Investigator
Professor · University of Toronto, Chemistry
Chemiluminescent Biosensor Utilizing Magnetic Particles for the Detection of Ovarian Cancer Biomarker Lysophosphatidic Acid
Lysophosphatidic acid (LPA) is a cell-signaling lipid that has been proposed as an early-stage biomarker for ovarian cancer (OC). Diagnosing OC in Stage I is critical to improving patient outcomes, increasing the survival rate from 30% (when diagnosed in late stages of the disease) to over 90%. This significant improvement is due to the success of early interventions; however, current diagnostic methods are not as effective at early-stage detection, with only 15% of cases diagnosed in Stage I and over 70% diagnosed in Stage III or IV. There is a strong need for LPA detection that is sensitive, specific, rapid, low-cost, and automated to truly validate its effectiveness as a diagnostic characteristic for OC. We report the preliminary development and characterization of one such biosensor, which makes use of the advantages of magnetic particles and chemiluminescence for quick, sensitive detection of LPA. The sensor has proven to be viable, with a positive response to LPA concentration, a measurement time of 5 s after incubation, and an LOD of 3.5 nM.
Coupled Electrostatic and Hydrophobic Destabilisation of the Gelsolin-Actin Complex Enables Facile Detection of Ovarian Cancer Biomarker Lysophosphatidic Acid
Lysophosphatidic acid (LPA) is a promising biomarker candidate to screen for ovarian cancer (OC) and potentially stratify and treat patients according to disease stage. LPA is known to target the actin-binding protein gelsolin which is a key regulator of actin filament assembly. Previous studies have shown that the phosphate headgroup of LPA alone is inadequate to bind to the short chain of amino acids in gelsolin known as the PIP2-binding domain. Thus, the molecular-level detail of the mechanism of LPA binding is poorly understood. Here, we model LPA binding to the PIP2-binding domain of gelsolin in the gelsolin-actin complex through extensive ten-microsecond atomistic molecular dynamics (MD) simulations. We predict that LPA binding causes a local conformational rearrangement due to LPA interactions with both gelsolin and actin residues. These conformational changes are a result of the amphipathic nature of LPA, where the anionic phosphate, polar glycerol and ester groups, and lipophilic aliphatic tail mediate LPA binding via charged electrostatic, hydrogen bonding, and van der Waals interactions. The negatively-charged LPA headgroup binds to the PIP2-binding domain of gelsolin-actin while its hydrophobic tail is inserted into actin, creating a strong LPA-insertion pocket that weakens the gelsolin–actin interface. The computed structure, dynamics, and energetics of the ternary gelsolin–LPA–actin complex confirms that a quantitative OC assay is possible based on LPA-triggered actin release from the gelsolin-actin complex.
Detection of the Ovarian Cancer Biomarker Lysophosphatidic Acid in Serum
Lysophosphatidic acid (LPA) is present during the medical condition of ovarian cancer at all stages of the disease, and, therefore possesses considerable potential as a biomarker for screening its presence in female patients. Unfortunately, there is currently no clinically employable assay for this biomarker. In the present work, we introduce a test based on the duel protein system of actin and gelsolin that could allow the quantitative measurement of LPA in serum samples in a biosensing format. In order to evaluate this possibility, actin protein was dye-modified and complexed with gelsolin protein, followed by surface deposition onto silica nanoparticles. This solid-phase system was exposed to serum samples containing various concentrations of LPA and analyzed by fluorescence microscopy. Measurements conducted for the LPA-containing serum samples were higher after exposure to the developed test than samples without LPA. Early results suggest a limit of detection of 5 μM LPA in serum. The eventual goal is to employ the chemistry described here in a biosensor configuration for the large population-scale, rapid screening of women for the potential occurrence of ovarian cancer.
Professor
University of Toronto · Chemistry