ArticleCancer science2006
Prediction of carcinogenic potential by a toxicogenomic approach using rat hepatoma cells.
Article in Cancer science, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed, 40 citations in OpenAlex.
- Application of transfer learning to predict drug-induced human in vivo gene expression changes using rat in vitro and in vivo data.PloS one · 2023Article
- Quantitative analysis of artificial intelligence on liver cancer: A bibliometric analysis.Frontiers in oncology · 2023Article
- Use of deep learning methods to translate drug-induced gene expression changes from rat to human primary hepatocytes.PloS one · 2020Article
- Tuning of essential oil properties by enzymatic treatment: towards sustainable processes for the generation of new fragrance ingredients.Molecules (Basel, Switzerland) · 2014Review
- Genetic toxicology in the 21st century: reflections and future directions.Environmental and molecular mutagenesis · 2011Review
- Toxicogenomic profiling of chemically exposed humans in risk assessment.Mutation research · 2010Review
- Toxicogenomic biomarkers for liver toxicity.Journal of toxicologic pathology · 2009Article
- Translational microarray systems for outcome prediction of hepatocellular carcinoma.Cancer science · 2008Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The long-term rodent bioassay is the standard method to predict the carcinogenic hazard of chemicals for humans. However, this assay is costly, and the results take at least two years to produce. In the present study, we conducted gene expression profiling of cultured cells exposed to carcinogenic chemicals with the aim of providing a basis for rapid and reliable prediction of carcinogenicity using microarray technology. We selected 39 chemicals, including 17 rat hepatocarcinogens and eight compounds demonstrating carcinogenicity in organs other than the liver. The remaining 14 were non-carcinogens. When rat hepatoma cells (MH1C1) were treated with the chemicals for 3 days at a non-toxic dose, analysis of gene expression changes with our in-house microarray allowed a set of genes to be identified differentiating hepatocarcinogens from non-carcinogens, and all carcinogens from non-carcinogens, by statistical methods. Moreover, optimization of the two gene sets for classification with an SVM and LOO-CV resulted in selection of 39 genes. The highest predictivity was achieved with 207 genes for differentiation between non-hepatocarcinogens and non-carcinogens. The overlap between the two selected gene sets encompassed 26 genes. This gene set contained significant genes for prediction of carcinogenicity, with a concordance of 84.6% by LOO-CV SVM. Using nine external samples, correct prediction of carcinogenicity by SVM was 88.9%. These results indicate that short-term bioassay systems for carcinogenicity using gene expression profiling in hepatoma cells have great promise.
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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.