Photoacoustic Ultrasound to Detect/Monitor Ovarian Cancer
Description: Screening for ovarian cancer in high risk women is rational because the disease is treatable in early stages, but very deadly in late stages. CA125 testing and transvaginal ultrasound imaging have encouraging metrics including sensitivity and specificity of 89.4% and 99.8%, but have positive predictive values below 50% and are insufficient for use in the general population. Folate binding proteins are highly expressed in ovarian cancer; hence, these targets can be used to increase the specificity and sensitivity of ovarian cancer screening. My central hypothesis is that nanoparticles targeted to the folate receptor will increase tumor signal and contrast above background greater than non-targeted nanoparticles—this will increase the sensitivity and specificity of screening. Because folate receptors are expressed on the cell surface, it is critical to use a contrast agent that leaves the vasculature. My expertise is in nanoparticle imaging agents that do just that—these contrast agents are built from the clinically approved indocyanine green and poly-lactic-co-glutamic acid. I will now use them for ultrasound-based molecular imaging of ovarian cancer. I will image folate binding proteins with both conventional ultrasound and novel photoacoustic ultrasound that combines the high contrast of optical imaging with the resolution of ultrasound. I will evaluate the performance metrics of both through the following steps. Step 1. We will make the nanoparticles via an emulsification process. Step 2. We will add a cloaking polymer and folate. Step 3. We will validate the contrast agent with cell culture experiments. Step 4. We will image an orthotopic model of human ovarian cancer. Ultrasound already provides excellent anatomical information, and the small size of nanoparticles facilitates imaging the sensitive and specific biomarkers present on the cell surface. Although deployed here for ovarian cancer, this imaging agent will have broad utility across many cancer types. This work is also easily reconfigurable to other imaging targets as they emerge in the literature. I will use this pilot data to seek additional funds from the NIH at the conclusion of this project, e.g. PAR-13-185 and PAR-13-189.
Amount: $75,000
Funding type: grant
Funder scheme: Faculty Seed Grants
Start date: 2019-01-01
End date: 2020-03-31
Investigator: Jesse Jokerst
Institution: University of California, San Diego
Funded outputs count: 0
Funder award ID: CRN-19-582184
OpenAlex ID: G7600879105