Prospective Validation of an Ex Vivo, Patient-Derived 3D Spheroid Model for Response Predictions in Newly Diagnosed Ovarian Cancer

Abstract

Although 70–80% of newly diagnosed ovarian cancer patients respond to first-line therapy, almost all relapse and five-year survival remains below 50%. One strategy to increase five-year survival is prolonging time to relapse by improving first-line therapy response. However, no biomarker today can accurately predict individual response to therapy. In this study, we present analytical and prospective clinical validation of a new test that utilizes primary patient tissue in 3D cell culture to make patient-specific response predictions prior to initiation of treatment in the clinic. Test results were generated within seven days of tissue receipt from newly diagnosed ovarian cancer patients obtained at standard surgical debulking or laparoscopic biopsy. Patients were followed for clinical response to chemotherapy. In a study population of 44, the 32 test-predicted Responders had a clinical response rate of 100% across both adjuvant and neoadjuvant treated populations with an overall prediction accuracy of 89% (39 of 44, p < 0.0001). The test also functioned as a prognostic readout with test-predicted Responders having a significantly increased progression-free survival compared to test-predicted Non-Responders, p = 0.01. This correlative accuracy establishes the test’s potential to benefit ovarian cancer patients through accurate prediction of patient-specific response before treatment.

Establishment and characterization of an in vitro 3D ovarian cancer model for drug screening assays

“…The results obtained indicated that the breast cancer spheroid model was not only predictive but might also be selective in discerning ineffective from effective treatment options. 48 Shuford et al 49 using ULA plates for spheroids generation, developed and validated a 7 days test to make patient-specific response predictions prior to initiation of ovarian cancer treatment in the clinic. 49 In a study population of 44, Kamilla Swiech https://orcid.org/0000-0002-4811-9751…”

Zebrafish Avatars towards Personalized Medicine—A Comparative Review between Avatar Models

“…In a very recent study with ovarian cancer, spheroids from 92 patients were generated in 24 h and then treated for 72 h with first-and second-line therapies. By comparing patient clinical responses with the spheroid tests, the authors show an outstanding prediction efficiency of 89% [34]. However, despite being 3D, most spheroids lack the original architecture, as well as stromal and immune components, which are crucial modulators of drug response.…”

“…To generate patient-derived spheroids, tumor pieces of freshly collected tissues are dissociated (partially or completely) and then cultured either in low adhesion plates or embedded in matrigel [32][33][34][35]. In a very recent study with ovarian cancer, spheroids from 92 patients were generated in 24 h and then treated for 72 h with first-and second-line therapies.…”

Modeling Immune Checkpoint Inhibitor Efficacy in Syngeneic Mouse Tumors in an Ex Vivo Immuno-Oncology Dynamic Environment

“…Microfluidic platforms for tumor slices [ 20 , 21 , 22 , 23 ] and bioprinting technologies have also emerged [ 24 ], as have systems that model angiogenesis, metastasis, extravasation, and other phenomena [ 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 ]. While these systems have shown utility in modeling chemotherapeutic responses and immune checkpoint behavior, most are non-perfused systems that do not capture the dynamics of lymphocyte migration and drug transport [ 34 ], and their study is often of limited duration due to a rapid decline in viability beyond 24–72 h [ 35 , 36 ]. An urgent need remains for engineered platforms capable of supporting viable tumor fragments over a longer time frame, accommodating dynamic interactions between lymphocytes and tumors, and enabling real-time imaging in order to quantify tumor killing and lymphocyte infiltration in response to ICI treatments.…”