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Homo sapiens
9 Downloadable Samples
NextSeq 500
Description
Asymmetric cell division results in two distinctly fated daughter cells to generate cellular diversity. A major molecular hallmark of an asymmetric division is the unequal partitioning of cell-fate determinant proteins. We have previously established that growth factor signaling promotes protein depalmitoylation to foster polarized protein localization, which in turns drives migration and metastasis. Here, we report protein palmitoylation as a key mechanism for the asymmetric partitioning of the cell-fate determinants Numb (Notch antagonist) and ß-catenin (canonical Wnt regulator) through the activity of a depalmitoylating enzyme, APT1. Using point mutants, we show specific palmitoylated residues on proteins, such as Numb, are required for asymmetric localization. Furthermore, by live-cell imaging, we show that reciprocal interactions between APT1 and CDC42 regulate the asymmetric localization of Numb and ß-catenin to the plasma membrane. This in turn restricts Notch and Wnt transcriptional activity to one daughter cell. Moreover, we show altering APT1 expression changes the transcriptional signatures to those resembling that of Notch and ß-catenin in MDA-MB-231 cells. We also show loss of APT1 depletes the population of CD44+/CD24lo/ALDH+ tumorigenic cells in colony formation assays. Together, the findings of this study demonstrate that palmitoylation, via APT1, is a major mechanism of asymmetric cell division regulating Notch and Wnt-associated protein dynamics, gene expression, and cellular functions. Overall design: Gene expression by RNAseq of MDA-MB-231 triple receptor negative breast cancer cells expressing scramble control vector, shAPT1 knockdown, and APT1wt performed in triplicate. Total of 9 samples were analyzed.
Publication Title
The depalmitoylase APT1 directs the asymmetric partitioning of Notch and Wnt signaling during cell division.
Sample Metadata Fields
Specimen part, Cell line, Treatment, Subject
View Samples- Homo sapiens
- 69 Downloadable Samples
Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
The five DLBCL cell lines were treated with R406 to assess the signature of SYK inhibition. In previous studies, R406 decreased the proliferation and induced apoptosis of these surface Ig+ cell lines. In the previous studies, R406 inhibited the autophosphorylation of SYK 525/526 and SYK-dependent phosphorylation of BCR signaling components such as BLNK.
Publication Title
SYK inhibition modulates distinct PI3K/AKT- dependent survival pathways and cholesterol biosynthesis in diffuse large B cell lymphomas.
Sample Metadata Fields
Specimen part, Cell line, Treatment, Time
View Samples- Homo sapiens
- 29 Downloadable Samples
- Affymetrix HT Human Genome U133A Array (hthgu133a)
Description
The two DLBCL cell lines were treated with R406 to assess the signature of SYK inhibition. In previous studies, R406 decreased the proliferation and induced apoptosis of these surface Ig+ cell lines. In the previous studies, R406 inhibited the autophosphorylation of SYK 525/526 and SYK-dependent phosphorylation of BCR signaling components such as BLNK.
Publication Title
SYK inhibition modulates distinct PI3K/AKT- dependent survival pathways and cholesterol biosynthesis in diffuse large B cell lymphomas.
Sample Metadata Fields
Specimen part, Cell line, Treatment
View Samples- Rattus norvegicus
- 18 Downloadable Samples
- Affymetrix Rat Gene 1.0 ST Array (ragene10st)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Reverse engineering a hierarchical regulatory network downstream of oncogenic KRAS.
Sample Metadata Fields
Cell line, Treatment
View Samples- Rattus norvegicus
- 16 Downloadable Samples
- Affymetrix Rat Gene 1.0 ST Array (ragene10st)
Description
RAS mutations are highly relevant for progression and therapy response of human tumours, but the genetic network that ultimately executes the oncogenic effects is poorly understood. Here we used a reverse-engineering approach in an ovarian cancer model to reconstruct KRAS oncogene-dependent cytoplasmic and transcriptional networks from perturbation experiments based on gene silencing and pathway inhibitor treatments. We measured mRNA and protein levels in manipulated cells by microarray, RT-PCR and Western Blot analysis, respectively. The reconstructed model revealed complex interactions among the transcriptional and cytoplasmic components, some of which were confirmed by double pertubation experiments. Interestingly, the transcription factors decomposed into two hierarchically arranged groups. To validate the model predictions we analysed growth parameters and transcriptional deregulation in the KRAS-transformed epithelial cells. As predicted by the model, we found two functional groups among the selected transcription factors. The experiments thus confirmed the predicted hierarchical transcription factor regulation and showed that the hierarchy manifests itself in downstream gene expression patterns and phenotype.
Publication Title
Reverse engineering a hierarchical regulatory network downstream of oncogenic KRAS.
Sample Metadata Fields
Cell line, Treatment
View Samples- Rattus norvegicus
- 2 Downloadable Samples
Affymetrix Rat Gene 1.0 ST Array (ragene10st)
Description
RAS mutations are highly relevant for progression and therapy response of human tumours, but the genetic network that ultimately executes the oncogenic effects is poorly understood. Here we used a reverse-engineering approach in an ovarian cancer model to reconstruct KRAS oncogene-dependent cytoplasmic and transcriptional networks from perturbation experiments based on gene silencing and pathway inhibitor treatments. We measured mRNA and protein levels in manipulated cells by microarray, RT-PCR and Western Blot analysis, respectively. The reconstructed model revealed complex interactions among the transcriptional and cytoplasmic components, some of which were confirmed by double pertubation experiments. Interestingly, the transcription factors decomposed into two hierarchically arranged groups. To validate the model predictions we analysed growth parameters and transcriptional deregulation in the KRAS-transformed epithelial cells. As predicted by the model, we found two functional groups among the selected transcription factors. The experiments thus confirmed the predicted hierarchical transcription factor regulation and showed that the hierarchy manifests itself in downstream gene expression patterns and phenotype.
Publication Title
Reverse engineering a hierarchical regulatory network downstream of oncogenic KRAS.
Sample Metadata Fields
Cell line, Treatment
View Samples- Homo sapiens
- 73 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
Gene expression profiling of surgical biopsies from 74 breast cancer patients of different subtypes from Hamburg dataset.
Publication Title
Prognostic relevance of glycosylation-associated genes in breast cancer.
Sample Metadata Fields
Sex, Specimen part
View Samples- Homo sapiens
- 84 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
Since follicular lymphoma (FL) grade 3A often coexist with a FL1/2 component a linear progression model of FL1, FL2 and FL3A has been developed. FL3B, on the other hand, is supposed to be more closely related to diffuse large B-cell lymphoma (DLBCL) and both FL3B and DLBCL are often simultaneously present in one tumor (DLBCL/FL3B).
Publication Title
Gene expression profiling reveals a close relationship between follicular lymphoma grade 3A and 3B, but distinct profiles of follicular lymphoma grade 1 and 2.
Sample Metadata Fields
Sex, Age, Specimen part
View Samples
GSE39079- Homo sapiens
- 29 Downloadable Samples
- Illumina HumanHT-12 V3.0 expression beadchip
Description
OBJECTIVE:
Publication Title
Foam cell specific LXRα ligand.
Sample Metadata Fields
Sex, Specimen part, Cell line
View Samples- Homo sapiens
- 86 Downloadable Samples
- Affymetrix Human Genome U133A 2.0 Array (hgu133a2)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Three human cell types respond to multi-walled carbon nanotubes and titanium dioxide nanobelts with cell-specific transcriptomic and proteomic expression patterns.
Sample Metadata Fields
Specimen part, Cell line, Treatment, Time
View Samples