Evidence map›Paper›PMID 40799151›Full record

ArticleEnvironmental and molecular mutagenesis2025

Tissue and Sex-Specific Performance of a Cancer Driver Based Biomarker in rasH2-Tg Mice.

Kelly L Harris, Jennifer B Faske, Binsheng Gong, Barbara L Parsons

Abstract read
In one paragraph

Article in Environmental and molecular mutagenesis, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. 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.

Kelly L HarrisDivision of Biochemical Toxicology, U.S. Food and Drug Administration, National Center for Toxicological Research, Jefferson, Arkansas, USA.ORCID 0000-0002-5134-4829
Jennifer B FaskeDivision of Genetic and Molecular Toxicology, U.S. Food and Drug Administration, National Center for Toxicological Research, Jefferson, Arkansas, USA.
Binsheng GongU.S. Food and Drug Administration, National Center for Toxicological Research, Division of Bioinformatics and Biostatistics, Jefferson, Arkansas, USA.
Barbara L ParsonsDivision of Genetic and Molecular Toxicology, U.S. Food and Drug Administration, National Center for Toxicological Research, Jefferson, Arkansas, USA.ORCID 0000-0002-3005-2552

Funding

Intramural FDA HHS FD999999U.S. Food and Drug Administration (FDA) National Center for Toxicological Research (NCTR)
6 · The paper itself

Abstract

The ability to predict rodent lifetime tumor responses from short-term exposures and a scientific basis for rodent to human extrapolation are unmet needs in cancer risk assessment. To address these needs, quantitation of cancer driver mutations (CDMs) was integrated with an error-corrected, next generation sequencing (NGS) approach. The method developed, CarcSeq, involves performing multiple, high-fidelity PCR reactions to amplify hotspot CDM-containing target sequences, tagging amplicons with 9 base unique identifier sequences, and constructing libraries from the pooled amplicons. Single-strand consensus sequences were constructed for error correction. A metric of variability in CDM levels, median absolute deviation in mutant fraction (MAD), is being developed as a biomarker of clonal expansion. This study leveraged the sex-related difference in spontaneous lung tumor development in the rasH2-Tg mouse model to validate and refine the CarcSeq approach for assessing clonal expansion. Significantly greater MAD was observed in male as compared to female rasH2-Tg mice, along with more recurrent mutations and a higher proportion of mutations conferring a potentially selectable phenotype in males, consistent with the greater propensity for spontaneous lung tumorigenesis in males. In the analysis of MAD, use of a sex-specific median and classification of lung-specific drivers based on a COSMIC-reported mutation frequency ≥ 5% performed better than use of the overall median MF and classification based on COSMIC's top ranked lung neoplasia genes. Thus, this study provides further validation of the CarcSeq/MAD biomarker approach and technical insight into best practices in evaluating clonal expansion based on measurement of cancer driver gene mutations.

Indexed as

Biomarkers, TumorLung NeoplasmsAnimalsFemaleHigh-Throughput Nucleotide SequencingMaleMiceMice, TransgenicMutationSex FactorsBiomarkers, Tumorcancer driver mutationcancer risk assessmentcarcinogenicity testingclonal expansionpredictive toxicologyregulatory sciences

Identifiers

PMID40799151
PMCPMC12459003

What Socratic holds

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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 Socratic graph.