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Redefining clinical practice through spatial profiling: a revolution in tissue analysis

Abstract:
Spatial biology, which combines molecular biology and advanced imaging, enhances our understanding of tissue cellular organisation. Despite its potential, spatial omics encounters challenges related to data complexity, computational requirements and standardisation of analysis. In clinical applications, spatial omics has the potential to revolutionise biomarker discovery, disease stratification and personalised treatments. It can identify disease-specific cell patterns, and could help risk stratify patients for clinical trials and disease-appropriate therapies. Although there are challenges in adopting it in clinical practice, spatial omics has the potential to significantly enhance patient outcomes. In this paper, we discuss the recent evolution of spatial biology, and its potential for improving our tissue level understanding and treatment of disease, to help advance precision and effectiveness in healthcare interventions.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1308/rcsann.2023.0091

Authors

More by this author
Institution:
University of Oxford
Division:
MSD
Department:
NDM
Sub department:
Centre for Human Genetics
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
NDM
Sub department:
Centre for Human Genetics
Role:
Author
ORCID:
0000-0003-1476-6982


More from this funder
Funder identifier:
https://ror.org/029chgv08
Grant:
090532/Z/09/Z
More from this funder
Funder identifier:
https://ror.org/054225q67
Grant:
DRCNPG-Jun22\100002
A26825 and A28223


Publisher:
Royal College of Surgeons of England
Journal:
Annals of The Royal College of Surgeons of England More from this journal
Volume:
106
Issue:
4
Pages:
305-312
Place of publication:
England
Publication date:
2024-04-01
Acceptance date:
2023-10-25
DOI:
EISSN:
1478-7083
ISSN:
0035-8843
Pmid:
38555868


Language:
English
Keywords:
Pubs id:
1987988
Local pid:
pubs:1987988
Deposit date:
2025-04-07
ARK identifier:

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