The ability to identify-early in the course of therapy-patients that are not responding to a particular neoadjuvant regimen would provide the opportunity to switch to a potentially more efficacious treatment and transform current practice. Unfortunately, existing methods of determining early response are inadequate. The vision for this program is to develop tumor-forecasting methods for predicting response in individual breast cancer patients after a single cycle of neoadjuvant therapy. We propose to combine time-resolved drug- response cell scale data with physiological and tissue scale imaging data in order to initialize and constrain a multi-scale angiogenesis-cell proliferation model designed to predict both size and spatial characteristics of breast tumors at the completion of therapy. To achieve this goal, we will pursue the following specific aims: 1. (Pre-clinical validation) In the BT-474 HER2+ human breast cancer cell line, we will obtain: 1a. (cell scale) in vitro data quantifying rates of entry of proliferating cells into quiescence and apoptosis; 1b. (physiologica scale) in vivo MRI and PET measurements of cellularity, vascularity, and metabolism; 1c. (tissue scale) in vivo MR elastography measurements to quantify the tumor mechanical properties; 1d. (all scales) in situ data from fixed tumor tissue to corroborate cell and imaging-based metrics. These data will be integrated into the multi-scale model to predict tumor response after one cycle of the targeted anti-HER2 agents trastuzumab and lapatinib. 2. (Clinical application) In HER2+ patients receiving neoadjuvant trastuzumab and lapatinib, we will obtain: 2a. (physiological scale) in vivo MRI and PET measurements of cellularity, vascularity, and metabolism; 2b. (tissue scale) in vivo MR elastography measurements to quantify tumor mechanical properties. Guided by the results from Aim 1, these data will be integrated into the multi-scale model and make predictions on breast tumor response outcomes after a single cycle of trastuzumab and/or lapatinib. If successful, our approach would be the foundation for high-impact, large-scale application in clinical settings.

Public Health Relevance

We hypothesize that patient specific imaging data combined with an estimate of the effect of the neoadjuvant regimen on tumor cell phenotype, will enable a multi-scale model to accurately predict the response of breast tumors after a single cycle of therapy on an individual basis. Our goal is to provide the breast cancer community with a rigorous, practical method of predicting therapeutic response that is appropriate for incorporation into clinical trials and, ultimately, clinical practice.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project--Cooperative Agreements (U01)
Project #
1U01CA174706-01
Application #
8476896
Study Section
Special Emphasis Panel (ZEB1-OSR-C (J2))
Program Officer
Zhang, Huiming
Project Start
2013-06-01
Project End
2018-05-31
Budget Start
2013-06-01
Budget End
2014-05-31
Support Year
1
Fiscal Year
2013
Total Cost
$540,382
Indirect Cost
$190,787
Name
Vanderbilt University Medical Center
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
004413456
City
Nashville
State
TN
Country
United States
Zip Code
37212