Periodic Reporting for period 3 - DECIDER (Improved clinical decisions via integrating multiple data levels to overcome chemotherapy resistance in high-grade serous ovarian cancer)
Periodo di rendicontazione: 2024-02-01 al 2025-07-31
Ovarian cancer takes the lives of over 40,000 women in Europe every year, and the most common type—high-grade serous ovarian cancer (HGSOC)—is also the hardest to treat. While many patients respond well to chemotherapy at first, the cancer almost always comes back, often within a few years, and survival rates remain below 40% after five years. One reason is that HGSOC is usually diagnosed late, when it has already spread through the abdomen and consists of billions of cancer cells with many genetic changes that help them resist treatment. This makes it extremely difficult to find drugs or combinations that work for the long term. To improve outcomes, we need a better understanding of how chemotherapy affects the cancer cells and why some patients respond better than others. This knowledge could pave the way for more personalised and effective treatments.
In the DECIDER project, our aim is to develop tools to discover these more effective treatment options for patients with HGSOC. For this, we study why chemotherapy often stops working by collecting tissue samples from DECIDER study patients and analysing them using advanced technologies that reveal changes in DNA, RNA, and other cellular mechanisms. We combine this information with histopathological and radiological images as well as clinical data to build a detailed picture of the tumour and its evolution during the course of the disease. Using this knowledge, we work to identify new treatment options for patients with specific genetic changes, often based on ex vivo cell model validations. We contribute to suggesting possible therapies for relapsed patients who no longer have standard-of-care treatment options available.
In the DECIDER project, our aim is to develop tools to discover these more effective treatment options for patients with HGSOC. For this, we study why chemotherapy often stops working by collecting tissue samples from DECIDER study patients and analysing them using advanced technologies that reveal changes in DNA, RNA, and other cellular mechanisms. We combine this information with histopathological and radiological images as well as clinical data to build a detailed picture of the tumour and its evolution during the course of the disease. Using this knowledge, we work to identify new treatment options for patients with specific genetic changes, often based on ex vivo cell model validations. We contribute to suggesting possible therapies for relapsed patients who no longer have standard-of-care treatment options available.
The DECIDER project started in February 2021 and will end in July 2026. The main results of the past 54 months of the project are detailed in the following.
The basis for all research in the DECIDER project is the prospective collection of tissue samples of HGSOC patients. At the Turku University Hospital in Finland, we have collected a very large, high-quality, longitudinal dataset of tissue samples, body fluids, and relevant clinical data from >400 HGSOC patients. This cohort includes patients who were recruited before February 2021 in the HERCULES study and received follow-up in the DECIDER project. The collected tissues are prepared for 1) tissue dissociation and processing as organoids and tumoroids for ex vivo validation, 2) analysis of digitalised haematoxylin and eosin (H&E) stained histopathological samples, and 3) DNA or RNA extraction and subsequent sequencing.
Whole genome sequencing data, as well as information about gene expression (RNA sequencing), are available for almost all included patients. Furthermore, we examine DNA methylation and circulating tumour DNA in plasma samples. We analyse the sequenced data to reveal changes in the patients’ genomes. This provides insight into how the tumour genome changes in response to therapy. After analysing the sequencing results, critical information is reported back to the patients’ treating clinicians. We hold regular virtual molecular tumour board (vMTB) meetings, focusing particularly on interpreting druggable targets identified in genomic data and validating them at the RNA expression level.
During the third reporting period, we further developed and validated our deep learning–based AI models to predict the chemotherapy response of HGSOC patients based on histopathological images of tumour tissues, as well as sequencing results. These tools are essential for the early identification of patients who are unlikely to benefit from standard therapy.
We have successfully grown 54 long-term organoid lines from patient samples collected in the DECIDER project. Those organoids are available for validation studies to the consortium and are the major ex vivo tool to evaluate the repurposing of drugs that were identified to be potentially usable as targets to treat resistant HGSOC.
The DECIDER patient cohort is not only large, but also longitudinal and multimodal. The open-source AI-based software Oncodash was developed to visualise all these clinical, sequencing, and histopathological data, as well as results from predictive models, and facilitate clinical decision-making based on the DECIDER findings. We furthermore published the Oncodash App Store, which serves as a centralised marketplace for sharing and distributing oncology-related software tools for the scientific community. The successful integration of DECIDER's tools into clinical workflows marks a significant achievement and is a crucial step toward personalised medicine in the treatment of HGSOC.
The basis for all research in the DECIDER project is the prospective collection of tissue samples of HGSOC patients. At the Turku University Hospital in Finland, we have collected a very large, high-quality, longitudinal dataset of tissue samples, body fluids, and relevant clinical data from >400 HGSOC patients. This cohort includes patients who were recruited before February 2021 in the HERCULES study and received follow-up in the DECIDER project. The collected tissues are prepared for 1) tissue dissociation and processing as organoids and tumoroids for ex vivo validation, 2) analysis of digitalised haematoxylin and eosin (H&E) stained histopathological samples, and 3) DNA or RNA extraction and subsequent sequencing.
Whole genome sequencing data, as well as information about gene expression (RNA sequencing), are available for almost all included patients. Furthermore, we examine DNA methylation and circulating tumour DNA in plasma samples. We analyse the sequenced data to reveal changes in the patients’ genomes. This provides insight into how the tumour genome changes in response to therapy. After analysing the sequencing results, critical information is reported back to the patients’ treating clinicians. We hold regular virtual molecular tumour board (vMTB) meetings, focusing particularly on interpreting druggable targets identified in genomic data and validating them at the RNA expression level.
During the third reporting period, we further developed and validated our deep learning–based AI models to predict the chemotherapy response of HGSOC patients based on histopathological images of tumour tissues, as well as sequencing results. These tools are essential for the early identification of patients who are unlikely to benefit from standard therapy.
We have successfully grown 54 long-term organoid lines from patient samples collected in the DECIDER project. Those organoids are available for validation studies to the consortium and are the major ex vivo tool to evaluate the repurposing of drugs that were identified to be potentially usable as targets to treat resistant HGSOC.
The DECIDER patient cohort is not only large, but also longitudinal and multimodal. The open-source AI-based software Oncodash was developed to visualise all these clinical, sequencing, and histopathological data, as well as results from predictive models, and facilitate clinical decision-making based on the DECIDER findings. We furthermore published the Oncodash App Store, which serves as a centralised marketplace for sharing and distributing oncology-related software tools for the scientific community. The successful integration of DECIDER's tools into clinical workflows marks a significant achievement and is a crucial step toward personalised medicine in the treatment of HGSOC.
The DECIDER project has achieved remarkable results that surpass the current state-of-the-art. By leveraging RNA sequencing and imaging data, the project uncovered cellular heterogeneity within HGSOC tumours and identified specific cell populations that exhibit resistance or sensitivity to chemotherapy. It has become increasingly clear that integrating multi-omics, imaging, and clinical data is necessary to better understand the molecular mechanisms driving chemotherapy resistance. With its large, multimodal dataset, the DECIDER project is optimally situated for such a comprehensive approach.
The vMTB's establishment has transformed clinical decision-making by enabling multidisciplinary teams to discuss and decide on personalised treatment plans based on genetic analyses. In the third reporting period alone, four of the patients discussed were referred to their hospital’s tumour board and the national FINPROVE trial. Recently, antibody-drug conjugates (ADCs) have emerged as a possible treatment option for HGSOC. DECIDER results have identified several patients who are now under consideration for this treatment. With the vMTB supported by DECIDER results, we can translate cutting-edge scientific results directly into treatment suggestions, demonstrating the project's impact on patient care.
In summary, the DECIDER project has achieved groundbreaking results with the potential to transform HGSOC treatment, bringing us closer to achieving truly personalised medicine. However, the success of these innovations depends on sustained investment in research, demonstration, and commercialisation, as well as a supportive regulatory environment. This will ensure that patients worldwide can benefit from the project's work.
The vMTB's establishment has transformed clinical decision-making by enabling multidisciplinary teams to discuss and decide on personalised treatment plans based on genetic analyses. In the third reporting period alone, four of the patients discussed were referred to their hospital’s tumour board and the national FINPROVE trial. Recently, antibody-drug conjugates (ADCs) have emerged as a possible treatment option for HGSOC. DECIDER results have identified several patients who are now under consideration for this treatment. With the vMTB supported by DECIDER results, we can translate cutting-edge scientific results directly into treatment suggestions, demonstrating the project's impact on patient care.
In summary, the DECIDER project has achieved groundbreaking results with the potential to transform HGSOC treatment, bringing us closer to achieving truly personalised medicine. However, the success of these innovations depends on sustained investment in research, demonstration, and commercialisation, as well as a supportive regulatory environment. This will ensure that patients worldwide can benefit from the project's work.