Background: Measurement of serum CA125, an antigenic fragment of human mucin 16 (MUC16), is used to monitor the clinical progression of epithelial ovarian cancer (EOC). However, rather than simply a passive marker reflecting tumor burden, MUC16 may have a more active role by binding to immune cells and altering their tumor response. We developed a research tool to measure MUC16-binding to the surfaces of peripheral blood mononuclear cell (PBMC) subtypes and tested its research value using specimens collected serially from a woman being treated for high grade serous EOC.
Methods: Cryopreserved PBMCs were mixed with anti-CA125 antibody-labeled plasmonic gold nanoparticles (PNPs) to detect cell surface MUC16-binding along with fluorescent stains to identify B cells, NK cells, NK-T cells, T cells, and monocytes. From 3D darkfield images, a computer algorithm was applied to enumerate PNP-binding and fluorescence microscopy to identify cell lineage. Average MUC16-binding was determined by fitting a Poisson distribution to PNP-counts across similar cell types. MUC16-binding to cell types was correlated with treatment details, CA125 levels, and complete blood count (CBC) data.
Results: Over a 21-month period, monocytes had the highest level of MUC16-binding which was positively correlated with serum CA125 and inversely correlated with circulating monocyte and lymphocyte counts. Fluctuations of PNP-binding to NK cells were associated temporally with types of chemotherapy and surgical events. Levels of MUC16 bound to NK cells were positively correlated with levels of MUC16 bound to T and NK-T cells and inversely correlated with circulating platelets.
Conclusions: Assessment of MUC16-binding among cryopreserved PBMC cell types can be accomplished using darkfield and fluorescence microscopy. Correlations observed between level of binding by cell type with serum CA125, CBC data, and treatment details suggest that the new techniques may offer novel insights into EOC's clinical course.
Keywords: CA125; Microscopy; Mononuclear cells; Nanoparticles; Ovarian Cancer.
© 2022. The Author(s).