Quantitative systems pharmacology modeling of macrophage-targeted therapy combined with PD-L1 inhibition in advanced NSCLC.
Humans
Carcinoma, Non-Small-Cell Lung
/ drug therapy
Lung Neoplasms
/ drug therapy
Immune Checkpoint Inhibitors
/ pharmacology
B7-H1 Antigen
/ antagonists & inhibitors
Antineoplastic Combined Chemotherapy Protocols
/ pharmacology
CD47 Antigen
/ antagonists & inhibitors
Macrophages
/ metabolism
Receptors, CCR2
/ antagonists & inhibitors
Network Pharmacology
/ methods
Computer Simulation
Models, Biological
Tumor-Associated Macrophages
/ drug effects
Journal
Clinical and translational science
ISSN: 1752-8062
Titre abrégé: Clin Transl Sci
Pays: United States
ID NLM: 101474067
Informations de publication
Date de publication:
Jun 2024
Jun 2024
Historique:
revised:
01
03
2024
received:
08
11
2023
accepted:
12
04
2024
medline:
30
5
2024
pubmed:
30
5
2024
entrez:
30
5
2024
Statut:
ppublish
Résumé
Immune checkpoint inhibitors remained the standard-of-care treatment for advanced non-small cell lung cancer (NSCLC) for the past decade. In unselected patients, anti-PD-(L)1 monotherapy achieved an overall response rate of about 20%. In this analysis, we developed a pharmacokinetic and pharmacodynamic module for our previously calibrated quantitative systems pharmacology model (QSP) to simulate the effectiveness of macrophage-targeted therapies in combination with PD-L1 inhibition in advanced NSCLC. By conducting in silico clinical trials, the model confirmed that anti-CD47 treatment is not an optimal option of second- and later-line treatment for advanced NSCLC resistant to PD-(L)1 blockade. Furthermore, the model predicted that inhibition of macrophage recruitment, such as using CCR2 inhibitors, can potentially improve tumor size reduction when combined with anti-PD-(L)1 therapy, especially in patients who are likely to respond to anti-PD-(L)1 monotherapy and those with a high level of tumor-associated macrophages. Here, we demonstrate the application of the QSP platform on predicting the effectiveness of novel drug combinations involving immune checkpoint inhibitors based on preclinical or early-stage clinical trial data.
Substances chimiques
Immune Checkpoint Inhibitors
0
B7-H1 Antigen
0
CD274 protein, human
0
CD47 Antigen
0
Receptors, CCR2
0
CD47 protein, human
0
CCR2 protein, human
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
e13811Subventions
Organisme : NIH HHS
ID : R01CA138264
Pays : United States
Informations de copyright
© 2024 The Authors. Clinical and Translational Science published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.
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