Multi-layer Data to Improve Diagnosis, Predict Therapy Resistance and Suggest Targeted Therapies in HGSOC (DECIDER)
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| ClinicalTrials.gov Identifier: NCT04846933 |
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Recruitment Status :
Recruiting
First Posted : April 15, 2021
Last Update Posted : June 18, 2023
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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, 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.
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.
| Condition or disease | Intervention/treatment |
|---|---|
| High Grade Ovarian Serous Adenocarcinoma High Grade Serous Carcinoma | Genetic: WGS and RNA sequencing Genetic: circulating tumor DNA (ctDNA) Diagnostic Test: FDG PET/CT imaging |
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 cultures from cancer patients in clinical care.
| Study Type : | Observational |
| Estimated Enrollment : | 200 participants |
| Observational Model: | Cohort |
| Time Perspective: | Prospective |
| Official Title: | Integration of Multiple Data Levels to Improve Diagnosis, Predict Treatment Response and Suggest Targets to Overcome Therapy Resistance in High-grade Serous Ovarian Cancer |
| Actual Study Start Date : | February 1, 2012 |
| Estimated Primary Completion Date : | December 2027 |
| Estimated Study Completion Date : | December 2029 |
| Group/Cohort | Intervention/treatment |
|---|---|
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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. |
Genetic: WGS and RNA sequencing Genetic: circulating tumor DNA (ctDNA) Diagnostic Test: FDG PET/CT imaging |
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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.
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Genetic: WGS and RNA sequencing Genetic: circulating tumor DNA (ctDNA) |
- 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.
- 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
- Successful validation of potentially druggable genetic alterations [ Time Frame: 5 years ]Number of potentially druggable genetic alterations found and validated with in-vitro methods
- Successful prediction of genomic features from tumor histology [ Time Frame: 5 years ]Number of genomic features that can be successfully recognized from tumor histology
- 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
- 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
Biospecimen Retention: Samples With DNA
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| Ages Eligible for Study: | 18 Years and older (Adult, Older Adult) |
| Sexes Eligible for Study: | Female |
| Accepts Healthy Volunteers: | No |
| Sampling Method: | Non-Probability Sample |
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.
To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.
Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT04846933
| Contact: Johanna Hynninen | +358 50 5383554 | johanna.hynninen@utu.fi | |
| Contact: Sampsa Hautaniemi | +358503364765 | sampsa.hautaniemi@helsinki.fi |
| Finland | |
| Turku University Hospital | Recruiting |
| Turku, Finland, 20520 | |
| Contact: Johanna Hynninen 0505383554 johanna.hynninen@utu.fi | |
| Principal Investigator: Johanna Hynninen, MD, PhD | |
| Study Director: | Sampsa Hautaniemi, DTech, Prof | University of Helsinki | |
| Principal Investigator: | Johanna Hynninen, MD, PhD | Turku University Hospital |
| Responsible Party: | Turku University Hospital |
| ClinicalTrials.gov Identifier: | NCT04846933 |
| Other Study ID Numbers: |
TO7/003/21 965193 ( Other Grant/Funding Number: EU HORIZON 2020 ) |
| First Posted: | April 15, 2021 Key Record Dates |
| Last Update Posted: | June 18, 2023 |
| Last Verified: | June 2023 |
| Studies a U.S. FDA-regulated Drug Product: | No |
| Studies a U.S. FDA-regulated Device Product: | No |
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chemoresistance personalized medicine WGS ctDNA digital pathology |
FDG PET/CT bioinformatics AI ovarian cancer tumor evolution |
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Cystadenocarcinoma, Serous Adenocarcinoma Carcinoma Neoplasms, Glandular and Epithelial |
Neoplasms by Histologic Type Neoplasms Cystadenocarcinoma Neoplasms, Cystic, Mucinous, and Serous |