Evidence map›Paper›PMID 37789377›Full record

ArticleMolecular cancer2023

Spatial transcriptomic analysis of virtual prostate biopsy reveals confounding effect of tissue heterogeneity on genomic signatures.

Sandy Figiel, Wencheng Yin, Dimitrios Doultsinos, Andrew Erickson, Ninu Poulose, Reema Singh, Anette Magnussen, Thineskrishna Anbarasan, Renuka Teague, Mengxiao He and 11 more

Abstract readLetter
PubMed Full text at PMC Publisher
In one paragraph

Article in Molecular cancer, 2023. 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
–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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Review
  6. Article
  7. Article
  8. Imaging genomics of cancer: a bibliometric analysis and review.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025
    Review
  9. Article
  10. Article
  11. Article
  12. 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

21 authors.

Sandy FigielNuffield Department of Surgical Sciences, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK.
Wencheng YinNuffield Department of Surgical Sciences, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK.
Dimitrios DoultsinosNuffield Department of Surgical Sciences, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK.
Andrew EricksonNuffield Department of Surgical Sciences, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK.
Ninu PouloseNuffield Department of Surgical Sciences, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK.
Reema SinghNuffield Department of Surgical Sciences, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK.
Anette MagnussenNuffield Department of Surgical Sciences, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK.
Thineskrishna AnbarasanNuffield Department of Surgical Sciences, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK.
Renuka TeagueNuffield Department of Surgical Sciences, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK.
Mengxiao HeScience for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Solna, Sweden.
Joakim LundebergScience for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Solna, Sweden.
Massimo LodaNuffield Department of Surgical Sciences, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK.
Clare VerrillNuffield Department of Surgical Sciences, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK.
Richard CollingNuffield Department of Surgical Sciences, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK.
Pelvender S GillNuffield Department of Surgical Sciences, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK.
Richard J BryantNuffield Department of Surgical Sciences, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK.
Freddie C HamdyNuffield Department of Surgical Sciences, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK.
Dan J WoodcockNuffield Department of Surgical Sciences, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK.
Ian G MillsNuffield Department of Surgical Sciences, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK.
Olivier CussenotNuffield Department of Surgical Sciences, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK.
Alastair D LambNuffield Department of Surgical Sciences, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK. alastair.lamb@nds.ox.ac.uk.

Funding

Cancer Research UK 25812Cancer Research UK C57899/A25812Department of HealthWellcome Trust
6 · The paper itself

Abstract

Genetic signatures have added a molecular dimension to prognostics and therapeutic decision-making. However, tumour heterogeneity in prostate cancer and current sampling methods could confound accurate assessment. Based on previously published spatial transcriptomic data from multifocal prostate cancer, we created virtual biopsy models that mimic conventional biopsy placement and core size. We then analysed the gene expression of different prognostic signatures (OncotypeDx®, Decipher®, Prostadiag®) using a step-wise approach with increasing resolution from pseudo-bulk analysis of the whole biopsy, to differentiation by tissue subtype (benign, stroma, tumour), followed by distinct tumour grade and finally clonal resolution. The gene expression profile of virtual tumour biopsies revealed clear differences between grade groups and tumour clones, compared to a benign control, which were not reflected in bulk analyses. This suggests that bulk analyses of whole biopsies or tumour-only areas, as used in clinical practice, may provide an inaccurate assessment of gene profiles. The type of tissue, the grade of the tumour and the clonal composition all influence the gene expression in a biopsy. Clinical decision making based on biopsy genomics should be made with caution while we await more precise targeting and cost-effective spatial analyses.

Indexed as

ProstateProstatic NeoplasmsBiopsyGenomicsHumansMaleTranscriptomePrognostic genetic signaturesProstate cancerSpatial transcriptomicsVirtual biopsy

Identifiers

PMID37789377
PMCPMC10546768

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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.