Purpose: The treatment of ovarian cancer poses a challenge since 70% of patients will relapse with incurable platinum resistant disease. Although ovarian cancers lack frequently-occurring driver mutations or amplifications, the study presented herein examines the concept of individualized therapy based on mate pair sequencing and protein expression in ovarian cancer patient-derived xenografts.

Experimental Procedure: Macrodissection of patient tumor was followed by genomic DNA isolation and next-generation sequencing using an Illumina Mate Pair protocol to identify structural genomic changes and copy number variations. Secondary analyses were carried out to select potential therapeutic targets among those. The tumors were also propagated intraperitoneally in immunocompromised mice and treated with standard chemotherapy or/and targeted therapy chosen based on genomic analyses.

Results: Mate pair analysis revealed that, in general, copy number changes (amplifications, gains and losses) were common in ovarian tumors and included genes potentially targetable. Tumors from early generation patient- derived xenografts showed a landscape of genomic aberrations identical to that of original patient tumor. One PDX model in which high expression of HER2 and copy number gains at RICTOR and AKT genetic loci were revealed, was treated with either chemotherapy and Pertuzumab/trastuzumab (HER2 inhibitors), MK-8669 (mTOR inhibitor) or MK-2206 (AKT inhibitor) or chemotherapy alone. Tumor size was measured by serial abdominal ultrasound and after 28 days, the final tumor size ratio compared to baseline was 0.23, 0.36, 0.55 and 0.56, respectively, indicating that the best response was seen in the combined chemotherapy and Pertuzumab/trastuzumab cohort and that was better than in the chemotherapy only cohort.

Conclusions: Patient-derived xenografts models in conjunction with genomic and protein analyses of patient tumors are valuable for testing of combination therapies including specific targeting drugs. This approach also provides actionable information for more tailored treatment of ovarian cancer patients.

Citation Format: Konstantinos Leventakos, Faye R. Harris, Lin Yang, Xiaonan Hou, Saravut Weroha, Irina V. Kovtun. Testing personalized therapies for ovarian cancer using mate pair genomic analysis and patient-derived xenografts [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4814. doi:10.1158/1538-7445.AM2017-4814