Periodic Reporting for period 2 - DECIDER (Improved clinical decisions via integrating multiple data levels to overcome chemotherapy resistance in high-grade serous ovarian cancer)
Berichtszeitraum: 2022-08-01 bis 2024-01-31
Epithelial ovarian cancer kills more than 40,000 women in Europe each year. High-grade serous ovarian cancer (HGSOC) is the most common and most difficult-to-treat subtype of this disease. Despite initially good response to platinum and taxane, the HGSOC tumours typically develop chemotherapy resistance leading to relapses and 5-year survival is <40%. A reason for the chemotherapy resistance is that HGSOC is often diagnosed when it has already metastasised to the abdomen and the tumours consist of billions of cancer cells with numerous genomic aberrations in their genome, some of which causing the ability to overcome the chemotherapy effect. Accordingly, it is extremely difficult to find effective drugs or combinations of drugs that provide a lasting effect for the patients. Current understanding of many important questions, such as chemotherapy’s effect on the genomes and to what degree tumour genomes differ between poor and good responders, is insufficient to tailor treatment based on an HGSOC patient’s genome.
In the DECIDER project, our overall goal is to deliver tools that enable more effective and cost-efficient treatment of HGSOC patients. Firstly, our goal is to comprehensively characterise chemotherapy resistance mechanisms in HGSOC. To accomplish this goal, we prospectively collect samples from HGSOC patients who have given consent to the DECIDER study. These samples are then analysed with state-of-the-art measurement technologies to reveal aberrations at DNA, RNA or epigenetic levels. These data are combined with data from histopathological and functional imaging, as well as clinical records. Secondly, we will utilise the acquired knowledge and suggest effective treatments for HGSOC patient groups characterised by genomic aberrations.
Thus, an important part of the DECIDER activities is to suggest treatment options, if such exist, for relapsed patients without standard-of-care treatment options and belonging to the DECIDER study based on genomic information or ex vivo cell model systems.
In the DECIDER project, our overall goal is to deliver tools that enable more effective and cost-efficient treatment of HGSOC patients. Firstly, our goal is to comprehensively characterise chemotherapy resistance mechanisms in HGSOC. To accomplish this goal, we prospectively collect samples from HGSOC patients who have given consent to the DECIDER study. These samples are then analysed with state-of-the-art measurement technologies to reveal aberrations at DNA, RNA or epigenetic levels. These data are combined with data from histopathological and functional imaging, as well as clinical records. Secondly, we will utilise the acquired knowledge and suggest effective treatments for HGSOC patient groups characterised by genomic aberrations.
Thus, an important part of the DECIDER activities is to suggest treatment options, if such exist, for relapsed patients without standard-of-care treatment options and belonging to the DECIDER study based on genomic information or ex vivo cell model systems.
The DECIDER project started in February 2021 and will end in July 2026. The main results of the first 36 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 so far collected high-quality longitudinal tissue samples, body fluids, and relevant clinical data from 305 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, 2) analysis of digitalised haematoxylin and eosin (H&E) stained histopathological samples, and 3) DNA or RNA extraction and subsequent sequencing.
From almost all included patients, whole genome sequencing data as well as information about the expression of the genes (RNA sequencing) are available. Furthermore, we examine the methylation of DNA, and the so-called circulating tumour DNA from plasma samples. The sequenced data are analysed to reveal changes in the patients’ genomes. This gives us insides into how the genome of the tumour changes in response to therapy. After analysis of the sequencing results, critical information is regularly reported back to the treating clinicians of the patients. In the first 36 months alone, we reported back to the clinic relevant information for 14 of the HGSOC patients included in DECIDER.
In this reporting period, we have further developed and validated our deep learning-based AI model to predict HGSOC patients’ chemotherapy response based on histopathological slide images from tumour tissues as well as sequencing results. This tool is critical to identify patients unlikely to benefit from standard therapy, at the time of diagnosis.
We have also verified eight of the established long-term organoids from patient samples collected during the DECIDER project with sequencing, and preparations for experiments in mice are underway. These experiments will be 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 project already produced a large amount of data for each patient, like clinical, sequencing, and histopathological data, and results from predictive models. The open-source AI-based software Oncodash was finalised to visualise the different patient data and greatly facilitate clinical decision-making based on the DECIDER findings.
The successful integration of DECIDER's tools into clinical workflows marks a significant achievement, demonstrating the project's impact on patient care. This integration 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 so far collected high-quality longitudinal tissue samples, body fluids, and relevant clinical data from 305 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, 2) analysis of digitalised haematoxylin and eosin (H&E) stained histopathological samples, and 3) DNA or RNA extraction and subsequent sequencing.
From almost all included patients, whole genome sequencing data as well as information about the expression of the genes (RNA sequencing) are available. Furthermore, we examine the methylation of DNA, and the so-called circulating tumour DNA from plasma samples. The sequenced data are analysed to reveal changes in the patients’ genomes. This gives us insides into how the genome of the tumour changes in response to therapy. After analysis of the sequencing results, critical information is regularly reported back to the treating clinicians of the patients. In the first 36 months alone, we reported back to the clinic relevant information for 14 of the HGSOC patients included in DECIDER.
In this reporting period, we have further developed and validated our deep learning-based AI model to predict HGSOC patients’ chemotherapy response based on histopathological slide images from tumour tissues as well as sequencing results. This tool is critical to identify patients unlikely to benefit from standard therapy, at the time of diagnosis.
We have also verified eight of the established long-term organoids from patient samples collected during the DECIDER project with sequencing, and preparations for experiments in mice are underway. These experiments will be 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 project already produced a large amount of data for each patient, like clinical, sequencing, and histopathological data, and results from predictive models. The open-source AI-based software Oncodash was finalised to visualise the different patient data and greatly facilitate clinical decision-making based on the DECIDER findings.
The successful integration of DECIDER's tools into clinical workflows marks a significant achievement, demonstrating the project's impact on patient care. This integration is a crucial step toward personalised medicine in the treatment of HGSOC.
The DECIDER project has already achieved remarkable results that extend beyond the existing state of the art. The development of AI-driven predictive tools capable of assessing chemothera-py response from histopathology images represents a significant leap forward. By harnessing the power of RNA sequencing, the project has uncovered the cellular heterogeneity within HGSOC tumours, identifying specific cell populations that exhibit resistance or sensitivity to chemother-apy.
Integration of multi-omics data has enabled a better understanding of the molecular mecha-nisms driving chemotherapy resistance. This comprehensive approach facilitates the identifica-tion of personalised treatment options, marking a significant step towards truly personalised medicine in oncology. Additionally, the establishment of the virtual Molecular Tumour Board (vMTB) has transformed clinical decision-making, allowing multidisciplinary teams to discuss and decide on personalised treatment plans based on genetic analyses.
In summary, the DECIDER project has achieved groundbreaking results that have the potential to transform the treatment of HGSOC, bringing us closer to the goal of personalised medicine. The success of these innovations depends on continued investment in research, demonstration, commercialisation, and a supportive regulatory environment, ensuring that the benefits of the project's work can be realised by patients worldwide.
Integration of multi-omics data has enabled a better understanding of the molecular mecha-nisms driving chemotherapy resistance. This comprehensive approach facilitates the identifica-tion of personalised treatment options, marking a significant step towards truly personalised medicine in oncology. Additionally, the establishment of the virtual Molecular Tumour Board (vMTB) has transformed clinical decision-making, allowing multidisciplinary teams to discuss and decide on personalised treatment plans based on genetic analyses.
In summary, the DECIDER project has achieved groundbreaking results that have the potential to transform the treatment of HGSOC, bringing us closer to the goal of personalised medicine. The success of these innovations depends on continued investment in research, demonstration, commercialisation, and a supportive regulatory environment, ensuring that the benefits of the project's work can be realised by patients worldwide.