Integrated MRI and Molecular Analyses to Predict Early Drug Response in Breast Cancer

Developmental Research Project:
Integrated MRI and Molecular Analyses to Predict Early Drug Response in Breast Cancer

Principal Investigators - Laura vanʻt Veer and Nola Hylton

Specific Aims

1. Explore the association between molecular and genomic profiles of breast tumors and tumor-associated stroma with imaging descriptors derived from contrast-enhanced breast MR images.
2. Augment early prediction of neoadjuvant drug response, that is after one cycle of chemotherapy, by integrating state-of-the-art MRI and biomarker data.

Dynamic contrast-enhanced breast MRI (DCE-MRI) images provide a three-dimensional picture of breast anatomy and microvascular function. In order to improve our ability to interpret the biologic meaning of image features and image changes resulting from treatment, we will study the relationship between enhancement patterns on breast DCE-MRI images and molecular and genomic factors, for instance changes in image features associated with angiogenic phenotypes. Integration of biological and image knowledge from the I-SPY 1 neoadjuvant breast cancer study could potentially improve our ability to predict of breast cancer treatment response. The hypotheses to be tested in this project are that sensitivity and specificity of response prediction can be improved: by using molecular and genomic information to evaluate alternative MRI metrics for quantifying response; and by testing predictive performance within biologically homogeneous subsets of disease.

We expect these studies to lead to more refined quantification approaches for imaging and molecular and genomics studies in I-SPY 2 and other neoadjuvant breast cancer trials. The imaging studies under I-SPY 2 will have greater dimensionality of functional measurements, adding both diffusion-weighted MRI to measure tissue cellularity, and 1H magnetic resonance spectroscopy to measure choline metabolites associated with membrane synthesis. Furthermore, this integrated approach will provide the tools for next phase clinical trials that may allow individualization of treatment through the adaptation of therapy after one treatment cycle.