Repurposing Ceritinib Induces DNA Damage and Enhances PARP Inhibitor Responses in High-Grade Serous Ovarian Carcinoma

Abstract

PARP inhibitors (PARPi) have activity in homologous recombination (HR) repair-deficient, high-grade serous ovarian cancers (HGSOC). However, even responsive tumors develop PARPi resistance, highlighting the need to delay or prevent the appearance of PARPi resistance. Here, we showed that the ALK kinase inhibitor ceritinib synergizes with PARPis by inhibiting complex I of the mitochondrial electron transport chain, which increases production of reactive oxygen species (ROS) and subsequent induction of oxidative DNA damage that is repaired in a PARP-dependent manner. In addition, combined treatment with ceritinib and PARPi synergized in HGSOC cell lines irrespective of HR status, and a combination of ceritinib with the PARPi olaparib induced tumor regression more effectively than olaparib alone in HGSOC patient-derived xenograft (PDX) models. Notably, the ceritinib and olaparib combination was most effective in PDX models with preexisting PARPi sensitivity and was well tolerated. These findings unveil suppression of mitochondrial respiration, accumulation of ROS, and subsequent induction of DNA damage as novel effects of ceritinib. They also suggest that the ceritinib and PARPi combination warrants further investigation as a means to enhance PARPi activity in HGSOC, particularly in tumors with preexisting HR defects.

Significance: The kinase inhibitor ceritinib synergizes with PARPi to induce tumor regression in ovarian cancer models, suggesting that ceritinib combined with PARPi may be an effective strategy for treating ovarian cancer.

Footnotes

Note: Supplementary data for this article are available at Cancer Research Online (http://cancerres.aacrjournals.org/).

Cancer Res 2022;82:307–19

Received March 5, 2021.Revision received August 5, 2021.Accepted November 15, 2021.Published first November 22, 2021.©2021 The Authors; Published by the American Association for Cancer Research

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs International 4.0 License.

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