Leveraging functional genomics to reveal novel targets for cancer treatment

From the Commission's own budget table for this call. Confirm against the topic page before you plan around it: these move when a work programme is amended.

Expected Outcome: Proposals under this topic should aim to deliver results that are directed and tailored towards and contribute to all of the following expected outcomes: Researchers and health professionals gain a deeper understanding of the functional effects of tumour heterogeneity during cancer initiation and progression, supporting the identification of more precise and novel therapeutic targets. Researchers, health professionals and innovators benefit from improved knowledge and tools to support the discovery and development of next generation genomically-informed cancer treatments. Researchers, innovators, and professionals across disciplines and sectors contribute to the UNCAN.eu research data platform by ensuring data interoperability, and enabling sustainable access to newly developed digital tools and models for the analysis and management of multimodal clinical data. Scope: The proposed topic will contribute to the EU Cancer Mission objective of improving the understanding of cancer initiation and progression. Of particular interest for this topic are paediatric and adolescent cancers [1] , cancers with limited treatment options, refractory cancers, rare cancers or cancer types with low five-year survival rates. Proposals may include the design of exploratory mechanistic studies using longitudinal patient bio-samples, clinical proof-of-concept studies and/or observational and translational studies involving newly collected or existing data, as appropriate. Applicants are encouraged to leverage technological advances in functional genomics [2] and structural biology including but not limited to rapid gene sequencing, single-cell studies, spatial gene mapping, spatial transcriptomics, epigenetic profiling, liquid biopsies and functional precision oncology pipelines. The use of causal inference, computational modelling and/or artificial intelligence tools is encouraged for the collection, visualisation, analysis and management of large, complex, and heterogeneous data sets. Collaboration among different scientific disciplines, including healthcare professionals, is envisaged [3] . Applicants should address all of the following activities: To identify and validate new targets for innovative therapeutic approaches, by developing experimental models [4] and technologies to access the functional effects of tumour temporal heterogeneity on disease initiation, progression and relapse. To investigate the mechanisms underlying the interply between the tumor’s dynamic multi-omics characteristics, its microenvironment and patient specific factors [5] dur…