Evidence map›Paper›PMID 35657155›Full record

ReviewThe Prostate2022

The evolving landscape of prostate cancer somatic mutations.

Kellie Cotter, Mark A Rubin

Open access · hybridAbstract readReview
In one paragraph

Review in The Prostate, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
4.0field-weighted citation impact, top 5% 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

17 citing papers in PubMed, 27 citations in OpenAlex.

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  2. International journal of molecular sciences · 2026
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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.

Kellie CotterDepartment for BioMedical Research, University of Bern, Bern, Switzerland.
Mark A RubinDepartment for BioMedical Research, University of Bern, Bern, Switzerland.ORCID 0000-0002-8321-9950
University of Bern · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe landscape of somatic mutations in prostate cancer (PCa) has quickly evolved over the past years.

resultsThis evolution was in part due to the improved quality and lower cost of genomic sequencing platforms available to an ever-larger group of clinicians and researchers. The result of these efforts is a better understanding of early and late mutations that are enriched or nearly exclusive to treated PCa. There are, however, some important limitations to the current knowledge. The expanding variety of next-generation sequencing (NGS) assays either capture a wide spectrum of mutations but at low coverage or are focused panels that cover a select number of genes, most often cancer-related, at a deep coverage. Both of these approaches have their advantages, but ultimately miss low-frequency mutations or fail to cover the spectrum of potential mutations. Additionally, some alterations, such as the common ETS gene fusions, require a mixture of DNA and RNA analysis to capture the true frequency. Finally, almost all studies rely on bulk PCa tumor samples, which fail to consider tumor heterogeneity. Given all these caveats, the true picture of the somatic landscape of PCa continues to develop. SUMMARY: In this review, the focus will be on how the landscape of mutations evolves during disease progression considering therapy. It will focus on a select group of early and late mutations and utilize SPOP mutations to illustrate recurrent alterations that may have clinical implications.

Indexed as

Prostatic NeoplasmsDisease ProgressionGene FusionHigh-Throughput Nucleotide SequencingHumansMaleMutationNuclear ProteinsRepressor ProteinsNuclear ProteinsRepressor ProteinsSPOP protein, humangene fusionmutationsprostate cancerSPOP

Identifiers

PMID35657155
PMCPMC9328313
OpenAlexW4281715133

What OpenQuestion holds

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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.