Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Drug repurposing identifies a synergistic high-order drug combination to treat sunitinib-resistant renal cell carcinoma

ABSTRACT: Drug repurposing identifies a synergistic high-order drug combination to treat sunitinib-resistant renal cell carcinoma

PROVIDER: PRJNA731385 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Similar Datasets

Drug repurposing identifies a synergistic high-order drug combination to treat sunitinib-resistant renal cell carcinoma

Project description:We report that in response to combination treatment with a synergistic low-dose four-drug combination, human Caki-1 cells resistant to sunitinib alter their pheno- and genotype. We detected that the metabolism of these cells is altered. Gene expression analysis revealed significant differential expression of genes related to mitosis, apoptosis and cell attachment. We detected regulation changes in enzymes mediating the ceramide and sphingolipid metabolism.

2021-05-21 | GSE174740 | GEO

Drug Repurposing to Identify a Synergistic High-Order Drug Combination to Treat Sunitinib-Resistant Renal Cell Carcinoma.

Project description: Not available

| S-EPMC8391235 | biostudies-literature

Machine Learning Identifies Candidates for Drug Repurposing in Alzheimer's Disease

Project description:Clinical trials of novel therapeutics for Alzheimer's Disease (AD) have consumed a large amount of time and resources with largely negative results. Repurposing drugs already approved by the Food and Drug Administration (FDA) for another indication is a more rapid and less expensive option. In this study, we profile 80 FDA-approved and clinically tested drugs in neural cell cultures, with the goal of producing a ranked list of possible repurposing candidates.

2021-01-14 | GSE164788 | GEO

Systems immunology-based drug repurposing framework to target inflammation in atherosclerosis [Tissue_RNA-seq]

Project description:we present a novel path to drug repurposing to identify new immunotherapies for ASCVD. The integration of time of-flight mass cytometry (CyTOF) and RNA-sequencing identified unique inflammatory signatures in peripheral blood mononuclear cells (PBMCs) stimulated with ASCVD plasma. By comparing these inflammatory signatures to large-scale gene expression data from the LINCS L1000 dataset, we identified drugs that could reverse this inflammatory response. In conclusion, a systems immunology-driven drug repurposing with pre- clinical validation strategy can aid the development of new cardiovascular immunotherapies.

2023-04-23 | GSE230216 | GEO

Systems immunology-based drug repurposing framework to target inflammation in atherosclerosis [DRUG_RNA-seq]

2023-04-23 | GSE230215 | GEO

Systems immunology-based drug repurposing framework to target inflammation in atherosclerosis [RNA-seq_PBMC]

2023-04-23 | GSE230214 | GEO

20230905 ReFRAME drug repurposing collection DDA spectra

Project description:DDA analysis of 14,000 drugs in the ReFRAME drug repurposing collection. Positive and negative ionizations.

| MSV000092822 | MassIVE

Drug repurposing unveils new combinatorial treatments to treat mutant KRAS lung cancer

Project description:We report data on a drug combination with synergistic antitumor effect in KRAS-driven lung cancer. We used RNAseq to characterize the transcriptional changes elicited by each drug in a mutant KRAS lung cancer cell lines (H1792)

2023-08-10 | GSE161218 | GEO

Gene expression profiling of generated sunitinib-resistant RCC cell lines

Project description:The clinical response to sunitinib in advanced renal-cell carcinoma (RCC) is frequently limited in magnitude and duration due to drug resistance, but the underlying mechanisms remain elusive. To discover mechanisms of resistance, we developed drug-resistant cell lines and have their gene expressions profiled and compared. Results provide insight into the molecular mechanisms underlying sunitinib-resistance.

2016-09-30 | GSE69535 | GEO

Differentially expressed genes analysis between dihydroberberine, sunitinib and dihydroberberine plus sunitinib.

Project description:To gain insights into the mechanisms of dihydroberberine, sunitinib and dihydroberberine plus sunitinib on inhibition to A549 cells, we have employed whole genome microarray expression profiling as a discovery platform to identify different genes between dihydroberberine, sunitinib and dihydroberberine plus sunitinib-treated sample and control.

2015-06-26 | GSE70282 | 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