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Updated: Jun 23, 2026
A Syngeneic Mouse Model of Metastatic Renal Cell Carcinoma for Quantitative and Longitudinal Assessment of Preclinical Therapies
Published on: April 12, 2017
'In silico' oncology for clinical decision making in the context of nephroblastoma
1Universität des Saarlandes, Klinik für Pädiatrische Onkologie und Hämatologie, Homburg, Germany. graf@uks.eu
Abstract:
The present paper outlines the initial version of the ACGT (Advancing Clinico-Genomic Trials) -- an Integrated Project, partly funded by the EC (FP6-2005-IST-026996)I-Oncosimulator as an integrated software system simulating in vivo tumour response to therapeutic modalities within the clinical trials environment aiming to support clinical decision making in individual patients. Cancer treatment optimization is the main goal of the system. The document refers to the technology of the system and the clinical requirements and the types of medical data needed for exploitation in the case of nephroblastoma. The outcome of an initial step towards the clinical adaptation and validation of the system is presented and discussed. Use of anonymized real data before and after chemotherapeutic treatment for the case of the SIOP 2001/GPOH nephroblastoma clinical trial constitutes the basis of the clinical adaptation and validation process. By using real medical data concerning nephroblastoma for a single patient in conjunction with plausible values for the model parameters (based on available literature) a reasonable prediction of the actual tumour volume shrinkage has been made possible. Obviously as more and more sets of medical data are exploited the reliability of the model "tuning" is expected to increase. The successful performance of the initial combined ACGT Oncosimulator platform, although usable up to now only as a test of principle, has been a particularly encouraging step towards the clinical translation of the system, being the first of its kind worldwide.
Insights
The Advancing Clinico-Genomic Trials (ACGT) Oncosimulator predicts tumor response to cancer therapies. Initial validation using nephroblastoma data shows promising tumor shrinkage prediction, advancing personalized cancer treatment.
Area of Science:
- Computational biology
- Medical informatics
- Oncology
Background:
- Cancer treatment optimization requires advanced decision-support tools.
- Simulating in vivo tumor response to therapies is crucial for clinical trials.
- Personalized medicine necessitates integrating clinical and genomic data.
Purpose of the Study:
- To present the initial version of the ACGT (Advancing Clinico-Genomic Trials) Oncosimulator.
- To simulate in vivo tumor response to therapeutic modalities within a clinical trials environment.
- To support clinical decision-making for individual cancer patients, focusing on nephroblastoma.
Main Methods:
- Development of an integrated software system (ACGT Oncosimulator).
- Utilizing anonymized real patient data from the SIOP 2001/GPOH nephroblastoma clinical trial.
- Employing plausible model parameters based on available literature for simulation.
Main Results:
- Demonstrated reasonable prediction of actual tumor volume shrinkage for nephroblastoma.
- Successfully adapted and validated the system using real clinical data.
- The ACGT Oncosimulator platform performed successfully as a proof of principle.
Conclusions:
- The ACGT Oncosimulator represents a significant step towards clinical translation of cancer treatment optimization tools.
- Initial results show the potential for reliable prediction of tumor response with increasing data.
- This system is the first of its kind globally, aiming to enhance personalized cancer therapy.
