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Mutagenicity and Carcinogenicity

Mutagenicity and Carcinogenicity

Mutagenicity and carcinogenicity refer to the ability of drugs to cause genetic defects and induce cancer, respectively. The International Agency for Research on Cancer (IARC) classifies agents into four groups based on their carcinogenic potential. Group 1 agents are known human carcinogens; group 2A agents are probably carcinogenic to humans; group 3 agents lack data to support their role in carcinogenesis; and group 4 includes agents for which data support that they are not likely to be...

In vitro Mutagenesis

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To learn more about the function of a gene, researchers can observe what happens when the gene is inactivated or “knocked out,” by creating genetically engineered knockout animals. Knockout mice have been particularly useful as models for human diseases such as cancer, Parkinson’s disease, and diabetes.

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Evaluating the Effectiveness of Cancer Drug Sensitization In Vitro and In Vivo

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Published on: February 6, 2015

Assessing compound carcinogenicity in vitro using connectivity mapping.

Florian Caiment¹, Maria Tsamou, Danyel Jennen

¹Department of Toxicogenomics, Maastricht University, 6200 Maastricht, The Netherlands.

|August 14, 2013

Summary

This summary is machine-generated.

Predicting chemical carcinogenicity is crucial. This study uses transcriptomics and connectivity mapping with human liver cells to improve cancer risk assessment, offering a promising alternative to animal testing.

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Area of Science:

Toxicology and Carcinogenesis
Genomics and Bioinformatics

Background:

Accurate prediction of compound carcinogenicity is a major challenge in toxicology.
The traditional 2-year rodent cancer bioassay faces criticism for limited specificity and increasing pressure to reduce animal testing.
There is an urgent need for alternative methods in chemical cancer risk assessment.

Purpose of the Study:

To demonstrate the improvement of transcriptomics assays using primary human hepatocytes for predicting liver carcinogenicity.
To apply the connectivity map methodology to enhance toxicogenomics approaches for carcinogenicity prediction.
To investigate the influence of time and dose on the accuracy of carcinogenicity predictions.

Main Methods:

Utilized transcriptomics, a high-throughput toxicogenomics technology, with primary human hepatocytes.
Applied the connectivity map methodology to link in vivo human cancer tissue expression profiles with in vitro toxicogenomics data.
Evaluated the effects of different compound doses and exposure times (e.g., 24 hours) on prediction accuracy.

Main Results:

Connectivity mapping effectively predicted compound carcinogenicity by integrating in vitro and in vivo data.
The study demonstrated improved prediction of putative liver carcinogenicity using transcriptomics.
Optimal prediction accuracy was observed for potential carcinogens at low doses and after 24-hour exposure.

Conclusions:

Transcriptomics combined with connectivity mapping offers a valuable tool for predicting compound carcinogenicity.
This approach provides a more specific and potentially faster alternative to traditional rodent bioassays.
Understanding time and dose dependencies is critical for accurate in vitro carcinogenicity assessment.