E-MTAB-7591
Ontology highlight
ABSTRACT:
PROVIDER: E-MTAB-7591 | ExpressionAtlas | 2025-01-23
REPOSITORIES: ExpressionAtlas
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Project description:RNA-seq of human glioblastoma cell lines with overexpression of SOX2, SFRP2
| PRJEB30789 | ENA
Project description:SOX2 is a lineage specifier oncogene for lung squamous cell carcinoma (LSCC) and frequently amplified and overexpressed in human LSCC tumors (up to 90% of the cases). Our study demonstrated that SOX2 is a key determinant of neutrophil recruitment to tumors even in the absence of squamous histology. We generated cell lines from KrasLSL-G12D/+;Trp53fl/fl (KP) tumors that overexpress Sox2 (i.e. tumors from Lenti-Sox2-Cre infected KP mice that are validated to have Sox2 overexpression) (abbreviated as KPS) and employed chromatin immunoprecipitation sequencing (ChIP-seq) to identify genomic binding loci of SOX2 in KPS lines as well as Lkb1fl/fl;Ptenfl/fl (LP) LSCC tumors.
2018-10-16 | GSE118244 | GEO
Project description:RNA-seq analysis of PROX1 overexpression and knockdown in glioblastoma cell lines
| PRJEB27945 | ENA
Project description:Overexpression of the transcription factor SRY-related box 2 (SOX2) is characteristic of Glioblastoma (GBM), yet its regulatory network in vivo is poorly understood. Using a human orthotopic tumor model of GBM for ChIP-Seq analysis, we mapped the SOX2 cistrome. Integrative analysis of SOX2 cistrome and GBM transcriptome data identified two transcription factors, oligodendrocyte lineage transcription factor 2 (OLIG2) and zinc finger E-box binding homeobox 1 (ZEB1) as critical SOX2 targets. Their expression is strongly correlated with SOX2 expression in clinical GBM specimens, and all three proteins are frequently co-expressed in primary Glioblastoma cells, even in the setting of EGFR intratumoral heterogeneity. Sox2, Olig2, and Zeb1 expression is activated by the oncogene EGFRvIII in a murine glioma model, and we demonstrate that co-expression of these transcription factors transforms tumor suppressor deficient astrocytes in the absence of an upstream oncogene and that the resulting tumors exhibit the major histopathological features of GBM.
2017-01-24 | GSE58345 | GEO
Project description:RNA-seq analysis of PROX1 overexpression and knockdown in glioblastoma cell lines
2025-01-23 | E-MTAB-6991 | ExpressionAtlas
Project description:RNA-seq of human endometrial stromal cell lines followng LINC00339 overexpression
| PRJNA692849 | ENA
Project description:RNA-Seq analysis of human medulloblastoma cell lines with SOX9 overexpression
| PRJNA328820 | ENA
Project description:Overexpression of SOX4 in LN229 glioblastoma cells prevents their cell cycle We used microarrays to detail the global programme of gene expression in SOX4 overexpression LN229 cells compared with mock control LN229 cells SOX4 overexpression LN229 cells and and control LN229 cells were cultured in DMEM cell culture media for RNA extraction and hybridization on Affymetrix microarrays. We sought to obtain the genes regulated by SOX4 in glioblastoma cell lines.
2014-09-30 | E-GEOD-51301 | biostudies-arrayexpress
Project description:The pluripotency transcription factor SOX2 is essential for the maintenance of glioblastoma stem cells (GSC), which drive tumor growth and treatment resistance.To understand how SOX2 is regulated in GSCs, we utilized a proteomic approach and identified the E3 ubiquitin ligase TRIM26 as a direct SOX2-interacting protein. Unexpectedly, we found TRIM26 depletion decreased SOX2 protein levels and increased SOX2 polyubiquitination in patient-derived GSCs, suggesting TRIM26 promotes SOX2 protein stability. Accordingly, TRIM26 knockdown reduced SOX2 transcriptional activity, self-renewal capacity, and in vivo tumorigenicity in multiple GSC lines. Mechanistically, we found TRIM26, via its C-terminal PRYSPRY domain, but independent of its RING domain, stabilizes SOX2 protein by directly inhibiting the interaction of SOX2 with WWP2, which we identify as a bona fide SOX2 E3 ligase in GSCs. Our work identifies E3 ligase competition as a critical mechanism of SOX2 regulation, with functional consequences for GSC identity and maintenance.
2021-11-04 | PXD028933 | Pride
Project description:Bordel2018 - GSMM for Human Metabolic
Reactions (HMR database)
This model is described in the article:
Constraint based modeling of
metabolism allows finding metabolic cancer hallmarks and
identifying personalized therapeutic windows
Sergio Bordel
Oncotarget. 2018; 9:19716-19729
Abstract:
In order to choose optimal personalized anticancer
treatments, transcriptomic data should be analyzed within the
frame of biological networks. The best known human biological
network (in terms of the interactions between its different
components) is metabolism. Cancer cells have been known to have
specific metabolic features for a long time and currently there
is a growing interest in characterizing new cancer specific
metabolic hallmarks. In this article it is presented a method
to find personalized therapeutic windows using RNA-seq data and
Genome Scale Metabolic Models. This method is implemented in
the python library, pyTARG. Our predictions showed that the
most anticancer selective (affecting 27 out of 34 considered
cancer cell lines and only 1 out of 6 healthy mesenchymal stem
cell lines) single metabolic reactions are those involved in
cholesterol biosynthesis. Excluding cholesterol biosynthesis,
all the considered cell lines can be selectively affected by
targeting different combinations (from 1 to 5 reactions) of
only 18 metabolic reactions, which suggests that a small subset
of drugs or siRNAs combined in patient specific manners could
be at the core of metabolism based personalized treatments.
This model is hosted on
BioModels Database
and identified by:
MODEL1707250000.
To cite BioModels Database, please use:
Chelliah V et al. BioModels: ten-year
anniversary. Nucl. Acids Res. 2015, 43(Database
issue):D542-8.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
| MODEL1707250000 | BioModels