Evidence map›Paper›PMID 31132080›Full record

ArticleToxicological sciences : an official journal of the Society of Toxicology2019

Aneugen Molecular Mechanism Assay: Proof-of-Concept With 27 Reference Chemicals.

Derek T Bernacki, Steven M Bryce, Jeffrey C Bemis, Stephen D Dertinger

Open access · greenAbstract read
In one paragraph

Article in Toxicological sciences : an official journal of the Society of Toxicology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.2field-weighted citation impact, top 24% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 18 citations in OpenAlex.

  1. Critical Evaluation of Methods for the Identification of Aneugens.Environmental and molecular mutagenesis · 2025
    Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. In vitro human cell-based aneugen molecular mechanism assay.Environmental and molecular mutagenesis · 2022
    Article
  8. Article
  9. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Derek T BernackiLitron Laboratories, Rochester, New York, 14623.
Steven M BryceLitron Laboratories, Rochester, New York, 14623.
Jeffrey C BemisLitron Laboratories, Rochester, New York, 14623.
Stephen D DertingerLitron Laboratories, Rochester, New York, 14623.
Litron Laboratories (United States) · US

Funding

Next Generation Testing Strategies for Assessment of GenotoxicityR44ES029014 · NIEHS · LITRON LABORATORIES, LTD. · PI BEMIS, JEFFREY C, DERTINGER, STEPHEN D · 2018 to 2020
$1.1M
NIEHS NIH HHS R44 ES029014
6 · The paper itself

Abstract

A tiered bioassay and data analysis scheme is described for elucidating the most common molecular targets responsible for chemical-induced in vitro aneugenicity: tubulin destabilization, tubulin stabilization, and inhibition of mitotic kinase(s). To evaluate this strategy, TK6 cells were first exposed to each of 27 presumed aneugens over a range of concentrations. After 4 and 24 h of treatment, γH2AX, p53, phospho-histone H3 (p-H3), and polyploidization biomarkers were evaluated using the MultiFlow DNA Damage Assay Kit. The assay identified 27 of 27 chemicals as genotoxic, with 25 exhibiting aneugenic signatures, 1 aneugenic and clastogenic, and 1 clastogenic. Subsequently, a newly described follow-up assay was employed to investigate the aneugenic agents' molecular targets. For these experiments, TK6 cells were exposed to each of 26 chemicals in the presence of 488 Taxol. After 4 h, cells were lysed and the liberated nuclei and mitotic chromosomes were stained with a nucleic acid dye and labeled with fluorescent antibodies against p-H3 and Ki-67. Flow cytometric analyses revealed that alterations to 488 Taxol-associated fluorescence were only observed with tubulin binders-increases in the case of tubulin stabilizers, decreases with destabilizers. Mitotic kinase inhibitors with known Aurora kinase B inhibiting activity were the only aneugens that dramatically decreased the ratio of p-H3-positive to Ki-67-positive nuclei. Unsupervised hierarchical clustering based on 488 Taxol fluorescence and p-H3: Ki-67 ratios clearly distinguished compounds with these disparate molecular mechanisms. Furthermore, a classification algorithm based on an artificial neural network was found to effectively predict molecular target, as leave-one-out cross-validation resulted in 25/26 agreement with a priori expectations. These results are encouraging, as they suggest that an adequate number of training set chemicals, in conjunction with a machine learning algorithm based on 488 Taxol, p-H3, and Ki-67 responses, can reliably elucidate the most commonly encountered aneugenic molecular targets.

Indexed as

AneugensCells, CulturedDNA DamageHistonesHumansKi-67 AntigenMachine LearningMutagenicity TestsNeural Networks, ComputerAneugensHistonesKi-67 Antigenaneugenflow cytometryMitotic kinase inhibitorsspindle poisonsTK6 cells

Identifiers

PMID31132080
PMCPMC6657583
OpenAlexW2947941237

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.