Ex vivo 3D micro-tumour testing platform for predicting clinical response to platinum-based therapy in patients with high-grade serous ovarian cancer.

用于预测高级别浆液性卵巢癌患者对铂类药物治疗的临床反应的体外 3D 微肿瘤测试平台

阅读:3
作者:Koedoot Esmee, van der Meer Dieudonné J, van Altena Anne M, Ceton Lieke J, Sijsenaar Timothy J P, Montero Marta G, Grillet Fanny, Piek Jurgen M J, Bekkers Ruud L M, van der Vorst Maurice J D L, Huijben Auke M T, Baalbergen Astrid, Voogdt Kevin G J A, Verhoeven Loes, Smedts Huberdina P M, Weber Klaus, Hazelbag Hans Marten, Bosse Tjalling, van Persijn-van Meerten Els L, de Kroon Cornelis D, Price Leo, Vader Willemijn, Kroep Judith R, Ottevanger Nelleke P B
Around 20% of patients with primary high-grade ovarian cancer do not respond to chemotherapy, but predictive biomarkers are lacking. The purpose of the current study is to establish and clinically validate an ex vivo 3D micro-tumour testing platform that predicts patient-specific response to standard of care chemotherapy. 104 ovarian cancer patients with malignant ascites were included in the study. Micro-tumours enriched from ascites were exposed to standard of care chemo- and targeted therapies, imaged using a high-content 3D screening platform. Morphological features were extracted for sensitivity profiling. A linear regression model was trained to predict the patient's CA125 decay rates, which were correlated to clinical outcomes (patient CA125 decay rate, change in tumour size, and progression-free survival). Isolated micro-tumours recapitulated ovarian cancer markers. A significant correlation (R = 0.77) between predicted and clinical CA125 rates was observed. Patients with predicted high ex vivo sensitivity to carboplatin/paclitaxel demonstrated significantly increased PFS and decreased tumour size. Complementary, patient-specific response profiles for second-line therapies were calculated and presented in integrated reports. In conclusion, an ex vivo 3D micro-tumour testing platform was established that predicted clinical response to neo-adjuvant chemotherapy in ovarian cancer patients and measured patient-specific responses to second-line therapies as a proof-of-concept. The platform enabled stratification of responders vs non-responders and has the potential to support informed treatment decisions after prospective validation. Results are generated within 2 weeks after sample collection, aligning with the clinical time frame for treatment decision-making.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。