Browse
Submit Data
Databases
API
Help

Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Deciphering myeloma risk loci by eQTL analysis

ABSTRACT: Recent genome-wide association studies have identified single nucleotide polymorphisms (SNPs) at 7 loci influencing multiple myeloma (MM) risk. We generated expression quantitative trait loci (eQTL) data on malignant plasma cells from two patient series (totaling 848) to fine map the risk loci associations and gain insight into their functional basis. At 7p11.2 the strongest association with MM risk is provided by rs4487645, which is associated with allele–specific cis-regulation of the MYC-interacting gene CDCA7L (P=4.1x10-25). These data are compatible with increased expression of CDCA7L being the functional basis of the 7p11.2 association exerting its effects through an extended pathway involving IRF4 and MYC. Note: This dataset re-uses files from ArrayExpress accessions E-TABM-937, E-MTAB-362, E-MTAB-372.

ORGANISM(S): Homo sapiens

SUBMITTER: Tobias Meissner

PROVIDER: E-MTAB-2299 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Json Xml

Similar Datasets

RNA-seq analysis after JQKD82 treatment in human multiple myeloma cell line MM.1S

Project description:Recent studies have highlighted the oncogenic roles of KDM5A; however, its molecular mechanism has not been fully delineated. Here we identifies KDM5A as a transcriptional activator of MYC target genes in multiple myeloma (MM). Genetic ablation of KDM5A or pharmacologic inhibition of KDM5 by novel inhibitor JQKD82 impairs MM cell growth. Gene expression profile reveals that JQKD82 decreases expression of MYC targets. Expression of MYC targets is similarly downregulated by KDM5A depletion, but little affected by KDM5B knockdown. Mechanistically, KDM5A co-localizes with MYC across the genome, and KDM5A and MYC coordinately promote MYC target gene transcription. The treatment with JQKD82 reduces phosphorylation level of RNA polymerase II (RNAPII), resulting in RNAPII pausing, accompanied by hyper-H3K4me3 status at the MYC loci. Finally, we shows that JQKD82 exerts anti-MM activity and prolongs overall survival in vivo mouse xenograft models. Our results delineate KDM5A function that reinforces MYC transcriptional program, and identify KDM5A as a potential therapeutic target in MM.

2021-03-22 | GSE148047 | GEO

ChIP-seq analyses for KDM5A, H3K4me3, RNAPII and TAF3 in human multiple myeloma cell line MM.1S

2021-03-22 | GSE148046 | GEO

ChIP-seq and RNA-seq analyses in human multiple myeloma cell line MM.1S

2021-03-22 | GSE148048 | GEO

C-terminal binding protein (CTBP2) is a novel tumor suppressor targeting the MYC-IRF4 axis in multiple myeloma

Project description:Multiple myeloma (MM) cells are addicted to MYC and its direct transactivation target IRF4 for proliferation and survival. MYC and IRF4 are still considered “undruggable” as the majority of small molecule inhibitors suffers from low potency, suboptimal pharmacokinetic properties and undesirable off-target effects. Indirect inhibition of MYC/IRF4 emerges as a therapeutic vulnerability in MM. Here, we uncover an unappreciated tumor suppressive role of C-terminal Binding Protein 2 (CTBP2) in MM via strong inhibition of the MYC-IRF4 axis. In contrast to epithelial cancers, CTBP2 is frequently downregulated in MM, in association with shortened survival, hyperproliferative features and adverse clinical outcomes. Restoration of CTBP2 exhibited potent anti-tumor effects against MM in vitro and in vivo, with marked repression of MYC-IRF4 network genes. Mechanistically, CTBP2 impeded transcription of MYC and IRF4 by histone H3 lysine 27 deacetylation (H3K27ac), and indirectly via activation of MYC repressor IFIT3. In addition, activation of interferon gene signature by CTBP2 suggested its concomitant immunomodulatory role in MM. Epigenetic studies revealed contribution of polycomb-mediated silencing and DNA methylation to CTBP2 inactivation in MM. Notably, inhibitors of Enhance of zeste homolog 2 (EZH2), histone deacetylase (HDACs) and DNA methyltransferase (DNMTs) currently under evaluation in clinical trials were effective in restoring CTBP2 expression in MM. Our findings indicated that loss of CTBP2 plays an essential role in myelomagenesis and decipher an additional mechanistic link on MYC-IRF4 dysregulation in MM. We envision that identification of novel critical regulators would facilitate the development of selective and effective approaches for treating this MYC/IRF4-addicted malignancy.

2024-03-10 | GSE255266 | GEO

Integrative multi-omics analyses to identify the genetic and functional mechanisms underlying ovarian cancer risk regions

Project description:To identify credible causal risk variants (CCVs) associated with different histotypes of epithelial ovarian cancer (EOC), we performed genome-wide association analysis for 470,825 genotyped and 10,163,797 imputed SNPs in 25,981 EOC cases and 105,724 controls of European origin. We identified five new histotype-specific EOC risk regions (P-value < 5 x 10-8) and confirmed previously reported associations for 27 risk regions. Conditional analyses identified an additional 11 signals independent of the primary signal at six risk regions (P-value < 10-5). Fine mapping identified 4,008 CCVs in these regions, of which 1,452 CCVs were located in ovarian cancer-related chromatin marks with significant enrichment in active enhancers, active promoters, and active regions for CCVs from each EOC histotype. Transcriptome-wide association and colocalization analyses across histotypes using tissue-specific and cross-tissue data sets identified 86 candidate susceptibility genes in known EOC risk regions and 32 genes in 23 additional genomic regions that may represent novel EOC risk loci (FDR < 0.05). Finally, by integrating genome-wide HiChIP interactome analysis with TWAS, variant effect predictor, transcription factor ChIP-seq, and motifbreakR data, we identified candidate gene-CCV interactions at each locus. This included risk loci where TWAS identified one or more candidate susceptibility genes (e.g., HOXD-AS2, HOXD8 and HOXD3 at 2q31) and other loci where no candidate gene was identified (e.g., MYC and PVT1 at 8q24) by TWAS. In summary, this study describes a functional framework and provides a greater understanding of the biological significance of risk alleles and candidate gene targets at EOC susceptibility loci identified by GWAS.

2024-03-27 | GSE255142 | GEO

Protein interaction networks in the vasculature prioritize genes and pathways underlying coronary artery disease (Whitehead data)

Project description:Population-based association studies have identified many genetic risk loci for coronary artery disease (CAD), but it is often unclear how genes within these loci are linked to CAD. Here, we performed interaction proteomics for 11 CAD-risk genes to map their protein-protein interactions (PPIs) in human vascular cells and elucidate their biological relevance in CAD pathogenesis. The PPI networks contain many protein interactions that are outside of known biology in the vasculature and are enriched for genes involved in immunity-related and arterial-wall-specific mechanisms. Furthermore, several PPI networks derived from smooth muscle cells are significantly enriched for genetic variants associated with CAD and related vascular phenotypes. Finally, our networks identified 61 genes that are found in genetic loci associated with risk of CAD, prioritizing them as the causal candidates within these loci. Together, our results indicate that the PPI networks we have generated are a rich resource for guiding future research into the molecular pathogenesis of CAD.

2023-02-27 | MSV000091373 | MassIVE

Gene expression profiling of human CD19+ B cells and EBV transformed lymphoblastoid cell lines (LCLs)

Project description:Genome wide association studies have identified >200 susceptibility loci accounting for much of the heritability of Multiple Sclerosis (MS). Epstein-Barr virus (EBV), a memory B cell tropic virus, has been identified as necessary but not sufficient for development of MS. The molecular and immunological basis for this has not been established. Infected B cell proliferation is driven by signalling through the EBV produced cell surface protein LMP1, a homologue of the MS risk gene CD40. Methods: We have investigated transcriptomes of B cells and EBV infected B cells at Latency III (LCLs) and identified MS risk genes with altered expression on infection

2019-04-01 | GSE126379 | GEO

Single-cell RNAseq of VQ myeloma cells reveals unique transcriptional signatures from normal plasma cells

Project description:NRAS Q61 mutations are prevalent in advanced/relapsed multiple myeloma (MM) and correlate with poor patient outcomes. Thus, we generated a novel MM model by conditionally activating expression of endogenous NrasQ61R and a MYC transgene in germinal center B cells (VQ mice). VQ mice developed a highly malignant MM characterized by high proliferation index, hyperactivation of ERK and AKT signaling, impaired hematopoiesis, widespread extramedullary disease, bone lesions, kidney abnormalities, preserved PD1 and TIGIT immune checkpoint pathways, and expression of human high-risk MM gene signatures. VQ MM mice recapitulate most of the biological and clinical features of human advanced/high-risk MM. These MM phenotypes are serially transplantable in syngeneic recipients. Two MM cell lines were also derived to facilitate future genetic manipulations. Combination therapies based on MEK inhibition significantly prolonged the survival of VQ mice with advanced stage MM. Our study provides a strong rationale to develop MEK inhibition-based therapies for treating advanced/relapsed MM.

2020-07-02 | GSE153627 | GEO

Transcriptomic profiling of normal plasma cells and MM models using bulk RNA-Seq

2020-07-02 | GSE153626 | GEO

Re-analysis of E-MTAB-1585

Project description:Raw data from E-MTAB-1585 was normalized by using reads per million. https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-1585/

2013-09-19 | GSE50860 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

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