Evidence map›Paper›PMID 38654435›Full record

ArticleThe Prostate2024

Molecular analysis of archival diagnostic prostate cancer biopsies identifies genomic similarities in cases with progression post-radiotherapy, and those with de novo metastatic disease.

Philip Vincent Charlton, Dawn O'Reilly, Yiannis Philippou, Srinivasa Rao Rao, Alastair David Gordon Lamb, Ian Geoffrey Mills, Geoff Stuart Higgins, Freddie Charles Hamdy, Clare Verrill, Francesca Meteora Buffa and 1 more

Open access · hybridAbstract read
In one paragraph

Article in The Prostate, 2024. 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
0.4field-weighted citation impact, top 38% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  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

11 authors at 2 institutions in 1 country.

Philip Vincent CharltonDepartment of Oncology, University of Oxford, Oxford, UK.
Dawn O'ReillyDepartment of Oncology, University of Oxford, Oxford, UK.
Yiannis PhilippouDepartment of Urology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
Srinivasa Rao RaoNuffield Department of Surgical Sciences, University of Oxford, Oxford, UK.
Alastair David Gordon LambDepartment of Urology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
Ian Geoffrey MillsNuffield Department of Surgical Sciences, University of Oxford, Oxford, UK.ORCID 0000-0001-5347-5083
Geoff Stuart HigginsDepartment of Oncology, University of Oxford, Oxford, UK.
Freddie Charles HamdyDepartment of Urology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
Clare VerrillNuffield Department of Surgical Sciences, University of Oxford, Oxford, UK.
Francesca Meteora BuffaDepartment of Oncology, University of Oxford, Oxford, UK.
Richard John BryantDepartment of Urology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.ORCID 0000-0002-8330-9251
University of Oxford · GBOxford University Hospitals NHS Trust · GB

Funding

Cancer Research UK 28736Cancer Research UK C39297/A22748Cancer Research UK C57899/A25812Cancer Research UK Development FundCancer Research UK DPhil studentshipCancer Research UK RadNet Oxford Center C6078/A28736CRUK Oxford Cancer CenterEuropean Research Council (ERC) Consolidator Award MICROC:772970John Black Charitable FoundationNIHR Oxford Biomedical Research CenterOxford NIHR BRC Surgical Innovation & Evaluation themeProstate Cancer UKRosetrees TrustUrology Foundation, John Black Charitable Foundation, Rosetrees Trust, Prostate Cancer UK, and NIHR-HTA
6 · The paper itself

Abstract

backgroundIt is important to identify molecular features that improve prostate cancer (PCa) risk stratification before radical treatment with curative intent. Molecular analysis of historical diagnostic formalin-fixed paraffin-embedded (FFPE) prostate biopsies from cohorts with post-radiotherapy (RT) long-term clinical follow-up has been limited. Utilizing parallel sequencing modalities, we performed a proof-of-principle sequencing analysis of historical diagnostic FFPE prostate biopsies. We compared patients with (i) stable PCa (sPCa) postprimary or salvage RT, (ii) progressing PCa (pPCa) post-RT, and (iii) de novo metastatic PCa (mPCa).

methodsA cohort of 19 patients with diagnostic prostate biopsies (n = 6 sPCa, n = 5 pPCa, n = 8 mPCa) and mean 4 years 10 months follow-up (diagnosed 2009-2016) underwent nucleic acid extraction from demarcated malignancy. Samples underwent 3'RNA sequencing (3'RNAseq) (n = 19), nanoString analysis (n = 12), and Illumina 850k methylation (n = 8) sequencing. Bioinformatic analysis was performed to coherently identify differentially expressed genes and methylated genomic regions (MGRs).

resultsEighteen of 19 samples provided useable 3'RNAseq data. Principal component analysis (PCA) demonstrated similar expression profiles between pPCa and mPCa cases, versus sPCa. Coherently differentially methylated probes between these groups identified ~600 differentially MGRs. The top 50 genes with increased expression in pPCa patients were associated with reduced progression-free survival post-RT (p < 0.0001) in an external cohort.

conclusions3'RNAseq, nanoString and 850k-methylation analyses are each achievable from historical FFPE diagnostic pretreatment prostate biopsies, unlocking the potential to utilize large cohorts of historic clinical samples. Profiling similarities between individuals with pPCa and mPCa suggests biological similarities and historical radiological staging limitations, which warrant further investigation.

Indexed as

Disease ProgressionProstatic NeoplasmsAgedBiopsyCohort StudiesGenomicsHumansMaleMiddle AgedNeoplasm MetastasisProstatediagnostic biopsiesmetastasismolecular analysisprostate cancerradiotherapy

Identifiers

PMID38654435
PMCPMC11253896
OpenAlexW4395079502

What Socratic 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 Socratic graph.