Evidence map›Paper›PMID 28439535›Full record

ArticleScience advances2017

A murine preclinical syngeneic transplantation model for breast cancer precision medicine.

Lorenzo Federico, Zechen Chong, Dong Zhang, Daniel J McGrail, Wei Zhao, Kang Jin Jeong, Christopher P Vellano, Zhenlin Ju, Mihai Gagea, Shuying Liu and 11 more

Open access · goldAbstract read
In one paragraph

Article in Science advances, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
0.6field-weighted citation impact, top 31% 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

12 citing papers in PubMed, 17 citations in OpenAlex.

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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

21 authors at 2 institutions in 1 country.

Lorenzo FedericoDepartment of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Zechen ChongDepartment of Bioinformatics and Computational Biology, University of Texas MD Anderson Cancer Center, Houston, TX 77230, USA.
Dong ZhangDepartment of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Daniel J McGrailDepartment of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.ORCID 0000-0002-6669-6069
Wei ZhaoDepartment of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Kang Jin JeongDepartment of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Christopher P VellanoDepartment of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Zhenlin JuDepartment of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Mihai GageaDepartment of Veterinary Medicine and Surgery, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.ORCID 0000-0002-2399-1375
Shuying LiuDepartment of Breast Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, TX 77230, USA.
Shreya MitraDepartment of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.ORCID 0000-0002-6420-8666
Jennifer B DennisonDepartment of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Philip L LorenziDepartment of Bioinformatics and Computational Biology, University of Texas MD Anderson Cancer Center, Houston, TX 77230, USA.ORCID 0000-0003-0385-7774
Robert CardnellDepartment of Thoracic Head and Neck Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Lixia DiaoDepartment of Bioinformatics and Computational Biology, University of Texas MD Anderson Cancer Center, Houston, TX 77230, USA.ORCID 0000-0001-6995-4492
Jing WangDepartment of Bioinformatics and Computational Biology, University of Texas MD Anderson Cancer Center, Houston, TX 77230, USA.
Yiling LuDepartment of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Lauren A ByersDepartment of Thoracic Head and Neck Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Charles M PerouDepartment of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA.ORCID 0000-0001-9827-2247
Shiaw-Yih LinDepartment of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Gordon B MillsDepartment of Systems Biology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.ORCID 0000-0002-0144-9614
The University of Texas MD Anderson Cancer Center · USUniversity of North Carolina at Chapel Hill · US

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Fabien Delerue · 1985 to 2026
$290.8M
Tissue Procurement & PathologyP50CA058223 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI CHARLES M PEROU · 1992 to 2026
$59.3M
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
NCI NIH HHS P30 CA016672NCI NIH HHS P50 CA058223NCI NIH HHS R01 CA148761
6 · The paper itself

Abstract

We previously demonstrated that altered activity of lysophosphatidic acid in murine mammary glands promotes tumorigenesis. We have now established and characterized a heterogeneous collection of mouse-derived syngeneic transplants (MDSTs) as preclinical platforms for the assessment of personalized pharmacological therapies. Detailed molecular and phenotypic analyses revealed that MDSTs are the most heterogeneous group of genetically engineered mouse models (GEMMs) of breast cancer yet observed. Response of MDSTs to trametinib, a mitogen-activated protein kinase (MAPK) kinase inhibitor, correlated with RAS/MAPK signaling activity, as expected from studies in xenografts and clinical trials providing validation of the utility of the model. Sensitivity of MDSTs to talazoparib, a poly(adenosine 5'-diphosphate-ribose) polymerase (PARP) inhibitor, was predicted by PARP1 protein levels and by a new PARP sensitivity predictor (PSP) score developed from integrated analysis of drug sensitivity data of human cell lines. PSP score-based classification of The Cancer Genome Atlas breast cancer suggested that a subset of patients with limited therapeutic options would be expected to benefit from PARP-targeted drugs. These results indicate that MDSTs are useful models for studies of targeted therapies, and propose novel potential biomarkers for identification of breast cancer patients likely to benefit from personalized pharmacological treatments.

Indexed as

AnimalsBiomarkers, TumorFemaleHumansMammary Neoplasms, ExperimentalMAP Kinase Signaling SystemMiceMice, TransgenicNeoplasm ProteinsNeoplasm TransplantationPhthalazinesPoly (ADP-Ribose) Polymerase-1Transplantation, IsogeneicBiomarkers, TumorNeoplasm ProteinsParp1 protein, mousePhthalazinesPoly (ADP-Ribose) Polymerase-1talazoparibanimal modelsBiomarkersbreast cancerlysophospholipidsPARP1personalized medicinetargeted therapy

Identifiers

PMID28439535
PMCPMC5397135
OpenAlexW2605819309

What OpenQuestion holds

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LicenceCC BY-NC
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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.