Development of Technologies for Early Detection and Stratification of Breast Cancer
Abstract
The overall goal of this work was to develop ultra-sensitive detection techniques to identify a panel of new biomarkers and indicators with diagnostic and predictive value in breast cancer. We successfully created several Single Molecule Array (Simoa) assays which were utilized to determine biomarker concentrations in breast cancer patients. We screened multiple biomarkers in breast cancer patient and healthy control samples and used additional markers, such as mt DNA, to improve the sensitivity and specificity of these assays. We used PSA to demonstrate that biomarkers can be measured at ultrasensitive levels within serum using Simoa prior to tumor formation in a mouse model. We successfully achieved full quantification of protein molecules within single cancer cells and discovered that highly cultured cells exhibited different protein expression levels than low-passage cells. Integration of ensemble Decision Aliquot Ranking (eDAR) with Simoa was accomplished to increase the throughput of the overall system.
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 01, 2016
- Accession Number
- AD1030618
Entities
People
- Charlotte Kuperwasser
- Daniel Chiu
- David R. Walt
- Gail Sonenshein
- Rachel Buchsbaum
Organizations
- Tufts University