1196P - Organoid growth-based oncological sensitivity test (OncoSensi) for predicting adjuvant therapy outcomes in ovarian cancer patients

Background

Epithelial ovarian cancer (EOC) often recurs despite platinum-based (Carboplatin/Paclitaxel) first-line treatments, impacting over 70% of patients within 5 years. To address this, researchers use patient-derived organoids (PDOs) to assess drug sensitivity, aiming to stratify patients into resistant and sensitive groups. However, traditional metrics like AUC and IC₅₀ lack accuracy in predicting clinical outcomes. This study introduces an organoid growth-based Oncological Sensitivity Test (OncoSensi), which employs a PDO growth rate-based approach to improve the prediction of adjuvant therapy outcomes, particularly recurrence, in EOC patients.

Methods

Ovarian cancer PDOs were extracted from surgical tissue and cultured on the surface of a 384-pillar plate to form an organoid array for high-throughput screening. Drug sensitivity testing, including the measurement of PDO growth rate, was completed within a 10-day timeframe and reported to medical staff. We cultured PDOs from a total of 169 ovarian cancer patients and subsequently conducted drug sensitivity analyses. Among these patients, 95 were evaluated for the outcomes of first-line anticancer drug treatment. To validate OncoSensi, we compared its predictive performance with that of existing drug sensitivity tests.

Results

The recurrence rate within one year for responder groups using OncoSensi is 4.762%, significantly lower than the 27.778% recurrence rate observed with the previous sensitivity test. Conversely, for non-responder groups, the recurrence rate within one year with OncoSensi is 41.509%, notably higher than the 21.951% recurrence rate identified by the previous sensitivity test. Consequently, OncoSensi demonstrates more than two times the accuracy in prediction compared to the previous method.

Conclusions

Therefore, the proposed OncoSensi can be useful in predicting the recurrence of ovarian cancer by analyzing the sensitivity of first-line anticancer drugs (paclitaxel and carboplatin) and can be applied to precision medical platforms.

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

D.W. Lee.

Funding

Medical & Bio Decision.

Disclosure

All authors have declared no conflicts of interest.