Evidence map›Paper›PMID 12970722›Full record

ReviewProstate cancer and prostatic diseases2003

Models of metastatic prostate cancer: a transgenic perspective.

S F Winter, A B Cooper, N M Greenberg

Abstract readReview
PubMed Publisher
In one paragraph

Review in Prostate cancer and prostatic diseases, 2003. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. Article
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  6. Review
  7. Review
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  11. Mouse models of prostate cancer.Prostate cancer · 2011
    Article
  12. Survivin is a potential mediator of prostate cancer metastasis.International journal of radiation oncology, biology, physics · 2010
    Article
  13. Review
  14. Article
  15. Article
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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.

S F WinterDepartment of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas 77030, USA.
A B Cooper
N M Greenberg

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTransgenic mouse models are proving to be invaluable in our effort to understand the molecular basis of metastatic prostate cancer (CaP). We review and discuss how current animal models have contributed to our understanding of the metastatic cascade and how transgenic technology is being used to develop the next generation of mouse models. Our goal is to provide a review of the recent advances and provide a framework for further studies. MATERIALS AND

methodsWe performed a MEDLINE search of the literature on CaP metastasis transgenic and animal models.

resultsWe present a summary of the characteristics of nine different animal models of CaP. Each model is unique and provides valuable insight into the molecular mechanisms governing the progression of CaP. Our experience with transgenic models and all the new data from the literature predicts that we will be able to develop genetically engineered mice that accurately mimic the heterogeneity, androgen-independent growth, and metastatic spread seen in clinical disease.

conclusionIn order to elucidate the molecular mechanisms of CaP metastasis, it will be necessary to compare gene and protein expression patterns and biochemical analyses of clinical metastatic disease with data obtained from current models. We will also need to refine our ability to engineer and characterize genetic perturbation models. This type of integrative and iterative approach should facilitate better understanding of the molecular biology of CaP metastases.

Indexed as

Disease Models, AnimalAnimalsAnimals, Genetically ModifiedHumansMaleNeoplasm MetastasisProstateProstatic Neoplasms

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.