Figure S1, schematic concept of the three-dimensional dark-field microscopy imaging setup; Figure S2, dynamic light scattering measurement of anti-CA125 and anti-Biotin antibody-conjugated 80 nm spherical gold plasmonic nanoparticles (PNPs); Figure S3, dynamic light scattering measurement and UV-visible absorption spectra of anti-CA125 and anti-Biotin antibody-conjugated PNPs treated with various concentrations of CA125 antigen; Figure S4, color quantization for monomer, dimer, and trimer based on the red/ green intensity ratios (R/G ratios); Figure S5, mathematical model for evaluating the systemic error of the color quantization method for bound PNPs in MUC16 binding on the surface of the cell; Figure S6, PNP-based digital cytometric assay on ovarian cancer cells (OVCAR3) with and without centrifugation; Figure S7, optimization of incubation conditions for the ratio of treated PNPs to cells in the PNP-based digital cytometric assay on ovarian cancer cells (OVCAR3); Figure S8, cell membrane mask generated by a deep convolutional neural network (U-Net) to exclude unbound PNPs nearby the cells in the enumeration of bound PNPs on the surface of cells; Figure S9, longitudinal study of bound MUC16/CA125 on the surface of EOC patient's PBMCs over a 17 month period at 1 month intervals; Figure S10, evaluation of the specific binding ability of anti-CA125 PNPs toward its targets on the patient's and healthy subject's PBMCs with various PBMC to PNP ratios; Figure S11, dark-field microscopy image montages of anti-CA125 PNPs bound to individual PBMCs in samples from five healthy donors and five serous invasive EOC patients; Figure S12, flow cytometric analysis for the evaluation of bound MUC16 on the surface of PBMCs from five healthy donors and five serous invasive ovarian cancer patients; Figure S13, scanning electron microscopy images of OVCAR3 clone treated with antibody-conjugated PNPs; and Table S1, ages and the CA125 levels in the serum of healthy donors and ovarian cancer patients (PDF)
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Apoptotic mechanisms are often dysregulated in cancerous phenotypes. Additionally, many anticancer treatments induce apoptosis and necrosis, and the monitoring of this apoptotic activity can allow researchers to identify therapeutic efficiency. Here, we introduce a microscope which combines quantitative phase imaging (QPI) with the ability to detect molecular events via fluorescence (or Förster) resonance energy transfer (FRET). The system was applied to study cells undergoing apoptosis to correlate the onset of apoptotic enzyme activity as observed using a FRET-based apoptosis sensor with whole cell morphological changes analyzed via QPI. The QPI data showed changes in cell disorder strength during the initiation of apoptotic enzymatic activity.
MUC16, a sialomucin that contains the ovarian cancer biomarker CA125, binds at low abundance to leucocytes via the immune receptor, Siglec-9. Conventional fluorescence-based imaging techniques lack the sensitivity to assess this low-abundance event, prompting us to develop a novel “digital” optical cytometry technique for qualitative and quantitative assessment of CA125 binding to peripheral blood mononuclear cells (PBMC). Plasmonic nanoparticle labeled detection antibody allows assessment of CA125 at the near-single molecule level when bound to specific immune cell lineages that are simultaneously identified using multiparameter fluorescence imaging. Image analysis and deep learning were used to quantify CA125 per each cell lineage. PBMC from treatment naïve ovarian cancer patients (N = 14) showed higher cell surface abundance of CA125 on the aggregate PBMC population as well as on NK (p = 0.013), T (p < 0.001) and B cells (p = 0.024) compared to circulating lymphocytes of healthy donors (N = 7). Differences in CA125 binding to monocytes or NK-T cells between the two cohorts were not significant. There was no correlation between the PBMC-bound and serum levels of CA125, suggesting that these two compartments are not in stoichiometric equilibrium. Understanding where and how subset-specific cell-bound surface CA125 takes place may provide guidance towards a new diagnostic biomarker in ovarian cancer.
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.
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