Investigating nano-sized tumor-derived extracellular vesicles in enhancing anti-PD-1 immunotherapy.


Journal

Nanoscale
ISSN: 2040-3372
Titre abrégé: Nanoscale
Pays: England
ID NLM: 101525249

Informations de publication

Date de publication:
25 Sep 2024
Historique:
medline: 25 9 2024
pubmed: 25 9 2024
entrez: 25 9 2024
Statut: aheadofprint

Résumé

Anti-PD1 immune checkpoint blockade (ICB) has shown promising results for treating several aggressive cancers, enhancing patient survival rates. The variability in clinical response to anti-PD1 ICB is thought to be driven by patient-specific biology and heterogeneity within the tumor microenvironment. Tumor-derived extracellular vesicles (TDEVs), nano-sized particles released from tumor cells, can modulate the tumor microenvironment, leading to immunosuppression and tumor progression. Hence, TDEVs may contribute to the variability in treatment response and play a crucial role in the failure of anti-PD1 immunotherapy. In this study, we develop a systems biology approach to interrogate the role of TDEVs on the response dynamics for anti-PD1 blockade. Our results suggest that the detection and profiling of TDEVs can help screen patients for anti-PD-1 immunotherapy. Moreover, the results in this study suggest that TDEVs and IL-12 can potentially be liquid biopsy biomarkers to profile patient response to anti-PD1 ICB and tailor patient-specific treatment protocols. Importantly, the methodology is generalizable to other types of cancer immunotherapies. Therefore, the collection of patient-specific liquid biopsy data, and the implementation of those data into the systems biology framework, may offer the opportunity to discover new biomarkers for patient drug screening and enable the continuous monitoring of patient response to treatment and adaptation of patient-specific immunotherapy treatment protocols to overcome therapeutic resistance.

Identifiants

pubmed: 39319505
doi: 10.1039/d4nr00729h
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Auteurs

Hesam Abouali (H)

Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Ontario, Canada. mahla.poudineh@uwaterloo.ca.

Michelle Przedborski (M)

Department of Applied Mathematics, University of Waterloo, Waterloo, Ontario, Canada. kohandel@uwaterloo.ca.

Mohammad Kohandel (M)

Department of Applied Mathematics, University of Waterloo, Waterloo, Ontario, Canada. kohandel@uwaterloo.ca.

Mahla Poudineh (M)

Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Ontario, Canada. mahla.poudineh@uwaterloo.ca.

Classifications MeSH