The overall goal of DISCERN is to understand the causes of three poorly understood cancers in Europe; renal, pancreatic and colorectal cancer, and help to explain their geographical distribution, including their high incidence in central and eastern Europe. This will be achieved by combining large-scale European biorepositories comprising population-based cohorts and tumour case-series with state-of-the-art molecular profiling techniques and machine learning approaches. In particular, DISCERN will identify potential new causal risk factors for the three cancers using novel exposomics and proteomics scans, as well detailed geospatial and environmental exposure information from 16 large-scale epidemiological cohorts including almost 900,000 individuals. It will also explore biological mechanisms on how these risk factors are potentially causing these cancer types with a focus on promoting factors in normal tissues using deep sequencing, single cell multi-omics and spatial proteomics. The causal effects of identified cancer risk factors and the cellular signalling responses they trigger will be further evaluated using a panel of stem cells and colon, renal and pancreatic 3D organoids. The results from DISCERN will be disseminated to citizens, patients and policy makers through collaborating patient and participant organizations. DISCERN will provide the critical evidence base required to develop new prevention strategies to tackle the growing burden of renal, pancreatic and colorectal cancer in Europe. This action is part of the Cancer Mission cluster of projects on "Understanding".

Incidence and mortality of colorectal cancer (CRC) is the second leading cause of cancer death in Europe. With current screening programs in most European countries, many CRCs are detected in an early and curable stage with excellent prognosis. The current standard treatment for early CRC is surgical tumour removal. This is considered as overly invasive especially for the growing number of elderly and frail patients. Expanding technical possibilities of local tumour removal by flexible endoscopy along with initial data supporting its oncological safety open the way to organ preserving therapy. This may result in avoiding surgery and improved patients´ quality of life (QoL). However, high-quality, long-term oncological outcome data of endoscopic removal as compared to surgery are lacking, and precise oncological risk criteria prior to the start of the therapy are urgently needed. The current project has two major aims: a) to assess oncological efficacy, safety, and patient QoL of local endoscopic removal of early CRC as compared to surgery in 3 randomized trials, and b) to develop and test criteria in this patient population to primarily identify high-risk lesions based on novel biomarkers, endoscopic imaging, and other clinical criteria, also within an artificial intelligence-guided treatment algorithm. We propose to provide state-of-the-art assessment of new, sustainable, less invasive treatment modalities for early-stage CRC and determine patient preferences around these therapies. We will perform large, international head-to-head randomized clinical trials. These trials will allow carbon cost effectiveness analyses, biomarker research and development of clinical practice guidelines to carve out the next-generation best clinical practice for patients with early-stage CRC. Our proposal aims at less invasive, sustainable organ-preserving therapies maintaining high oncological efficacy and helping physicians and patients to perform individual shared decision-making.

Most cases of gastric cancer (GC) are detected at a late stage, when patients have a median life expectancy of about a year. Diagnosing people at risk of developing GC at the pre-symptomatic stage, typically chronic gastric inflammation, could significantly improve the outlook. Artificial intelligence (AI) can help clinicians make sense of their own data by automating much of the treatment and analysis, which require manual work and years of experience. But it can do more: it can bring together available data from various sources into a vast data lake and cross-correlate the data to derive a ‘risk score’ for gastric cancer and shed light on the mechanisms of its evolution. Aida aims to do just that. It helps researchers understand the mechanisms that trigger gastric oncogenesis, helps clinicians diagnose precancerous inflammation at the earliest possible stage, suggests personalised therapeutic strategies for treatment and follow-up, and makes personalised recommendations for monitoring patient health status, thus contributing to gastric cancer prevention. This places Aida squarely on Europe’s agenda of ‘Staying healthy in a rapidly changing society’. Aida unites some of Europe’s leading authorities in the field of gastric inflammation, gastric cancer, leading AI and machine learning experts, experts on data governance and privacy, representatives of the public administration and patient advocates. Aida also has strong ties with the industry. After the project, the results will live on in an association that acts as a transnational focal point for chronic gastric inflammation — and GC in general. We hope that the solid, inclusive design principles of Aida, its societal relevance and its durability will spawn a vigorous ecosystem around chronic gastric inflammation, its understanding and its treatment. And we hope that it will inspire other data collaboratives in health — for other chronic inflammations, other forms of cancer or other ailments altogether.

Advancing personalized approaches in cancer therapy, aiding identification and adaptation of multi-modal treatment strategies for improved outcomes depends on clinical implementation of novel diagnostic technologies. For most cancer types the risk-features used to select individuals for post-operative adjuvant multimodal therapy are suboptimal, where many patients are overtreated and others undertreated. Liquid biopsy has opened a new diagnostic avenue to detect and monitor minimal residual disease (MRD) in individual cancer patients, especially for selecting patients for multi-modal therapies post-operatively. However, despite many circulating tumor DNA (ctDNA) diagnostics being developed there is a lack of standardization, harmonization, and robust data to demonstrate clinical validity. GUIDE.MRD is a consortium of leading academics, technology companies, pharmaceutical companies, and experts in multi-stakeholder engagements. Together, we will tackle the critical questions by developing reference standards for ctDNA diagnostics, clinically validate promising ctDNA diagnostics and develop data to guide the use of multi-modal therapies with a non-invasive diagnostic test. With robust engagement with regulatory authorities, payers and importantly patients themselves, we will develop recommendations and guidelines based on objective data to use ctDNA diagnostics to guide multi-modal therapy selection to improve patient outcomes.

SAGITTARIUS aim to optimize the clinical management of locoregional stage II high-risk/stage III colon cancer (LRCC). Approximately half of all LRCC patients relapse within two years from time of curative surgery because of imaging-undetectable micro-metastatic residual disease (MMRD). Given the lack of reliable predictors of individual risk, LRCC patients are treated with a one-fits-all adjuvant chemotherapy. This gunshot approach results in either over- or under-treatment. Measuring circulating tumor DNA (ctDNA) in the patients’ bloodstream can diagnose MMRD. Retrospective studies show that ctDNA detection after surgery predicts cancer recurrence with high sensitivity and specificity. SAGITTARIUS will deploy a ctDNA assay to detect the absence, presence, or persistence of MMRD in individual patients. The diagnosis of MMRD will guide and personalize therapeutic interventions. SAGITTARIUS is a pragmatic trial whereby real-world patients are treated in two parallel trials based on their MMRD status and the genomic landscape of their tumors. ctDNA positive patients are randomized to conventional or personalized targeted therapy. ctDNA negative patients are randomized to a physician-driven therapy or a Wait&See strategy. The efficacy and effectiveness of this potentially ground-breaking new strategy of care will be measured via multiple outcomes, including safety and time to events variables, patient-reported outcome measures, and health-economics evaluation. Since colon cancer deaths are usually associated with metastases rather than local disease, MMRD will also reclassify how this disease is perceived by clinicians. This new prism will allow for treatment to be better matched against the tumor biology, also allowing for better monitoring – via ctDNA – to assess disease evolution in each patient, minimizing harm and maximizing the odds of cure. This action is part of the Cancer Mission cluster of projects on ‘Diagnosis and treatment.