) models recapitulate the biology and treatment responsiveness. Through systematic orthotopic implantation of tumor samples from 926 ethnically diverse individuals into non-obese diabetic (NOD)/severe combined immunodeficiency (SCID) mice, we generate a resource comprising 172 independently derived, stably engrafted TG lines from 148 individuals. TG lines are characterized histologically and genomically (whole-exome [n = 97] and RNA [n = 102] sequencing). The platform features a variety of histological and oncogenotypes, including TCGA clades further corroborated through orthogonal metabolomic analyses. We illustrate how it enables a deeper understanding of RCC biology; enables the development of tissue- and imaging-based molecular probes; and supports advances in drug development.
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Project description:Most anticancer drugs entering clinical trials fail to achieve approval from the U.S. Food and Drug Administration. Drug development is hampered by the lack of preclinical models with therapeutic predictive value. Herein, we report the development and validation of a tumorgraft model of renal cell carcinoma (RCC) and its application to the evaluation of an experimental drug. Tumor samples from 94 patients were implanted in the kidneys of mice without additives or disaggregation. Tumors from 35 of these patients formed tumorgrafts, and 16 stable lines were established. Samples from metastatic sites engrafted at higher frequency than those from primary tumors, and stable engraftment of primary tumors in mice correlated with decreased patient survival. Tumorgrafts retained the histology, gene expression, DNA copy number alterations, and more than 90% of the protein-coding gene mutations of the corresponding tumors. As determined by the induction of hypercalcemia in tumorgraft-bearing mice, tumorgrafts retained the ability to induce paraneoplastic syndromes. In studies simulating drug exposures in patients, RCC tumorgraft growth was inhibited by sunitinib and sirolimus (the active metabolite of temsirolimus in humans), but not by erlotinib, which was used as a control. Dovitinib, a drug in clinical development, showed greater activity than sunitinib and sirolimus. The routine incorporation of models recapitulating the molecular genetics and drug sensitivities of human tumors into preclinical programs has the potential to improve oncology drug development.
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Project description:Renal cell carcinoma (RCC) encompasses a heterogenous group of diseases, creating challenges for drug development. Preclinical models which are both translatable and representative of disease heterogeneity are needed. Patient-derived xenograft (PDX) or tumorgraft (TG) models recapitulate the biology and treatment responsiveness of RCC. Through the orthotopic implantation into NOD/SCID mice of tumor samples from >900 ethnically-diverse patients at UT Southwestern Medical Center and the affiliated county hospital, we have generated a resource comprising 172 independently-derived stably-engrafted TG lines from 148 patients. The lines have been characterized histologically and genomically (whole exome sequencing [n = 97] and RNA sequencing [n =102]). They represent a variety of histological and on
cogenotypes including representative TCGA clades further validated through orthogonal metabolomic analyses in a subset. We illustrate how this platform has enabled a deeper understanding of the biology and molecular genetics of RCC, the development of both tissue- and imaging-based biomarkers, as well as advances in drug development. This resource expands the diversity of models available to the scientific community to advance precision diagnosis and therapy in RCC.
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Project description:The objective of the present work was to establish a large panel of preclinical models of human renal cell carcinoma (RCC) directly from patients, faithfully reproducing the biological features of the original tumor. RCC tissues (all stages/subtypes) were collected for 8 years from 336 patients undergoing surgery, xenografted subcutaneously in nude mice, and serially passaged into new mice up to 13 passages. Tissue samples from the primary tumor and tumors grown in mice through passages were analyzed for biological tissue stability by histopathology, mRNA profiling, von Hippel-Lindau gene sequencing, STR fingerprinting, growth characteristics and response to current therapies. Metastatic models were also established by orthotopic implantation and analyzed by imagery. We established a large panel of 30 RCC models (passage > 3, 8.9% success rate). High tumor take rate was associated with high stage and grade. Histopathologic, molecular and genetic characteristics were preserved between original tumors and case-matched xenografts. The models reproduced the sensitivity to targeted therapies observed in the clinic. Overall, these models constitute an invaluable tool for the clinical design of efficient therapies, the identification of predictive biomarkers and translational research.
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Project description:Renal cell carcinoma (RCC) is a kidney cancer with an onset mainly during the sixth or seventh decade of the patient's life. Patients with advanced, metastasized RCC have a poor prognosis. The majority of patients develop treatment resistance towards Standard of Care (SoC) drugs within months. Tyrosine kinase inhibitors (TKIs) are the backbone of first-line therapy and have been partnered with an immune checkpoint inhibitor (ICI) recently. Despite the most recent progress, the development of novel therapies targeting acquired TKI resistance mechanisms in advanced and metastatic RCC remains a high medical need. Preclinical models with high translational relevance can significantly support the development of novel personalized therapies. It has been demonstrated that patient-derived xenograft (PDX) models represent an essential tool for the preclinical evaluation of novel targeted therapies and their combinations. In the present project, we established and molecularly characterized a comprehensive panel of subcutaneous RCC PDX models with well-conserved molecular and pathological features over multiple passages. Drug screening towards four SoC drugs targeting the vascular endothelial growth factor (VEGF) and PI3K/mTOR pathway revealed individual and heterogeneous response profiles in those models, very similar to observations in patients. As unique features, our cohort includes PDX models from metastatic disease and multi-tumor regions from one patient, allowing extended studies on intra-tumor heterogeneity (ITH). The PDX models are further used as basis for developing corresponding in vitro cell culture models enabling advanced high-throughput drug screening in a personalized context. PDX models were subjected to next-generation sequencing (NGS). Characterization of cancer-relevant features including driver mutations or cellular processes was performed using mutational and gene expression data in order to identify potential biomarker or treatment targets in RCC. In summary, we report a newly established and molecularly characterized panel of RCC PDX models with high relevance for translational preclinical research.
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