Development of novel approaches for the treatment of recurrent ovarian cancer
Creators: name: Mohammadali Pourmalekshah, Obeid
Publisher: name: No Publisher Supplied
Year: 2020

description: Ovarian cancer is among the five leading types of cancer incidence and has the highest mortality rate of all gynecologic malignancies in the US. The standard of care for this type of cancer is debulking surgery, followed by chemotherapy with a combination of platinum-based anticancer drugs and paclitaxel. Even though most ovarian tumors are sensitive to chemotherapy at the time of diagnosis, approximately 90% of patients after suboptimal resection and 70% of patients after optimal cytoreduction go on to experience relapse within 18–24 months. The main reason for this outcome is the late-stage diagnosis of ovarian cancer, which leads to tumor cell metastasis into the peritoneal cavity and the creation of tumorspheres. These tumorspheres are rich in cancer stem‐like cells (CSCs), are resistant to therapy, and are considered a significant source of relapse. Therefore, to tackle these challenges, we aimed at developing treatment methods than can eradicate the peritoneal CSC‐rich tumorspheres and inhibit relapse.The first part of this dissertation describes the development of a safe chemotherapeutic approach for patients who are candidates for debulking surgery. To achieve this goal, OVASC‐1 that is resistant to standard‐of‐care chemotherapy was obtained from a patient with ovarian carcinoma and recurrent disease. The most effective combination of drugs that could eradicate CSC‐rich tumorspheres at nanomolar levels was identified. Luciferase‐expressing OVASC‐1 cells were used to produce an ovarian cancer xenograft in the peritoneal cavity of nude mice and treated with the selected drug combination. Quantitative imaging was used to study the progression of the disease, and its response to therapy and histopathology was used to study abdominal tissues for any sign of toxicity. Our low‐dose intraperitoneal (IP) therapy approach effectively restricted the cytotoxic effects to the tumor cells in the peritoneal cavity, provided a complete response, and eliminated the chance of cancer relapse. These results encourage further investigation into this approach as a potential clinical application either as a first‐ or second-line therapy in cases of acquired resistance to cisplatin and paclitaxel.The next part of this dissertation describes a targeted stem cell-based non-surgical treatment strategy in patients who are not candidates for debulking surgery. These patients have unresectable tumors for reasons such as the patient’s age and the tumor location. For this purpose, different enzyme/prodrug systems for cancer gene therapy were examined to determine which is the most effective treatment against drug-resistant ovarian cancer cells. Next, the sensitivity of the OVASC-1 cells/spheroids to the metabolites of three enzyme/prodrug systems were assessed, and SN-38 was found to be the most potent drug. Adipose-derived stem cells (ASCs) with inherent tumor tropic properties were genetically engineered to express recombinant secretory human carboxylesterase-2 and nanoluciferase genes for disease therapy and quantitative imaging, respectively. The migration and localization of engineered ASCs in tumor stroma and necrotic regions were showed using bioluminescent imaging (BLI), magnetic resonance imaging (MRI), and histopathology studies. This migration and homing capacity of ASC provides a unique opportunity to deliver drugs to not only the tumor-supporting cells in the stroma but also the CSCs in the necrotic/hypoxic regions. The statistical analysis showed that the administration of the engineered ASCs in combination with the prodrug (Irinotecan) cured 4/5 mice (p&lt;0.00004), inhibited relapse, and provided a survival benefit (80%). The histopathology and hematology data did not show any toxicity to major intraperitoneal organs. Overall, our studies demonstrate the possibility of overcoming drug resistance in ovarian cancer by using the above-mentioned protocols.