Evidence map›Paper›PMID 37686488›Full record

ReviewCancers2023

Pre-Clinical Models to Study Human Prostate Cancer.

Martin K Thomsen, Morten Busk

Open access · goldAbstract readReview
In one paragraph

Review in Cancers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.3field-weighted citation impact, top 11% 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

8 citing papers in PubMed, 9 citations in OpenAlex.

  1. 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

2 authors at 2 institutions in 1 country.

Martin K ThomsenDepartment of Biomedicine, Aarhus University, 8000 Aarhus, Denmark.ORCID 0000-0002-5055-7531
Morten BuskDepartment of Experimental Clinical Oncology, Aarhus University Hospital, 8200 Aarhus, Denmark.
Aarhus University · DKAarhus University Hospital · DK

Funding

Danish Cancer Society R204-A12490Danish Cancer Society R231-A13828Danish Cancer Society R231-A14066
6 · The paper itself

Abstract

Prostate cancer is a common cancer among men and typically progresses slowly for several decades before becoming aggressive and spreading to other organs, leaving few treatment options. While large animals have been studied, the dog's prostate is anatomically similar to humans and has been used to study spontaneous prostate cancer. However, most research currently focuses on the mouse as a model organism due to the ability to genetically modify their prostatic tissues for molecular analysis. One milestone in this research was the identification of the prostate-specific promoter Probasin, which allowed for the prostate-specific expression of transgenes. This has led to the generation of mice with aggressive prostatic tumors through overexpression of the SV40 oncogene. The Probasin promoter is also used to drive Cre expression and has allowed researchers to generate prostate-specific loss-of-function studies. Another landmark moment in the process of modeling prostate cancer in mice was the orthoptic delivery of viral particles. This technology allows the selective overexpression of oncogenes from lentivirus or the use of CRISPR to generate complex loss-of-function studies. These genetically modified models are complemented by classical xenografts of human prostate tumor cells in immune-deficient mice. Overall, pre-clinical models have provided a portfolio of model systems to study and address complex mechanisms in prostate cancer for improved treatment options. This review will focus on the advances in each technique.

Indexed as

adenocarcinomaallograftsandrogenclustered regularly interspaced short palindromic repeatsmiceprostateprostatic intraepithelial neoplasiaprostatic neoplasmstransgenestumor suppressor

Identifiers

PMID37686488
PMCPMC10486646
OpenAlexW4386091806

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.