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
2 other identifiers
interventional
200
1 country
1
Brief Summary
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.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for not_applicable
Started Feb 2012
Longer than P75 for not_applicable
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
Click on a node to explore related trials.
Study Timeline
Key milestones and dates
Study Start
First participant enrolled
February 1, 2012
CompletedFirst Submitted
Initial submission to the registry
April 12, 2021
CompletedFirst Posted
Study publicly available on registry
April 15, 2021
CompletedPrimary Completion
Last participant's last visit for primary outcome
December 1, 2027
ExpectedStudy Completion
Last participant's last visit for all outcomes
December 1, 2029
January 16, 2025
January 1, 2025
15.8 years
April 12, 2021
January 14, 2025
Conditions
Keywords
Outcome Measures
Primary Outcomes (2)
Successful clinical translation
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
Successful prediction of patient outcome with AI methods
Proportion of patients whose disease outcome (PFS, OS) is predicted correctly with digital histopathology images, genomic data and routine laboratory values
5 years
Secondary Outcomes (4)
Successful validation of potentially druggable genetic alterations
5 years
Successful prediction of genomic features from tumor histology
5 years
Prediction of primary treatment response from tumor histology using H&E stained whole slide images and AI-based methods
5 years
Establishment of an updated version of Chemoresponse score (CRS) for measuring histological effect in tumor tissue after chemotherapy
5 years
Study Arms (2)
HGSOC patients treated with Neoadjuvant chemotherapy (NACT)
OTHERDiagnostic 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.
HGSOC patients treated with primary debulking surgery (PDS)
OTHERPDS 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.
Interventions
Eligibility Criteria
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.
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- Turku University Hospitallead
- University of Helsinkicollaborator
Study Sites (1)
Turku University Hospital
Turku, 20520, Finland
Related Publications (2)
Afenteva D, Yu R, Rajavuori A, Salvadores M, Launonen IM, Lavikka K, Zhang K, Pirttikoski A, Marchi G, Jamalzadeh S, Isoviita VM, Li Y, Micoli G, Erkan EP, Falco MM, Ungureanu D, Lahtinen A, Oikkonen J, Hietanen S, Vaharautio A, Sur I, Virtanen A, Farkkila A, Hynninen J, Muranen TA, Taipale J, Hautaniemi S. Multi-omics analysis reveals the attenuation of the interferon pathway as a driver of chemo-refractory ovarian cancer. Cell Rep Med. 2025 Sep 16;6(9):102316. doi: 10.1016/j.xcrm.2025.102316. Epub 2025 Aug 29.
PMID: 40885189DERIVEDLahtinen A, Lavikka K, Virtanen A, Li Y, Jamalzadeh S, Skorda A, Lauridsen AR, Zhang K, Marchi G, Isoviita VM, Ariotta V, Lehtonen O, Muranen TA, Huhtinen K, Carpen O, Hietanen S, Senkowski W, Kallunki T, Hakkinen A, Hynninen J, Oikkonen J, Hautaniemi S. Evolutionary states and trajectories characterized by distinct pathways stratify patients with ovarian high grade serous carcinoma. Cancer Cell. 2023 Jun 12;41(6):1103-1117.e12. doi: 10.1016/j.ccell.2023.04.017. Epub 2023 May 18.
PMID: 37207655DERIVED
Related Links
MeSH Terms
Conditions
Interventions
Condition Hierarchy (Ancestors)
Intervention Hierarchy (Ancestors)
Study Officials
- STUDY DIRECTOR
Sampsa Hautaniemi, DTech, Prof
University of Helsinki
- PRINCIPAL INVESTIGATOR
Johanna Hynninen, MD, PhD
Turku University Hospital
Central Study Contacts
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- NON RANDOMIZED
- Masking
- NONE
- Purpose
- BASIC SCIENCE
- Intervention Model
- PARALLEL
- Sponsor Type
- OTHER GOV
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
April 12, 2021
First Posted
April 15, 2021
Study Start
February 1, 2012
Primary Completion (Estimated)
December 1, 2027
Study Completion (Estimated)
December 1, 2029
Last Updated
January 16, 2025
Record last verified: 2025-01