Toward Practical Integration of Omic and Imaging Data in Co-Clinical Trials

Author:

Alkim Emel1,Dowst Heidi2ORCID,DiCarlo Julie34ORCID,Dobrolecki Lacey56,Hernández-Herrera Anadulce2,Hormuth David34ORCID,Liao Yuxing5ORCID,McOwiti Apollo2,Pautler Robia7ORCID,Rimawi Mothaffar58,Roark Ashley58,Srinivasan Ramakrishnan5,Virostko Jack34910ORCID,Zhang Bing5ORCID,Zheng Fei2,Rubin Daniel11112ORCID,Yankeelov Thomas349101314ORCID,Lewis Michael256ORCID

Affiliation:

1. Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA 94305, USA

2. Dan L. Duncan Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA

3. Oden Institute for Computational Engineering and Sciences, Austin, TX 78712, USA

4. Livestrong Cancer Institutes, Austin, TX 78712, USA

5. Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX 77030, USA

6. Department of Molecular and Cellular Biology and Radiology, Baylor College of Medicine, Houston, TX 77030, USA

7. Department of Physiology, Baylor College of Medicine, Houston, TX 77030, USA

8. Department of Medicine, Baylor College of Medicine, Houston, TX 77030, USA

9. Department of Oncology, The University of Texas at Austin, Austin, TX 78712, USA

10. Department of Diagnostic Medicine, The University of Texas at Austin, Austin, TX 78712, USA

11. Department of Radiology, Stanford University School of Medicine, Stanford, CA 94305, USA

12. Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA

13. Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX 78712, USA

14. Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA

Abstract

Co-clinical trials are the concurrent or sequential evaluation of therapeutics in both patients clinically and patient-derived xenografts (PDX) pre-clinically, in a manner designed to match the pharmacokinetics and pharmacodynamics of the agent(s) used. The primary goal is to determine the degree to which PDX cohort responses recapitulate patient cohort responses at the phenotypic and molecular levels, such that pre-clinical and clinical trials can inform one another. A major issue is how to manage, integrate, and analyze the abundance of data generated across both spatial and temporal scales, as well as across species. To address this issue, we are developing MIRACCL (molecular and imaging response analysis of co-clinical trials), a web-based analytical tool. For prototyping, we simulated data for a co-clinical trial in “triple-negative” breast cancer (TNBC) by pairing pre- (T0) and on-treatment (T1) magnetic resonance imaging (MRI) from the I-SPY2 trial, as well as PDX-based T0 and T1 MRI. Baseline (T0) and on-treatment (T1) RNA expression data were also simulated for TNBC and PDX. Image features derived from both datasets were cross-referenced to omic data to evaluate MIRACCL functionality for correlating and displaying MRI-based changes in tumor size, vascularity, and cellularity with changes in mRNA expression as a function of treatment.

Funder

National Institutes of Health

Cancer Prevention and Research Institute of Texas

Publisher

MDPI AG

Subject

Radiology, Nuclear Medicine and imaging

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