Rational selection of syngeneic preclinical tumor models for immunotherapeutic drug discovery
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ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE85509 | GEO | 2016/12/07
SECONDARY ACCESSION(S): PRJNA338671
REPOSITORIES: GEO
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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
| PRJNA338671 | ENA
Project description:BACKGROUND:The ability to modulate immune-inhibitory pathways using checkpoint blockade antibodies such as ?PD-1, ?PD-L1, and ?CTLA-4 represents a significant breakthrough in cancer therapy in recent years. This has driven interest in identifying small-molecule-immunotherapy combinations to increase the proportion of responses. Murine syngeneic models, which have a functional immune system, represent an essential tool for pre-clinical evaluation of new immunotherapies. However, immune response varies widely between models and the translational relevance of each model is not fully understood, making selection of an appropriate pre-clinical model for drug target validation challenging. METHODS:Using flow cytometry, O-link protein analysis, RT-PCR, and RNAseq we have characterized kinetic changes in immune-cell populations over the course of tumor development in commonly used syngeneic models. RESULTS:This longitudinal profiling of syngeneic models enables pharmacodynamic time point selection within each model, dependent on the immune population of interest. Additionally, we have characterized the changes in immune populations in each of these models after treatment with the combination of ?-PD-L1 and ?-CTLA-4 antibodies, enabling benchmarking to known immune modulating treatments within each model. CONCLUSIONS:Taken together, this dataset will provide a framework for characterization and enable the selection of the optimal models for immunotherapy combinations and generate potential biomarkers for clinical evaluation in identifying responders and non-responders to immunotherapy combinations.
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Project description:Oncology drug efficacy is evaluated in mouse models by continuously monitoring tumor volumes, which can be mathematically described by growth kinetic models. Although past studies have investigated various growth models, their reliance on small datasets raises concerns about whether their findings are truly representative of tumor growth in diverse mouse models under different vehicle or drug treatments. In this study, we systematically evaluated six parametric models (exponential, exponential quadratic, monomolecular, logistic, Gompertz, and von Bertalanffy) and the semiparametric generalized additive model (GAM) on fitting tumor volume data from more than 30,000 mice in 930 experiments conducted in patient-derived xenografts, cell line-derived xenografts, and syngeneic models. We found that the exponential quadratic model is the best parametric model and can adequately model 87% studies, higher than other models including von Bertalanffy (82%) and Gompertz (80%) models; the latter is often considered the standard growth model. At the mouse group level, 7.5% of growth data could not be fit by any parametric model and were fitted by GAM. We show that endpoint gain integrated in time, a GAM-derived efficacy metric, is equivalent to exponential growth rate, a metric we previously proposed and conveniently calculated by simple algebra. Using five studies on paclitaxel, anti-PD1 antibody, cetuximab, irinotecan, and sorafenib, we showed that exponential and exponential quadratic models achieve similar performance in uncovering drug mechanism and biomarkers. We also compared exponential growth rate-based association analysis and exponential modeling approach in biomarker discovery and found that they complement each other. Modeling methods herein are implemented in an open-source R package freely available at https://github.com/hjzhou988/TuGroMix.SignificanceWe present a general strategy for mathematically modeling tumor growth in mouse models using data from 30,000 mice and show that modeling and nonmodeling approaches are complementary in biomarker discovery and drug mechanism studies.
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Project description:Numerous drug treatments that have recently entered the clinic or clinical trials have their genesis in zebrafish. Zebrafish are well established for their contribution to developmental biology and have now emerged as a powerful preclinical model for human disease, as their disease characteristics, aetiology and progression, and molecular mechanisms are clinically relevant and highly conserved. Zebrafish respond to small molecules and drug treatments at physiologically relevant dose ranges and, when combined with cell-specific or tissue-specific reporters and gene editing technologies, drug activity can be studied at single-cell resolution within the complexity of a whole animal, across tissues and over an extended timescale. These features enable high-throughput and high-content phenotypic drug screening, repurposing of available drugs for personalized and compassionate use, and even the development of new drug classes. Often, drugs and drug leads explored in zebrafish have an inter-organ mechanism of action and would otherwise not be identified through targeted screening approaches. Here, we discuss how zebrafish is an important model for drug discovery, the process of how these discoveries emerge and future opportunities for maximizing zebrafish potential in medical discoveries.
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2015-09-17 | E-GEOD-69214 | biostudies-arrayexpress
Project description:Nontuberculous mycobacteria (NTM) represent an increasingly prevalent etiology of soft tissue infections in animals and humans. NTM are widely distributed in the environment and while, for the most part, they behave as saprophytic organisms, in certain situations, they can be pathogenic, so much so that the incidence of NTM infections has surpassed that of Mycobacterium tuberculosis in developed countries. As a result, a growing body of the literature has focused attention on the critical role that drug susceptibility tests and infection models play in the design of appropriate therapeutic strategies against NTM diseases. This paper is an overview of the in vitro and in vivo models of NTM infection employed in the preclinical phase for early drug discovery and vaccine development. It summarizes alternative methods, not fully explored, for the characterization of anti-mycobacterial compounds.
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Project description:Atypical teratoid rhabdoid tumor (ATRT) is an aggressive embryonal brain tumor among infants and young children. Two challenges exist for preclinical testing in ATRT. First, genetically quiet, ATRT is a difficult tumor to target molecularly. Tumor cells need to divide to propagate tumor growth-intercepting the common crossroads in cell cycle progression is a feasible strategy. KIF11 is needed for bipolar spindle formation in metaphase. We identified KIF11 as a universal target of all ATRT-molecular-subtypes. Ispinesib, a KIF11-inhibitor, effectively inhibited tumor proliferation in all seven cell lines. A second challenge-a major challenge in preclinical drug testing in-vivo among aggressive tumor models, is the narrow therapeutic window to administer drugs within the limited murine lifespan. Our most aggressive ATRT tumor model was lethal in all mice within ~ 1 month of tumor implantation. Such short-surviving mouse models are difficult to employ for preclinical drug testing due to the narrow time window to administer drugs. To overcome this time restriction, we developed a clinical staging system which allowed physically-fit mice to continue treatment, in contrast to the conventional method of fixed drug-dose-duration regimen in preclinical testing which will not be feasible in such short-surviving mouse models. We validated this approach in a second embryonal brain tumor, medulloblastoma. This is a clinically relevant, cost-efficient approach in preclinical testing for cancer and non-cancer disease phenotypes. Widely used preclinical mouse models are not the most accurate and lack the aggressive tumor spectrum found within a single tumor type. Mice bearing the most aggressive tumor spectrum progress rapidly in the limited murine life-span, resulting in a narrow therapeutic window to administer drugs, and are thus difficult to employ in preclinical testing. Our approach overcomes this challenge. We discovered ispinesib is efficacious against two embryonal brain tumor types.
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Project description:The lack of reliable animal models to assess the safety and efficacy of drugs and to explore the underlying molecular mechanisms is one of the most severe impediments in head and neck squamous cell carcinoma (HNSCC) tumor immunology research. The majority of xenograft tumor models established using immunodeficient mice neglect the effects of T cells. To date, to the best of our knowledge, there is no syngeneic tumor model available that reflects the immune microenvironmental features of HNSCC tumors. To solve this issue, the present study used 4‑nitroquinoline‑1‑oxide (4‑NQO) to induce squamous cell carcinoma in C57BL/6 mice. Three HNSCC cell lines were then established, and one of these, termed JC1, was selected for further analysis due to its enhanced proliferative ability and tumorigenicity in immunodeficient nude mice. However, none of the 3 cell lines could form tumors in immunocompetent mice. Due to the different tumorigenicities in nude and C57BL/6 mice, the immune system may play an important role in inoculated JC1 tumor progression. Chemical induction was used to establish the tumorigenicity‑enhanced cell line, JC1‑2, which can form syngeneic tumors in immunocompetent C57BL/6 mice. Next‑generation sequencing (NGS) was used to perform the immunogenomic and transcriptomic characterization of the JC1‑2 cells. Splenocytes were isolated from C57BL/6 mice and co‑cultured with JC1‑2 cells to verify the responsiveness of the interferon (IFN)‑γ pathway in the JC1‑2 cell line. Unlike the majority of syngeneic mouse tumors, the JC1‑2‑formed tumors resembled 'inflamed tumors' due to the abundancy of immune cells in the tumor microenvironment. Moreover, more intense immune responses were observed in the orthotopic mouse model than in the heterotopic model. Thus, this model could be used to delineate the interactions between HNSCC and lymphocytes, and to validate novel immunotherapy targets.
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