Multi-layer Data to Improve Diagnosis, Predict Therapy Resistance and Suggest Targeted Therapies in HGSOC (DECIDER)
Integration of Multiple Data Levels to Improve Diagnosis, Predict Treatment Response and Suggest Targets to Overcome Therapy Resistance in High-grade Serous Ovarian Cancer
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.
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
Specific aims include:
- Develop tools and methods for personalized medicine approaches to cancer patients.
- Develop open-source visualization and interpretation software that facilitate clinical decision making via data integration and interpretation of multilevel data from cancer patients.
- Rapidly identify HGSOC patients who are likely to respond poorly to current therapies combining information on digitalized histopathology samples, genomic and clinical data with AI methods.
- Deploy validated personalized medicine treatment options using longitudinal measurement and ex vivo organoid cultures from cancer patients in clinical care.
Study Type
Study Type
Enrollment (Estimated)
Enrollment
Phase
Phase
- Not Applicable
Contacts and Locations
Study Contact
Study Contact
- Name: Johanna Hynninen
- Phone Number: +358 50 5383554
- Email: johanna.hynninen@utu.fi
Study Contact Backup
- Name: Sampsa Hautaniemi
- Phone Number: +358503364765
- Email: sampsa.hautaniemi@helsinki.fi
Study Locations
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-
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Turku, Finland, 20520
- Recruiting
- Turku University Hospital
-
Contact:
- Johanna Hynninen
- Phone Number: 0505383554
- Email: johanna.hynninen@utu.fi
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Contact:
- Johanna Hynninen, MD, PhD
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-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Study Population
Description
Inclusion Criteria:
- 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
Exclusion Criteria:
- 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.
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Basic Science
- Allocation: Non-Randomized
- Interventional Model: Parallel Assignment
- Masking: None (Open Label)
Number of Arms
Arms and Interventions
Participant Group / ArmParticipant Group / Arm |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
Other: HGSOC patients treated with Neoadjuvant chemotherapy (NACT)
Diagnostic laparoscopy followed with 3-4 cycles of platinum-taxane NACT and interval debulking surgery (IDS). Treatment response is monitored with FDG PET/CT. IDS is followed by standard adjuvant therapy (ESGO/ESMO + local guidelines). Digital H&E slides and WGS, RNAseq are obtained from performed surgeries including relapse operations/ascites drainages. Patients are followed with longitudinal ctDNA sampling. |
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Other: HGSOC patients treated with primary debulking surgery (PDS)
PDS is followed by standard adjuvant therapy (ESGO/ESMO + local guidelines).
Digital H&E slides and WGS, RNAseq obtained from PDS and possible relapse operations/ascites drainages when performed.
Patients are followed with longitudinal ctDNA sampling.
|
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Successful clinical translation
Time Frame: 5 years
|
The magnitude of successful clinical translation is measured by the number of times project-derived personalized medicine has impacted patients care by application of novel and existing biomarkers and therapies.
|
5 years
|
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Successful prediction of patient outcome with AI methods
Time Frame: 5 years
|
Proportion of patients whose disease outcome (PFS, OS) is predicted correctly with digital histopathology images, genomic data and routine laboratory values
|
5 years
|
Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Successful validation of potentially druggable genetic alterations
Time Frame: 5 years
|
Number of potentially druggable genetic alterations found and validated with in-vitro methods
|
5 years
|
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Successful prediction of genomic features from tumor histology
Time Frame: 5 years
|
Number of genomic features that can be successfully recognized from tumor histology
|
5 years
|
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Prediction of primary treatment response from tumor histology using H&E stained whole slide images and AI-based methods
Time Frame: 5 years
|
Number of patients whose outcome (primary therapy outcome, PFS) is predicted correctly
|
5 years
|
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Establishment of an updated version of Chemoresponse score (CRS) for measuring histological effect in tumor tissue after chemotherapy
Time Frame: 5 years
|
Predictive power of the updated CRS at interval surgery is compared with traditional CRS
|
5 years
|
Collaborators and Investigators
Sponsor
Sponsor
Collaborators
Collaborators
Investigators
Investigators
- Study Director: Sampsa Hautaniemi, DTech, Prof, University of Helsinki
- Principal Investigator: Johanna Hynninen, MD, PhD, Turku University Hospital
Publications and helpful links
Helpful Links
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Estimated)
Primary Completion
Study Completion (Estimated)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Keywords
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- TO7/003/21
- 965193 (Other Grant/Funding Number: EU HORIZON 2020)
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
product manufactured in and exported from the U.S.
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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