Unknown,Transcriptomics,Genomics,Proteomics

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Subtype-specific response to bevacizumab is reflected in the metabolome and transcriptome of breast cancer xenografts

ABSTRACT: The VEGF targeted antiangiogenic drug bevacizumab has shown varying results in clinical trials of breast cancer. Identifying robust biomarkers for selecting patients that may benefit from bevacizumab treatment and for monitoring of response is important for the future use of this drug. Two established xenograft models representing basal-like and luminal-like breast cancer were used to study bevacizumab treatment response on the metabolic and gene expression levels. Mice given no treatment or treated with bevacizumab, doxorubicin or the combination of these two drugs were sacrificed at day 3 or 10. High resolution magic angle spinning magnetic resonance spectroscopy (HR MAS MRS) and gene expression microarray analysis was performed on all tumor samples. Combination treatment with bevacizumab had the strongest growth inhibiting effect in the basal-like tumors, and this was reflected in a significant response in the metabolomic and transcriptomic profiles. In the luminal-like xenografts, addition of bevacizumab did not improve the effect of doxorubicin. On the global transcriptomic level, the largest changes in gene expression were observed for the most efficient treatment in each of the two xenograft models. The metabolite glycerophosphocholine (GPC) showed opposite response in the treated xenografts compared with untreated controls: lower in basal-like tumors and higher in luminal-like tumors. Lower levels of creatine, taurine and glycine were observed in the basal-like xenografts given bevacizumab as monotherapy compared with untreated xenografts. Comparing combination therapy with doxorubicin monotherapy in basal-like xenografts, 14 genes showed significant differential expression, including higher expression of very low density lipoprotein receptor (VLDLR), and lower expression of hemoglobin, theta 1 (HBQ1). Using published gene expression signatures, bevacizumab treated tumors were associated with a more hypoxic phenotype, while no evidence was found for associations between bevacizumab treatment and vascular invasion or increasing tumor grade. This study underlines the importance of characterizing biological differences between subtypes of breast cancer to identify personalized biomarkers for selecting patients for bevacizumab treatment and evaluating response to therapy. 60 samples are analyzed. For each of the two xenograft models, tumors were collected from animals that were untreated or treated with bevacizumab (5 mg/kg), doxorubicin (8 mg/kg) or a combination of the two therapies (n = 6 tumors for each group). Bevacizumab treatment was repeated at day 4 and day 7. Animals were sacrificed and tissue harvested at either day 3 or 10 after treatment, in triplicates within each treatment group. This resulted in 24 tumor samples from each of the models. In addition, untreated and bevacizumab treated luminal-like xenografts not fed with estradiol were included for comparison (n = 12). Note that the untreated controls are overlapping with the samples in the GEO series with accession number: GSE25915.

ORGANISM(S): Homo sapiens

SUBMITTER: Eldrid Borgan

PROVIDER: E-GEOD-37543 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:The VEGF targeted antiangiogenic drug bevacizumab has shown varying results in clinical trials of breast cancer. Identifying robust biomarkers for selecting patients that may benefit from bevacizumab treatment and for monitoring of response is important for the future use of this drug. Two established xenograft models representing basal-like and luminal-like breast cancer were used to study bevacizumab treatment response on the metabolic and gene expression levels. Mice given no treatment or treated with bevacizumab, doxorubicin or the combination of these two drugs were sacrificed at day 3 or 10. High resolution magic angle spinning magnetic resonance spectroscopy (HR MAS MRS) and gene expression microarray analysis was performed on all tumor samples. Combination treatment with bevacizumab had the strongest growth inhibiting effect in the basal-like tumors, and this was reflected in a significant response in the metabolomic and transcriptomic profiles. In the luminal-like xenografts, addition of bevacizumab did not improve the effect of doxorubicin. On the global transcriptomic level, the largest changes in gene expression were observed for the most efficient treatment in each of the two xenograft models. The metabolite glycerophosphocholine (GPC) showed opposite response in the treated xenografts compared with untreated controls: lower in basal-like tumors and higher in luminal-like tumors. Lower levels of creatine, taurine and glycine were observed in the basal-like xenografts given bevacizumab as monotherapy compared with untreated xenografts. Comparing combination therapy with doxorubicin monotherapy in basal-like xenografts, 14 genes showed significant differential expression, including higher expression of very low density lipoprotein receptor (VLDLR), and lower expression of hemoglobin, theta 1 (HBQ1). Using published gene expression signatures, bevacizumab treated tumors were associated with a more hypoxic phenotype, while no evidence was found for associations between bevacizumab treatment and vascular invasion or increasing tumor grade. This study underlines the importance of characterizing biological differences between subtypes of breast cancer to identify personalized biomarkers for selecting patients for bevacizumab treatment and evaluating response to therapy.

Project description:Dysregulated choline metabolism is a well-known feature of breast cancer, but the underlying mechanisms are not fully understood. In this study, the metabolomic and transcriptomic characteristics of a large panel of human breast cancer xenograft models were mapped, with focus on choline metabolism. Methods: Tumor specimens from 34 patient-derived xenograft models were collected and divided in two. One part was examined using high-resolution magic angle spinning (HR-MAS) MR spectroscopy while another part was analysed using gene expression microarrays. Expression data of genes encoding proteins in the choline metabolism pathway were analysed and correlated to the levels of choline (Cho), phosphocholine (PCho) and glycerophosphocholine (GPC) using Pearson’s correlation analysis. For comparison purposes, metabolic and gene expression data were collected from human breast tumors belonging to corresponding molecular subgroups. Results: Most of the xenograft models were classified as basal-like (N=19) or luminal B (N=7). These two subgroups showed significantly different choline metabolic and gene expression profiles. The luminal B xenografts were characterized by a high PCho/GPC ratio while the basal-like xenografts were characterized by highly variable PCho/GPC ratio. Also, Cho, PCho and GPC levels were correlated to expression of several genes encoding proteins in the choline metabolism pathway, including choline kinase alpha (CHKA) and glycerophosphodiester phosphodiesterase domain containing 5 (GDPD5). These characteristics were similar to those found in human tumor samples. Discussion: The higher PCho/GPC ratio found in luminal B compared with most basal-like breast cancer xenograft models and human tissue samples do not correspond to results observed from in vitro studies. It is likely that microenvironmental factors play a role in the in vivo regulation of choline metabolism. Cho, PCho and GPC were correlated to different choline pathway-encoding genes in luminal B compared with basal-like xenografts, suggesting that regulation of choline metabolism may vary between different breast cancer subgroups. The concordance between the metabolic and gene expression profiles from xenograft models with breast cancer tissue samples from patients indicates that these xenografts are representative models of human breast cancer and represent relevant models to study tumor metabolism in vivo. Gene expression was measured in 30 human breast cancer xenografts, one sample from each model

Project description:Bevacizumab induces glioblastoma resistance in two in vivo xenograft models. Two cell lines were developed with acquired resistance to bevacizumab. Gene expression difference were analyzed between treated and untreated tumors. Purpose: Antiangiogenic therapy reduces vascular permeability and delays progression but may ultimately promote an aggressive treatment-resistant phenotype. The aim of the present study was to identify mechanisms responsible for glioblastoma resistance to antiangiogenic therapy. Experimental Design: Glioma stem cell (GSC) NSC11 and U87 cell lines with acquired resistance to bevacizumab were developed from orthotopic xenografts in nude mice treated with bevacizumab. Genome-wide analyses were used to identify changes in tumor subtype and specific factors associated with resistance. Results: Mice with established parental NSC11 and U87 cells responded to bevacizumab, whereas glioma cell lines derived at the time of acquired resistance to anti-VEGF therapy were resistant to bevacizumab and did not have prolongation of survival compared to untreated controls. Gene expression profiling comparing anti-VEGF therapy-resistant cell lines to untreated controls demonstrated an increase in genes associated with a mesenchymal origin, cellular migration/invasion, and inflammation. Gene Set Enrichment Analysis (GSEA) demonstrated that bevacizumab-treated tumors showed a highly significant correlation to published mesenchymal gene signatures. Mice bearing resistant tumors showed significantly greater infiltration of myeloid cells in NSC11 and U87 resistant tumors. Invasion-related genes were also upregulated in both NSC11 and U87 resistant cells, which had higher invasion rates in vitro compared with their respective parental cell lines. Conclusions: Our studies identify multiple pro-inflammatory factors associated with resistance and identify a proneural-to-mesenchymal transition (PMT) in tumors resistant to antiangiogenic therapy. Glioma cell lines were injected into the caudate of nude mice and were allowed to grow untreated (samples labeled control) or were treated with 10 mg/kg IP twice weekly with bevacizumab (samples labeled Avastin). At the time of animal death, tumor tissue from the mouse was removed, and RNA was isolated and analyzed using gene expression. U87R and NSC11R represent cells resistant to bevacizumab (Avastin).

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Subtype-specific response to bevacizumab is reflected in the metabolome and transcriptome of breast cancer xenografts

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