Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Chromatin landscape analysis of ccRCC cell line upon SETD2 rescue [ATACseq_JHRCC12]

ABSTRACT: SETD2, a H3K36 trimethyltransferase, is frequently mutated in human cancers with the highest prevalence (13%) in clear cell renal cell carcinoma (ccRCC). Genomic profiling of primary ccRCC tumors reveals a positive correlation between SETD2 mutations and metastasis. However, whether and how SETD2-loss promotes metastasis remains unclear. Here, we detected SETD2 mutations in 24 of 51 (47%) metastatic ccRCC tumors. Using SETD2-mutant metastatic ccRCC patient-derived cell line and xenograft models, we showed that H3K36me3 restoration greatly reduced distant metastases of ccRCC in mice. An integrated ATAC-seq, ChIP-seq, and transcriptome analysis concluded a tumor suppressor model in which loss of SETD2-mediated H3K36me3 activates enhancers to drive oncogenic transcription through dysregulating histone chaperone recruitment, enhancing histone exchange, and expanding chromatin accessibility. Furthermore, we uncovered mechanism-based therapeutic strategies for SETD2-deficient cancer through inhibition of histone chaperones. Overall, SETD2-loss creates a permissive epigenetic landscape for cooperating oncogenic drivers to amplify transcriptional output, providing unique therapeutic opportunities.

ORGANISM(S): Homo sapiens

PROVIDER: GSE146537 | GEO | 2021/11/15

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Chromatin landscape analysis of murine renal tubular epithelial cells upon SETD2 knockout [ATACseq_RTE]

Project description:SETD2, a H3K36 trimethyltransferase, is frequently mutated in human cancers with the highest prevalence (13%) in clear cell renal cell carcinoma (ccRCC). Genomic profiling of primary ccRCC tumors reveals a positive correlation between SETD2 mutations and metastasis. However, whether and how SETD2-loss promotes metastasis remains unclear. Here, we detected SETD2 mutations in 24 of 51 (47%) metastatic ccRCC tumors. Using SETD2-mutant metastatic ccRCC patient-derived cell line and xenograft models, we showed that H3K36me3 restoration greatly reduced distant metastases of ccRCC in mice. An integrated ATAC-seq, ChIP-seq, and transcriptome analysis concluded a tumor suppressor model in which loss of SETD2-mediated H3K36me3 activates enhancers to drive oncogenic transcription through dysregulating histone chaperone recruitment, enhancing histone exchange, and expanding chromatin accessibility. Furthermore, we uncovered mechanism-based therapeutic strategies for SETD2-deficient cancer through inhibition of histone chaperones. Overall, SETD2-loss creates a permissive epigenetic landscape for cooperating oncogenic drivers to amplify transcriptional output, providing unique therapeutic opportunities.

2021-11-15 | GSE146538 | GEO

Gene expression analysis of murine renal tubular epithelial cells upon SETD2 knockout [RNAseq_RTE]

2021-11-15 | GSE146541 | GEO

Gene expression analysis of ccRCC cell line upon SETD2 rescue [RNAseq_JHRCC12]

2021-11-15 | GSE146540 | GEO

Genome binding/occupancy profiling of ccRCC cell line upon SETD2 rescue [ChIPseq_JHRCC12]

2021-11-15 | GSE146539 | GEO

SETD2 loss sensitizes kidney cancer cells to DNA hypomethylating agents

Project description:Large-scale sequencing efforts in Clear cell renal cell carcinoma (ccRCC) have found a high prevalence of mutations in chromatin-related genes. Prominent within this group is SETD2, which is mutated in 15% of ccRCC and is associated with aggressive disease. SETD2 is a methyltransferase responsible for trimethylating lysine 36 on histone H3 (H3K36me3). Although it is not completely understood how SETD2 loss contributes to ccRCC tumorigenesis, it is thought that it reprograms the epigenetic landscape of the cell. Here we explore the impact that SETD2/H3K36me3 loss has on the DNA methylome in ccRCC cells. DNA methylation was measured using the EPIC DNA methylation assay in 786-O ccRCC cells and non-cancerous transformed proximal tubule kidney cells (HKC) with and without SETD2. Sensitivity to DNA hypomethylating agents was assessed by dose-response assay using 5-aza-2'-deoxycytidine. Apoptosis was measured via Annexin-V/PI staining by flow cytometry. Mitochondrial fitness was evaluated by electron microscopy and flow cytometry. Moreover, activity of 5-aza-2'-deoxycytidine, a DNA hypomethylating agent, in was assessed in SETD2 WT/KO xenografts in NOD-Scid mice. SETD2 loss resulted in DNA hypermethylation in HKC cells and to a greater extent in 786-O. Dose-response assays showed that SETD2-null ccRCC cells are sensitive to 5-aza-2'-deoxycytidine. Furthermore, Annexin-V/PI staining revealed more apoptotic and necrotic cells in SETD2-null cells following 5-aza-2'-deoxycytidine treatment, which was rescued using a Caspase inhibitor. In addition, 5-aza-2'-deoxycytidine induced profound changes in mitochondria in SETD2-null cells, including loss of membrane potential and size reduction. Indeed, in vivo experiments verified increased SETD2-null xenografts’ sensitivity to 5-aza-2'-deoxycytidine. We show that SETD2 loss in ccRCC cells causes DNA hypermethylation, creating a synthetic lethal dependency with DNA hypomethylating agents.

2024-07-01 | GSE223688 | GEO

RNA mis-splicing sensitizes SETD2-mutant kidney cancer cells to DNMTi (Methylation)

Project description:The dysregulation of the histone H3 lysine 36 (H3K36) methyltransferase, SETD2, is associated with worse clinical outcomes and metastasis in clear cell Renal Cell Carcinoma (ccRCC). Here, we reveal that kidney cancer cells displaying diminished H3K36me3 levels (SETD2 deficiency) show increased sensitivity to the anti-tumor effects of the DNA hypomethylating agent 5-aza-2’-deoxycytidine (Decitabine/DAC). DAC treatment induced stronger viral mimicry activation and immunostimulatory signals by higher transposable element (TE) expression in SETD2-mutant cancer cells. Surprisingly, we demonstrate that the increased TE abundance in SETD2-knockout (SETD2-KO) kidney cancer cells is substantially derived from mis-spliced products induced by DAC treatment. Epigenetic profiling suggests that differential DNA methylation, H3K36me3, and H3K9me3 marks across exons and intronic TEs might contribute to elevated mis-splicing rates specifically in the SETD2 loss context. Finally, SETD2 dysregulation also sensitized tumors in vivo to combinatorial therapy of DAC and immune checkpoint inhibitors highlighting the translational potential for this precision medicine.

2023-01-27 | GSE198673 | GEO

RNA mis-splicing sensitizes SETD2-mutant kidney cancer cells to DNMTi (ChiP-Seq and RNA-Seq)

2023-01-27 | GSE198670 | GEO

Proteomics analysis on SETD2 loss induced ccRCC formation

Project description:Patients with polycystic kidney disease (PKD) encounter a high risk of clear cell renal cell carcinoma (ccRCC), a malignant tumor with dysregulated lipid metabolism. SET domain–containing 2 (SETD2) has been identified as an important tumor suppressor gene in ccRCC. However, the role of SETD2 in tumorigenesis during the transition from PKD to ccRCC remains largely unexplored. Herein, we performed metabolomics, lipidomics, transcriptomics and proteomics with SETD2 loss induced PKD-ccRCC transition mouse model. To characterize biological responses triggered by SETD2 deletion during PKD-ccRCC transition at the protein level, we conducted global proteomics studies.

2023-10-31 | PXD038966 | Pride

Gene expression data from the 786-O renal cell carcinoma cell line and its metastatic derivatives.

Project description:Inactivation of the von Hippel-Lindau tumor suppressor gene, VHL, is an archetypical tumor-initiating event in clear cell renal carcinoma (ccRCC) that leads to the activation of hypoxia-inducible transcription factors (HIFs). However, VHL mutation status in ccRCC is not correlated with clinical outcome. Here we show that during ccRCC progression, cancer cells exploit diverse epigenetic alterations to empower a branch of the VHL-HIF pathway for metastasis, and the strength of this activation is associated with poor clinical outcome. By analyzing metastatic subpopulations of VHL-deficient ccRCC cells, we discovered an epigenetically altered VHL-HIF response that is specific to metastatic ccRCC. Focusing on the two most prominent pro-metastatic VHL-HIF target genes, we show that loss of polycomb repressive complex 2 (PRC2)-dependent histone H3 Lys27 trimethylation (H3K27me3) activates HIF-driven chemokine (C-X-C motif) receptor 4 (CXCR4) expression in support of chemotactic cell invasion, whereas loss of DNA methylation enables HIF-driven cytohesin 1 interacting protein (CYTIP) expression to protect cancer cells from death cytokine signals. Thus, metastasis in ccRCC is based on an epigenetically expanded output of the tumor-initiating pathway. Gene expression profiles of 786-O renal cell carcinoma cells and metastatic subpopulations isoloated by in vivo selection in immunocomrpmized mice. The derivatives are significantly enriched in the metastatic propensity as measure by experimental metastasis assays.

2012-12-05 | E-GEOD-32295 | biostudies-arrayexpress

SETD2 loss in renal epithelial cells drives epithelial to mesenchymal transition in a TGFβ-independent manner [RNA-Seq]

Project description:SETD2 is one of most frequently mutated genes in renal cell carcinoma. It is generally known as the only histone methyltransferase that catalyze the trimethylation of lysine 36 on histone H3 (H3K36me3). Mutation of this gene and/or loss of its mark have been linked to metastasis and worse patient outcomes in kidney cancer. In this paper, we will examine the mechanism by which SETD2 loss induces epithelial-to-mesenchymal transition (EMT), which is a major pathway that drives invasion and early metastasis in various cancer types. To achieve the goals, we performed several omics analysis including RNA-seq, ChIP-seq and ATAC-seq to characterize how SETD2 deletion alters transcriptome and epigenome.

2023-07-12 | GSE213258 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data