Scholarlink

<p>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.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

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

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年8月30日

查看全文
  • Esmee Koedoot,
  • Dieudonné J. van der Meer,
  • Anne M. van Altena,
  • Lieke J. Ceton,
  • Timothy J. P. Sijsenaar,
  • Marta G. Montero,
  • Fanny Grillet,
  • Jurgen M. J. Piek,
  • Ruud L. M. Bekkers,
  • Maurice J. D. L. van der Vorst,
  • Auke M. T. Huijben,
  • Astrid Baalbergen,
  • Kevin G. J. A. Voogdt,
  • Loes Verhoeven,
  • Huberdina P. M. Smedts,
  • Klaus Weber,
  • Hans Marten Hazelbag,
  • Tjalling Bosse,
  • Els L. van Persijn-van Meerten,
  • Cornelis D. de Kroon,
  • Leo Price,
  • Willemijn Vader,
  • Judith R. Kroep,
  • Nelleke P. B. Ottevanger

摘要

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.