Abstract
Ovarian cancer, a leading cause of cancer related deaths among women, has been notoriously difficult to routinely screen for and diagnose early. Researchers and clinicians continue to seek routinely usable, non-invasive, screening methods as early detection significantly improves survival. Biomarker screening is ideal; however, currently available ovarian cancer biomarkers lack desirable sensitivity and specificity. Furthermore, the most fatal forms, high grade serous cancers often originate in the fallopian tube; therefore, sampling from the vaginal environment provides more proximal sources for tumor detection. To address these shortcomings and leverage proximal sampling, we developed an untargeted mass spectrometry microprotein profiling method and identified a signature of cystatin A, validated this protein in an animal model, and sought to overcome the limits of detection inherent to mass spectrometry by demonstrating that cystatin A is present at 100 pM concentrations using a label-free microtoroid resonator. The findings highlight the potential utility for early-stage detection where cystatin A levels would be low.
Significance Statement It is now clear that high-grade serous ovarian cancer can originate in the fallopian tube epithelium. These tumors colonize the ovary and then metastasize throughout the peritoneum. This discovery has raised important, and yet unaddressed, questions how we might be able to detect and screen for this deadly disease for which there is no routine screening. We have leveraged vaginal lavages from a murine model of the disease as a complex biological fluid for untargeted discovery of microproteins using mass. We improved our limits of detection by conjugating a cystatin A antibody to the surface of a microtoroid resonator to allow us to specifically detect cystatin A from vaginal lavages at early time points across biological replicates.
Competing Interest Statement
The authors declare the following competing interests: Judith Su owns a financial stake in Femtorays Technologies which develops label-free molecular sensors.
Footnotes
↵* Judith Su, Laura M. Sanchez. Email: lmsanche{at}ucsc.edu; judy{at}optics.arizona.edu
https://massive.ucsd.edu/ProteoSAFe/dataset.jsp?task=af5151bad98849cc87bade7c39388db4
https://massive.ucsd.edu/ProteoSAFe/dataset.jsp?task=14dd24c99035493fbf05c6af1cae1ce1