Development and characterization of patient-derived xenografts from non-small cell lung cancer brain metastases.
ABSTRACT: Non-small cell lung cancer (NSCLC) brain metastasis cell lines and in vivo models are not widely accessible. Herein we report on a direct-from patient-derived xenograft (PDX) model system of NSCLC brain metastases with genomic annotation useful for translational and mechanistic studies. Both heterotopic and orthotopic intracranial xenografts were established and RNA and DNA sequencing was performed on patient and matching tumors. Morphologically, strong retention of cytoarchitectural features was observed between original patient tumors and PDXs. Transcriptome and mutation analysis revealed high correlation between matched patient and PDX samples with more than more than 95% of variants detected being retained in the matched PDXs. PDXs demonstrated response to radiation, response to selumetinib in tumors harboring KRAS G12C mutations and response to savolitinib in a tumor with MET exon 14 skipping mutation. Savolitinib also demonstrated in vivo radiation enhancement in our MET exon 14 mutated PDX. Early passage cell strains showed high consistency between patient and PDX tumors. Together, these data describe a robust human xenograft model system for investigating NSCLC brain metastases. These PDXs and cell lines show strong phenotypic and molecular correlation with the original patient tumors and provide a valuable resource for testing preclinical therapeutics.
Project description:Gastrointestinal stromal tumors (GISTs) with KIT or platelet-derived growth factor receptor alpha (PDGFRa) oncogenic driver gene mutations, respond to tyrosine kinase inhibitors (TKIs) including imatinib, sunitinib, and regorafenib. However, most patients develop TKI resistance; therefore, novel agents are required. We established three TKI-resistant GIST patient-derived xenograft (PDX) models for effective drug development. These were PDX models harboring primary and secondary KIT and additional mutations; KIT exon 11 (p.Y570_L576del), KIT exon 17 (p.D816E), and PTEN (p.T321fs) mutations in GIST-RX1 from a patient who was unresponsive to imatinib, sunitinib, and sorafenib, and KIT exon 11 (p.K550_splice) and KIT exon 14 (p.T670I) mutations in GIST-RX2 and KIT exon 9 (p.502_503insYA) and KIT exon 17 (p.D820E) mutations in GIST-RX4 from patients with imatinib and imatinib/sunitinib resistance, respectively. The histological features and mutation statuses of GIST PDXs were consistent with those of the original patient tumors, and the models showed TKI sensitivity comparable to clinical responses. Imatinib inhibited the KIT pathway in imatinib-sensitive GIST-T1 but not GIST-RX1, RX2, and RX4. These GIST PDX models will be useful for studying TKI resistance mechanisms and evaluating novel targeted agents in GIST.
Project description:The vast majority of mortality in breast cancer results from distant metastasis. Brain metastases occur in as many as 30% of patients with advanced breast cancer, and the 1-year survival rate of these patients is around 20%. Pre-clinical animal models that reliably reflect the biology of breast cancer brain metastasis are needed to develop and test new treatments for this deadly condition. The patient-derived xenograft (PDX) model maintains many features of a donor tumor, such as intra-tumor heterogeneity, and permits the testing of individualized treatments. However, the establishment of orthotopic PDXs of brain metastasis is procedurally difficult. We have developed a method for generating such PDXs with high tumor engraftment and growth rates. Here, we describe this method and identify variables that affect its outcomes. We also compare the brain-orthotopic PDXs with ectopic PDXs grown in mammary pads of mice, and show that the responsiveness of PDXs to chemotherapeutic reagents can be dramatically affected by the site that they are in.
Project description:Colorectal cancer (CRC) is the second most common cancer in Europe and a leading cause of death worldwide. Patient-derived xenograft (PDX) models maintain complex intratumoral biology and heterogeneity and therefore remain the platform of choice for translational drug discovery. In this study, we implanted 37 primary CRC tumors and five CRC cell lines into NU/J mice to develop xenograft models. Primary tumors and established xenografts were histologically assessed and surveyed for genetic variants and gene expression using a panel of 409 cancer-related genes and RNA-seq, respectively. More than half of CRC tumors (20 out of 37, 54%) developed into a PDX. Histological assessment confirmed that PDX grading, stromal components, inflammation, and budding were consistent with those of the primary tumors. DNA sequencing identified an average of 0.14 variants per gene per sample. The percentage of mutated variants in PDXs increased with successive passages, indicating a decrease in clonal heterogeneity. Gene Ontology analyses of 4180 differentially expressed transcripts (adj. p value < 0.05) revealed overrepresentation of genes involved in cell division and catabolic processes among the transcripts upregulated in PDXs; downregulated transcripts were associated with GO terms related to extracellular matrix organization, immune responses, and angiogenesis. Neither a transcriptome-based consensus molecular subtype (CMS) classifier nor three other predictors reliably matched PDX molecular subtypes with those of the primary tumors. In sum, both genetic and transcriptomic profiles differed between donor tumors and PDXs, likely as a consequence of subclonal evolution at the early phase of xenograft development, making molecular stratification of PDXs challenging.
Project description:Herein, we report an oral cavity squamous cell carcinoma (OCSCC) patient-derived xenograft (PDX) platform, with genomic annotation useful for co-clinical trial and mechanistic studies. Genomic analysis included whole-exome sequencing (WES) and transcriptome sequencing (RNA-seq) on 16 tumors and matched PDXs and additional whole-genome sequencing (WGS) on 9 of these pairs as a representative subset of a larger OCSCC PDX repository (n = 63). In 12 models with high purity, more than 90% of variants detected in the tumor were retained in the matched PDX. The genomic landscape across these PDXs reflected OCSCC molecular heterogeneity, including previously described basal, mesenchymal, and classical molecular subtypes. To demonstrate the integration of PDXs into a clinical trial framework, we show that pharmacological intervention in PDXs parallels clinical response and extends patient data. Together, these data describe a repository of OCSCC-specific PDXs and illustrate conservation of primary tumor genotypes, intratumoral heterogeneity, and co-clinical trial application.
Project description:This protocol provides the steps required for the establishment of patient-derived xenograft (PDX) tumors for head and neck squamous cell carcinomas (HNSCCs) and their utility in examining drug responses. PDXs recapitulate the heterogeneity observed in the corresponding human tumors, which makes them an ideal pre-clinical model system. This protocol outlines the detailed steps required for (1) the generation of HNSCC-PDXs, (2) the processing of tumor tissues, and (3) the expansion of PDX models into cohorts for (4) drug testing. For complete details on the use and execution of this protocol please refer to Karamboulas et al. (2018).
Project description:BACKGROUND:The seed and soil hypothesis was proposed over a century ago to describe why cancer cells (seeds) grow in certain organs (soil). Since then, the genetic properties that define the cancer cells have been heavily investigated; however, genomic mediators within the organ microenvironment that mediate successful metastatic growth are less understood. These studies sought to identify cancer- and organ-specific genomic programs that mediate metastasis. METHODS:In these studies, a set of 14 human breast cancer patient-derived xenograft (PDX) metastasis models was developed and then tested for metastatic tropism with two approaches: spontaneous metastases from mammary tumors and intravenous injection of PDX cells. The transcriptomes of the cancer cells when growing as tumors or metastases were separated from the transcriptomes of the microenvironment via species-specific separation of the genomes. Drug treatment of PDX spheroids was performed to determine if genes activated in metastases may identify targetable mediators of viability. RESULTS:The experimental approaches that generated metastases in PDX models were identified. RNA sequencing of 134 tumors, metastases, and normal non-metastatic organs identified cancer- and organ-specific genomic properties that mediated metastasis. A common genomic response of the liver microenvironment was found to occur in reaction to the invading PDX cells. Genes within the cancer cells were found to be either transiently regulated by the microenvironment or permanently altered due to clonal selection of metastatic sublines. Gene Set Enrichment Analyses identified more than 400 gene signatures that were commonly activated in metastases across basal-like PDXs. A Src signaling signature was found to be extensively upregulated in metastases, and Src inhibitors were found to be cytotoxic to PDX spheroids. CONCLUSIONS:These studies identified that during the growth of breast cancer metastases, there were genomic changes that occurred within both the cancer cells and the organ microenvironment. We hypothesize that pathways upregulated in metastases are mediators of viability and that simultaneously targeting changes within different cancer cell pathways and/or different tissue compartments may be needed for inhibition of disease progression.
Project description:Patient-derived xenograft (PDX) models are important tools in precision medicine and for the development of targeted therapies to treat cancer patients. This study aimed to evaluate our precision medicine strategy that integrates genomic profiling and preclinical drug-screening platforms, in order to personalize cancer treatments using PDX models.We performed array-comparative genomic hybridization, microarray, and targeted next-generation sequencing analyses, in order to determine the oncogenic driver mutations. PDX cells were obtained from PDXs and subsequently screened in vitro with 17 targeted agents.PDX tumors recapitulated the histopathologic and genetic features of the patient tumors. Among the samples from lung cancer patients that were molecularly-profiled, copy number analysis identified unique focal MET amplification in one sample, 033 T, without RTK/RAS/RAF oncogene mutations. Although HER2 amplification in 033 T was not detected in the cancer panel, the selection of HER2-amplified clones was found in PDXs and PDX cells. Additionally, MET and HER2 overexpression were found in patient tumors, PDXs, and PDX cells. Crizotinib or EGFR tyrosine kinase inhibitor treatments significantly inhibited cell growth and impaired tumor sphere formation in 033 T PDX cells.We established PDX cell models using surgical samples from lung cancer patients, and investigated their preclinical and clinical implications for personalized targeted therapy. Additionally, we suggest that MET and EGFR inhibitor-based therapy can be used to treat MET and HER2-overexpressing lung cancers, without receptor tyrosine kinase /RAS/RAF pathway alterations.
Project description:While patient-derived xenograft (PDX) models of hepatocellular carcinoma (HCC) have been successfully generated from resected tissues, no reliable methods have been reported for the generation of PDXs from patients who are not candidates for resection and represent the vast majority of patients with HCC. Here we compare two methods for the creation of PDXs from HCC biopsies and find that implantation of whole biopsy samples without the addition of basement membrane matrix favors the formation of PDX tumors that resemble Epstein-Barr virus (EBV)-driven B-cell lymphomas rather than HCC tumors. In contrast, implantation with Matrigel supports growth of HCC cells and leads to a high rate of HCC tumor formation from these biopsies. We validate the resulting PDXs, confirm their fidelity to the patients' disease and conclude that minimally invasive percutaneous liver biopsies can be used with relatively high efficiency to generate PDXs of HCC.
Project description:Pancreatic ductal adenocarcinoma (PDAC) is the most challenging type of cancer to treat, with a 5-year survival rate of <10%. Furthermore, because of the large portion of the inoperable cases, it is difficult to obtain specimens to study the biology of the tumors. Therefore, a patient-derived xenograft (PDX) model is an attractive option for preserving and expanding these tumors for translational research. Here we report the generation and characterization of 20 PDX models of PDAC. The success rate of the initial graft was 74% and most tumors were re-transplantable. Histological analysis of the PDXs and primary tumors revealed a conserved expression pattern of p53 and SMAD4; an exome single nucleotide polymorphism (SNP) array and Comprehensive Cancer Panel showed that PDXs retained over 94% of cancer-associated variants. In addition, Polyphen2 and the Sorting Intolerant from Tolerant (SIFT) prediction identified 623 variants among the functional SNPs, highlighting the heterologous nature of pancreatic PDXs; an analysis of 409 tumor suppressor genes and oncogenes in Comprehensive Cancer Panel revealed heterologous cancer gene mutation profiles for each PDX-primary tumor pair. Altogether, we expect these PDX models are a promising platform for screening novel therapeutic agents and diagnostic markers for the detection and eradication of PDAC.
Project description:Tumor heterogeneity and evolution drive treatment resistance in metastatic colorectal cancer (mCRC). Patient-derived xenografts (PDXs) can model mCRC biology; however, their ability to accurately mimic human tumor heterogeneity is unclear. Current genomic studies in mCRC have limited scope and lack matched PDXs. Therefore, the landscape of tumor heterogeneity and its impact on the evolution of metastasis and PDXs remain undefined. We performed whole-genome, deep exome, and targeted validation sequencing of multiple primary regions, matched distant metastases, and PDXs from 11 patients with mCRC. We observed intricate clonal heterogeneity and evolution affecting metastasis dissemination and PDX clonal selection. Metastasis formation followed both monoclonal and polyclonal seeding models. In four cases, metastasis-seeding clones were not identified in any primary region, consistent with a metastasis-seeding-metastasis model. PDXs underrepresented the subclonal heterogeneity of parental tumors. These suggest that single sample tumor sequencing and current PDX models may be insufficient to guide precision medicine.