Project description:Colorectal cancer (CRC) is a challenging disease, with a high mortality rate and limited effective treatment options, particularly for late-stage disease. Patient-derived xenografts (PDXs) have emerged as an informative, renewable experimental resource to model CRC architecture and biology. Here, we describe the generation of a biobank of CRC PDXs from stage I to stage IV patients. We demonstrate that PDXs within our biobank recapitulate the histopathological and mutation features of the original patient tumor. In addition, we demonstrate the utility of this resource in pre-clinical chemotherapy and targeted treatment studies, highlighting the translational potential of PDX models in the identification of new therapies that will improve the overall survival of CRC patients.
Project description:Breast cancer research is hampered by difficulties in obtaining and studying primary human breast tissue, and by the lack of in vivo preclinical models that reflect patient tumor biology accurately. To overcome these limitations, we propagated a cohort of human breast tumors grown in the epithelium-free mammary fat pad of SCID/Beige and NOD/SCID/IL2γ-receptor null (NSG) mice, under a series of transplant conditions. Both models yielded stably transplantable xenografts at comparably high rates (~23% and ~19%, respectively). Of the conditions tested, xenograft take rate was highest in the presence of a low-dose estradiol pellet. Overall, 32 stably transplantable xenograft lines were established, representing unique 25 patients. Most tumors yielding xenografts were “triple-negative” (ER-PR-HER2+) (n=19). However, we established lines from three ER-PR-HER2+ tumors, one ER+PR-HER2-, one ER+PR+HER2- and one “triple-positive” (ER+PR+HER2+) tumor. Serially passaged xenografts show biological consistency with the tumor of origin, are phenotypic stability across multiple transplant generations at the histological, transcriptomic, proteomic, and genomic levels, and show comparable treatment responses. Xenografts representing 12 patients, including two ER+ lines, showed metastasis to the mouse lung. These models thus serve as a renewable, quality-controlled tissue resource for preclinical studies investigating treatment response and metastasis. The study was designed to determine how stable patient-derived xenografts are across multiple transplant generations in mice, and to determine how closely xenografts established with pre-treatment samples cluster with xenografts established with post-treatment samples. Overall, pre-treatment and post-treatment samples derived from the same patient cluster together, and multiple transplant generations of xenografts derived from an individual patient cluster together.
Project description:PurposePatient-derived xenograft (PDX) models accurately recapitulate the tumor of origin in terms of histopathology, genomic landscape, and therapeutic response, but some limitations due to costs associated with their maintenance and restricted amenability for large-scale screenings still exist. To overcome these issues, we established a platform of 2D cell lines (xeno-cell lines, XL), derived from PDXs of colorectal cancer with matched patient germline gDNA available.Experimental designWhole-exome and transcriptome sequencing analyses were performed. Biomarkers of response and resistance to anti-HER therapy were annotated. Dependency on the WRN helicase gene was assessed in MSS, MSI-H, and MSI-like XLs using a reverse genetics functional approach.ResultsXLs recapitulated the entire spectrum of colorectal cancer transcriptional subtypes. Exome and RNA-seq analyses delineated several molecular biomarkers of response and resistance to EGFR and HER2 blockade. Genotype-driven responses observed in vitro in XLs were confirmed in vivo in the matched PDXs. MSI-H models were dependent upon WRN gene expression, while loss of WRN did not affect MSS XLs growth. Interestingly, one MSS XL with transcriptional MSI-like traits was sensitive to WRN depletion.ConclusionsThe XL platform represents a preclinical tool for functional gene validation and proof-of-concept studies to identify novel druggable vulnerabilities in colorectal cancer.
Project description:Cetuximab is an approved treatment for metastatic colorectal carcinoma (mCRC) with codon 12/13-KRAS mutations, recently questioned for its validity, and alternative mutation-based biomarkers were proposed. We set out to investigate whether an expression signature can also predict response by utilizing a cetuximab mouse clinical trial (MCT) dataset on a cohort of 25 randomly selected EGFR+ CRC patient-derived xenografts (PDXs). While we found that the expression of EGFR and its ligands are not predictive of the cetuximab response, we tested a published RAS pathway signature, a 147-gene expression signature proposed to describe RAS pathway activity, against this MCT dataset. Interestingly, our study showed that the observed cetuximab activity has a strong correlation with the RAS pathway signature score, which was also demonstrated to have a certain degree of correlation with a historic clinical dataset. Altogether, the independent validations in unrelated datasets from independent cohort of CRCs strongly suggest that RAS pathway signature may be a relevant expression signature predictive of CRC response to cetuximab. Our data seem to suggest that an mRNA expressing signature may also be developed as a predictive biomarker for drug response, similarly to genetic mutations.
Project description:BackgroundBecause 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.MethodsWe 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.ResultsHuman 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+ T cells, CD4+ T cells, or CD19+ 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+ T cells showed that they were PD-1-, CD45RO+, and either CD62L+ or CD62L-, suggesting they were likely memory T cells. Immunohistochemical staining showed that human T cells (CD8+ or CD4+), B cells (CD19+), and macrophages (CD68+) 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.ConclusionsPatient-derived immune cells co-exist in early passages of PDXs in some lung cancer PDX models. The CD8+ 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: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.
Project description:INTRODUCTION: Identification of new therapeutic agents for breast cancer (BC) requires preclinical models that reproduce the molecular characteristics of their respective clinical tumors. In this work, we analyzed the genomic and gene expression profiles of human BC xenografts and the corresponding patient tumors. METHODS: Eighteen BC xenografts were obtained by grafting tumor fragments from patients into Swiss nude mice. Molecular characterization of patient tumors and xenografts was performed by DNA copy number analysis and gene expression analysis using Affymetrix Microarrays. RESULTS: Comparison analysis showed that 14/18 pairs of tumors shared more than 56% of copy number alterations (CNA). Unsupervised hierarchical clustering analysis showed that 16/18 pairs segregated together, confirming the similarity between tumor pairs. Analysis of recurrent CNA changes between patient tumors and xenografts showed losses in 176 chromosomal regions and gains in 202 chromosomal regions. Gene expression profile analysis showed that less than 5% of genes had recurrent variations between patient tumors and their respective xenografts; these genes largely corresponded to human stromal compartment genes. Finally, analysis of different passages of the same tumor showed that sequential mouse-to-mouse tumor grafts did not affect genomic rearrangements or gene expression profiles, suggesting genetic stability of these models over time. CONCLUSIONS: This panel of human BC xenografts maintains the overall genomic and gene expression profile of the corresponding patient tumors and remains stable throughout sequential in vivo generations. The observed genomic profile and gene expression differences appear to be due to the loss of human stromal genes. These xenografts, therefore, represent a validated model for preclinical investigation of new therapeutic agents.
Project description:Tumor budding has been found to be of prognostic significance for several cancers, including colorectal cancer (CRC). Additionally, the molecular classification of CRC has led to the identification of different immune microenvironments linked to distinct prognosis and therapeutic response. However, the association between tumor budding and the different molecular subtypes of CRC and distinct immune profiles have not been fully elucidated. This study focused, firstly, on the validation of derived xenograft models (PDXs) for the evaluation of tumor budding and their human counterparts and, secondly, on the association between tumor budding and the immune tumor microenvironment by the analysis of gene expression signatures of immune checkpoints, Toll-like receptors (TLRs), and chemokine families. Clinical CRC samples with different grades of tumor budding and their corresponding PDXs were included in this study. Tumor budding grade was reliably reproduced in early passages of PDXs, and high-grade tumor budding was intimately related with a poor-prognosis CMS4 mesenchymal subtype. In addition, an upregulation of negative regulatory immune checkpoints (PDL1, TIM-3, NOX2, and IDO1), TLRs (TLR1, TLR3, TLR4, and TLR6), and chemokine receptors and ligands (CXCR2, CXCR4, CXCL1, CXCL2, CXCL6, and CXCL9) was detected in high-grade tumor budding in both human samples and their corresponding xenografts. Our data support a close link between high-grade tumor budding in CRC and a distinctive immune-suppressive microenvironment promoting tumor invasion, which may have a determinant role in the poor prognosis of the CMS4 mesenchymal subtype. In addition, our study demonstrates that PDX models may constitute a robust preclinical platform for the development of novel therapies directed against tumor budding in CRC.