Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Analysis of in vivo mutation data can inform cancer risk assessment.

Regulatory toxicology and pharmacology : RTP - 1 Jul 2008

Moore Martha M, Heflich Robert H, Haber Lynne T, Allen Bruce C, Shipp Annette M, Kodell Ralph L

Abstract excerpt

Under the new U.S. Environmental Protection Agency (EPA) Cancer Risk Assessment Guidelines [U.S. EPA, 2005. Guidelines for Carcinogen Risk Assessment. EPA/630/P-03/001B, March 2005], the quantitative model chosen for cancer risk assessment is based on the mode-of-action (MOA) of the chemical under consideration. In particular, the risk assessment model depends on whether or not the chemical causes tumors through...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Carcinogens
Share to DNA
Share to Dose-Response Relationship, Drug

Methodology Data sources Editorial policy Privacy Delete account & data About Contact Helena Bioinformatics

Share to Guidelines as Topic

Share to Mutagens

Share to Neoplasms

Share to Risk Assessment

Share to United States

Source

Identifiers

PMID: 18321622
DOI: 10.1016/j.yrtph.2008.01.015

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence. Graph snapshot: 2026-09-29.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Analysis of in vivo mutation data can inform cancer risk assessment.PMID 18321622Read ↗

Mechanistic data and cancer risk assessment: the need for quantitative molecular endpoints.Semantic proximity Read ↗

Risk estimation from somatic mutation assays.Semantic proximity Read ↗

Mechanistic insights from biomarker studies: somatic mutations and rodent/human comparisons following exposure to a potential carcinogen.Semantic proximity Read ↗

Modernizing Human Cancer Risk Assessment of Therapeutics.Semantic proximity Read ↗

Biomarkers in toxicology and risk assessment: informing critical dose-response relationships.Semantic proximity Read ↗

A Review of the Molecular Mechanisms of Chemically Induced Neoplasia in Rat and Mouse Models in National Toxicology Program Bioassays and Their Relevance to Human CancerSemantic proximity Read ↗

Severity of effect considerations regarding the use of mutation as a toxicological endpoint for risk assessment: A report from the 8th International Workshop on Genotoxicity Testing (IWGT).Semantic proximity Read ↗

Cancer risk assessment at the crossroads: the need to turn to a biological approach.Semantic proximity Read ↗

The potential use of mutation spectra in cancer related genes in genetic toxicology: a statement of a GUM working group.Semantic proximity Read ↗

Mutational spectrometry in animal toxicity testing.Semantic proximity Read ↗

Alternatives to the carcinogenicity bioassay:<i>in silico</i>methods, and the<i>in vitro</i>and<i>in vivo</i>mutagenicity assaysSemantic proximity Read ↗

Genetic Toxicity Assessment: Employing the Best Science for Human Safety Evaluation Part IV:Recommendation of a Working Group of the Gesellschaft fuer Umwelt-Mutationsforschung (GUM) for a Simple and Straightforward Approach to Genotoxicity TestingSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.