Comparative glycoproteomics study on the surface of SKOV3 versus IOSE80 cell lines

Glycan diversity in ovarian cancer: Unraveling the immune interplay and therapeutic prospects

Ovarian cancer remains a formidable challenge in oncology due to its late-stage diagnosis and limited treatment options. Recent research has revealed the intricate interplay between glycan diversity and the immune microenvironment within ovarian tumors, shedding new light on potential therapeutic strategies. This review seeks to investigate the complex role of glycans in ovarian cancer and their impact on the immune response. Glycans, complex sugar molecules decorating cell surfaces and secreted proteins, have emerged as key regulators of immune surveillance in ovarian cancer. Aberrant glycosylation patterns can promote immune evasion by shielding tumor cells from immune recognition, enabling disease progression. Conversely, certain glycan structures can modulate the immune response, leading to either antitumor immunity or immune tolerance. Understanding the intricate relationship between glycan diversity and immune interactions in ovarian cancer holds promise for the development of innovative therapeutic approaches. Immunotherapies that target glycan-mediated immune evasion, such as glycan-based vaccines or checkpoint inhibitors, are under investigation. Additionally, glycan profiling may serve as a diagnostic tool for patient stratification and treatment selection. This review underscores the emerging importance of glycan diversity in ovarian cancer, emphasizing the potential for unraveling immune interplay and advancing tailored therapeutic prospects for this devastating disease.

Dual-Aptamer Recognition of DNA Logic Gate Sensor-Based Specific Exosomal Proteins for Ovarian Cancer Diagnosis

Clinical diagnosis of ovarian cancer lacks high accuracy due to the weak selection of specific biomarkers along with the circumstance biomarkers localization. Clustering analysis of proteins transported on exosomes enables a more precise screening of effective biomarkers. Herein, through bioinformatics analysis of ovarian cancer and exosome proteomes, two coexpressed proteins, EpCAM and CD24, specifically enriched, were identified, together with the development of an as-derived dual-aptamer targeted exosome-based strategy for ovarian cancer screening. In brief, a DNA ternary polymer with aptamers targeting EpCAM and CD24 was designed to present a logic gate reaction upon recognizing ovarian cancer exosomes, triggering a rolling circle amplification chemiluminescent signal. A dynamic detection range of 6 orders of magnitude was achieved by quantifying exosomes. Moreover, for clinical samples, this strategy could accurately differentiate exosomes from healthy persons, other cancer patients, and ovarian cancer patients, enabling promising in situ detection. By accurately selecting biomarkers and constructing a dual-targeted exosomal protein detection strategy, the limitation of insufficient specificity of traditional protein markers was circumvented. This work contributed to the development of exosome-based prognosis monitoring in ovarian cancer through the identification of disease-specific exosome protein markers.