Ovarian Cancer Ascites Inhibits Transcriptional Activation of NK Cells Partly through CA125.

Malignant ascites is a common clinical problem in ovarian cancer. NK cells are present in the ascites, but their antitumor activity is inhibited. The underlying mechanisms of the inhibition have yet to be fully elucidated. Using an Fcγ receptor-mediated NK cell activation assay, we show that ascites from ovarian cancer patients potently inhibits NK cell activation. Part of the inhibitory activity is mediated by CA125, a mucin 16 fragment shed from ovarian cancer tumors. Moreover, transcriptional analyses by RNA sequencing reveal upregulation of genes involved in multiple metabolic pathways but downregulation of genes involved in cytotoxicity and signaling pathways in NK cells purified from ovarian cancer patient ascites. Transcription of genes involved in cytotoxicity pathways are also downregulated in NK cells from healthy donors after in vitro treatment with ascites or with a CA125-enriched protein fraction. These results show that ascites and CA125 inhibit antitumor activity of NK cells at transcriptional levels by suppressing expression of genes involved in NK cell activation and cytotoxicity. Our findings shed light on the molecular mechanisms by which ascites inhibits the activity of NK cells and suggest possible approaches to reactivate NK cells for ovarian cancer immunotherapy.

Affinity-free enrichment and mass spectrometry analysis of the ovarian cancer biomarker CA125 (MUC16) from patient-derived ascites.

Developing a mass spectrometry-based assay for the ovarian cancer biomarker CA125 (MUC16) is a desirable goal, because it may enable detection of molecular regions that are not recognized by antibodies and are therefore analytically silent in the current immunoassay. Additionally, the ability to characterize the CA125 proteoforms expressed by individuals may offer clinical insight. Enrichment of CA125 from malignant ascites may provide a high-quality source of this important ovarian cancer biomarker, but a reliable strategy for such enrichment is currently lacking. Beginning with crude ascites isolated from three individual patients with high grade serous ovarian cancer, we enriched for MUC16 using filtration, ion exchange, and size exclusion chromatography and then performed bottom-up proteomics on the isolated proteins. This approach of enrichment and analysis reveals that the peptides detected via mass spectrometry map to the SEA domain and C-loop regions within the tandem repeat domains of CA125 and that peptide abundance correlates with clinical CA125 counts.

Characterization of Cell-Bound CA125 on Immune Cell Subtypes of Ovarian Cancer Patients Using a Novel Imaging Platform.

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.