Research in the Whelan lab is motivated by the need to detect and treat ovarian cancer in its early stages, when therapeutic intervention is most effective. We approach the problem of ovarian cancer detection with a diverse tool kit drawn from bioanalytical chemistry, molecular biology, bioinformatics, and nanoscience. We have an abiding interest in fundamental analytical method development as well as biomedical and clinical application. Ongoing projects include:
Identifying and Validating DNA Aptamers for Ovarian Cancer Biomarkers
Aptamers are single stranded oligonucleotides - DNA or RNA - that are selected out of a large, random pool on the basis of a particular function. Often aptamers function as high-affinity binders to biological molecules. The process of selecting aptamers ("SELEX") relies on repeated cycles of selection and amplification until a small number of oligonucleotides with the desired binding property dominate the pool. We are currently selecting aptamers for the important ovarian cancer biomarkers MUC16 (CA125), HE4, and mesothelin. Informed by the particular attributes of the protein target, we tailor the aptamer selection process to fit. Selection modes we have recently employed include capillary electrophoresis-based (CE-SELEX), One- Pot SELEX, cell SELEX, and magnetic-bead-based fluidic SELEX. Every selection process concludes with high-throughput sequencing of the evolved oligonucleotide pool, followed by bioinformatics to mine the resulting sequence data for the best aptamers. Bioinformatics also identifies bias, contamination, and the development of structural trends over the selection process. The binding properties of aptamer candidates are evaluated using capillary electrophoresis, fluorescence anisotropy, surface plasmon resonance spectroscopy, isothermal titration calorimetry, and competitive ELISA immunoassay. The resulting aptamers can be used as substitutes for antibodies in any application for which affinity recognition is valuable.
Proteomics Analysis of Ovarian Cancer Biomarkers
CA125 is the most widely used biomarker for clinical monitoring of epithelial ovarian cancer. Serum levels of CA125 are monitored during treatment, and increases correlate with cancer recurrence. CA125 is the repeating peptide epitope of the mucin protein MUC16 and is currently detected via double determinant immunoassay. Previous work from our lab and others indicates that the antibodies used in existing CA125 clinical assays do not respond uniformly to all domains of CA125, suggesting that these assays underestimate levels of this biomarker in patients, and that earlier detection would be enabled by new assays based on improved affinity recognition. Importantly, the epitopes that are recognized by the antibodies used in the clinic are not known. In collaboration with the lab of Dr. Manish Patankar at the University of Wisconsin School of Medicine and Public Health, we are using capillary-electrophoresis-mass spectrometry (CE-MS) to characterize MUC16 (CA125) from various sources, including bacterial expression systems, mammalian cell lines, and ascites fluid from ovarian cancer patients. We will correlate amino acid sequence information with immunogenicity to the antibodies used in clinical assays. This study will enable us in future work to the test the hypothesis that heterogeneity in this protein has clinically relevant predictive power.
