(683e) Synthetic Peptide Ligands for Early Detection of Ovarian Cancer: A Computationally Driven Approach

Ovarian cancer (OvCa) diagnosis remains a challenge due to the lack of specific and sensitive methods for detecting the presence of OvCa cells in the body. This often leads to delayed treatment and poor prognosis. Approximately 72% of OvCa cases are diagnosed at advanced stages (III or IV), with a corresponding 5-year survival rate of only around 31%. Early detection, however, provides a much brighter outlook, with 5-year survival rates exceeding 90% for localized cancers (stage I). Extracellular vesicles (EVs), particularly exosomes, are emerging as promising minimally invasive biomarkers for OvCa diagnosis. EVs contain a variety of biomolecules that reflect the originating cell's state. Analyzing EV protein profiles allows for the identification of tumor-specific antigens, offering a potential tool for early cancer detection.

We aim to computationally design peptide ligands (termed SPLEX: Synthetic Peptide Ligands for EXtracellular vesicles) as a novel approach to improve OvCa early detection. SPLEX probes are peptide ligands that bind to transmembrane proteins like tetraspanins (CD81, CD9) and EpCAM, a biomarker of malignant OvCa-derived EVs. SPLEX potentially offers various advantages over traditional antibody-based immunoassays: (1) their smaller size allows better sensitivity, and (2) the computational design minimizes cross-reactivity.

Towards this goal, we employ PepBD (Peptide Binding design), a Monte Carlo-based algorithm developed in our lab that iteratively searches for peptide sequences with high affinity and specificity toward target OvCa EV membrane proteins. The top-scoring sequences (~10-20) identified through PepBD are further evaluated using explicit-solvent molecular dynamics simulations to assess binding affinity. This rigorous approach ensures the selection of highly specific SPLEX candidates. Our experimental collaborators are synthesizing the designed peptides and characterizing them for their binding affinity and selectivity toward the target proteins. Using established biochemical techniques such as Bio-layer Interferometry and single EV imaging techniques, we aim to achieve high analytical accuracy and precision in EV identification and biomarker analysis.

Preliminary results with EV imaging for SPLEX probes targeting EpCAM expression show slightly superior and comparable detection of EpCAM-positive EVs compared to antibodies. We anticipate SPLEX to have nanomolar binding affinities and good selectivity, enabling fast and efficient EV identification.