We seek to develop robust platforms for capturing, enumerating and analyzing circulating tumor cells and
associated cancer cells from the blood of cancer patients. We will leverage our previously developed precisely
engineered microfilter platform that allows effective separation and collection of viable CTC from patient blood.
In parallel, we have developed novel imaging methods perfectly suited for rapid analyses for circulating tumor
cells, clusters and associated cancer cell subtypes (such as Cancer Associated Fibroblasts, or CAF).
We propose to integrate these two novel technologies to create a robust diagnostic tool for clinical pathology
as well as basic research that enables capture, enumeration, and analyses of circulating tumor cells and
associated cancer cells. Our multidisciplinary team proposes the following Specific Aims:
1) Build and validate the technology to rapidly acquire CTC/CAF images using Fourier
Microscopy and evaluate the images with a deep learning algorithm
2) Evaluation of the integrated platform for using CTC/CAF in predicting recurrence/survival in early stage
breast cancer patients
For these studies in early stage breast cancer, we have robust collaborations with industry partners in
Circulogix Inc (Microfilter technology for cell capture), ClearBridge Inc. (FPM imaging of the microfilter surface),
and Google Software (Deep learning algorithm for analyzing FPM images of microfilter).
The ability to reliably and rapidly detect and analyze CTC and associated cancer cells in early stage breast
cancer patients would deliver a major new tool for oncology research, a platform for screening of novel drugs,
and a critical advance in precision cancer management.