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

NCT04846933 — Not applicable, Recruiting, 200 participants, Turku University Hospital

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Integration of Multiple Data Levels to Improve Diagnosis, Predict Treatment Response and Suggest Targets to Overcome Therapy Resistance in High-grade Serous Ovarian Cancer

Registry	NCT04846933, acronym DECIDER
Status	Recruiting
Phase	Not applicable
Study type	Interventional; non randomized, parallel, masking: none, basic science
Enrollment	200 (Estimated)
Sponsor	Turku University Hospital (Other gov); collaborators: University of Helsinki
Conditions	High Grade Ovarian Serous Adenocarcinoma, High Grade Serous Carcinoma
Interventions	WGS and RNA sequencing, circulating tumor DNA (ctDNA), FDG PET/CT imaging (Genetic, diagnostic test)
Dates	start 2012-02-01, primary completion 2027-12-01 (estimated), completion 2029-12-01 (estimated), first posted 2021-04-15, last updated 2025-01-16
Locations	1 site in Finland

-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.

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+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.

+Arms and interventions

Arm	Type	Interventions	Description
HGSOC patients treated with Neoadjuvant chemotherapy (NACT)	Other	Genetic: WGS and RNA sequencing; Genetic: circulating tumor DNA (ctDNA); Diagnostic Test: FDG PET/CT imaging	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.
HGSOC patients treated with primary debulking surgery (PDS)	Other	Genetic: WGS and RNA sequencing; Genetic: circulating tumor DNA (ctDNA); Diagnostic Test: FDG PET/CT imaging	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.

WGS and RNA sequencing (Genetic)
circulating tumor DNA (ctDNA) (Genetic)
FDG PET/CT imaging (Diagnostic test)

+Outcome measures

Primary outcomes

Successful clinical translation [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 [5 years]: Proportion of patients whose disease outcome (PFS, OS) is predicted correctly with digital histopathology images, genomic data and routine laboratory values

Secondary outcomes

Successful validation of potentially druggable genetic alterations [5 years]: Number of potentially druggable genetic alterations found and validated with in-vitro methods
Successful prediction of genomic features from tumor histology [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 [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 [5 years]: Predictive power of the updated CRS at interval surgery is compared with traditional CRS

+Eligibility

Sex: Female, ages: 18 Years to any

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.

+Locations (1)

Facility	City	Country	Status
Turku University Hospital	Turku	Finland	Recruiting

+Publications

Results publication: 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 40885189
Results publication: Lahtinen 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 37207655

+Investigators

Sampsa Hautaniemi, DTech, Prof, Study director, University of Helsinki
Johanna Hynninen, MD, PhD, Principal investigator, Turku University Hospital