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

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 can...

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Autores principales: Figiel, Sandy, Yin, Wencheng, Doultsinos, Dimitrios, Erickson, Andrew, Poulose, Ninu, Singh, Reema, Magnussen, Anette, Anbarasan, Thineskrishna, Teague, Renuka, He, Mengxiao, Lundeberg, Joakim, Loda, Massimo, Verrill, Clare, Colling, Richard, Gill, Pelvender S., Bryant, Richard J., Hamdy, Freddie C., Woodcock, Dan J., Mills, Ian G., Cussenot, Olivier, Lamb, Alastair D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10546768/
https://www.ncbi.nlm.nih.gov/pubmed/37789377
http://dx.doi.org/10.1186/s12943-023-01863-2
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author Figiel, Sandy
Yin, Wencheng
Doultsinos, Dimitrios
Erickson, Andrew
Poulose, Ninu
Singh, Reema
Magnussen, Anette
Anbarasan, Thineskrishna
Teague, Renuka
He, Mengxiao
Lundeberg, Joakim
Loda, Massimo
Verrill, Clare
Colling, Richard
Gill, Pelvender S.
Bryant, Richard J.
Hamdy, Freddie C.
Woodcock, Dan J.
Mills, Ian G.
Cussenot, Olivier
Lamb, Alastair D.
author_facet Figiel, Sandy
Yin, Wencheng
Doultsinos, Dimitrios
Erickson, Andrew
Poulose, Ninu
Singh, Reema
Magnussen, Anette
Anbarasan, Thineskrishna
Teague, Renuka
He, Mengxiao
Lundeberg, Joakim
Loda, Massimo
Verrill, Clare
Colling, Richard
Gill, Pelvender S.
Bryant, Richard J.
Hamdy, Freddie C.
Woodcock, Dan J.
Mills, Ian G.
Cussenot, Olivier
Lamb, Alastair D.
author_sort Figiel, Sandy
collection PubMed
description 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12943-023-01863-2.
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spelling pubmed-105467682023-10-04 Spatial transcriptomic analysis of virtual prostate biopsy reveals confounding effect of tissue heterogeneity on genomic signatures Figiel, Sandy Yin, Wencheng Doultsinos, Dimitrios Erickson, Andrew Poulose, Ninu Singh, Reema Magnussen, Anette Anbarasan, Thineskrishna Teague, Renuka He, Mengxiao Lundeberg, Joakim Loda, Massimo Verrill, Clare Colling, Richard Gill, Pelvender S. Bryant, Richard J. Hamdy, Freddie C. Woodcock, Dan J. Mills, Ian G. Cussenot, Olivier Lamb, Alastair D. Mol Cancer Correspondence 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12943-023-01863-2. BioMed Central 2023-10-03 /pmc/articles/PMC10546768/ /pubmed/37789377 http://dx.doi.org/10.1186/s12943-023-01863-2 Text en © Crown 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Correspondence
Figiel, Sandy
Yin, Wencheng
Doultsinos, Dimitrios
Erickson, Andrew
Poulose, Ninu
Singh, Reema
Magnussen, Anette
Anbarasan, Thineskrishna
Teague, Renuka
He, Mengxiao
Lundeberg, Joakim
Loda, Massimo
Verrill, Clare
Colling, Richard
Gill, Pelvender S.
Bryant, Richard J.
Hamdy, Freddie C.
Woodcock, Dan J.
Mills, Ian G.
Cussenot, Olivier
Lamb, Alastair D.
Spatial transcriptomic analysis of virtual prostate biopsy reveals confounding effect of tissue heterogeneity on genomic signatures
title Spatial transcriptomic analysis of virtual prostate biopsy reveals confounding effect of tissue heterogeneity on genomic signatures
title_full Spatial transcriptomic analysis of virtual prostate biopsy reveals confounding effect of tissue heterogeneity on genomic signatures
title_fullStr Spatial transcriptomic analysis of virtual prostate biopsy reveals confounding effect of tissue heterogeneity on genomic signatures
title_full_unstemmed Spatial transcriptomic analysis of virtual prostate biopsy reveals confounding effect of tissue heterogeneity on genomic signatures
title_short Spatial transcriptomic analysis of virtual prostate biopsy reveals confounding effect of tissue heterogeneity on genomic signatures
title_sort spatial transcriptomic analysis of virtual prostate biopsy reveals confounding effect of tissue heterogeneity on genomic signatures
topic Correspondence
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10546768/
https://www.ncbi.nlm.nih.gov/pubmed/37789377
http://dx.doi.org/10.1186/s12943-023-01863-2
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