Multi-layer Data to Improve Diagnosis, Predict Therapy Resistance and Suggest Targeted Therapies in HGSOC

Recruiting now · Not applicable

Conditions studied: High Grade Ovarian Serous Adenocarcinoma, High Grade Serous Carcinoma

In brief

Chemotherapy resistance is the greatest contributor to mortality in advanced cancers and severe challenges remain in finding effective treatment modalities to cancer patients with metastasized and relapsed disease. High-grade serous ovarian cancer (HGSOC) is typically diagnosed at a stage where the disease is already widely spread to the abdomen and current standard of practice treatment consists of surgery followed by platinum-taxane based chemotherapy and maintenance therapy. While 90% of HGSOC patients show no clinically detectable signs of cancer after surgery and chemotherapy, only 43% of the patients are alive five years after diagnosis because of chemoresistant cancer. This prospective, observational trial focuses on revealing major mechanisms causing chemoresistance in HGSOG patients and derive personalized treatment regimens for chemotherapy resistant HGSOC patients. The investigators recruit newly diagnosed advanced stage HGSOC patients who are then thoroughly followed during their cancer treatment. Longitudinal sampling includes digitalized H\&E stained histology slides mainly collected during routine diagnostics, fresh tumor \& ascites samples for next-generation sequencing/proteomics (WGS, RNA-seq, DNA-methylation, ATAC-seq, ChIP-seq, mass cytometry, etc.) and ex vivo experiments, plasma samples for circulating tumor DNA (ctDNA) analyses. Broad range of clinical parameters such as laboratory and radiologic parameters (e.g., FDG PET/CT), given cancer treatments and their outcomes are collected. Radiomic analyses are performed to PET/CT and CT scans. Long-term patient derived organoid lines are established from fresh tumor tissues. Actionable genomic alterations are searched. The general objective is to establish a clinically useful precision oncology approach based on multi-level data collected in longitudinal setting, and translate the most potent and validated discoveries into clinical use. DECIDER project will produce AI-powered diagnostic tools, cutting-edge software platforms for clinical decision-making, novel data analysis \& integration methods, and high-throughput ex vivo drug screening approaches.

Key facts

Study ID

NCT04846933

Run by

Turku University Hospital

People needed

200

Starts

2012-02-01

Expected to finish

2029-12-01

Last updated by the study team

2025-01-16

Who can join

Age: 18 and older. Sex: female. Healthy volunteers: not accepted.

You may qualify if…

• Patients with a suspected ovarian cancer diagnosis treated at the Turku University Hospital
• Ability to understand and the willingness to sign a written informed consent document

You may not qualify if…

• Age <18 years, too poor condition for active treatment (surgery, chemotherapy)
• FDG PET/CT scan is not performed for patients with diabetes mellitus and poor glucose balance.

Where it is running

• Turku University Hospital — Turku, Finland (enrolling)

Full record on ClinicalTrials.gov

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