Capture at the single cell level of metabolic modules distinguishing aggressive and indolent glioblastoma cells
Abstract Glioblastoma cell ability to adapt their functioning to microenvironment changes is a source of the extensive intra-tumor heterogeneity characteristic of this devastating malignant brain tumor. A systemic view of the metabolic pathways underlying glioblastoma cell functioning states is lack...
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| Format: | Article |
| Language: | English |
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BMC
2019-10-01
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| Series: | Acta Neuropathologica Communications |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s40478-019-0819-y |
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| author | Mirca S. Saurty-Seerunghen Léa Bellenger Elias A. El-Habr Virgile Delaunay Delphine Garnier Hervé Chneiweiss Christophe Antoniewski Ghislaine Morvan-Dubois Marie-Pierre Junier |
| author_facet | Mirca S. Saurty-Seerunghen Léa Bellenger Elias A. El-Habr Virgile Delaunay Delphine Garnier Hervé Chneiweiss Christophe Antoniewski Ghislaine Morvan-Dubois Marie-Pierre Junier |
| author_sort | Mirca S. Saurty-Seerunghen |
| collection | DOAJ |
| description | Abstract Glioblastoma cell ability to adapt their functioning to microenvironment changes is a source of the extensive intra-tumor heterogeneity characteristic of this devastating malignant brain tumor. A systemic view of the metabolic pathways underlying glioblastoma cell functioning states is lacking. We analyzed public single cell RNA-sequencing data from glioblastoma surgical resections, which offer the closest available view of tumor cell heterogeneity as encountered at the time of patients’ diagnosis. Unsupervised analyses revealed that information dispersed throughout the cell transcript repertoires encoded the identity of each tumor and masked information related to cell functioning states. Data reduction based on an experimentally-defined signature of transcription factors overcame this hurdle. It allowed cell grouping according to their tumorigenic potential, regardless of their tumor of origin. The approach relevance was validated using independent datasets of glioblastoma cell and tissue transcriptomes, patient-derived cell lines and orthotopic xenografts. Overexpression of genes coding for amino acid and lipid metabolism enzymes involved in anti-oxidative, energetic and cell membrane processes characterized cells with high tumorigenic potential. Modeling of their expression network highlighted the very long chain polyunsaturated fatty acid synthesis pathway at the core of the network. Expression of its most downstream enzymatic component, ELOVL2, was associated with worsened patient survival, and required for cell tumorigenic properties in vivo. Our results demonstrate the power of signature-driven analyses of single cell transcriptomes to obtain an integrated view of metabolic pathways at play within the heterogeneous cell landscape of patient tumors. |
| first_indexed | 2024-12-12T10:34:43Z |
| format | Article |
| id | doaj.art-732dd8ed93614f5eb34573125ed00532 |
| institution | Directory Open Access Journal |
| issn | 2051-5960 |
| language | English |
| last_indexed | 2024-12-12T10:34:43Z |
| publishDate | 2019-10-01 |
| publisher | BMC |
| record_format | Article |
| series | Acta Neuropathologica Communications |
| spelling | doaj.art-732dd8ed93614f5eb34573125ed005322022-12-22T00:27:15ZengBMCActa Neuropathologica Communications2051-59602019-10-017111610.1186/s40478-019-0819-yCapture at the single cell level of metabolic modules distinguishing aggressive and indolent glioblastoma cellsMirca S. Saurty-Seerunghen0Léa Bellenger1Elias A. El-Habr2Virgile Delaunay3Delphine Garnier4Hervé Chneiweiss5Christophe Antoniewski6Ghislaine Morvan-Dubois7Marie-Pierre Junier8CNRS UMR8246, Inserm U1130, Sorbonne Université, Neuroscience Paris Seine-IBPS, Team glial plasticity and neurooncologyARTbio Bioinformatics Analysis Facility, Sorbonne Université, CNRS, Institut de Biologie Paris SeineCNRS UMR8246, Inserm U1130, Sorbonne Université, Neuroscience Paris Seine-IBPS, Team glial plasticity and neurooncologyCNRS UMR8246, Inserm U1130, Sorbonne Université, Neuroscience Paris Seine-IBPS, Team glial plasticity and neurooncologyCell Death and Drug Resistance in Lymphoproliferative Disorders Team, Centre de Recherche des Cordeliers, Sorbonne Université, INSERM UMRS 1138CNRS UMR8246, Inserm U1130, Sorbonne Université, Neuroscience Paris Seine-IBPS, Team glial plasticity and neurooncologyARTbio Bioinformatics Analysis Facility, Sorbonne Université, CNRS, Institut de Biologie Paris SeineCNRS UMR8246, Inserm U1130, Sorbonne Université, Neuroscience Paris Seine-IBPS, Team glial plasticity and neurooncologyCNRS UMR8246, Inserm U1130, Sorbonne Université, Neuroscience Paris Seine-IBPS, Team glial plasticity and neurooncologyAbstract Glioblastoma cell ability to adapt their functioning to microenvironment changes is a source of the extensive intra-tumor heterogeneity characteristic of this devastating malignant brain tumor. A systemic view of the metabolic pathways underlying glioblastoma cell functioning states is lacking. We analyzed public single cell RNA-sequencing data from glioblastoma surgical resections, which offer the closest available view of tumor cell heterogeneity as encountered at the time of patients’ diagnosis. Unsupervised analyses revealed that information dispersed throughout the cell transcript repertoires encoded the identity of each tumor and masked information related to cell functioning states. Data reduction based on an experimentally-defined signature of transcription factors overcame this hurdle. It allowed cell grouping according to their tumorigenic potential, regardless of their tumor of origin. The approach relevance was validated using independent datasets of glioblastoma cell and tissue transcriptomes, patient-derived cell lines and orthotopic xenografts. Overexpression of genes coding for amino acid and lipid metabolism enzymes involved in anti-oxidative, energetic and cell membrane processes characterized cells with high tumorigenic potential. Modeling of their expression network highlighted the very long chain polyunsaturated fatty acid synthesis pathway at the core of the network. Expression of its most downstream enzymatic component, ELOVL2, was associated with worsened patient survival, and required for cell tumorigenic properties in vivo. Our results demonstrate the power of signature-driven analyses of single cell transcriptomes to obtain an integrated view of metabolic pathways at play within the heterogeneous cell landscape of patient tumors.http://link.springer.com/article/10.1186/s40478-019-0819-yGliomaComputational modelingscRNA-seqPUFAElongase |
| spellingShingle | Mirca S. Saurty-Seerunghen Léa Bellenger Elias A. El-Habr Virgile Delaunay Delphine Garnier Hervé Chneiweiss Christophe Antoniewski Ghislaine Morvan-Dubois Marie-Pierre Junier Capture at the single cell level of metabolic modules distinguishing aggressive and indolent glioblastoma cells Acta Neuropathologica Communications Glioma Computational modeling scRNA-seq PUFA Elongase |
| title | Capture at the single cell level of metabolic modules distinguishing aggressive and indolent glioblastoma cells |
| title_full | Capture at the single cell level of metabolic modules distinguishing aggressive and indolent glioblastoma cells |
| title_fullStr | Capture at the single cell level of metabolic modules distinguishing aggressive and indolent glioblastoma cells |
| title_full_unstemmed | Capture at the single cell level of metabolic modules distinguishing aggressive and indolent glioblastoma cells |
| title_short | Capture at the single cell level of metabolic modules distinguishing aggressive and indolent glioblastoma cells |
| title_sort | capture at the single cell level of metabolic modules distinguishing aggressive and indolent glioblastoma cells |
| topic | Glioma Computational modeling scRNA-seq PUFA Elongase |
| url | http://link.springer.com/article/10.1186/s40478-019-0819-y |
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