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Modeling Longitudinal Preclinical Tumor Size Data to Identify Transient Dynamics in Tumor Response to Antiangiogenic Drugs.

ABSTRACT: Experimental evidence suggests that antiangiogenic therapy gives rise to a transient window of vessel normalization, within which the efficacy of radiotherapy and chemotherapy may be enhanced. Preclinical experiments that measure components of vessel normalization are invasive and expensive. We have developed a mathematical model of vascular tumor growth from preclinical time-course data in a breast cancer xenograft model. We used a mixed-effects approach for model parameterization, leveraging tumor size data to identify a period of enhanced tumor growth that could potentially correspond to the transient window of vessel normalization. We estimated the characteristics of the window for mice treated with an anti-VEGF antibody (bevacizumab) or with a bispecific anti-VEGF/anti-angiopoietin-2 antibody (vanucizumab). We show how the mathematical model could theoretically be used to predict how to coordinate antiangiogenic therapy with radiotherapy or chemotherapy to maximize therapeutic effect, reducing the need for preclinical experiments that directly measure vessel normalization parameters.

SUBMITTER: Hutchinson LG

PROVIDER: S-EPMC5192995 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature

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Modeling Longitudinal Preclinical Tumor Size Data to Identify Transient Dynamics in Tumor Response to Antiangiogenic Drugs.

Hutchinson L G LG Mueller H-J HJ Gaffney E A EA Maini P K PK Wagg J J Phipps A A Boetsch C C Byrne H M HM Ribba B B

CPT: pharmacometrics & systems pharmacology 20161114 11

Experimental evidence suggests that antiangiogenic therapy gives rise to a transient window of vessel normalization, within which the efficacy of radiotherapy and chemotherapy may be enhanced. Preclinical experiments that measure components of vessel normalization are invasive and expensive. We have developed a mathematical model of vascular tumor growth from preclinical time-course data in a breast cancer xenograft model. We used a mixed-effects approach for model parameterization, leveraging t ...[more]

PMID: 27863175

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Project description:BackgroundEvaluation of changes in tumor size from images acquired by ultrasound (US), computed tomography (CT) or magnetic resonance imaging (MRI) is a common measure of cancer chemotherapy efficacy. Tumor size measurement based on either the World Health Organization (WHO) criteria or the Response Evaluation Criteria in Solid Tumors (RECIST) is the only imaging biomarker for anti-cancer drug testing presently approved by the United States Food and Drug Administration (FDA). The aim of this paper was to design and test a quality assurance phantom with the capability of monitoring tumor size changes with multiple preclinical imaging scanners (US, CT and MRI) in order to facilitate preclinical anti-cancer drug testing.MethodsThree phantoms (Gammex/UTHSCSA Mark 1, Gammex/UTHSCSA Mark 2 and UTHSCSA multimodality tumor measurement phantom) containing tumor-simulating test objects were designed and constructed. All three phantoms were scanned in US, CT and MRI devices. The size of test objects in the phantoms was measured from the US, CT and MRI images. RECIST, WHO and volume analyses were performed.ResultsThe smaller phantom size, simplified design and better test object CT contrast of the UTHSCSA multimodality tumor measurement phantom allowed scanning of the phantom in preclinical US, CT and MRI scanners compared with only limited preclinical scanning capability of Mark 1 and Mark 2 phantoms. For all imaging modalities, RECIST and WHO errors were reduced for UTHSCSA multimodality tumor measurement phantom (≤1.69 ± 0.33%) compared with both Mark 1 (≤ -7.56 ± 6.52%) and Mark 2 (≤ 5.66 ± 1.41%) phantoms. For the UTHSCSA multimodality tumor measurement phantom, measured tumor volumes were highly correlated with NIST traceable design volumes for US (R2 = 1.000, p < 0.0001), CT (R2 = 0.9999, p < 0.0001) and MRI (R2 = 0.9998, p < 0.0001).ConclusionsThe UTHSCSA multimodality tumor measurement phantom described in this study can potentially be a useful quality assurance tool for verifying radiologic assessment of tumor size change during preclinical anti-cancer therapy testing with multiple imaging modalities.

Dataset Information

Modeling Longitudinal Preclinical Tumor Size Data to Identify Transient Dynamics in Tumor Response to Antiangiogenic Drugs.

Publications

Modeling Longitudinal Preclinical Tumor Size Data to Identify Transient Dynamics in Tumor Response to Antiangiogenic Drugs.

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