Transcriptomics

Dataset Information

0

Temporal Concordance between Apical and Transcriptional Points-of-Departure for Chemical Risk Assessment


ABSTRACT: The number of legacy chemicals without toxicity reference values combined with the rate of new chemical development are overwhelming the capacity of the traditional risk assessment paradigm. More efficient approaches are needed to quantitatively estimate chemical risks. In this study, rats were dosed orally with multiple doses of six chemicals for 5 days, 2, 4, and 13 weeks. Target organs were analyzed for traditional histological and organ weight changes and transcriptional changes using microarrays. Histological and organ weight changes in this study and the tumor incidences in the original cancer bioassays were analyzed using benchmark dose (BMD) methods to identify noncancer and cancer points-of-departure. The dose-response changes in gene expression were also analyzed using BMD methods and the responses grouped based on signaling pathways. A comparison of transcriptional BMD values for the most sensitive pathway with BMD values for the noncancer and cancer apical endpoints showed a high degree of correlation at all time points. When the analysis included data from an earlier study with 8 additional chemicals, transcriptional BMD values for the most sensitive pathway were significantly correlated with noncancer (r = 0.827, p = 0.0031) and cancer-related (r = 0.940, p = 0.0002) BMD values at 13 weeks. The average ratio of apical-to-transcriptional BMD values was less than two suggesting that for the current chemicals, transcriptional perturbation did not occur at significantly lower doses than apical responses. Based on our results, we propose a practical framework for application of transcriptomic data to chemical risk assessment.

ORGANISM(S): Rattus norvegicus

PROVIDER: GSE45892 | GEO | 2013/04/22

SECONDARY ACCESSION(S): PRJNA196610

REPOSITORIES: GEO

Dataset's files

Source:
Action DRS
Other
Items per page:
1 - 1 of 1

Similar Datasets

2013-04-22 | E-GEOD-45892 | biostudies-arrayexpress
2020-05-12 | GSE147072 | GEO
2008-08-08 | GSE12353 | GEO
2010-10-27 | GSE24899 | GEO
2010-07-24 | GSE23018 | GEO
2024-08-31 | E-MTAB-14033 | biostudies-arrayexpress
2021-12-12 | GSE179232 | GEO
2014-10-30 | GSE62807 | GEO
2014-10-30 | GSE62806 | GEO
2018-10-04 | GSE120805 | GEO