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The Use of Survival Dose-Rate Dependencies as Theoretical Discrimination Criteria for In-Silico Dynamic Radiobiological Models.
Mingo Barba, Sergio; Lobo-Cerna, Fernando; Krawczyk, Przemek M; Lattuada, Marco; Füchslin, Rudolf M; Petri-Fink, Alke; Scheidegger, Stephan.
Afiliación
  • Mingo Barba S; School of Engineering, Zürich University of Applied Sciences (ZHAW), Winterthur, Switzerland.
  • Lobo-Cerna F; Chemistry Department, University of Fribourg, Fribourg, Switzerland.
  • Krawczyk PM; Adolphe Merkle Institute, University of Fribourg, Fribourg, Switzerland.
  • Lattuada M; Department of Medical Biology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands.
  • Füchslin RM; Cancer Center Amsterdam, Amsterdam, The Netherlands.
  • Petri-Fink A; Department of Medical Biology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands.
  • Scheidegger S; Cancer Center Amsterdam, Amsterdam, The Netherlands.
Dose Response ; 22(3): 15593258241279906, 2024.
Article en En | MEDLINE | ID: mdl-39224699
ABSTRACT

Introduction:

Cell repair dynamics are crucial in optimizing anti-cancer therapies. Various assays (eg, comet assay and γ-H2AX) assess post-radiation repair kinetics, but interpreting such data is challenging and model-based data analyses are required. However, ambiguities in parameter calibration remain an unsolved challenge. To address this, we propose combining survival dose-rate effects with computer simulations to gain knowledge about repair kinetics.

Methods:

After a literature review, theoretical discriminators based on common fractionation/dose-rate-related effects were defined to discard unrealistic model dynamics. The Multi-Hit Repair (MHR) model was calibrated with canine osteosarcoma Abrams cell line data to study the discriminators' efficacy in scenarios with limited survival data. Additionally, survival dose-rate-dependent data from the human SiHa cervical cancer cell line were used to illustrate the survival behavior at diverse dose-rates and the capability of the MHR to model these data.

Results:

SiHa data confirmed the validity of the proposed discriminators. The discriminators filtered 99% of parameter sets, improving the calibration of Abrams cells data. Furthermore, results from both cell lines may hint universal aspects of cellular repair.

Conclusions:

Dose-rate theoretical discrimination criteria are an effective method to understand repair kinetics and improve radiobiological model calibration. Moreover, this methodology may be used to analyze diverse biological data using dynamic models in-silico.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Dose Response Año: 2024 Tipo del documento: Article País de afiliación: Suiza Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Dose Response Año: 2024 Tipo del documento: Article País de afiliación: Suiza Pais de publicación: Estados Unidos