Summary
To improve the poor clinical outcomes in high-grade serous ovarian carcinoma (HGSC), we need to understand the cancer cell-tumour microenvironment (TME) dynamic interactions upon disease evolution and treatment. In my proposed project, I will establish a unique TME-HGSC patient-derived organoid (PDO) multi-culture model system to identify and understand how the TME impacts treatment responses and how treatment resistance can be overcome.
To generate multi-culture PDO preclinical models of HGSC for the first time, I will use my own expertise in 3D culture and stromal cell isolation from patient-derived material, and I will integrate self-generated “TME units” with well-characterized HGSC PDOs established at the host laboratory. I will then use this model to study the chemotherapy-induced changes at the single cell level. I will compare the transcriptional states of the treated models to the interval/recurrent PDOs and correlate their in vitro treatment responses to the patient responses. I will predict strategies to increase the sensitivity of the cancer cells to the HGSC standard treatment by targeting the tumour-TME interactions or the cancer cells themselves without generating a more tumour-supportive TME, by using the multi-culture PDOs in high-throughput drug screens and subsequently integrating the generated data. Finally, I will functionally validate the predicted therapeutic strategies by CRISPR gene editing and drug treatment of the models.
I expect that my project will generate profound knowledge on the chemoresistance mechanisms in HGSC and provide the scientific community with a unique experimental model that incorporates the TME to state-of-the-art HGSC PDOs. In addition, this fellowship will allow me to enhance my international visibility through high-impact publications independent from my PhD supervisor and provide me with a great track record in obtaining independent funding, essential to successfully secure independent research grants in the future.
To generate multi-culture PDO preclinical models of HGSC for the first time, I will use my own expertise in 3D culture and stromal cell isolation from patient-derived material, and I will integrate self-generated “TME units” with well-characterized HGSC PDOs established at the host laboratory. I will then use this model to study the chemotherapy-induced changes at the single cell level. I will compare the transcriptional states of the treated models to the interval/recurrent PDOs and correlate their in vitro treatment responses to the patient responses. I will predict strategies to increase the sensitivity of the cancer cells to the HGSC standard treatment by targeting the tumour-TME interactions or the cancer cells themselves without generating a more tumour-supportive TME, by using the multi-culture PDOs in high-throughput drug screens and subsequently integrating the generated data. Finally, I will functionally validate the predicted therapeutic strategies by CRISPR gene editing and drug treatment of the models.
I expect that my project will generate profound knowledge on the chemoresistance mechanisms in HGSC and provide the scientific community with a unique experimental model that incorporates the TME to state-of-the-art HGSC PDOs. In addition, this fellowship will allow me to enhance my international visibility through high-impact publications independent from my PhD supervisor and provide me with a great track record in obtaining independent funding, essential to successfully secure independent research grants in the future.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101063359 |
| Start date: | 01-01-2023 |
| End date: | 31-12-2024 |
| Total budget - Public funding: | - 214 934,00 Euro |
Cordis data
Original description
To improve the poor clinical outcomes in high-grade serous ovarian carcinoma (HGSC), we need to understand the cancer cell-tumour microenvironment (TME) dynamic interactions upon disease evolution and treatment. In my proposed project, I will establish a unique TME-HGSC patient-derived organoid (PDO) multi-culture model system to identify and understand how the TME impacts treatment responses and how treatment resistance can be overcome.To generate multi-culture PDO preclinical models of HGSC for the first time, I will use my own expertise in 3D culture and stromal cell isolation from patient-derived material, and I will integrate self-generated “TME units” with well-characterized HGSC PDOs established at the host laboratory. I will then use this model to study the chemotherapy-induced changes at the single cell level. I will compare the transcriptional states of the treated models to the interval/recurrent PDOs and correlate their in vitro treatment responses to the patient responses. I will predict strategies to increase the sensitivity of the cancer cells to the HGSC standard treatment by targeting the tumour-TME interactions or the cancer cells themselves without generating a more tumour-supportive TME, by using the multi-culture PDOs in high-throughput drug screens and subsequently integrating the generated data. Finally, I will functionally validate the predicted therapeutic strategies by CRISPR gene editing and drug treatment of the models.
I expect that my project will generate profound knowledge on the chemoresistance mechanisms in HGSC and provide the scientific community with a unique experimental model that incorporates the TME to state-of-the-art HGSC PDOs. In addition, this fellowship will allow me to enhance my international visibility through high-impact publications independent from my PhD supervisor and provide me with a great track record in obtaining independent funding, essential to successfully secure independent research grants in the future.
Status
SIGNEDCall topic
HORIZON-MSCA-2021-PF-01-01Update Date
09-02-2023
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