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Expression of S1P metabolizing enzymes and receptors correlate with survival time and regulate cell migration in glioblastoma multiforme.

ABSTRACT: A signaling molecule which is involved in proliferation and migration of malignant cells is the lipid mediator sphingosine-1-phosphate (S1P). There are hints for a potential role of S1P signaling in malignant brain tumors such as glioblastoma multiforme (GBM) which is characterized by a poor prognosis. Therefore, a comprehensive expression analysis of S1P receptors (S1P1-S1P5) and S1P metabolizing enzymes in human GBM (n = 117) compared to healthy brain (n = 10) was performed to evaluate their role for patient´s survival. Furthermore, influence of S1P receptor inhibition on proliferation and migration were studied in LN18 GBM cells. Compared to control brain, mRNA levels of S1P1, S1P2, S1P3 and S1P generating sphingosine kinase-1 were elevated in GBM. Kaplan-Meier analyses demonstrated an association between S1P1 and S1P2 with patient´s survival times. In vitro, an inhibitory effect of the SphK inhibitor SKI-II on viability of LN18 cells was shown. S1P itself had no effect on viability but stimulated LN18 migration which was blocked by inhibition of S1P1 and S1P2. The participation of S1P1 and S1P2 in LN18 migration was further supported by siRNA-mediated silencing of these receptors. Immunoblots and inhibition experiments suggest an involvement of the PI3-kinase/AKT1 pathway in the chemotactic effect of S1P in LN18 cells.In summary, our data argue for a role of S1P signaling in proliferation and migration of GBM cells. Individual components of the S1P pathway represent prognostic factors for patients with GBM. Perspectively, a selective modulation of S1P receptor subtypes could represent a therapeutic approach for GBM patients and requires further evaluation.

SUBMITTER: Bien-Moller S

PROVIDER: S-EPMC4914339 | biostudies-literature | 2016 Mar

REPOSITORIES: biostudies-literature

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Expression of S1P metabolizing enzymes and receptors correlate with survival time and regulate cell migration in glioblastoma multiforme.

Bien-Möller Sandra S Lange Sandra S Holm Tobias T Böhm Andreas A Paland Heiko H Küpper Johannes J Herzog Susann S Weitmann Kerstin K Havemann Christoph C Vogelgesang Silke S Marx Sascha S Hoffmann Wolfgang W Schroeder Henry W S HW Rauch Bernhard H BH

Oncotarget 20160301 11

A signaling molecule which is involved in proliferation and migration of malignant cells is the lipid mediator sphingosine-1-phosphate (S1P). There are hints for a potential role of S1P signaling in malignant brain tumors such as glioblastoma multiforme (GBM) which is characterized by a poor prognosis. Therefore, a comprehensive expression analysis of S1P receptors (S1P1-S1P5) and S1P metabolizing enzymes in human GBM (n = 117) compared to healthy brain (n = 10) was performed to evaluate their r ...[more]

PMID: 26887055

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Project description:Glioblastoma multiforme (GBM) is the most common and aggressive adult primary brain cancer, with <10% of patients surviving for more than 3 years. Demographic and clinical factors (e.g. age) and individual molecular biomarkers have been associated with prolonged survival in GBM patients. However, comprehensive systems-level analyses of molecular profiles associated with long-term survival (LTS) in GBM patients are still lacking. We present an integrative study of molecular data and clinical variables in these long-term survivors (LTSs, patients surviving >3 years) to identify biomarkers associated with prolonged survival, and to assess the possible similarity of molecular characteristics between LGG and LTS GBM. We analyzed the relationship between multivariable molecular data and LTS in GBM patients from the Cancer Genome Atlas (TCGA), including germline and somatic point mutation, gene expression, DNA methylation, copy number variation (CNV) and microRNA (miRNA) expression using logistic regression models. The molecular relationship between GBM LTS and LGG tumors was examined through cluster analysis. We identified 13, 94, 43, 29, and 1 significant predictors of LTS using Lasso logistic regression from the somatic point mutation, gene expression, DNA methylation, CNV, and miRNA expression data sets, respectively. Individually, DNA methylation provided the best prediction performance (AUC = 0.84). Combining multiple classes of molecular data into joint regression models did not improve prediction accuracy, but did identify additional genes that were not significantly predictive in individual models. PCA and clustering analyses showed that GBM LTS typically had gene expression profiles similar to non-LTS GBM. Furthermore, cluster analysis did not identify a close affinity between LTS GBM and LGG, nor did we find a significant association between LTS and secondary GBM. The absence of unique LTS profiles and the lack of similarity between LTS GBM and LGG, indicates that there are multiple genetic and epigenetic pathways to LTS in GBM patients.

Project description:BACKGROUND:Alternative exon usage (AEU) is an important component of gene regulation. Exon expression platforms allow the detection of associations between AEU and phenotypes such as cancer. Numerous studies have identified associations between gene expression and the brain cancer glioblastoma multiforme (GBM). The few consistent gene expression biomarkers of GBM that have been reported may be due to the limited consideration of AEU and the analytical approaches used. The objectives of this study were to develop a model that accounts for the variations in expression present between the exons within a gene and to identify AEU biomarkers of GBM survival. METHODS:The expression of exons corresponding to 25,403 genes was related to the survival of 250 individuals diagnosed with GBM in a training data set. Genes exhibiting AEU in the training data set were confirmed in an independent validation data set of 78 patients. A hierarchical mixed model that allows the consideration of covariation between exons within a gene and of the effect of the epidemiological characteristics of the patients was developed to identify associations between exon expression and patient survival. This general model describes all three possible scenarios: multi-exon genes with and without AEU, and single-exon genes. RESULTS:AEU associated with GBM survival was identified on 2477 genes (P-value < 5.0E-04 or FDR-adjusted P-value < 0.05). G-protein coupled receptor 98 (Gpr98) and epidermal growth factor (Egf) were among the genes exhibiting AEU with 30 and 9 exons associated with GBM survival, respectively. Pathways enriched among the AEU genes included focal adhesion, ECM-receptor interaction, ABC transporters and pathways in cancer. In addition, 24 multi-exon genes without AEU and 8 single-exon genes were associated with GBM survival (FDR-adjusted P-value < 0.05). CONCLUSIONS:The inferred patterns of AEU were consistent with in silico AS models. The hierarchical model used offered a flexible and simple way to interpret and identify associations between survival that accommodates multi-exon genes with or without AEU and single exon genes. Our results indicate that differential expression of AEU could be used as biomarker for GBM and potentially other cancers.

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Expression of S1P metabolizing enzymes and receptors correlate with survival time and regulate cell migration in glioblastoma multiforme.

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Expression of S1P metabolizing enzymes and receptors correlate with survival time and regulate cell migration in glioblastoma multiforme.

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