Evidence map›Paper›PMID 41787470›Full record

ArticleGenome medicine2026

Multifocal cohort analysis unveils cell types associated with regional lymph node seeding in prostate cancer.

Louise de Schaetzen van Brienen, Taewoo Jung, Maarten Larmuseau, Kim Van der Eecken, Marie Van Hecke, Jef Haerinck, Jordy De Coninck, Jan Vanwelkenhuyzen, Nicolaas Lumen, Bram De Laere and 7 more

Abstract read
In one paragraph

Article in Genome medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

17 authors.

Louise de Schaetzen van Brienen *Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium.
Taewoo Jung *Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium.
Maarten Larmuseau *Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium.
Kim Van der EeckenCancer Research Institute Ghent (CRIG), Ghent University, Ghent, Belgium.
Marie Van HeckeDepartment of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium.
Jef HaerinckCancer Research Institute Ghent (CRIG), Ghent University, Ghent, Belgium.
Jordy De ConinckCancer Research Institute Ghent (CRIG), Ghent University, Ghent, Belgium.
Jan VanwelkenhuyzenCancer Research Institute Ghent (CRIG), Ghent University, Ghent, Belgium.
Nicolaas LumenCancer Research Institute Ghent (CRIG), Ghent University, Ghent, Belgium.
Bram De LaereCancer Research Institute Ghent (CRIG), Ghent University, Ghent, Belgium.
Nele De WitteCancer Research Institute Ghent (CRIG), Ghent University, Ghent, Belgium.
Giles MiclotteDepartment of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium.
Sofie VerbekeCancer Research Institute Ghent (CRIG), Ghent University, Ghent, Belgium.
Geert BerxCancer Research Institute Ghent (CRIG), Ghent University, Ghent, Belgium.
Jo Van DorpeCancer Research Institute Ghent (CRIG), Ghent University, Ghent, Belgium.
Piet Ost *Cancer Research Institute Ghent (CRIG), Ghent University, Ghent, Belgium.
Kathleen Marchal *Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium. Kathleen.Marchal@ugent.be.

Funding

Bijzonder Onderzoeksfonds UGent BOF 01J06219Fonds Wetenschappelijk Onderzoek 11H9523NFonds Wetenschappelijk Onderzoek 3F013118Fonds Wetenschappelijk Onderzoek 3G045620Fonds Wetenschappelijk Onderzoek 3S037019Geconcerteerde Onderzoeksacties UGent BOF.FOA.2021.0005.02Kom op tegen Kanker STI.DIV.2020.0017.01Stichting Tegen Kanker STI.STK.2021.0001.01
6 · The paper itself

Abstract

backgroundUnderstanding the molecular features that underlie metastatic prostate cancer (PCa) is essential to develop prognostic markers and improve treatment decisions. However, such studies are hampered by substantial intratumor and interpatient heterogeneity.

methodsTo cope with this heterogeneity, we propose a unique study design that leverages the statistical power of multifocal bulk transcriptome profiling with the resolution of a single-cell analysis to identify processes and cell types associated with regional metastatic lymph node seeding in PCa.

resultsElaborate analysis of these data allowed identifying a metric to distinguish, based on the multifocal expression data between lesions with high and low potential for regional metastatic lymph node seeding. Subsequently comparing the expression profiles of these lesions with respectively high and low metastatic potential identified an aggressiveness signature. Overlaying this signature with single cell data identified proliferative luminal cells, an adipose derived cancer-associated fibroblast (CAF) state and a specific subtype of arterial endothelial cells. Assessing the prognostic value of these cell states in an independent dataset (TCGA-PRAD) confirmed their association with regional metastatic lymph node seeding and progression free survival and unveiled a complementary role for the proliferative luminal cells and the adipose derived CAF state in driving regional metastatic lymph node seeding.

conclusionsBased on our analysis, we hypothesize that lesions with high potential for regional metastatic lymph node seeding are mostly characterized by the presence of highly proliferative luminal cells and a transitioning towards an aggressive adipose derived CAF state. Markers associated with these cell states largely explain the prognostic signal of currently used commercial signatures in PCa, further supporting the role of the identified cell states in driving regional metastatic lymph node seeding and providing an in depth understanding of the success of the currently used commercial signatures.

Indexed as

Lymph NodesProstatic NeoplasmsBiomarkers, TumorCancer-Associated FibroblastsCohort StudiesGene Expression ProfilingGene Expression Regulation, NeoplasticHumansLymphatic MetastasisMalePrognosisTranscriptomeBiomarkers, Tumoradipose-derived stromal stem cellscancer-associated fibroblastscell state transitionmetastatic seedingmultifocal transcriptome profilingprostate cancer

Identifiers

PMID41787470
PMCPMC13072551

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.