Conservation of copy number profiles during engraftment and passaging of patient-derived cancer xenografts.
ABSTRACT: Patient-derived xenografts (PDXs) are resected human tumors engrafted into mice for preclinical studies and therapeutic testing. It has been proposed that the mouse host affects tumor evolution during PDX engraftment and propagation, affecting the accuracy of PDX modeling of human cancer. Here, we exhaustively analyze copy number alterations (CNAs) in 1,451 PDX and matched patient tumor (PT) samples from 509 PDX models. CNA inferences based on DNA sequencing and microarray data displayed substantially higher resolution and dynamic range than gene expression-based inferences, and they also showed strong CNA conservation from PTs through late-passage PDXs. CNA recurrence analysis of 130 colorectal and breast PT/PDX-early/PDX-late trios confirmed high-resolution CNA retention. We observed no significant enrichment of cancer-related genes in PDX-specific CNAs across models. Moreover, CNA differences between patient and PDX tumors were comparable to variations in multiregion samples within patients. Our study demonstrates the lack of systematic copy number evolution driven by the PDX mouse host.
Project description:Patient-derived xenografts (PDXs) have become a prominent cancer model system, as they are presumed to faithfully represent the genomic features of primary tumors. Here we monitored the dynamics of copy number alterations (CNAs) in 1,110 PDX samples across 24 cancer types. We observed rapid accumulation of CNAs during PDX passaging, often due to selection of preexisting minor clones. CNA acquisition in PDXs was correlated with the tissue-specific levels of aneuploidy and genetic heterogeneity observed in primary tumors. However, the particular CNAs acquired during PDX passaging differed from those acquired during tumor evolution in patients. Several CNAs recurrently observed in primary tumors gradually disappeared in PDXs, indicating that events undergoing positive selection in humans can become dispensable during propagation in mice. Notably, the genomic stability of PDXs was associated with their response to chemotherapy and targeted drugs. These findings have major implications for PDX-based modeling of human cancer.
Project description:Progress in defining genomic fitness landscapes in cancer, especially those defined by copy number alterations (CNAs), has been impeded by lack of time-series single-cell sampling of polyclonal populations and temporal statistical models<sup>1-7</sup>. Here we generated 42,000 genomes from multi-year time-series single-cell whole-genome sequencing of breast epithelium and primary triple-negative breast cancer (TNBC) patient-derived xenografts (PDXs), revealing the nature of CNA-defined clonal fitness dynamics induced by TP53 mutation and cisplatin chemotherapy. Using a new Wright-Fisher population genetics model<sup>8,9</sup> to infer clonal fitness, we found that TP53 mutation alters the fitness landscape, reproducibly distributing fitness over a larger number of clones associated with distinct CNAs. Furthermore, in TNBC PDX models with mutated TP53, inferred fitness coefficients from CNA-based genotypes accurately forecast experimentally enforced clonal competition dynamics. Drug treatment in three long-term serially passaged TNBC PDXs resulted in cisplatin-resistant clones emerging from low-fitness phylogenetic lineages in the untreated setting. Conversely, high-fitness clones from treatment-naive controls were eradicated, signalling an inversion of the fitness landscape. Finally, upon release of drug, selection pressure dynamics were reversed, indicating a fitness cost of treatment resistance. Together, our findings define clonal fitness linked to both CNA and therapeutic resistance in polyclonal tumours.
Project description:<h4>Motivation</h4>The accurate detection of copy number alterations (CNAs) in human genomes is important for understanding susceptibility to cancer and mechanisms of tumor progression. CNA detection in tumors from single nucleotide polymorphism (SNP) genotyping arrays is a challenging problem due to phenomena such as aneuploidy, stromal contamination, genomic waves and intra-tumor heterogeneity, issues that leading methods do not optimally address.<h4>Results</h4>Here we introduce methods and software (PennCNV-tumor) for fast and accurate CNA detection using signal intensity data from SNP genotyping arrays. We estimate stromal contamination by applying a maximum likelihood approach over multiple discrete genomic intervals. By conditioning on signal intensity across the genome, our method accounts for both aneuploidy and genomic waves. Finally, our method uses a hidden Markov model to integrate multiple sources of information, including total and allele-specific signal intensity at each SNP, as well as physical maps to make posterior inferences of CNAs. Using real data from cancer cell-lines and patient tumors, we demonstrate substantial improvements in accuracy and computational efficiency compared with existing methods.
Project description:Rodent models mimic the heterogeneity of head and neck cancer (HNC) malignancies and are used to investigate HNC-associated biomarkers and evaluate drug responses. To assess the utility of patient-derived xenografts (PDXs) as an HNC model, 18 tumour samples were obtained from surgical specimens of patients with HNC and implanted into non-obese diabetic severe combined immunodeficient mice. The histological features of PDXs and corresponding patient samples were compared. Furthermore, the present study investigated how PDX responses to anticancer drugs mimic patient clinical responses, as well as the expression of adenosine triphosphate-binding cassette transporters through chemotherapy in an HNC-PDX model. A total of five PDXs from patients with HNC exhibiting high correspondence with histopathological features of the original patient samples were established (establishment rate, 28%). The responses of three PDXs to cisplatin were associated with clinical responses of the patients. ABC transporter expression was augmented in one PDX model after anticancer drug treatment, but not in PBS-treated passaged PDXs. PDX models exhibited similar biological and chemosensitive characteristics to those of the primary tumours. PDXs could be a useful preclinical tool to test novel therapeutic agents and identify novel targets and biomarkers in HNC.
Project description:<h4>Background</h4>Because patient-derived xenografts (PDXs) are grown in immunodeficient mouse strains, PDXs are regarded as lacking an immune microenvironment. However, whether patients' immune cells co-exist in PDXs remains uncharacterized.<h4>Methods</h4>We cultured small pieces of lung PDX tissue in media containing human interleukin-2 and characterized the proliferated lymphocytes by flow cytometric assays with antibodies specific for human immune cell surface markers. Presence of immune cells in PDXs was also determined by immunohistochemical staining.<h4>Results</h4>Human tumor-infiltrating lymphocytes (TILs) were cultured from nine of 25 PDX samples (36%). The mean time of PDX growth in immunodeficient mice before obtaining TILs in culture was 113 days (range 63-292 days). The TILs detected in PDXs were predominantly human CD8<sup>+</sup> T cells, CD4<sup>+</sup> T cells, or CD19<sup>+</sup> B cells, depending on cases. DNA fingerprint analysis showed that the TILs originated from the same patients as the PDXs. Further analysis of two PDX-derived CD8<sup>+</sup> T cells showed that they were PD-1<sup>-</sup>, CD45RO<sup>+</sup>, and either CD62L<sup>+</sup> or CD62L<sup>-</sup>, suggesting they were likely memory T cells. Immunohistochemical staining showed that human T cells (CD8<sup>+</sup> or CD4<sup>+</sup>), B cells (CD19<sup>+</sup>), and macrophages (CD68<sup>+</sup>) were present in stroma or intraepithelial cancer structures and that human PD-L1 was expressed in stromal cells. Moreover, the patient-derived immune cells in PDX can be passaged to the F2 generation and may migrate to spleens of PDX-bearing mice.<h4>Conclusions</h4>Patient-derived immune cells co-exist in early passages of PDXs in some lung cancer PDX models. The CD8<sup>+</sup> cells from PDXs were likely memory T cells. These results suggest that PDXs can be used for evaluating the functionality of immune components in tumor microenvironments.
Project description:<h4>Background</h4>Renal medullary carcinoma (RMC) is a rare but aggressive tumor often complicated by early lung metastasis with few treatment options and very poor outcomes. There are currently no verified RMC patient-derived xenograft (PDX) mouse models established from metastatic pleural effusion (PE) available to study RMC and evaluate new therapeutic options.<h4>Methods</h4>Renal tumor tissue and malignant PE cells from an RMC patient were successfully engrafted into 20 NOD.Cg-Prkdc<sup>scid</sup> Il2rg<sup>tm1Wjl</sup>/SzJ (NSG) mice. We evaluated the histopathological similarity of the renal tumor and PE PDXs with the original patient renal tumor and PE, respectively. We then evaluated the molecular integrity of the renal tumor PDXs between passages, as well as the PE PDX compared to two generations of renal tumor PDXs, by microarray analysis. The therapeutic efficacy of sunitinib and temsirolimus was tested in a serially-transplanted generation of 27 PE PDX mice.<h4>Results</h4>The pathologic characteristics of the patient renal tumor and patient PE were retained in the PDXs. Gene expression profiling revealed high concordance between the two generations of renal tumor PDXs (RMC-P0 vs. RMC-P1, r=0.865), as well as between the first generation PE PDX and each generation of the renal tumor PDX (PE-P0 vs. RMC-P0, r=0.919 and PE-P0 vs. RMC-P1, r=0.843). A low number (626) of differentially-expressed genes (DEGs) was seen between the first generation PE PDX and the first generation renal tumor PDX. In the PE-P1 xenograft, sunitinib significantly reduced tumor growth (p<0.001) and prolonged survival (p=0.004) compared to the vehicle control.<h4>Conclusions</h4>A metastatic PE-derived RMC PDX model was established and shown to maintain histologic features of the patient cancer. Molecular integrity of the PDX models was well maintained between renal tumor and PE PDX as well as between two successive renal tumor PDX generations. Using the PE PDX model, sunitinib demonstrated therapeutic efficacy for RMC. This model can serve as a foundation for future mechanistic and therapeutic studies for primary and metastatic RMC.
Project description: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:Patient derived xenografts (PDXs) represent an essential tool in oncologic research, and we sought to further expand our repertoire of head and neck squamous cell carcinoma (HNSCC) while determining potential boundaries for this system.We consented new patients for PDX development and determined if a 24-h time delay from tumor excision to xenograft implantation affected PDX establishment. We developed a tissue microarray (TMA) from formalin fixed, paraffin embedded PDXs and their subsequent passages and carried out quantitative immunohistochemistry for EGFR, pEGFR, pAkt, pERK and ERCC1. First and last passaged PDXs were compared via a paired t-test to examine for the stability of protein expression across passages. We performed a similar comparison of the mutational profile of the patient tumor and resulting xenografts using a targeted sequencing approach.No patient/tumor characteristics influenced PDX take rate and the 24-h time delay from tumor excision to xenograft implantation did not affect PDX establishment, growth or histology. There was no significant difference in biomarker expression between the first and last passaged PDXs for EGFR, pEGFR, pAkt, and ERCC1. For pERK there was a significant difference (p=0.002), but further analysis demonstrated this only arose in three of 15 PDXs. Targeted sequencing revealed striking stability of passenger and likely driver mutations from patient to xenograft.The stability of protein expression across PDX passages will hopefully allow greater investigation of predictive biomarkers in order to identify ones for further pre-clinical and clinical investigation.
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.