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Simultaneous analysis of tumor and stromal gene expression profiles from xenograft models

ABSTRACT: Identifying the gene expression alterations that occur in both the tumor and stroma is essential to understanding tumor biology. We have developed a dual-species microarray analysis method that allows the dissection of both tumor and stromal gene expression profiles from xenograft models, based on limited interspecies cross-hybridization on Illumina gene expression beadchips. This methodology allows for simultaneous genome-wide analysis of gene expression profiles of both tumor cells and the associated stromal tissue. Data is provided regarding the crosshybridization of mouse liver RNA on human microarray, and MDA-MB-231 breast cancer cell line RNA on mouse microarray. Data is also provided for comparisons of MDA-MB-231 gene expression in vitro vs. in vivo, and mouse liver gene expression in control mice vs. stroma from MDA-MB-231 xenograft liver metastasis in tumor bearing mice A total of 18 samples were analyzed. Samples consist of 6 different types with each type in triplicate. Types are (1) MDA-MB-231 cell line grown in vitro and arrayed on mouse chips, (2) mouse liver from NOD/SCID mice arrayed on human chips, (3) MDA-MB-231 cell line grown in vitro arrayed on human chips, (4) MDA-MB-231 xenograft liver metastasis arrayed on human chips, (5) mouse liver from NOD/SCID mice arrayed on mouse chips, and (6) MDA-MB-231 xenograft liver metastasis arrayed on mouse chips. The overall design had three objectives: (1) to determine crosshybridizing probes based on sample types 1, 2, 3, and 5, (2) detect stromal and tumor expression using sample types 4 and 6, and (3) determine genes differentially expressed in tumor or metastasis compared to normal by comparing sample types 3 and 4 and comparing sample types 1 and 5.

ORGANISM(S): Homo sapiens

SUBMITTER: Iorns E

PROVIDER: S-ECPF-GEOD-30993 | biostudies-other | 2012 Jan

REPOSITORIES: biostudies-other

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Project description:Advanced gastrointestinal stromal tumors (GIST) are typically treated with tyrosine kinase inhibitors, and imatinib is the most commonly used standard of care in first line treatments. The use of this and other tyrosine kinase inhibitors is associated with objective tumor responses and prolongation of progression-free and overall survival, but the treatment of metastatic disease is non-curative due to the selection or acquisition of secondary mutations and the activation of alternative kinase signaling pathways, leading to resistance and disease progression after an initial response. The present preclinical study evaluated the potential use of the fibroblast growth factor receptor inhibitors infigratinib and dovitinib alone or in combination with the mitogen-activated protein kinase inhibitor binimetinib in mouse models of GIST with different sensitivity or resistance to imatinib. Patient- and cell-line-derived GIST xenografts were established by bilateral, subcutaneous transplantation of human GIST tissue in female adult nu/nu NMRI mice. The mice were treated with dovitinib, infigratinib, or binimetinib, either alone or in combination with imatinib. The safety of treated animals was assessed by well-being inspection and body weight measurement. Antitumor effects were assessed by caliper-based tumor measurement. H&E staining and immunohistochemistry were used for assessing anti-mitotic and pro-apoptotic activity of the experimental treatments. Western blotting was used for assessing effects of the agents on kinase signaling pathways. Anti-angiogenic activity was assessed by measuring tumor vessel density. Dovitinib was found to have antitumor efficacy in GIST xenografts characterized by different imatinib resistance patterns. Dovitinib had better efficacy than imatinib (both at standard and increased dose) and was found to be well tolerated. Dovitinib had better efficacy in a KIT exon 9 mutant model, highlighting a role of patient selection in clinical GIST trials with the agent. In a model with KIT exon 11 and 17 mutations, dovitinib induced tumor necrosis, most likely due to anti-angiogenic effects. Additive effects combining dovitinib with binimetinib were limited.

Project description:BACKGROUND: Increased concentrations of choline-containing compounds are frequently observed in breast carcinomas, and may serve as biomarkers for both diagnostic and treatment monitoring purposes. However, underlying mechanisms for the abnormal choline metabolism are poorly understood. METHODS: The concentrations of choline-derived metabolites were determined in xenografted primary human breast carcinomas, representing basal-like and luminal-like subtypes. Quantification of metabolites in fresh frozen tissue was performed using high-resolution magic angle spinning magnetic resonance spectroscopy (HR MAS MRS). The expression of genes involved in phosphatidylcholine (PtdCho) metabolism was retrieved from whole genome expression microarray analyses. The metabolite profiles from xenografts were compared with profiles from human breast cancer, sampled from patients with estrogen/progesterone receptor positive (ER+/PgR+) or triple negative (ER-/PgR-/HER2-) breast cancer. RESULTS: In basal-like xenografts, glycerophosphocholine (GPC) concentrations were higher than phosphocholine (PCho) concentrations, whereas this pattern was reversed in luminal-like xenografts. These differences may be explained by lower choline kinase (CHKA, CHKB) expression as well as higher PtdCho degradation mediated by higher expression of phospholipase A2 group 4A (PLA2G4A) and phospholipase B1 (PLB1) in the basal-like model. The glycine concentration was higher in the basal-like model. Although glycine could be derived from energy metabolism pathways, the gene expression data suggested a metabolic shift from PtdCho synthesis to glycine formation in basal-like xenografts. In agreement with results from the xenograft models, tissue samples from triple negative breast carcinomas had higher GPC/PCho ratio than samples from ER+/PgR+ carcinomas, suggesting that the choline metabolism in the experimental models is representative for luminal-like and basal-like human breast cancer. CONCLUSIONS: The differences in choline metabolite concentrations corresponded well with differences in gene expression, demonstrating distinct metabolic profiles in the xenograft models representing basal-like and luminal-like breast cancer. The same characteristics of choline metabolite profiles were also observed in patient material from ER+/PgR+ and triple-negative breast cancer, suggesting that the xenografts are relevant model systems for studies of choline metabolism in luminal-like and basal-like breast cancer.

Project description:BackgroundPreclinical models like cancer cell lines and patient-derived xenografts (PDXs) are vital for studying disease mechanisms and evaluating treatment options. It is essential that they accurately recapitulate the disease state of interest to generate results that will translate in the clinic. Prior studies have demonstrated that preclinical models do not recapitulate all biological aspects of human tissues, particularly with respect to the tissue of origin gene expression signatures. Therefore, it is critical to assess how well preclinical model gene expression profiles correlate with human cancer tissues to inform preclinical model selection and data analysis decisions.AimsHere we evaluated how well preclinical models recapitulate human cancer and non-diseased tissue gene expression patterns in silico with respect to the full gene expression profile as well as subsetting by the most variable genes, genes significantly correlated with tumor purity, and tissue-specific genes.MethodsBy using publicly available gene expression profiles across multiple sources, we evaluated cancer cell line and patient-derived xenograft recapitulation of tumor and non-diseased tissue gene expression profiles in silico.ResultsWe found that using the full gene set improves correlations between preclinical model and tissue global gene expression profiles, confirmed that glioblastoma (GBM) PDX global gene expression correlation to GBM tumor global gene expression outperforms GBM cell line to GBM tumor global gene expression correlations, and demonstrated that preclinical models in our study often failed to reproduce tissue-specific expression. While including additional genes for global gene expression comparison between cell lines and tissues decreases the overall correlation, it improves the relative rank between a cell line and its tissue of origin compared to other tissues. Our findings underscore the importance of using the full gene expression set measured when comparing preclinical models and tissues and confirm that tissue-specific patterns are better preserved in GBM PDX models than in GBM cell lines.ConclusionFuture studies can build on these findings to determine the specific pathways and gene sets recapitulated by particular preclinical models to facilitate model selection for a given study design or goal.

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Simultaneous analysis of tumor and stromal gene expression profiles from xenograft models

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