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Assessing PARP trapping dynamics in ovarian cancer using a CRISPR-engineered FRET biosensor
Daniel Marks1, Edwin Garcia1, Sunil Kumar2
1Ovarian Cancer Action Research Centre, Department of Surgery and Cancer, Imperial College London, London W12 0NN, UK; Francis Crick Institute, London NW1 1AT, UK; Department of Physics, Imperial College London, London SW7 2AZ, UK.
Abstract:
Poly(ADP-ribose) polymerase inhibitors (PARPi) have revolutionized the treatment of ovarian high-grade serous carcinoma (HGSC), particularly in homologous recombination-deficient tumors. However, the emergence of resistance poses a critical challenge, as over 50% of patients relapse within 3 years. The mechanisms underlying changes in PARP trapping, a central aspect of PARPi efficacy, are not well understood, as current experimental methodologies lack resolution and throughput. To address this, we develop an intramolecular fluorescence resonance energy transfer (FRET)-based biosensor by CRISPR-Cas9 dual labeling of endogenous PARP1 with EGFP and mCherryFP in OVCAR4 cells. This biosensor enables real-time, single-cell analysis of PARP trapping dynamics. Using fluorescence lifetime imaging microscopy (FLIM), we reveal dose-dependent PARP trapping, differentiate the trapping efficiencies of four clinically approved PARPi, and observe reduced trapping in PARPi-resistant models in vitro and in vivo. This biosensor provides critical insights into PARPi resistance mechanisms, with implications for developing more effective therapies and advancing personalized treatment for ovarian cancer patients.
Insights
We developed a novel biosensor to track Poly(ADP-ribose) polymerase inhibitors (PARPi) activity in real-time. This tool reveals how PARPi resistance develops, offering insights for improved ovarian cancer treatments.
Area of Science:
- Biochemistry
- Molecular Biology
- Oncology
Background:
- Poly(ADP-ribose) polymerase inhibitors (PARPi) are vital in treating ovarian high-grade serous carcinoma (HGSC), especially in homologous recombination-deficient cancers.
- Tumor resistance to PARPi is a significant clinical challenge, leading to relapse in over 50% of patients within three years.
- Understanding PARP trapping mechanisms is crucial for overcoming PARPi resistance, but current methods lack the necessary resolution and throughput.
Purpose of the Study:
- To develop a high-resolution biosensor for real-time, single-cell monitoring of PARP trapping dynamics.
- To investigate the mechanisms of PARPi resistance by analyzing PARP trapping efficiency.
- To provide a tool for evaluating PARPi efficacy and informing personalized ovarian cancer therapy.
Main Methods:
- CRISPR-Cas9 dual labeling of endogenous PARP1 with EGFP and mCherryFP in OVCAR4 cells to create a FRET-based biosensor.
- Utilizing fluorescence lifetime imaging microscopy (FLIM) for quantitative, real-time analysis of PARP trapping.
- Assessing PARPi efficacy and resistance in vitro and in vivo models.
Main Results:
- The FRET biosensor successfully enabled real-time, single-cell analysis of PARP trapping dynamics.
- FLIM revealed dose-dependent PARP trapping and differentiated the efficiencies of four clinical PARPi.
- Reduced PARP trapping was observed in PARPi-resistant ovarian cancer models.
Conclusions:
- The developed FRET biosensor offers unprecedented insights into PARP trapping mechanisms and PARPi resistance.
- This technology can help elucidate resistance pathways and guide the development of more effective PARPi therapies.
- The biosensor has significant implications for advancing personalized treatment strategies for ovarian cancer patients.
