Single cell sequencing of mouse syngeneic tumor models
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ABSTRACT:
PROVIDER: PRJNA498671 | ENA |
REPOSITORIES: ENA
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Project description:Tumor ecosystems are composed of multiple cell types that communicate by ligand-receptor interactions. Targeting ligand-receptor interactions, for instance with immune check-point inhibitors, can provide significant benefit for patients. However, our knowledge of which interactions occur in a tumor and how these interactions affect outcome is still limited. We present an approach to characterize communication by ligand-receptor interactions across all cell types in a microenvironment using single-cell RNA sequencing. We apply this approach to identify and compare ligand-receptor interactions present in six syngeneic mouse tumor models. To identify interactions potentially associated with outcome, we regress interactions against phenotypic measurements of tumor growth rate. In addition, we quantify ligand-receptor interactions between T-cell subsets and their relation to immune infiltration using a publicly available human melanoma data-set. Overall, this approach provides a tool for studying cell-cell interactions, their variability across tumors, and their relationship to outcome.
2018-10-27 | GSE121861 | GEO
Project description:The cell line-derived xenografts and patient derived xenografts have limited use in cancer immunotherapy evaluation because an immune compromised host is required for xenotransplantation. Syngeneic mouse models are derived by transplanting established mouse cell lines or tumor tissues to strain matched mouse hosts, which are better suited to study the interplay between immune and tumor cells. We investigated the differences as well as similarities of a panel of ten mouse syngeneic models to features of human tumors by proteomics, which will provide valuable information to assist experimental biologists in model selection.
2019-12-03 | PXD011885 | Pride
Project description:STK11/LKB1 mutation is a primary driver for immunotherapy resistance. We employed KRAS/LKB1 syngeneic mouse models by injecting tumor cells with Kras mutation, Kras/Stk11 mutation and MCT4 knockout. We used single-cell RNA-seq to analyze the impact of LKB1 deficiency on the immune microenvironment.
2023-05-10 | GSE231742 | GEO
Project description:Characterisation of murine syngeneic tumor models enables rational preclinical model selection for immuno-oncology drug discovery
| PRJEB12925 | ENA
Project description:Murine syngeneic tumor models are the cornerstone of novel immuno-oncology (IO)-based therapy development but the molecular and immunological features of these models are still not clearly defined. The translational relevance of differences between the models is not fully understood, impeding appropriate preclinical model selection for target validation, and ultimately hindering drug development. Within a panel of commonly-used murine syngeneic tumor models, we showed variable responsiveness to IO-therapies. We employed aCGH, whole-exome sequencing, exon microarray analysis and flow cytometry to extensively characterise these models and revealed striking differences that may underlie these contrasting response profiles. We identified strong differential gene expression in immune-related pathways and changes in immune cell-specific genes that suggested differences in tumor immune infiltrates between models. We further investigated this using flow cytometry, which showed differences in both the composition and magnitude of the tumor immune infiltrates, identifying models that harbor ‘inflamed’ and ‘non-inflamed’ tumor immune infiltrate phenotypes. Moreover, we found that immunosuppressive cell types predominated in syngeneic mouse tumor models that did not respond to immune-checkpoint blockade, whereas cytotoxic effector immune cells were enriched in responsive models. A cytotoxic cell-rich tumor immune infiltrate has been correlated with increased efficacy of IO-therapy in the clinic and these differences could underlie the varying response profiles to IO-therapy between the syngeneic models. This characterisation highlighted the importance of extensive profiling and will enable investigators to select appropriate models to interrogate the activity of IO-therapies as well as combinations with targeted therapies in vivo.
2016-12-07 | GSE85508 | GEO
Project description:Murine syngeneic tumor models are the cornerstone of novel immuno-oncology (IO)-based therapy development but the molecular and immunological features of these models are still not clearly defined. The translational relevance of differences between the models is not fully understood, impeding appropriate preclinical model selection for target validation, and ultimately hindering drug development. Within a panel of commonly-used murine syngeneic tumor models, we showed variable responsiveness to IO-therapies. We employed aCGH, whole-exome sequencing, exon microarray analysis and flow cytometry to extensively characterise these models and revealed striking differences that may underlie these contrasting response profiles. We identified strong differential gene expression in immune-related pathways and changes in immune cell-specific genes that suggested differences in tumor immune infiltrates between models. We further investigated this using flow cytometry, which showed differences in both the composition and magnitude of the tumor immune infiltrates, identifying models that harbor ‘inflamed’ and ‘non-inflamed’ tumor immune infiltrate phenotypes. Moreover, we found that immunosuppressive cell types predominated in syngeneic mouse tumor models that did not respond to immune-checkpoint blockade, whereas cytotoxic effector immune cells were enriched in responsive models. A cytotoxic cell-rich tumor immune infiltrate has been correlated with increased efficacy of IO-therapy in the clinic and these differences could underlie the varying response profiles to IO-therapy between the syngeneic models. This characterisation highlighted the importance of extensive profiling and will enable investigators to select appropriate models to interrogate the activity of IO-therapies as well as combinations with targeted therapies in vivo.
2016-12-07 | GSE85507 | GEO
Project description:Rational selection of syngeneic preclinical tumor models for immunotherapeutic drug discovery
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Project description:Molecular Determinants of Response to Anti–PD-1 Immunotherapy in Syngeneic Tumor Mouse Models
| PRJNA714237 | ENA
Project description:Murine syngeneic tumor models have been extensively used for cancer research for several decades. These tumor models are very simplistic cancer models, but recent reports have, however, indicated that the different inoculated cancer cells can lead to the formation of very different tumor microenvironments (TMEs). Importantly, these types of tumor models have been instrumental in driving the discovery and development of cancer immunotherapies. In order to gain more knowledge from studies based on syngeneic tumor models it is essential to know in more details the cellular and molecular composition of the TME in the different models. It is also important to know about other parameters such as the mechanical tumor stiffness of the different models. This type of knowledge can be used for the rational selection of tumor models for specific studies and for studying the correlation between different tumor-promoting parameters. Here, we compare the tumor microenvironment (TME) of tumors derived from six different commonly used syngeneic tumor models. Using flow cytometry and transcriptomic analyses we show that strikingly different TMEs are formed by the different cancer cell lines. The differences are reflected as changes in abundance and phenotype of myeloid, lymphoid and stromal cells in the tumors. The gene expression profile of tumors from the different models supported the different cellular composition of the TMEs and indicate that different mechanisms of immune suppression are employed in the different tumor models. Cancer-associated fibroblasts also acquire very different phenotypes in the different tumor models. These differences include differential expression of genes encoding ECM proteins, MMPs, and immunosuppressive factors. In consistence with these observations, the mechanical stiffness of the tumors from different models do not simply correlate to the number of infiltrating CAFs even though collagen produced by stromal cells is an important reason for the increased stiffness of tumors. The gene expression profiles suggest that CAFs can contribute to the formation of an immunosuppressive TME and flow cytometry analyses show CAFs express high levels of PD-L1 in the immunogenic tumor models MC38 and CT26. Comparison with CAF subsets identified in other studies show that CAFs from the different models are skewed towards specific subsets. CAFs from CT26 tumors show similarities to iCAFs and myCAFs, and in athymic mice without infiltrating cytotoxic T cells, CAFs express lower levels of PD-L1 and lower levels of fibroblast activation markers.
2024-01-29 | GSE245293 | GEO
Project description:Epithelial ovarian cancer (EOC) is the most lethal gynecologic cancer with an imperative need for new treatments. Immunotherapy has had marked success in some cancer types; however, clinical trials studying the efficacy of immune checkpoint inhibitors for the treatment of EOC provided benefit in <15% of patients. EOC is a particularly complex cancer since it develops from various tissues in the reproductive tract and metastasizes into the peritoneal cavity where it is able to colonize almost all organs, creating different tumor microenvironments (TME) containing a variety of immune profiles. In this study, we assessed the immune composition of different murine syngeneic models of EOC from different cellular origins (ovarian and fallopian tube epithelium) and harboring known mutations relevant to human disease, including TP53 mutation, PTEN suppression, and constitutive KRAS activation. We determined immunogenicity of multiple tumor models in vivo, the T and myeloid profile of orthotopic tumors and the immune composition of ascites, by flow cytometry, IHC and single cell RNA-sequencing. Our findings allowed us to predict which models might respond best to PD-L1 blockage, according to key characteristics such as tumor immunogenicity, MHC status, and T cell infiltration. Together these data highlight the heterogeneity found in murine EOC, as in human disease, identified features that might predict immune checkpoint inhibitor efficacy, and revealed crucial information about differences between murine models in the TME composition vs. ascites fluid. These data provide a solid foundation for selecting models in future testing of immunotherapies according to the immune composition and tumor characteristics.
2022-06-01 | GSE183368 | GEO