Filters
Technology
Platform
Mus musculus
8 Downloadable Samples
Affymetrix Murine Genome U74A Version 2 Array (mgu74av2)
Description
Transcriptome of murine testis from wild type mice and mice lacking telomerase for three generations (G3-Terc), Ku86 or both telomerase and Ku86.
Publication Title
Effectors of mammalian telomere dysfunction: a comparative transcriptome analysis using mouse models.
Sample Metadata Fields
No sample metadata fields
View Samples
GSE2684- Mus musculus
- 4 Downloadable Samples
- Affymetrix Mouse Expression 430A Array (moe430a)
Description
Recent studies suggest that telomerase promotes cell growth by mechanisms that extend beyond the rescue of critically short telomeres. The in vitro model of mTert overexpressing MEFs recapitulates fundamental aspects of the growth-promoting effects of mTert in vivo. First, in Terc-proficient cells, mTert overexpression favors escape from replicative senescence and enhances anchorage-independent growth in response to oncogenic stress, which fits well with previous data showing that mTert overexpression promotes tumor formation. Second, in Terc-deficient cells, retroviral transduction with mTert results in a delayed onset of immortalization and impairs colony formation in response to oncogenic stress, which is in agreement with the inhibitory effect of mTert overexpression on tumorigenesis in a Terc null mouse background. To unravel the molecular targets of telomerase that impact on cell growth, we compared the transcriptome of MEFs, before and after mTert introduction. We found that ectopic expression of mTert was associated with detectable gene expression changes (greater than 1.5-fold; validated by qRT-PCR) of 26 transcripts. Analysis of the observed transcriptional changes indicates that ectopic expression of mTert suppresses in a coordinated manner functionally related genes with overlapping roles in growth arrest, resistance to transformation, and apoptosis. We show that the majority of the telomerase target genes are growth-inhibitory, transforming growth factor-beta (TGF-beta) -inducible genes and provide functional evidence for the potential of telomerase to abrogate TGF-beta -mediated growth inhibition. Thus, in line with the current view that the diversity of TGF-beta responses is not so much a consequence of the use of different signaling pathways but caused by different ways of reading the output from the same basic pathway, we propose that the telomerase status of a cell creates a gene expression pattern that determines how cells read growth inhibitory signals, among them signals propagated through the TGF-beta pathway.
Publication Title
Expression of mTert in primary murine cells links the growth-promoting effects of telomerase to transforming growth factor-beta signaling.
Sample Metadata Fields
No sample metadata fields
View Samples GSE76943- Homo sapiens
- 4 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Expression data from HEK293 cells expressing a doxcycline-inducible RANBP6 shRNA
Publication Title
EGFR feedback-inhibition by Ran-binding protein 6 is disrupted in cancer.
Sample Metadata Fields
Treatment
View Samples- Homo sapiens
- 20 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
The UBC-40 Urothelial Bladder Cancer cell line index: a genomic resource for functional studies.
Sample Metadata Fields
Specimen part, Cell line
View Samples- Homo sapiens
- 20 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
This is a comprehensive genomic characterization of 40 urothelial bladder carcinoma (UBC) cell lines including information on origin, mutation status of genes implicated in bladder cancer (FGFR3, PIK3CA, TP53, and RAS), copy number alterations assessed using high density SNP arrays, uniparental disomy (UPD) events, and gene expression. Based on gene mutation patterns and genomic changes we identify lines representative of the FGFR3-driven tumor pathway and of the TP53/RB tumor suppressor-driven pathway. High-density array copy number analysis identified significant focal gains (1q32, 5p13.1-12, 7q11, and 7q33) and losses (i.e. 6p22.1) in regions altered in tumors but not previously described as affected in bladder cell lines. We also identify new evidence for frequent regions of UPD, often coinciding with regions reported to be lost in tumors. Previously undescribed chromosome X losses found in UBC lines also point to potential tumor suppressor genes. Cell lines representative of the FGFR3-driven pathway showed a lower number of UPD events. Overall, there is a predominance of more aggressive tumor subtypes among the cell lines. We provide a cell line classification that establishes their relatedness to the major molecularly-defined bladder tumor subtypes. The compiled information should serve as a useful reference to the bladder cancer research community and should help to select cell lines appropriate for the functional analysis of bladder cancer genes, for example those being identified through massive parallel sequencing.
Publication Title
The UBC-40 Urothelial Bladder Cancer cell line index: a genomic resource for functional studies.
Sample Metadata Fields
Specimen part, Cell line
View Samples GSE2487- Homo sapiens
- 10 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
This experiment was designed to study oncogene-induced senescence (OIS). To this end we generated a series of cell lines derived from normal human diploid fibroblasts IMR90 forced to express the catalytic subunit of telomerase (hTERT). This cells were then subjected to further manipulation by orderly introducing defined genetic elements by retroviral transduction. The first cell line generated was ITV, which was obtained from the original cell line (IMR90 with hTERT) after introducing an empty vector. Subsequently, we introduced Mek:ER, which is a switchable version of the Mek kinase, a relevant downstream effector of Ras signaling during Ras-induced senescence, to generate ITM cells. We further modified this cell line by introducing SV40 small-t antigen (ST), papillomavirus oncoproteins E6 and E7 (E6/E7) or the combination of both (E6/E7 and ST). In this manner, we obtained ITMST, ITME6E7 and ITME6E7ST respectively.
Publication Title
Tumour biology: senescence in premalignant tumours.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 31 Downloadable Samples
- Affymetrix Human Gene 1.0 ST Array (hugene10st)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Integration Analysis of Three Omics Data Using Penalized Regression Methods: An Application to Bladder Cancer.
Sample Metadata Fields
Specimen part
View Samples- Homo sapiens
- 31 Downloadable Samples
- Affymetrix Human Gene 1.0 ST Array (hugene10st)
Description
Omics data integration is becoming necessary to investigate the still unknown genomic mechanisms of complex diseases. During the integration process, many challenges arise such as data heterogeneity, the smaller number of individuals in comparison to the number of parameters, multicollinearity, and interpretation and validation of results due to their complexity and lack of knowledge about biological mechanisms. To overcome some of these issues, innovative statistical approaches are being developed. In this work, we applied penalized regression methods (LASSO and ENET) to explore relationships between common genetic variants, DNA methylation and gene expression measured in bladder tumor samples and have proposed a permutation-based method to concomitantly assess significance and correct by multiple testing with the MaxT algorithm. The overall analysis flow consisted of three steps: (1) SNPs/CpGs were selected per each gene probe within 1Mb window upstream and downstream the gene; (2) LASSO and ENET were applied to assess the association between each expression probe and the selected SNPs/CpGs in three multivariable models (SNP, CPG, and Global models, the latter integrating SNPs and CPGs); and (3) the significance of each model was assessed using the permutation-based MaxT method. We identified 48 genes whom expression levels were associated with both SNPs and GPGs. Importantly, we replicated results for 36 (75%) of them in an independent data set (TCGA). We checked the performance of the proposed method with a simulation study and further supported our results with a biological interpretation based on an enrichment analysis. The approach we propose allows reducing computational time and is flexibly and easy to implement when analyzing several omics data. Our results highlight the importance of integrating omics data by applying appropriate statistical strategies to discover new insights into the complexity of disease genetic mechanisms.
Publication Title
Integration Analysis of Three Omics Data Using Penalized Regression Methods: An Application to Bladder Cancer.
Sample Metadata Fields
Specimen part
View Samples- Homo sapiens
- 34 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Engraftment of primary pancreas ductal adenocarcinomas (PDAC) in mice to generate patient derived xenograft (PDX) models is a promising platform to for biological and therapeutic studies in this disease. However, these models are still incompletely characterized. Here, we measured the impact of the murine environment on the gene expression of the engrafted human tumoral cells. We have analyzed gene expression profiles from 35 new PDX models and compared them with previously published microarray data from PDAC and hepatocellular carcinoma (HCC). Our results showed that PDX models derived from PDAC, or HCC, were clearly different to the cell lines derived from the same cancer tissues. Indeed, PDAC- and HCC-derived cell lines are indistinguishable one from the other based in their gene expression profiles. In contrast, the transcriptomes of PDAC and HCC PDX models are clearly different and more similar to their original tumor than to PDX models from the other tumor type. Interestingly, the main differences between pancreatic PDX models and human PDAC is the expression of genes involved in pathways related with extracellular matrix interactions and cell cycle regulation likely reflecting the adaptations of the tumors to the new environment. Furthermore, most of these differences are detected in the first passages after the tumor engraftment, indicating early phases of the adaptation process. In conclusion, different from conventional cancer cell lines, PDX models of PDAC retain similar gene expression profiles of PDAC. Expression changes are mainly related to genes involved in stromal pathways likely reflecting the adaptation to new environments. We also provide evidence of the stability of gene expression patterns over subsequent passages.
Publication Title
Transcriptional dissection of pancreatic tumors engrafted in mice.
Sample Metadata Fields
Specimen part
View Samples- Mus musculus
- 28 Downloadable Samples
- Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Combined inhibition of DDR1 and Notch signaling is a therapeutic strategy for KRAS-driven lung adenocarcinoma.
Sample Metadata Fields
Specimen part
View Samples