Skip to main content
eScholarship
Open Access Publications from the University of California

Exosome-Based Early Detection of Cancer and Parkinson’s Disease

  • Author(s): Sun, Haofan
  • Advisor(s): Yanik, Ahmet Ali
  • et al.
Abstract

Exosomes have emerged as novel biomarkers for disease diagnostics and prognosis. Exosomes are present in bodily fluids and closely resemble the contents of their parental cells; thus, they have a huge potential to serve as a liquid biopsy tool in the diagnosis of multiple diseases. In particular, tumor exosomes have the potential as biomarkers for the early detection of cancer since their contents reflect the genomic and metabolic abnormalities in their parental cells. With the development of techniques for high-throughput purification and isolation of exosomes and exosome content analysis, exosomal proteins is rapidly becoming an important tool for the early diagnosis of cancer.

Exosomes are extracellular vesicles with a diameter of 30 - 150 nm. These nanovesicles are produced by almost all types of mammalian cells and cancer cells through fusion of an intermediate endocytic compartment, namely, multivesicular bodies, with the plasma membrane.

In the introduction part of this thesis, I introduce the concept of the exosome, its definition, biogenesis and characteristics, and composition. Then I discuss the use of exosomes for cancer prognosis, and α-synuclein circulating exosomes as an example to explain how exosomal proteins work and its high specificity to Parkinson Disease. Finally, I discuss the different methods of isolating and collecting specific types of exosomes.

One unanswered question is at what stage of disease and cancer development can the exosome-based method be useful for diagnosis. To test the practicability of exosome-based methods in cancer and diseases diagnosis, I will establish a mathematical model and analytically calculate the concentrations of cancer-specific exosomes based on tumor growth. Then I will predict how early the exosome-based method can detect cancer and other diseases considering the detection limits of current diagnostic technologies. In addition, I will introduce and discuss the parameters required to inspect and verify the feasibility of my mathematical model. This thesis is focused on two specific exosomes: α-synuclein circulating exosomes for Parkinson disease and HSP70 proteins for liver cancer.

After the exosomes are extracted and purified, they can be resuspended into a small volume solution. Therefore, exosomal samples yield higher concentrations of biomarkers in a resuspension solution than those in blood. In the following, we show that it takes about 2.05 years for a parental cell to expand to a cell population that can secrete a baseline value of the α-synuclein circulating exosomes in Parkinson disease (PD) patients, and 0.73 years for a parental tumor cell to expand to a cell population that can secrete the baseline number of HSP70 proteins circulating exosomes in liver cancer patients. In conclusion, the mathematical model I established can help us predict how exosomal protein can be used to detect cancer and PD.

Main Content
Current View