Exosome Characterization Platform for Early Detection of Breast Cancer

Breast cancer is the most common cancer among women worldwide. Early detection is the most critical element, as the survival rate increases by up to 99%.

Although there are conventional screening techniques such as mammography, breast cancer is still the second leading cause of cancer death in women. One of the holy grails in cancer research is to develop a blood test for early detection.

Sensitive, non-invasive, and easy-to-use liquid biopsy techniques will revolutionize cancer diagnosis and treatment monitoring.

The goal of this project is to develop a complete platform for the isolation and label-free optical characterization of biological nanoparticles called exosomes extracted from blood. Exosomes are secreted from the cells into the body fluids and play an important role in intercellular communication.

These particles are emerged as potential biomarkers for liquid biopsy applications, as they carry information about their original cell.

However, the translation of exosome-based analyses from research labs to clinical settings is limited due to the lack of efficient isolation and quantification tools available.

We aim to develop a novel exosome characterization platform, named multimodal Interferometric-Raman imaging platform to detect and quantify exosomes at a single-particle level without using any labels.

The combination of the label-free imaging capability of interferometric microscopy and the chemical content information provided by Raman spectroscopy will be an important step for exosome-based diagnostics applications.

The proposed system will be integrated into a state-of-the-art isolation tool, creating complete isolation and multiparameter characterization platform.

The proposed platform will be tested with the exosomes isolated from tumor cells to determine possible biomarkers that can be used for diagnosis.

The diagnostic capability of the system will be validated with healthy donors and breast cancer patients(30 persons each)