Evidence map›Paper›PMID 24220145›Full record

ArticleGenome biology2013

Transcriptomic classification of genetically engineered mouse models of breast cancer identifies human subtype counterparts.

Adam D Pfefferle, Jason I Herschkowitz, Jerry Usary, Joshua Chuck Harrell, Benjamin T Spike, Jessica R Adams, Maria I Torres-Arzayus, Myles Brown, Sean E Egan, Geoffrey M Wahl and 2 more

Abstract read
In one paragraph

Article in Genome biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 165 papers.

0numbers the graph read from it
0cells of the map it votes in
165citing 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

165 citing papers in PubMed.

  1. A Co-clinical Trial of Exercise Therapy in Breast Cancer Prevention.Clinical cancer research : an official journal of the American Association for Cancer Research · 2025
    Trial
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  7. RUNX1-deficiency drives immune-active ERbioRxiv : the preprint server for biology · 2026
    Article
  8. Review
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  20. Leveraging preclinical models of metastatic breast cancer.Biochimica et biophysica acta. Reviews on cancer · 2024
    Review

105 more citing papers are in PubMed but not listed here.

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

12 authors.

Adam D Pfefferle
Jason I Herschkowitz
Jerry Usary
Joshua Chuck Harrell
Benjamin T Spike
Jessica R Adams
Maria I Torres-Arzayus
Myles Brown
Sean E Egan
Geoffrey M Wahl
Jeffrey M Rosen
Charles M Perou

Funding

Virology Research Program (Program 4)P30CA016086 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Deborah F. Tate · 1985 to 2026
$201.5M
Tissue Procurement & PathologyP50CA058223 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI KATHERINE A. HOADLEY · 1992 to 2026
$59.3M
Use of Organotypic and Mammary Gland Models to Investigate the Outcomes of ClonalP01CA080111 · NCI · WHITEHEAD INSTITUTE FOR BIOMEDICAL RES · PI DILLON, DEBORAH · 1999 to 2018
$36.0M
Therapeutic Targeting of Breast Cancer Tumor Initiating CellsR01CA148761 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI PEROU, CHARLES M, ROSEN, JEFFREY MARK · 2010 to 2025
$6.5M
ENVIRONMENTAL PATHOLOGYT32ES007017 · NIEHS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI KAUFMAN, DAVID G. · 1985 to 2011
$5.1M
Conserved Biology of Tumor and Microenvironment in Breast Cancer ProgressionR01CA138255 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI PEROU, CHARLES M, TROESTER, MELISSA A. · 2008 to 2012
$2.4M
NCI NIH HHS P01 CA080111NCI NIH HHS P30 CA016086NCI NIH HHS P50 CA058223NCI NIH HHS P50-CA58223NCI NIH HHS R01-CA138255NCI NIH HHS R01-CA148761NIEHS NIH HHS T32-ES07017
6 · The paper itself

Abstract

backgroundHuman breast cancer is a heterogeneous disease consisting of multiple molecular subtypes. Genetically engineered mouse models are a useful resource for studying mammary cancers in vivo under genetically controlled and immune competent conditions. Identifying murine models with conserved human tumor features will facilitate etiology determinations, highlight the effects of mutations on pathway activation, and should improve preclinical drug testing.

resultsTranscriptomic profiles of 27 murine models of mammary carcinoma and normal mammary tissue were determined using gene expression microarrays. Hierarchical clustering analysis identified 17 distinct murine subtypes. Cross-species analyses using three independent human breast cancer datasets identified eight murine classes that resemble specific human breast cancer subtypes. Multiple models were associated with human basal-like tumors including TgC3(1)-Tag, TgWAP-Myc and Trp53-/-. Interestingly, the TgWAPCre-Etv6 model mimicked the HER2-enriched subtype, a group of human tumors without a murine counterpart in previous comparative studies. Gene signature analysis identified hundreds of commonly expressed pathway signatures between linked mouse and human subtypes, highlighting potentially common genetic drivers of tumorigenesis.

conclusionsThis study of murine models of breast carcinoma encompasses the largest comprehensive genomic dataset to date to identify human-to-mouse disease subtype counterparts. Our approach illustrates the value of comparisons between species to identify murine models that faithfully mimic the human condition and indicates that multiple genetically engineered mouse models are needed to represent the diversity of human breast cancers. The reported trans-species associations should guide model selection during preclinical study design to ensure appropriate representatives of human disease subtypes are used.

Indexed as

Disease Models, AnimalGene Expression Regulation, NeoplasticAnimalsBreast NeoplasmsCarcinogenesisCluster AnalysisFemaleHumansMiceMice, TransgenicOligonucleotide Array Sequence AnalysisSequence Analysis, DNATranscriptome

Identifiers

PMID24220145
PMCPMC4053990

What OpenQuestion holds

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Registered trials

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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.