CombPDX: a unified statistical framework for evaluating drug synergism in patient-derived xenografts.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
29 07 2022
29 07 2022
Historique:
received:
18
03
2022
accepted:
18
07
2022
entrez:
29
7
2022
pubmed:
30
7
2022
medline:
3
8
2022
Statut:
epublish
Résumé
Anticancer combination therapy has been developed to increase efficacy by enhancing synergy. Patient-derived xenografts (PDXs) have emerged as reliable preclinical models to develop effective treatments in translational cancer research. However, most PDX combination study designs focus on single dose levels, and dose-response surface models are not appropriate for testing synergism. We propose a comprehensive statistical framework to assess joint action of drug combinations from PDX tumor growth curve data. We provide various metrics and robust statistical inference procedures that locally (at a fixed time) and globally (across time) access combination effects under classical drug interaction models. Integrating genomic and pharmacological profiles in non-small-cell lung cancer (NSCLC), we have shown the utilities of combPDX in discovering effective therapeutic combinations and relevant biological mechanisms. We provide an interactive web server, combPDX ( https://licaih.shinyapps.io/CombPDX/ ), to analyze PDX tumor growth curve data and perform power analyses.
Identifiants
pubmed: 35906256
doi: 10.1038/s41598-022-16933-6
pii: 10.1038/s41598-022-16933-6
pmc: PMC9338066
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
12984Subventions
Organisme : NCI NIH HHS
ID : U54 CA224065
Pays : United States
Organisme : NIH HHS
ID : 2P50CA070907-21A1
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA244845
Pays : United States
Organisme : NCI NIH HHS
ID : P01 CA078778
Pays : United States
Organisme : NCI NIH HHS
ID : P50 CA070907
Pays : United States
Organisme : NIH HHS
ID : 5U54CA224065-04
Pays : United States
Informations de copyright
© 2022. The Author(s).
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