Evidence map›Paper›PMID 26380555›Full record

ReviewCancer growth and metastasis2015

Emerging and Evolving Ovarian Cancer Animal Models.

Alexander S Bobbs, Jennifer M Cole, Karen D Cowden Dahl

Open access · hybridAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Cancer growth and metastasis, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
1.7field-weighted citation impact, top 14% 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

33 citing papers in PubMed, 46 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

3 authors at 2 institutions in 1 country.

Alexander S BobbsDepartment of Biochemistry and Molecular Biology, Indiana University School of Medicine-South Bend, South Bend, IN, USA. ; Harper Cancer Research Institute, South Bend, IN, USA.
Jennifer M ColeDepartment of Biochemistry and Molecular Biology, Indiana University School of Medicine-South Bend, South Bend, IN, USA. ; Harper Cancer Research Institute, South Bend, IN, USA.
Karen D Cowden DahlDepartment of Biochemistry and Molecular Biology, Indiana University School of Medicine-South Bend, South Bend, IN, USA. ; Harper Cancer Research Institute, South Bend, IN, USA. ; Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN, USA. ; Indiana University Melvin and Bren Simon Cancer Center, Indianapolis, IN, USA.
Indiana University School of MedicineMike and Josie Harper Cancer Research Institute

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ovarian cancer (OC) is the leading cause of death from a gynecological malignancy in the United States. By the time a woman is diagnosed with OC, the tumor has usually metastasized. Mouse models that are used to recapitulate different aspects of human OC have been evolving for nearly 40 years. Xenograft studies in immunocompromised and immunocompetent mice have enhanced our knowledge of metastasis and immune cell involvement in cancer. Patient-derived xenografts (PDXs) can accurately reflect metastasis, response to therapy, and diverse genetics found in patients. Additionally, multiple genetically engineered mouse models have increased our understanding of possible tissues of origin for OC and what role individual mutations play in establishing ovarian tumors. Many of these models are used to test novel therapeutics. As no single model perfectly copies the human disease, we can use a variety of OC animal models in hypothesis testing that will lead to novel treatment options. The goal of this review is to provide an overview of the utility of different mouse models in the study of OC and their suitability for cancer research.

Indexed as

Adeno-Cregenetically engineered mouse modelshigh-grade serous ovarian cancerovarian cancerpatient-derived xenograftxenograft

Identifiers

PMID26380555
PMCPMC4558890
OpenAlexW2113376755

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.