Breast cancer is the leading cancer diagnosed in women and in the US roughly 250,000 women are diagnosed each year resulting in about 40,000 deaths. Future progress in several key areas of cancer research will rely upon the ability of investigators to reliably detect, characterize and track subtle changes that occur in the tumor environment during the transformation from the benign to cancerous state. The central objective of this project is to design, develop and evaluate computational tools, which provide insight regarding the physical and morphological changes that occur starting with the onset of a malignancy and follow those changes throughout the course of disease progression. The overarching objectives of the project are: 1) to investigate changes in the mechanical/electrical/thermal characteristics of sampled tissues, 2) to increase the sampling throughput to allow automated assessment of multiple regions of interest, simultaneously, using an array of micro force sensors based on micro-electro-mechanical systems (MEMS) technology, and 3) to compare the mechanical/electrical/thermal changes, expression signatures, and spatial distribution of biomarkers in the normal tissue samples with those collected at the onset of malignancy and throughout the primary stages of disease progression for breast cancer cases. This work was on the cover page of IEEE Transactions of Biomedical Engineering in July 2016.
Jaydev P. Desai (Georgia Institute of Technology) and David J. Foran (Rutgers Cancer Institute of New Jersey)
