The in situ transcriptomic landscape of breast tumour-associated and normal adjacent endothelial cells.

Abnormal vasculature Spatial profiling Triple Negative Breast Cancer Tumour endothelial cells Whole transcriptome analyses

Journal

Biochimica et biophysica acta. Molecular basis of disease
ISSN: 1879-260X
Titre abrégé: Biochim Biophys Acta Mol Basis Dis
Pays: Netherlands
ID NLM: 101731730

Informations de publication

Date de publication:
06 Dec 2023
Historique:
received: 09 08 2023
revised: 17 11 2023
accepted: 03 12 2023
pubmed: 8 12 2023
medline: 8 12 2023
entrez: 7 12 2023
Statut: aheadofprint

Résumé

Triple Negative Breast Cancer (TNBC) is associated with increased angiogenesis, which is known to aid tumour growth and metastasis. Anti-angiogenic therapies that have been developed to target this feature have mostly generated disappointing clinical results. Further research into targeted approaches is limited by a lack of understanding of the in situ molecular profile of tumour-associated vasculature. In this study, we aimed to understand the differences in the molecular profiles of tumour endothelial cells vs normal-adjacent endothelial cells in TNBC tissues. We have applied unbiased whole transcriptome spatial profiling of in situ gene expressions of endothelial cells localized in full-face patient TNBC tissues (n = 4) and normal-adjacent regions of the same patient breast tissues. Our comparative analysis revealed that 2412 genes were differentially expressed (p Overall, the results revealed unique molecular profiles and signalling pathways of tumour-associated vasculature, which is a critical step towards larger cohort studies investigating potential targets for TNBC prognosis and anti-angiogenic treatments.

Sections du résumé

BACKGROUND AND AIMS OBJECTIVE
Triple Negative Breast Cancer (TNBC) is associated with increased angiogenesis, which is known to aid tumour growth and metastasis. Anti-angiogenic therapies that have been developed to target this feature have mostly generated disappointing clinical results. Further research into targeted approaches is limited by a lack of understanding of the in situ molecular profile of tumour-associated vasculature. In this study, we aimed to understand the differences in the molecular profiles of tumour endothelial cells vs normal-adjacent endothelial cells in TNBC tissues.
METHOD METHODS
We have applied unbiased whole transcriptome spatial profiling of in situ gene expressions of endothelial cells localized in full-face patient TNBC tissues (n = 4) and normal-adjacent regions of the same patient breast tissues.
RESULTS RESULTS
Our comparative analysis revealed that 2412 genes were differentially expressed (p
CONCLUSION CONCLUSIONS
Overall, the results revealed unique molecular profiles and signalling pathways of tumour-associated vasculature, which is a critical step towards larger cohort studies investigating potential targets for TNBC prognosis and anti-angiogenic treatments.

Identifiants

DOI: 10.1016/j.bbadis.2023.166985 PMID: 38061601
pubmed: 38061601
pii: S0925-4439(23)00351-4
doi: 10.1016/j.bbadis.2023.166985
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

166985

Informations de copyright

Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Akhilandeshwari Ravichandran (A)

School of Mechanical, Medical and Process Engineering, Faculty of Engineering, Queensland University of Technology, Kelvin Grove, QLD 4059, Australia; Centre for Biomedical Technologies, Queensland University of Technology (QUT), Brisbane, QLD 4059, Australia. Electronic address: akhilandeshwari.ravichandran@qut.edu.au.

James Monkman (J)

Frazer Institute, Faculty of Medicine, The University of Queensland, Woolloongabba, QLD 4102, Australia.

Ahmed M Mehdi (AM)

Frazer Institute, Faculty of Medicine, The University of Queensland, Woolloongabba, QLD 4102, Australia; Queensland Cyber Infrastructure Foundation Ltd, Facility for Advanced Bioinformatics, Brisbane, QLD 4072, Australia.

Tony Blick (T)

Frazer Institute, Faculty of Medicine, The University of Queensland, Woolloongabba, QLD 4102, Australia.

Cameron Snell (C)

Peter MacCallum Cancer Centre, Melbourne, VIC 3000, Australia; Mater Pathology, Mater Hospital Brisbane, Mater Health Services, Brisbane, QLD 4101, Australia.

Arutha Kulasinghe (A)

Frazer Institute, Faculty of Medicine, The University of Queensland, Woolloongabba, QLD 4102, Australia. Electronic address: arutha.kulasinghe@uq.edu.au.

Laura J Bray (LJ)

School of Mechanical, Medical and Process Engineering, Faculty of Engineering, Queensland University of Technology, Kelvin Grove, QLD 4059, Australia; Centre for Biomedical Technologies, Queensland University of Technology (QUT), Brisbane, QLD 4059, Australia; Centre for the Personalised Analysis of Cancers, Queensland University of Technology, Translational Research Institute, QLD 4102, Australia; Australian Research Council (ARC) Training Centre for Cell and Tissue Engineering Technologies, Queensland University of Technology (QUT), Brisbane, QLD 4000, Australia. Electronic address: laura.bray@qut.edu.au.

Classifications MeSH