Plasmonic Nanoparticle-Based Digital Cytometry to Quantify MUC16 Binding on the Surface of Leukocytes in Ovarian Cancer

Abstract

Although levels of the circulating ovarian cancer marker (CA125) can distinguish ovarian masses that are likely to be malignant and correlate with severity of disease, serum CA125 has not proved useful in general population screening. Recently, cell culture studies have indicated that MUC16 may bind to the Siglec-9 receptor on natural killer (NK) cells where it downregulates the cytotoxicity of NK cells, allowing ovarian cancer cells to evade immune surveillance. We present evidence that the presence of MUC16 can be locally visualized and imaged on the surface of peripheral blood mononuclear cells (PBMCs) in ovarian cancer via a novel "digital" cytometry technique that incorporates: (i) OC125 monoclonal antibody-conjugated gold nanoparticles as optical nanoprobes, (ii) a high contrast dark-field microscopy system to detect PBMC-bound gold nanoparticles, and (iii) a computational algorithm for automatic counting of these nanoparticles to estimate the quantity of surface-bound MUC16. The quantitative detection of our technique was successfully demonstrated by discriminating clones of the ovarian cancer cell line, OVCAR3, based on low, intermediate, and high expression levels of MUC16. Additionally, PBMC surface-bound MUC16 was tracked in an ovarian cancer patient over a 17 month period; the results suggest that the binding of MUC16 on the surface of immune cells may play an early indicator for recurrent metastasis 6 months before computational tomography-based clinical diagnosis. We also demonstrate that the levels of surface-bound MUC16 on PBMCs from five ovarian cancer patients were greater than those from five healthy controls.

Keywords: MUC16/CA125; computational analysis; dark-field microscopy; digital cytometry; leukocytes; longitudinal study; ovarian cancer; plasmonic gold nanoparticle.

Figure 1.

Schematic procedure of plasmonic nanoparticle-based digital cytometry.

Figure 2.

Characterization of the anti-CA125 antibody-conjugated plasmonic nanoparticles (anti-CA125 PNPs). (a) Dark-field microscopy image of anti-CA125 PNPs and (b) evaluation of specific binding ability of anti-CA125 PNPs to CA125 antigens before and after lyophilization. The anti-Biotin antibody-conjugated PNPs (anti-Biotin PNPs) were utilized as a negative control. The size of samples was measured by dynamic light scattering (DLS).

Figure 3.

Color quantization of plasmonic-coupled PNPs under dark-field microscopy condition. (a) Dark-field microscopy image of dried anti-CA125 PNPs and (b) plasmonic resonant light scattering spectra of green, yellow-orange, and red dots as well as native PBMCs from hyperspectral images. Under DFM conditions, gold PNPs are shown in distinct colors based on their plasmonic resonance light scattering properties: green for monomers of an 80 nm gold nanosphere, yellow-orange for dimers, and red for trimers.

Figure 4.

PNP-based digital cytometry results of MUC16 (having CA125 epitopes) expression on ovarian cancer (OVCAR3) clone cells having low (AB9), intermediate (BC9), and high (AG8) MUC16 expression levels. (a) Flow cytometry results of the MUC16 expression level on the OVCAR3 clones. The three OVCAR3 clones were treated with monoclonal anti-CA125 antibodies labeled with Alexa Fluor 488 fluorophores (AF488-OC125). Flow cytometric analysis was performed for cells from each of OVCAR3 clones without the AF488-OC125 treatment, as a negative control (gray), and for each of AF488-OC125 treated OVCAR3 clones (red). Data is representative of three independent experiments. (b) Histograms of the number of bound antibody-conjugated PNPs per cell for cells without PNPs, cells treated with anti-Biotin PNPs, and cells treated with anti-CA125 PNPs. (c) Statistical quantification of the CA125 biomarker on the surface of individual single cells with Poisson distribution by computational automatic PNP counting algorithm. Mean ± standard deviation (SD, n = 3 replicates). A pairwise t-test with Bonferroni’s correction was performed on the mean of the bound anti-CA125 PNPs per cells in the OVCAR3 clones. ***p < 0.001; NS, not statistically significant (p > 0.05).

Figure 5.

Longitudinal study of CA125 levels on the surface of EOC patient’s PBMCs. (a) Dark-field microscopy image montages and (b) histograms of anti-CA125 PNPs bound to individual PBMCs in samples from representative months (Jan 2017, Aug 2017, and Jan 2018). (c) Statistical quantification (lambda of Poisson distribution fitting) of the number of anti-CA125 PNPs binding on the surface of EOC patient’s PBMCs with 95% confidence intervals (red) in comparison with CA125 levels in serum (black) as a function of time. The scale bars are 10 μm.

Figure 6.

Evaluation of anti-CA125 PNPs binding on the surface of PBMCs from five healthy donors (H1, H2, H3, H4, and H5) and five serous invasive EOC patients (P1, P2, P3, P4, and P5). All PBMCs were treated with a 1:2000 ratio of PBMCs to anti-CA125 PNPs. (a) Histogram of anti-CA125 PNPs bound to individual PBMCs and (b) percentage of PBMCs bound over 5 anti-CA125 PNPs/cell. The clinically relevant healthy control baseline of anti-CA125 PNP binding (ca. 5 PNPs/cell) was determined by averaging the lambda of Poisson distribution fitting in the number of bound anti-CA125 PNPs on five healthy donors.