Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Qualitative differences in diseases-associated mutants reveal molecular signatures and aberrant signaling-crosstalk

ABSTRACT: Qualitative differences in diseases-associated mutants reveal molecular signatures and aberrant signaling-crosstalk

PROVIDER: PRJNA697974 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Similar Datasets

Qualitative differences in diseases-associated mutants reveal molecular signatures and aberrant signaling-crosstalk

Project description:We generated HEK293 cells stably expressing diseases-derived mutants and performed a genome-wide transcriptome analysis using the 60K SurePrint G3 Human gene expression microarray technology. By the analysis of their gene expression profiles, we identified diseases-associated signature genes that may serve as diagnostic markers or therapeutic targets for the diseases.

2022-06-13 | GSE165823 | GEO

Qualitative differences in disease-associated MEK mutants reveal molecular signatures and aberrant signaling-crosstalk in cancer.

Project description: Not available

| S-EPMC9279491 | biostudies-literature

Mutant FUS and ELAVL4 (HuD) aberrant crosstalk in Amyotrophic Lateral Sclerosis

Project description:Mutant FUS and ELAVL4 (HuD) aberrant crosstalk in Amyotrophic Lateral Sclerosis

| PRJNA485313 | ENA

Targeting Histone Modification Crosstalk as a Therapeutic Strategy for EZH2-aberrant Solid Tumors

Project description:Mutations or aberrant upregulation of the histone methyltransferase EZH2 occur frequently in human cancers yet EZH2-targeted therapies have only shown very limited clinical benefits in hematological malignancies. We report here that upon EZH2 inhibition, MLL1 interacts with p300/CBP complex that directs H3K27me loss to gain of H3K27ac modification. This histone modification crosstalk leads to transcriptional reprogramming that restricts the therapeutic response to EZH2 inhibition. Concurrent inhibition of H3K27 methylation and acetylation results in transcriptional repression and growth dependency on the MAPK signaling pathway in a large cancer subset. In pre-clinical models encompassing a broad spectrum of EZH2-aberrant solid tumors, a combination of EZH2 and BRD4 inhibitors or a triple-combination including MAPK inhibition display robust efficacy with tolerable toxicity, in particular in liver and pancreatic cancers. Our results suggest an attractive precision treatment and patient stratification strategy for EZH2-aberrant tumors on the basis of intrinsic MLL1 expression and feedback MAPK activation.

2018-09-10 | PXD010842 | iProX

IMPACT: Unraveling intracellular signal transduction and pathway crosstalk by exploring pathway landscape

Project description:Understanding complicated modularization and crosstalk of intracellular signal transduction pathways holds the key to battle against drug resistance in human cancer research. We propose an integrative approach, namely Inferring Modularization of PAthway CrossTalk (IMPACT), to identify aberrant pathway modules and their between-module crosstalk by exploring pathway landscape that is reconstructed from a sampling strategy. The pathway identification method (i.e., IMPACT) was applied to breast cancer data to uncover aberrant pathway modules, which were further investigated with cell line studies to understand drug resistance in breast cancer. The patient datasets we mentioned are published and are available in the GEO database as GSE6532 and GSE17705. The re-processed GSE6532 and GSE17705 patient datasets are linked below as supplementary files. The GSE6532_matrix.txt and GSE17705_matrix.txt are processed by Affy Gene console with plier as normailization. But importantly, we also used 'Combat' method (http://www.bu.edu/jlab/wp-assets/ComBat/Abstract.html) to remove potential institutional batch effect. Four MCF7 derived cell models were included in the study: MCF7-STR, MCF7RR-STR, LCC1 and LCC2 cell lines. MCF7-STR and MCF7RR-STR were grown in phenol red-free IMEM supplemented with 5% charcoal-stripped calf serum and 1nM estradiol for 72 h prior to RNA extraction. LCC1 and LCC2 cells were grown in phenol red-free IMEM supplemented with 5% charcoal-stripped calf serum. The cell line data were used to validate computational results derived from patient datasets.

2013-09-07 | E-GEOD-50564 | biostudies-arrayexpress

IMPACT: Unraveling intracellular signal transduction and pathway crosstalk by exploring pathway landscape

2013-09-07 | GSE50564 | GEO

A robust qualitative transcriptional signature for the early diagnosis of gastric cancer

Project description:Pathological examination of gastroscopy biopsy specimens will make false diagnosis for gastric cancer (GC) due to inaccurate sampling locations and/or insufficient sampling amount. We extracted a robust qualitative transcriptional signature, based on the within-sample relative expression orderings (REOs) of gene pairs, to discriminate both GC tissues and adjacent-normal tissues from non-GC gastritis and normal gastric tissues.The qualitative transcriptional signature can be robustly applied at the individual level to aid the diagnosis of early GC.

2018-07-10 | GSE116782 | GEO

Transcriptomic analysis of DENV-specific CD8+T cell responses in acute disease does not support qualitative differences as drivers of disease severity

Project description:In this study, we assessed the contribution of dengue-specific CD8+T cells in hospitalized samples with mild (dengue fever; DF) and severe (dengue hemorrhagic fever; DHF) forms of the disease. Our in-depth transcriptomic analysis provides no evidence for qualitative differences in terms of CD8+T cell response against dengue, therefore, concluding that CD8+T cell response is not a contributing factor in the development of severe dengue disease.

2021-09-21 | GSE174482 | GEO

Pevonedistat inhibits aberrant protein NEDDylation in Polycystic Liver Diseases.

Project description:Background: Polycystic liver diseases (PLD) are genetic disorders characterized by progressive growth of numerous liver cysts, causing significant morbidity. Previous studies revealed genes affecting protein biogenesis and more recently, protein SUMOylation, a posttranslational modification (PTM), has been implicated in PLD pathobiology. On the other hand, protein NEDDylation is a newly-characterized PTM, modulating a plethora of biological processes and its dysregulation is associated with development and progression of several human diseases. In this regard, the role of NEDDylation in PLD remains elusive and unraveling its role in the pathogenesis of these genetic disorders could open new avenues for the development of novel treatments in the future. Objective: To explore the role of protein NEDDylation in PLD and its potential therapeutic regulatory value. Methods: Expression and function of NEDDylation, including response to Pevonedistat (first-in-class selective inhibitor of the NEDDylation E1 enzyme NAE1), were assessed in vitro. Proteomic analyses of immunoprecipitated NEDDylated proteins were performed by mass spectrometry.

2022-02-16 | PXD022571 | Pride

A Qualitative Transcriptional Signature for the Histological Classification of Non-Small Cell Lung Cancer

Project description:Histological classification by routine pathology assessment with hematoxylin-eosin staining and immunostaining for poorly differentiated tumors, particularly those from small biopsies, is still challenging. In this study, using gene expression profiles of pathologically-determined lung squamous cell carcinomas and adenocarcinomas, denoted as pSCC and pADC respectively, we developed a qualitative transcriptional signature, based on the within-sample relative gene expression orderings (REOs) of gene pairs, to individually distinguish ADC from SCC. The signature was validated in the frozen tissues, FFPE materials, mixed tumors, small biopsy specimens and poorly differentiated samples.In summary, the qualitative signature, independent of the subjective diagnosis of pathologists, would be an effective auxiliary tool in distinguishing ADC from SCC.

2018-10-11 | GSE121090 | 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