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In Vivo Efficacy Testing of Peptide Receptor Radionuclide Therapy Radiosensitization Using Olaparib.
Danny Feijtel1,2, Thom G A Reuvers1,2, Christine van Tuyll-van Serooskerken2
1Department of Radiology and Nuclear Medicine, Erasmus MC Cancer Institute, Erasmus University Medical Center, 3015 GD Rotterdam, The Netherlands.
Cancers
|February 11, 2023
Summary
Combining peptide receptor radionuclide therapy (PRRT) with olaparib showed tumor-type dependent efficacy in neuroendocrine tumors (NETs). Molecular stratification is needed to predict patient response to this combination therapy.
Area of Science:
- Oncology
- Radiotherapy
- Molecular Biology
Background:
- Peptide receptor radionuclide therapy (PRRT) using [177Lu]Lu[DOTA0-Tyr3]octreotate treats metastasized neuroendocrine tumors (NETs).
- PRRT efficacy is limited, as most patients are not cured, highlighting the need for potentiating strategies.
- DNA damage repair inhibition is a potential strategy to enhance PRRT effectiveness.
Purpose of the Study:
- To evaluate the in vivo efficacy of combining PRRT with the PARP inhibitor olaparib.
- To determine if this combination therapy improves therapeutic outcomes in xenografted mouse models of NETs.
Main Methods:
- Utilized two different xenografted mouse models for in vivo validation.
- Administered combination therapy of [177Lu]Lu[DOTA0-Tyr3]octreotate and olaparib.
- Assessed therapeutic efficacy and anti-tumor response.
Main Results:
- Combination therapy demonstrated increased therapeutic efficacy in only one of the two tested xenograft models.
- The anti-tumor response to the combination of PRRT and olaparib was found to be tumor-type dependent.
- No significant therapeutic benefit was observed in the second model.
Conclusions:
- The combination of PRRT and PARP inhibition with olaparib shows variable efficacy in different NET models.
- Molecular stratification of tumors is crucial for predicting clinical benefit from combining PARP inhibition with PRRT.
- Further research is needed to identify biomarkers for patient selection.
