ArticlePLoS computational biology2016
Assessing Concordance of Drug-Induced Transcriptional Response in Rodent Liver and Cultured Hepatocytes.
Article in PLoS computational biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
30 citing papers in PubMed, 62 citations in OpenAlex.
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- Characterisation of the NRF2 transcriptional network and its response to chemical insult in primary human hepatocytes: implications for prediction of drug-induced liver injury.Archives of toxicology · 2019Article
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Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The effect of drugs, disease and other perturbations on mRNA levels are studied using gene expression microarrays or RNA-seq, with the goal of understanding molecular effects arising from the perturbation. Previous comparisons of reproducibility across laboratories have been limited in scale and focused on a single model. The use of model systems, such as cultured primary cells or cancer cell lines, assumes that mechanistic insights derived from the models would have been observed via in vivo studies. We examined the concordance of compound-induced transcriptional changes using data from several sources: rat liver and rat primary hepatocytes (RPH) from Drug Matrix (DM) and open TG-GATEs (TG), human primary hepatocytes (HPH) from TG, and mouse liver/HepG2 results from the Gene Expression Omnibus (GEO) repository. Gene expression changes for treatments were normalized to controls and analyzed with three methods: 1) gene level for 9071 high expression genes in rat liver, 2) gene set analysis (GSA) using canonical pathways and gene ontology sets, 3) weighted gene co-expression network analysis (WGCNA). Co-expression networks performed better than genes or GSA when comparing treatment effects within rat liver and rat vs. mouse liver. Genes and modules performed similarly at Connectivity Map-style analyses, where success at identifying similar treatments among a collection of reference profiles is the goal. Comparisons between rat liver and RPH, and those between RPH, HPH and HepG2 cells reveal lower concordance for all methods. We observe that the baseline state of untreated cultured cells relative to untreated rat liver shows striking similarity with toxicant-exposed cells in vivo, indicating that gross systems level perturbation in the underlying networks in culture may contribute to the low concordance.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.