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

RNA-seq data of primary human hepatocytes spheroids treated with compounds (experiment 1)

ABSTRACT: Primary human hepatocytes from 3 different donors as 3D spheroids treated with 14 compounds (3 concentrations, 0.1xCmax, Cmax and 10xCmax) and vehicle for 7 h. Compounds have different degree of drug-induced liver injury concern. Data for Figure 1 in connected publication. Experiment 1 of 2.

INSTRUMENT(S): Illumina NovaSeq 6000

ORGANISM(S): Homo sapiens

SUBMITTER: John Hellgren

PROVIDER: E-MTAB-15586 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Json Xml

Similar Datasets

RNA-seq data of primary human hepatocytes spheroids treated with compounds (experiment 2)

Project description:Primary human hepatocytes from 3 different donors as 3D spheroids treated with 8 compounds (3 concentrations, 0.1xCmax, Cmax and 10xCmax) and vehicle for 7 h. Compounds have different degree of drug-induced liver injury concern. Data for Figure 1 in connected publication. Experiment 2 of 2.

2026-01-16 | E-MTAB-15587 | biostudies-arrayexpress

RNA-seq data of primary human hepatocytes spheroids from healthy and Metabolic dysfunction associated steatotic liver disease (MASLD) donors following troglitazone treatment

Project description:Primary human hepatocytes from healthy and Metabolic dysfunction associated steatotic liver disease (MASLD) patients (6 donors each) as 3D spheroids treated with troglitazone (3 concentrations, 0.1xCmax, Cmax and 10xCmax) and vehicle for 7 h. Data for Figure 5 in connected publication.

2026-01-16 | E-MTAB-15610 | biostudies-arrayexpress

RNA-seq data of primary human hepatocytes spheroids treated with AZD1979

Project description:Primary human hepatocytes from 3 different donors as 3D spheroids treated with AZD1979 (5 concentrations) and vehicle for 7 h. Data for Figure 4 in connected publication.

2026-01-16 | E-MTAB-15609 | biostudies-arrayexpress

DRUG-seq data of HepG2 treated with compounds

Project description:HepG2 treated with 40 compounds (3 concentrations, 0.1xCmax, Cmax and 10xCmax) and vehicle for 7 h. Compounds have different degree of drug-induced liver injury concern. Data for Figure 2 in connected publication.

2026-01-16 | E-MTAB-15601 | biostudies-arrayexpress

DRUG-seq data of primary human hepatocyte spheroids treated with compounds

Project description:Primary human hepatocytes treated with 40 compounds (3 concentrations, 0.1xCmax, Cmax and 10xCmax) and vehicle for 7 h. Compounds have different degree of drug-induced liver injury concern. Data for Figure 2 in connected publication.

2026-01-16 | E-MTAB-15612 | biostudies-arrayexpress

Classification of developmental toxicants in a human iPSC transcriptomics-based test

Project description:There is a great need for in vitro tests that identify developmental toxicants in relation to human oral doses and blood concentrations. In the present study, we used the hiPSC-based UKK-24h-test and analyzed genome-wide expression profiles of 23 known teratogens and 16 non-teratogens. All compounds were analyzed at the maximal plasma concentration (Cmax) and the 20-fold Cmax for a 24 h incubation period in three independent experiments. Using the 1,000 probe sets with the highest variability and including information on cytotoxicity, a penalized logistic regression based classifier (top-1,000 classifier) reached an AUC, accuracy, sensitivity, and specificity of 0.96, 0.92, 0.96 and 0.88, respectively to correctly classify the compounds as teratogens or non-teratogens. This top-1,000 classifier reached a higher AUC, accuracy and sensitivity than a second classifier (SPS-classifier), which used the number of significant probe sets to classify the compounds. At least, the SPS-classifier had a specificity of 1. Classification at 20-fold Cmax did not lead to better performance metrics than testing at 1-fold Cmax. Finally, inclusion of cytotoxicity information into the classifier clearly improved the performance metrics. In conclusion, although further optimization by additional readouts and inclusion of cell systems that model different developmental processes is required, the UKK-24h-test will support the early discovery-phase detection of human developmental toxicants already in its present form.

2022-06-24 | GSE187001 | GEO

RNA-Seq of A549 cells treated with chemical modification patterns for microRNA therapeutic mimics, a case-study on miR-200c

Project description:We examined the influence of chemical modifications patterns in a set of miR-200c mimics, assessing the regulation of the whole transcriptome in A549 cells. We examined 37 mimics and provided an initial set of rules for designing miRNA mimics with potency and selectivity similar to an unmodified miRNA duplex.

2023-12-20 | E-MTAB-12574 | biostudies-arrayexpress

RNA-Seq of chemical modification patterns for microRNA therapeutic mimics, a case-study on miR-200c, miR-155 and miR34a

Project description:We examined the influence of chemical modifications patterns in a set of miR-200c, miR-155 and miR-34a mimics, assessing the regulation of the whole transcriptome in A549 cells. We examined the mimics and provided an initial set of rules for designing miRNA mimics with potency and selectivity similar to an unmodified miRNA duplex.

2024-02-15 | E-MTAB-13801 | biostudies-arrayexpress

RNA-Seq to probe transcription of patient-derived organotypic colorectal cancer.

Project description:Patient-derived cancer organoids (PCOs) provide a platform to model resistant to targeted therapies. Following culture maturation, PCOs were treated with stepwise dose escalation of EGFR inhibitors. Cultures were started at 20% physiologic Cmax panitumumab (46ug/ml) and assessed for growth (normalized change in diameter at 96 hours). If cultures surpassed ≥20% growth, stepwise dose escalation was repeated with interval increase of 20% Cmax. Time to resistant (TTR) was defined by duration of time from the initiation of dose escalation to persistent growth at 100% Cmax panitumumab. All samples were collected in triplicate biological replicates at baseline and after achieving resistance to EGFRi with persistent growth at 100% physiologic Cmax. RNA library was constructed using TruSeq Stranded total RNA with rRNA reduction (Illumina). Quality control was performed by Eukaryote Total RNA electrophoresis using NanoDropOne. The library included 2x150bp paired end reads with sequencing performed by NovaSeq 6000 using MiSeq NanoCell at University of Wisconsin Biotechnology Center.

2023-07-01 | GSE180480 | GEO

Targeted RNA-seq (TempO-Seq) of temporal concentration responses to drug exposures in PHH and HepaRG cells

Project description:For the purpose of mechanism-based risk assessment, we investigated temporal concentration-dependent responses in cultures of PHH and HepaRG cells exposed to three drugs, acetaminophen (APAP), cyclosporine A (CSA) and valproic acid (VPA), that have a high liability for drug-induced liver injury. To facilitate the identification of early KEs and visualisation of their development over time, samples were collected at 4 time points, namely 8 and 24 hours (single exposure), 48 and 72 hours (daily repeated exposure), after exposure to a broad concentration range. Concentrations were selected based on the reported total Cmax of each drug. As these are approved drugs currently on the market, they are not expected to induce overt adverse effects around Cmax. Therefore, the selected maximum concentration was set at approximately 30x Cmax, whilst the minimum tested concentration was approximately 0.1x Cmax. The large concentration range allowed to apply benchmark concentration (BMC) modelling on individual genes as well as gene co-expression networks to derive in vitro transcriptomics benchmark concentrations (BMCs) and assess their suitability to be used as PoD in chemical risk assessment.

2024-03-01 | E-MTAB-12668 | biostudies-arrayexpress

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