Evidence map›Paper›PMID 34147640›Full record

ReviewSeminars in cancer biology2022

Prostate cancer cell heterogeneity and plasticity: Insights from studies of genetically-engineered mouse models.

Weiping Li, Michael M Shen

Open access · greenAbstract readReview
In one paragraph

Review in Seminars in cancer biology, 2022. 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
1.8field-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

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

2 authors at 1 institution in 1 country.

Weiping LiDepartments of Medicine, Genetics and Development, Urology, and Systems Biology, Herbert Irving Comprehensive Cancer Center, Columbia University College of Physicians and Surgeons, New York, NY 10032 USA.
Michael M ShenDepartments of Medicine, Genetics and Development, Urology, and Systems Biology, Herbert Irving Comprehensive Cancer Center, Columbia University College of Physicians and Surgeons, New York, NY 10032 USA. Electronic address: mshen@columbia.edu.
Columbia University · US

Funding

Investigating lineage plasticity in castration-resistant prostate cancerR01CA251527 · NCI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI SHEN, MICHAEL M. · 2020 to 2024
$2.1M
Analysis of epithelial heterogeneity in prostate development and cancerR01CA238005 · NCI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI SHEN, MICHAEL M. · 2019 to 2023
$2.1M
NCI NIH HHS R01 CA238005NCI NIH HHS R01 CA251527
6 · The paper itself

Abstract

Although prostate adenocarcinoma lacks distinguishable histopathological subtypes, prostate cancer displays significant inter- and intratumor heterogeneity at the molecular level and with respect to disease prognosis and treatment response. In principle, understanding the basis for prostate cancer heterogeneity can help distinguish aggressive from indolent disease, and help overcome castration-resistance in advanced prostate cancer. In this review, we will discuss recent advances in understanding the cell types of origin, putative cancer stem cells, and tumor plasticity in prostate cancer, focusing on insights from studies of genetically engineered mouse models (GEMMs). We will also outline future directions for investigating tumor heterogeneity using mouse models of prostate cancer.

Indexed as

ProstateProstatic NeoplasmsAnimalsDisease Models, AnimalHumansMaleMiceNeoplastic Stem CellsCancer stem cellCastration-resistanceCell of originGenetically engineered mouse modelLineage plasticityTumor heterogeneity

Identifiers

PMID34147640
PMCPMC8683576
OpenAlexW3174006290

What OpenQuestion holds

Textmetadata
LicenceTDM
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.